This is the course outline.
Throughout this course, you will be asked to work with various worksheets, which I refer to here as matrices. The reason for calling these worksheets "matrices" is derived from the social sciences, where matrices are used throughout various disciplines to organize the collection and evaluation of qualitative data. We take this very same kind of approach here, with the matrices I have designed, for qualitatively identifying and evaluating across a wide variety of ethical issues.
Rule Zero: DON'T PANIC [1]
First rule in using the matrices: You should not stick to the one sheet of paper. These matrices are conceptual frameworks, and I do not expect that you would be able to fit all the necessary detail in just the rows and columns of the pdf. Also, do not fill these out by hand and then scan and turn them in... this makes it very difficult for me read and to grade and give back comments. The best thing is to move your responses to a text file where you basically work through the columns and rows in a linear flowing manner, down the page. Just be sure to identify which of the sections you are responding to with a header for that section.
Second rule: Not all categories may be applicable to the case you are evaluating. Think carefully about it, but if it does not seem applicable, either indicate as such or just don't include that sub-category. However, and this is the tricky part, the specific topic/sub-category may not currently seem to be an issue; however, could it become an issue in the future if certain actions or consequences are not taken into consideration? This is the "anticipatory" aspect of ethical analyses which takes time to develop.
Third rule: Just because something does not seem to be an ethical issue since it has not been addressed does not mean it should not be considered. For example, just because a project does not address the needs and considerations of under-represented groups does not mean that it shouldn't address those needs. This is what I refer to as an "ethical deficit" or "ethical gap," where the lack of addressing an ethical need does not mean that there is no ethical issue there. Again, this is another example of trying to anticipate where ethical issues may go unrecognized.
Fourth rule: Always always always explain your reasoning. Remember the old "what, who, why, where, when and how?" rule of problem solving? Well, that should be a basic assumption in all your writing for this course, and others. For example, in the stakeholder matrix, just listing a person or group is not enough for anyone to go on... you need to explain what they have at stake and why.
Final rule: Do your best to think through these and apply the concepts. The reason why we go through a variety of these exercises is to improve your practice and familiarity with the various categories encountered in each of the matrices. I build room for improving your learning and do not expect perfection on the first attempts.
Choose a topic or use the one assigned to you, depending on the assignment. Begin to orient your topic in relation to the columns on the worksheet.
Stage 1: Identify and clarify initial conditions for analysis. Provide as much clarity to the description of the topics as possible. This is crucial. You need to define your case/topic clearly and in depth. A title alone will not suffice. Expect to write a paragraph describing. Remember the "who, what, where, when, why and how," in your description.
Stage 2: Review the three top-level categories on the course website, and remember they are inclusive, i.e., one issue can be in multiple categories
Stage 3: Begin with notes or quick phrases to fill the columns out. Make notes as needed and be able to describe further what the tags mean in context. Try to identify at least three issues per column. Provide a sentence or two describing each topic. Hint: you are looking for topics or issues that would make a difference if it were not done well or if it were done some other way, e.g., would your prefer surgery without anesthetics?
Stage 4: Then, rank the topics you identified in Stage 3 in order of importance, where importance can be either ethically "better or worse," it just indicates that it needs to be addressed and is of a high priority. Provide a brief summary (a few sentences) as to why you ranked them this way.
Q. So here what analysis we are talking about? Do you want us to pick a topic? Can you please give me examples of topics that can be picked? e.g., Topic can be “renewable energy over Fossil fuel”?
A: The topic of analysis depends on the assignment for that lesson. For the first assignment, I want you to begin thinking about a topic you would like to cover for your final project. You don't have to commit to what you decide upon now, but try to pick a case that you yourself would find useful to study more in-depth. Consider something you could either use and apply in your current work or a topic that you would like to add to your portfolio. If you are a solar, wind, or biofuels person, I suggest choosing something in that arena which you would like to learn more about. Try to avoid broad and sweeping topics, such as renewable energy over fossil fuels, and narrow your topic down as specifically as possible. The more specific you are, the easier it is to do the analysis because you are working with specifics. For example, we will later look at the ethical issues surrounding biofuels, and why some biofuels are much more ethical than others. So, it would be much better to do a comparison between, say first-generation biofuels and third generation biofuels, or the ethical issues of corn ethanol.
Q: So for Stage 3, do you want us to fill space under the Categories (I. Prof and Research integrity, II Broader Social and Enviro Impact, III Embedded Ethics) for the selected topic?
A: Yes, that is the goal. The first pass is to just sketch out the topics, like brainstorming, and the second pass is to add description and reasoning as to why those topics.
Q: Please clarify Stage 4, “Rank in order of importance”? Should the ranking be based on positive impact or negative impact?
A: Positive and negative impacts can very much depend on who you ask (we'll see this much more in terms of stakeholders.) Your ranking should really be based on the overall magnitude of the impacts, as opposed to whether or not they are positive or negative.
This first lesson is an overview of the Ethical Dimensions of Systems Research (EDSR), providing general terminology and approach to understanding the following case studies. The EDSR program describes how to recognize and evaluate ethical issues in research procedure and conduct, in the consideration of broader public and environmental impacts, and as values become embedded in research and analysis itself. Because common topics, types, and methods for ethical recognition and analysis are applied across all of the case modules, students should develop a set of tools for critical reflection on various issues of ethical importance. As developed in the EDSR approach, three main categorical distinctions for research ethics used here are broader social and political impacts (extrinsic ethics), research practice and conduct (procedural ethics), and embedded values (intrinsic ethics). By showing where and how to look for these types of ethical issues, the EDSR approach helps practitioners to anticipate where ethical issues may arise in a given research and/or application context.
This lesson will take us one week to complete. Please refer to the Course Syllabus for specific time frames and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Familiarize yourself with all the Lesson 1 Readings and assignments. |
Read | Week 1:
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Assignment | Week 1:
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This educational module provides users with concepts and examples for the development of tools for learning ethical analysis. "Ethics tools" are used to identify and design towards optimal solutions that satisfy a wide variety of ethical dimensions.
Whether you are a student or instructor, you will be able to interact with this module and learn more about other resources available on the specific topics under consideration. Users of this module, and any module within the Ethical Dimensions of Coupled Energy and Environment Systems Research series, are enhancing and refining their moral literacy by expanding their knowledge of ethical concepts and in considering examples and cases where ethical reasoning is required.
Expanding your knowledge of ethical concepts and studying of examples will help to enhance your ethical literacy.
We present here an approach that attempts to help you find firm footing in engaging and responding to questions concerning ethical and moral behavior encountered in the production and application of systems research. However, we understand that any approach will fall short on being a universally applicable approach to all contexts in research ethics. Further, while we focus on concepts particular to the production of knowledge (i.e., scientific research), many of these issues are also critical to industry, the public, and
One issue always worthy of consideration concerns addressing, “who bears the burden of intended and unintended consequences of our research?” Another issue that requires particular care in attention is in assessing the broader social impacts of research, particularly during the formation of the research itself.
If you have any questions, please post them to the General Questions discussion forum (not email), located under the Communicate tab or the Lesson tab in Canvas. Your instructor will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you are able to help out another student.
Let's say that, in a particular year, the climatic conditions in the U.S. produce significant droughts for certain regions in the Midwest. In this scenario, these severe droughts happen in regions that typically expect a significant amount of rainfall every year to support the extensive growth of corn. This lack of rainfall causes a near-complete failure of the corn crops in the region, which grows the most corn per unit area in the world. This failure of crops leads to increased prices in corn products and other foods that use corn as feed (chicken, beef, even fish). But this drought also leads to a sudden jump in price because corn is used as the main feedstock for brewing most of the ethanol that goes into our gas tanks ("up to 10% ethanol per gallon"). Now, let's think about how this impacts prices at the pump and at the grocery store. Prices per gallon or per pound go up for everyone that buys these products. However, if we consider the increase in cost to the consumer is, say, an increase of $1.00 per gallon or pound, that $1.00 per gallon or pound is four times the percentage of someone's income that makes $30,000 per year than it is for someone that makes $120,000 per year. Also, as a result of the drought, the price of the white corn that is used to make tortillas, a main food staple in Mexico, goes up. The white corn crop might not even be impacted by the drought, but because the price of white corn is tied to the price of yellow corn, used to feed livestock and brew biofuels, the price of this common food staple also goes up.
Having considered this scenario, what do you think about it? Is there something here we can describe as a better or worse decision about using corn for ethanol? Is there something good or bad about food prices competing directly with fuel prices? These questions do not have simple answers.
Engaging complex systems, whether they are tied to energy or environment, requires significant investigation and research support. This applies to engagement through politics and economics as well as it does with science and engineering.
The development of sustainability strategies and the technological and scientific research in the support and pursuit of renewable energy require rational and well thought through processes of evaluation. These well thought through processes of evaluation form a basis of research practice that is common to both engineering and science. Complex systems also often require multidisciplinary approaches to addressing a variety of questions and concerns, usually towards a framework of problem-solving. While one might not be engaged specifically in the scientific aspects of a complex system, the need for research and further discovery is needed in engineering, economics, policymaking, intellectual property, ecology, etc. For the purposes of this module series, we consider anyone conducting research into some aspect of complex systems to be engaged in "systems research." Further, whether one is conducting basic research on materials or looking at the global economic implications of sea level rise, one needs to be aware of the ethical dimensions of the systems they are researching. The modules of this series investigate various ethical issues that arise in the research of energy and environment systems.
Complex systems do not always imply environment or human systems, which implicitly require an ethical analysis and treatment. However, all of the modules in this series do involve some aspect of environmental systems and some aspect of energy systems. And energy systems, by their very definition, involve human systems.
All aspects of scientific research relate, in some manner, to social processes and are subject to the constraints of law and civil behavior that we expect from any public or private undertaking. Scientific research comprises more than just studies within a lab, as it can also describe advances in engineering, technical and computational developments, applying science to meet public needs, using technical information to guide policy, and other similar areas where a scientific approach is being used to address needs for new knowledge and insight into problems and curiosities.
The production of scientific research is tied to politics, social needs, public funding, venture capital, human health, environmental security, and economic development, as well as many other concerns of human society. As such, scientific research itself is subject to many forces and constraints working it, constraints which shape research questions, methods, and outcomes. Understanding and determining appropriate responses to many of these constraints requires a broad understanding of research ethics.
All scientific research is subject to social forces, therefore all research necessitates the consideration of ethics.
Research ethics, thus: are a matter of responsible professional conduct fitting to the norms of a research community (procedural ethics); require a consideration of the broader social, political, and economic impacts (extrinsic ethics); and, point to where (social, personal, institutional) values and preferences become embedded in the analytical inputs and outputs of research itself (intrinsic ethics). A comprehensive consideration of research ethics requires a critical analysis of the procedural, extrinsic, and intrinsic aspects of the research or outputs under consideration. Goals for learning ethics include the identification and application of ethical tools for prescribing optimal solutions, the development of moral literacy, awareness of stakeholders, and the minimization of risk.
Understanding how to make good choices as practitioners and leaders in the fields of renewables and sustainability will require both scientific knowledge and an awareness of the various positions along with projected trade-offs. These types of analyses require the consideration of more than technological optimization or basic costs and benefits; as numerous cases demonstrate, they often require the deeper consideration of ethical issues and embedded values. Not understanding these ethical issues and embedded values in the production of research and professional application of training can lead to outcomes that are unjust, increase risk, change economic relationships.
Not paying attention to ethical norms and proper research conduct can impact careers.
Careers can be directly impacted by ethical violations. Tenured jobs are lost over research ethics violations; foreign nationals can be deported over non-compliance when researching on government funds; entire labs have been closed due to ethics violations.
Ethics can be tricky, particularly when a practitioner researcher may be representing both personal interests and organizational interests in the same role (such as a reviewer of grant applications). It is not always obvious what is right and wrong behavior in certain situations, such as in considering conflicts of interest, or whether one can remove bias in reviewing the work of a friend or the work of someone from an opposing viewpoint. The key is to learn about ethics and where to go to learn more–find someone you can talk with about the issues at hand.
The Ethical Dimensions of Scientific/Systems Research (EDSR) approach describes how to recognize and evaluate ethical issues in research procedure and conduct, in the consideration of broader public and environmental impacts, and as values become embedded in research and analysis itself. Because common topics, types, and methods for ethical recognition and analysis are common across many cases of scientific research and technical application, it is efficient and helpful to develop a set of tools for critical reflection on various issues of ethical importance.
As developed in the EDSR approach, three main categorical distinctions for research ethics used here are 1) broader social and political impacts of research (extrinsic ethics), 2) research practice and conduct (procedural ethics), and 3) embedded values within research (intrinsic ethics). By showing where and how to look for these types of ethical issues, the EDSR approach helps practitioners to anticipate where ethical issues may arise in a given research or application context.
Type of Ethics in Research | Description |
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Ethics Extrinsic to Research - Social/Political | NSF broader impacts criteria, social justice issues, S&T policy, policy implications, improving representation and distribution |
Ethical Research Procedure - RCR/Professional | Responsible conduct of research, professional codes, conflicts of interest, treatment of human & animal subjects, informed consent |
Ethics Intrinsic to Research - Analytical/Technical | Embedded values, parameterizations, theory selection, error analysis, global assumptions, outliers, data cleaning |
Research ethics is not a matter of memorization of rules about proper behavior. Rather, it is important to approach learning research ethics as the skill of being able to derive the ethics of a given situation, by asking similar key questions across multiple situations. While ethical contexts and possibilities are vast for a field like sustainability or renewable energy, we can still maintain a reasonable handle on things by addressing some core principles.
There are the ethical considerations of how to proceed in the course of conducting any manner of scientific research. These are referred to as procedural ethics and signify the typical areas of responsible conduct of research, including issues such as falsification of data, fabrication of data, and plagiarism, as well as considerations around conflicts of interest, research misconduct, treatment of human and animal subjects, and responsible authorship. While there are many considerations around procedural ethics that are highly relevant to nanotechnology research, such as fabrication of experimental results, responsible authorship amongst colleagues, etc., for the most part, the same type of considerations of procedural ethics will appear in nanotechnology as they do is most any other field of science and engineering research.
According to the National Office for Research Integrity, there are nine main areas to consider in the Responsible Conduct of Research:
“Federal and institutional research misconduct policies define research practices that researchers must avoid.”
"Authorship and collaboration problems are a serious threat to the research enterprise and to the motivation of young scientists, especially when they involve misappropriation of ideas and data."
Floyd E. Bloom. Science 287:589, 2000.
"Every job occupied, every grant received and every paper published by someone who engages in misconduct deprives at least one honest scientist of an opportunity to which he or she was entitled.”
Herbert N. Arst, Jr., Imperial College School of Medicine, London. Nature 403:478, 2000.
Known as the three “cardinal sins” of research conduct, falsification, fabrication, and plagiarism (FFP) are the primary concerns in avoiding research misconduct. Any divergence from these norms undermines the integrity of research for that individual, lab, university/corporation, and the field as a whole.
Falsification is the changing or omission of research results (data) to support claims, hypotheses, other data, etc. Falsification can include the manipulation of research instrumentation, materials, or processes. Manipulation of images or representations in a manner that distorts the data or “reads too much between the lines” can also be considered falsification.
Fabrication is the construction and/or addition of data, observations, or characterizations that never occurred in the gathering of data or running of experiments. Fabrication can occur when “filling out” the rest of experiment runs, for example. Claims about results need to be made on complete data sets (as is normally assumed), where claims made based on incomplete or assumed results is a form of fabrication.
Plagiarism is, perhaps, the most common form of research misconduct. Researchers must be aware to cite all sources and take careful notes. Using or representing the work of others as your own work constitutes plagiarism, even if committed unintentionally. When reviewing privileged information, such as when reviewing grants or journal article manuscripts for peer review, researchers must recognize that what they are reading cannot be used for their own purposes because it cannot be cited until the work is published or publicly available.
“Cases of misconduct in science involving fabrication, falsification, and plagiarism breach the trust that allows scientists to build on others’ work, as well as eroding the trust that allows policymakers and others to make decisions based on scientific and objective evidence. The inability or refusal of research institutions to address such cases can undermine both the integrity of the research process and self-governance by the research community.”
Responsible Science: Ensuring the Integrity of the Research Process. Vol. 1:20, NAS, 1992.
A conflict of interest arises when one’s judgment is compromised based on connections, favors, or competing interests, and/or when one’s position is used to gain favor or extra rewards. Conflicts of interest are not always immediately obvious, nor does a conflict of interest in-and-of-itself constitute wrongdoing.
Personal obligations, connections to other institutions, participation in other research programs, or drawing from competing pools of funding can influence one’s capacity to be impartial in a given situation. Being impartial is as necessary in producing and reviewing scientific research as it is in jury selection in a court of law or in the practice of medicine. Perfect impartiality is not really possible, as we are always assessing a situation based on the unique culmination of our experiences and perspectives. Nevertheless, there are experiences, perspectives, and connections that may cause us to not be able to think outside of our own interests. Knowing when we are or are not able to think outside of our other interests is crucial to understanding how to avoid possible conflicts of interest. It is important to note that having an opposing viewpoint does not constitute a conflict of interest and is a cornerstone to robust reviews.
“Authors should also realize that disclosing financial support does not automatically diminish the credibility of the research. However, failure to disclosed a competing financial interest that is subsequently discovered immediately opens the authors to questions about objectivity.”
Thomas J. Goehl, Editor-in-Chief, Environmental Health Perspectives, V. 112, No. 14, October 2004, p. A 788.
Problems that can erode impartiality in a given analysis should be explicitly stated and made transparent, often arising when different sources of resources are being invested in research. Using public funds for research in support of research for a private company can also be problematic. Conflicts of interest can also skew one’s perspective towards seeing or interpreting results that may not be there, or in ignoring data that are there. For example, conflicts can arise when companies are determining the health risks their products may pose, such as the risks of smoking being tested by tobacco companies.
The key to avoiding possible conflicts of interest is transparency of plausible interest in a given situation. Reveal all relevant connections to the case at hand. Recuse oneself from the case at hand if necessary.
Data are the core of research. The recent requirements by federally funded grants to develop data management plans summarize the imperatives here, including long-term storage of data, sharing of data, and other aspects of assuring data integrity, continuity, and federation. Data is considered part of the investment into research, in that it should be accessible to future researchers. Further, data or samples may be subject to other forms of analysis in the future, thus the future potential for data should also be taken into consideration when implementing management plans. As well, data security and privacy of subject data is of key importance to the protection of research subjects.
Interoperability of data, particularly across research institutions, is crucial in conducting collaborative research across a large network, such as in large scale public health networks. Paying attention and adhering to meta-data standards (information about data types and data structures) is of growing importance in sharing data between research communities, across disciplines, between regulatory institutions, governmental offices, and NGOs.
Attention to research data standards is crucial to avoiding cases such as when the thrust of the Mars Climate Orbiter was using metric unit Newtons (N) while the NASA ground crew was using the Imperial measure Pound-force (lbf), a mistake which caused the subsequent loss of the $500 million (US) satellite.
Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections, and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing.
The identification of authors, the ordering of authors, the speed of publication of research findings, modes of research dissemination, acknowledgments, relevancy, and other aspects of publishing and disseminating findings. Proper citations are the foremost responsibility of authorship in the sciences. It is extremely important to adequately and accurately cite literature to give credit to those who have conducted research before you. It is better to be cautious and cite when unsure to avoid even the appearance of plagiarism.
Authorship credit should go to anyone providing a substantial intellectual contribution to the paper. Disciplines have a variety of traditions in who should be counted as an author. This is also the case for the order of authorship, particularly who gets to be listed as the first and last author, as many labs and/or fields have their own best practices for listing authors. This is a conversation worth having with an advisor at some point during graduate training. Provide an acknowledgment for those individuals and organizations that provided advice, revision suggestions, material resources, and funding.
It is worth discussing authorship at the beginning of a project to avoid conflicting expectations when it comes time to publish. All authors must be ready to defend the integrity of the research and the findings presented within. On multi-authored papers, individuals are responsible for their contributions.
“Authorship and collaboration problems are a serious threat to the research enterprise and to the motivation of young scientists, especially when they involve misappropriation of ideas and data.” Floyd E. Bloom. Science 287:589, 2000.
Responsible authorship also must consider membership within a research community. Avoid fragmentary publications, where research findings can be presented in a comprehensive format, i.e., publishing fewer results per paper to increase the number of personal publications. Further, avoid simultaneous manuscript submissions to multiple journals. (Most journals have policies against simultaneous submissions.) Publish substantial findings, first and foremost, in a timely fashion. As well, be fair in the peer review process.
Coupled Energy and Environment Systems present significant challenges and opportunities to questions concerning the broader impacts on societal (economic, political, cultural) and environmental (ecological, biological, land-use) domains. This is where ethical considerations become more specific to the content and context of energy and environment systems research as it extends to and applied in the world outside of the laboratory.
The NSF broader impacts criterion (i.e., the second merit criterion) poses many similar questions in the area of extrinsic ethics, and provides a useful framework for beginning to think about how the research applies to societal and environmental concerns, particularly in the formulation of research agendas and in thinking about the implications a specific line of research may imply for policymakers, regulatory agencies, and civil society organizations (CSOs).
Further considerations of issues around the distribution of benefits and harms of energy and environment systems need to also be taken into account, to assure, for example, that the output of systems benefits only all sectors of society.
Scientific research can and often does impact public policy in a manner of ways. Understanding that one’s research may be applicable to informing public policy decisions or be subject to regulatory mechanisms is crucial. There are many three main intersections between policy and research that need to be considered, such as policy and regulation about the scientific research and/or technology (policy of science, or science policy); scientific research and technological capacity often informs crucial decision-making processes, such as determination of risks and evaluation of responses (science for policy); and, institutional policies in support of funding and conducting research (research management policy).
Energy and Environment Systems present some significantly challenging scenarios for current and future generations. Further, this type of research is often used to direct regulatory policies, such as in the choice of national sustainable energy strategies and analysis of contingencies, etc.
Energy and environmental systems need to be co-guided to assure public and environmental safety as well as effective production in meeting demands. How, where, and when energy systems research will be applied will often come under the consideration of public officials and agency specialists.
"Science is organized knowledge. Wisdom is organized life." -Immanuel Kant
Scientific research is often put to use in decision-making processes. Further, science often informs society about risks that need to be avoided. Of course, much debate can arise from what to do about this new knowledge, such as has often been the case with climate change. Analyses, information, data, expert opinion, reports to congressional commissions, models, projections, solutions, new directions for economic development, etc., all require considering implications.
The coupled and interconnected nature of energy and environment systems will present many unique legal challenges, particularly where regulatory issues cross paths with land use changes, intellectual property rights, licensing agreements, public investments, commercialization, international trade, and distribution. Some of these concerns will also be covered by wider policies and regulation of energy markets, assessment of environmental impacts, and institution specific requirements.
New patents in energy are being filed globally on a daily basis, establishing a rapidly changing legal framework around ownership of and access to new energy technologies. The total (global) patent filings in alternative energy alone, "have increased at a rate of 10 percent per year starting in the 1990s and at a rate of 25 percent from 2001." (World Intellectual Property Organization, 2009) Questions also arise when considering how to license these technologies depending on location and development conditions. The rate of filing new energy related patents is projected to continue increasing over the next two decades, presenting significant opportunities and many uncertainties.
Energy systems are quite diverse and can have a wide range of impacts on private and public property. Biofuels present significant opportunities for a low-carbon impact production of energy, but they also will likely change how we manage forests, crops, and other large-scale feedstock production. Wind energy technologies, while promising, will continue to pose oppositions to their locations, such as impacts on property values, visual preferences, etc. Regardless of the specific technology, innovation, adoption, and licensing of energy technologies will inevitably require further nuance and distinction, often based along ethical considerations.
Energy and environment science and technology present possibilities that could potentially transform the shape of economic production, output, market arrangements, etc. For example, if developments in renewable energy can begin to produce long-lasting and economically feasible means for producing reliable energy at significantly reduced price, competitive advantage will typically drive producers towards adoption of new energy production techniques, which could have broad-reaching implications for economic conditions globally.
It is crucial to ask whether the research could impact how society functions on a day-to-day basis; for example, how we grow food, produce energy, etc. Energy innovations will certainly have sweeping impacts across many aspects of society, aspects and issues which need to be contemplated in the formulation of research and design trajectories, and not just after the fact of invention.
The public understanding of energy and environment systems presents significant challenges, particularly in trying to communicate risks, challenges, etc. Further, rising to the challenge of a prepared “sustainable energy” workforce is very much a concern of K-Graduate education.
Transformations in energy and environment systems will inevitably present challenging questions about economic growth, social welfare, and public goods, the education of both future energy and environment scientists, increases in public understanding of energy systems, etc. The full arrival of sustainable energy based manufacturing will also have profound effects on traditional modes of fabrication and production.
Most people would tend to agree with the stance that our developments in science and technology should adhere to, or at least not be entirely counter to, our notions of the common good, not harming others, not causing further hardships, etc. After all, most people view science and technology as a positive force in society. However, this cannot always be assumed. Further, how we go about making sure society actually does benefit from innovations and new knowledge is not always straightforward, particularly in considering cutting edge research. There are three basic areas worthy of deeper analysis when considering the broader impacts of a given development trajectory.
Are the costs, harms, and benefits of nanotechnologies being distributed equitably over society? Can energy technology be used to improve the least well off first? Are certain populations more at risk from energy production than others (children, poor, elderly)?
How are decisions about energy and environment regulation being taken into account, and who is making the decisions and choices? If groups or individuals are going to be impacted by the development and application of certain energy technologies (i.e., stakeholders), are they included in the decision-making process? What sort of representation and proof of risk must an organization provide before moving forward with a new product or process?
Choices made now about infrastructure, investments, longevity, and risk can have implications for generations to come. For example, once the decision was made to develop nuclear technology, a choice was also made for many, many generations to follow. Infrastructure that is developed also needs to be maintained, or allowed to go to waste. All of these imply costs and opportunities (gained and lost) for decades, centuries, and in some cases, millennia.
Approaching any new territory in science and technology can present great payoffs and public goods, but it can also present daunting challenges that can change and shape international relations. For example, nuclear science and technology continue to present similar challenges to governments and populations across the world. Once certain knowledge or technology is produced, published, circulated, or otherwise manifested into the world, it cannot be undone.
Understanding and fully defining the risks of a given technical scenario require both an analysis of the science itself (see intrinsic ethics issues on handling of uncertainty), and a projection as to how the technology could potentially cause harm or otherwise negatively impact human well-being. Risk has two aspects that need to be considered when thinking about a project. Could the research or technology itself present any apparent or immediate risk? Could the technology increase the overall risk profile of a society?
What constitutes a viable risk assessment for energy and environment technologies? Precaution in the face of risk needs to be considered and taken into account in any case, and certain aspects of energy production can present an exceptional risk to human and environmental health. As such, regulation will need to be comprehensive, robust, and conservative with respect to risk projections.
Precautionary measures mandate that we proceed cautiously (but not necessarily slowly) and deliberatively in the face of high risks coupled with any uncertainties. The precautionary principle in its most simple expression suggests that we plan for worst-case scenarios in the face of high risks coupled with uncertainties. The main idea is that, when faced with taking risks (intended and unintended) that could affect a significant portion of the population or environment, we proceed through the process cautiously and deliberately. The precautionary principle should be invoked when high-risk, irreversible, or catastrophic situations are possible, even at a very low probability.
While considerations of procedural ethics require a framework of responsible research behavior, and extrinsic ethics requires an explicit consideration of broader impacts, intrinsic ethics requires a deeper analysis of how the research itself is constructed and where certain choices being made in the line of research embed value judgments and can impact real-world outcomes. For example, the handling of uncertainty and margins of error tend to be mathematical questions concerning the probability of a certain event to occur, yet, these uncertainties can determine real-world decisions about actions, regulations, etc. (Note: Choices made about intrinsic issues can have extrinsic impacts, as the two are intricately related.)
The basic idea of intrinsic ethics concerns choices that seem to be only considered in mathematical or within the terms of the art, yet can embed certain values and result in different implications as to the application or future direction of the energy and environment knowledge. As well, ethics/values can be embedded in choosing not to pay attention to certain limits or parameters, i.e., in what is not being represented in a given analysis.
The means to address intrinsic ethics is through reflexive analysis (reflection based on values questions -> course correction) of research choices being made based on the kinds of questions highlighted here. This reflexivity should occur both while conducting research and while engaging in the peer review process.
Values and ethics become embedded within the production of research, oftentimes at the very decision about research topic and question. Such decisions are rarely made within ideal conditions, where resources and time are of no issue. Research is done dependent on deadlines, budgets, peer review feedback, departmental resources, etc. How research is framed, the choice of explanatory frameworks and global assumptions about variables, and the explanations about causal relationships in a given model all present choices that can embed values about representative samples, as is a common question in biomedical or genetic research.
Research results are inevitably impacted by the scope and range of research questions. Context dependent values can impact problem choice; whether due to individual interests, funding agency interests, or broader societal interests, contextual values become interwoven into research practice. Further, choice of research question can also influence whether or not certain risks are taken into account, or are able to even be considered within the framework of a given nanotechnology research program.
If we knew what it was we were doing, it would not be called research, would it? –Albert Einstein
Interests of the researcher are reflected in accepting certain framework conditions, such as the representational limits of an analysis, or in choosing the values of certain variables, within a model, as being “more” representative of reality than a different variable, model, or limit.
Causal explanations produce a conception as to what is happening within a given nanotechnology model or analysis. However, many simplifications and reductions are made just to make a model usable, and in doing so, there is no guarantee that a significant causal relationship does not go either unseen or unconsidered.
Conducting and publishing research is a process of interpreting observations and describing the results. Questions about research and hypothesis formation point us in a specific direction and guide the interpretation of results. But how do we determine what we are seeing adequately supports our claims? How many observations do we need to make to assume our interpretation is correct? As well, does our research apparatus adequately support our ability to answer our research question in the detail or resolution necessary? How does an observation count if it does not fit our expected results?
Complex phenomena require complex models and descriptions. Not adding enough complexity to a research hypothesis could result in oversimplification of a situation, leaving out crucial thresholds or other limits in the system(s) under consideration. Often, in research, a compromise needs to be made, even for reasons of cost, between adequate observations and extremely comprehensive observations (such as sampling across a large site.) All of these choices can potentially lead to a false confidence in projections of model adequacy, which can result in real-world impacts.
The method of science depends on our attempts to describe the world with simple theories: theories that are complex may become untestable, even if they happen to be true. Science may be described as the art of systematic over-simplification—the art of discerning what we may with advantage omit. – Karl Raimund Popper
Were adequate tests conducted to assure the phenomena observed are consistent, is the study reproducible, or is the instrumentation working within viable parameters and/or limits of observation? As nanotechnology is an emerging field with increasingly finer tolerance, many observations and conceptions of adequacy can change over time.
What is the scope of the study under consideration? Is the study significantly comprehensive to be relevant to various conditions? Is there detail being lost through the over-simplification of a model or representation?
What constitutes certainty about a given observation? How many times must it be observed to be considered “valid proof” of a particular event? What is considered to be statistically significant for a given event to be occurring? Answering these kinds of questions seems a somewhat arbitrary matter, but consider that what is considered proof in one context is considered a “shadow of doubt” in another context. As well, being wrong in some cases will cost more than being wrong in other cases (as we see in the politics of climate science).
Standards of proof often incorporate social values. As Anderson writes, “Social scientists reject the null hypothesis (that observed results in a statistical study reflect mere chance variation in the sample) only for P-values\5%, an arbitrary level of statistical significance. Bayesians and others argue that the level of statistical significance should vary, depending on the relative costs of type I error (believing something false) and type II error (failing to believe something true).
where the test produces a positive result when the negative result is the case, such as in a medical patient testing positive for a disease they do not have. In terms of data analysis, new information falsely changes previous estimates of uncertainty.
where the test produces a negative result when the positive result is the case, such as when a medical patient has an ailment that goes undetected by test(s). Regarding data, new information does not correctly change previous estimates of probability of occurrence.
Both types of errors present different costs in different contexts, and result in a choice about values.
In medicine, clinical trials are routinely stopped and results accepted as genuine notwithstanding much higher P-values, if the results are dramatic enough and the estimated costs to patients of not acting on them are considered high enough” (Anderson 2009). Type I and II errors can have significant impacts in energy applications, and will require mindful foresight and consideration both by researcher and peer-reviewers.
Oftentimes when we travel, we determine where we want to go before we know how we are going to get there. Much the same can be said how we approach research. We know the kind of knowledge we would like to gather, or effect we would like to tease out of a certain set of materials, before we know how we are going to get there. Methods selection itself can shift over the duration of the experimental process (though, hopefully not during an experiment!) of a given investigation. As we travel through the research process, we gather data about observations. This data is shaped by our selection of methods, and also conforms to our classification schemes.
As researchers, how we collect data and how we choose to categorize data are two other processes through which values become embedded in research. This suggests that we should pay close attention to how we justify our methods selection, understand the limitations of what our methods allow us to argue, and are able to justify our categorical and organizational choices.
Rumour has it that the gardens of natural history museums are used for surreptitious burial of those intermediate forms between species which might disturb the orderly classifications of the taxonomist.
– David Lambert Lack
Choice of methods for either data collection and/or analysis reflects the context of the researcher and impact significantly the intellectual merit and framework of the nanotechnology research. “The methods selected for investigating phenomena depend on the questions one asks and the kinds of knowledge one seeks, both of which may reflect the social interests of the investigator” (Anderson 2009). Also, certain methods may not be as applicable in a given situation as others. Comprehensive assessment of methods selection should be clearly stated and justified in the research proposal, included an analysis of possible methods biases.
The classification of an observation or phenomena, particularly when the classification strategy is being developed, the adequacy of certain definitions, the granularity of classifications, etc., can have significant impacts in later developments, lead to certain oversights, and even lead to misleading conclusions.
I want you to think of the approach and cases we cover in this class as more like "ethics forensics" and how to apply tools for ethics investigations, as opposed to learning strict ethical theory, moral laws, etc. Perhaps another way to put it, in pop culture terms, is that our course is more like a detective show than a courtroom drama.
As such, I don't expect you to have the absolutely correct answers or perfect choices for examples. I want you to try ideas out, experiment with different hypotheses, suggest various paths of action, etc. I want you to notice things, looking closely at important details. (You certainly may not have time to look at all of the details; but, in time, you will begin to notice things as you go.)
The matrix assignments are all intended towards helping you discover possible ethical issues when evaluating a given topic of interest – in this case, in renewable energy and sustainability-related issues. Each of the columns represents a different dimension in which ethical issues can be viewed. You can take a topic, as broadly or narrowly defined as you like and apply this matrix. It is best to stick with one topic at a time, i.e., the same topic evaluated according to each column. Complete the assignment in column form or written out as paragraphs or in some combination... as long as I can recognize what you are doing, then that should work.
The first column should get us thinking about the issues concerning professional and research integrity that help keep processes safe, transparent, honest, etc.
The second column should prompt us to think about questions concerning the work that could affect other people, society, the environment, and other broader impacts.
The third column requires thinking closely about the processes and technologies that can embed certain ethical choices, perhaps without even realizing it. This kind of analysis is a bit tricky and requires an understanding of the professional and/or research practices themselves. The choices we make as professionals can have consequences we may not have considered.
Let's try an example: Consider public architecture in the U.S. before the Americans with Disabilities Act of 1990. Architects were free to design public buildings that were difficult, if not impossible, to access for citizens in wheelchairs. Leaving out consideration of access to a public space by not just people in wheelchairs, but pretty much anyone not on two good legs produces significant inequity in opportunities and access to public resources for that group. Using the first column (professional and research integrity), we would say that architects at the time were following the best practices of their field, meeting code and other professional expectations, so all was ok there. Using the second column, we would begin to see, however, that a significant sector of society at any given point (even people on crutches, with a broken leg, who may at other points be bi-pedal) may not be able to access a public building (courthouse, town hall, library, etc.) without significant difficulty, if at all. Using the third column, we would see that architectural practice and design of public spaces did not take into account the wide variety of human variability, and the only way to change that is to change that practice of the design of public spaces. After 25 years of significant protest (which began with the wave of returning injured soldiers returning from Vietnam), regulation and sets of guidelines were designed that became law [24] in 1990. We can see this as a process in that the ADA goes back and significantly changes the first column which now makes following these considerations professional responsibility, and not following these regulations will not pass inspection. This is a historical process that reflects these three dimensions, but we can, and will, use it in a variety of areas.
Davis, M. 2006. Engineering ethics, individuals, and organizations. Science and Engineering Ethics 12 (2):223-231.
Devon, Richard. 1999. Toward a social ethics of engineering: the norms of engagement. Journal of Engineering Education 88 (1):87-92.
Holbrook, J. Britt. 2005. Assessing the science–society relation: The case of the US National Science Foundation’s second merit review criterion Technology in Society 27:437-451.
Schienke, Erich, Seth Baum, Nancy Tuana, Ken Davis, and Klaus Keller. 2010. Intrinsic Ethics Regarding Integrated Assessment Models for Climate Management. Science and Engineering Ethics.
Schienke, Erich, Michelle Stickler, and Nancy Tuana. forthcoming. Assessment of Impacts of an Educational Intervention on Learning Responsible Conduct of Research Principles. Journal of Empirical Research on Human Research Ethics.
Schienke, Erich, Nancy Tuana, Don Brown, Ken Davis, Klaus Keller, James Shortle, Michelle Stickler, and Seth Baum. 2009. The Role of the NSF Broader Impacts Criterion in Enhancing Research Ethics Pedagogy. Social Epistemology 23 (3-4):317–336.
Shrader-Frechette, K. S. 1985. Science policy, ethics, and economic methodology: some problems of technology assessment and environmental impact analysis. Dordrecht; Boston, Hingham, MA: D. Reidel Pub. Co.
Shrader-Frechette, K. S. 1985. Risk analysis and scientific method: methodological and ethical problems with evaluating societal hazards. Dordrecht; Boston Hingham, MA: D. Reidel.
Shrader-Frechette, K. S. 1994. Ethics of scientific research. Lanham, Md.: Rowman & Littlefield.
Star, Susan Leigh. 1985. Scientific Work and Uncertainty. Social Studies of Science 15 (3):391-427.
Committee on Assessing Integrity in Research, Environments, Council National Research, and Integrity United States. Office of the Assistant Secretary for Health. Office of Research. Integrity in Scientific Research: Creating an Environment That Promotes Responsible Conduct [25]. National Academies Press 2002.
Committee on Science, Engineering, Policy Public, Sciences National Academy of, Engineering National Academy of, and Medicine Institute of. 2009. On being a scientist: a guide to responsible conduct in research. Washington, D.C.: National Academies Press.
Kalichman, M. 2002. Ethical decision-making in research: Identifying all competing interests - Commentary on “Six Domains of Research Ethics”. Science and Engineering Ethics 8 (2):215-218.
Kalichman, M. 2003. Ethics and the scientist. Scientist 17 (20):43-43.
Kalichman, M. 2009. Evidence-Based Research Ethics. American Journal of Bioethics 9 (6-7):85-87.
Steneck, N. H. 2006. Fostering integrity in research: definitions, current knowledge, and future directions. Science and Engineering Ethics 12 (1):53-74.
Steneck, N. H., and R. E. Bulger. 2007. The history, purpose, and future of instruction in the responsible conduct of research. Academic Medicine 82 (9):829-834.
Steneck, Nicholas H., and Integrity United States. Office of the Assistant Secretary for Health. Office of Research. 2004. ORI Introduction to the responsible conduct of research. Rockville, Md.; Washington, DC: U.S. Dept. of Health and Human Services, Office of Research Integrity]; For sale by the Supt. of Docs., U.S. G.P.O.
Davis, M. 2006. Integrating ethics into technical courses: Micro-insertion. Science and Engineering Ethics 12 (4):717-730.
Herkert, Joseph. 2005. Ways of thinking about and teaching ethical problem solving: Microethics and macroethics in engineering. Science and Engineering Ethics 11 (3):373-385.
Herkert, J. R. 2001. Future directions in engineering ethics research: microethics, macroethics and the role of professional societies. Science and Engineering Ethics 7 (3):403-14.
Hollander, Rachelle D., Deborah G. Johnson, Jonathan R. Beckwith, and Betsy Fader. 1995. Why teach ethics in science and engineering? Science and Engineering Ethics 1 (1).
Hollander, R. D. 2001. Mentoring and ethical beliefs in graduate education in science. Commentary on ‘Influences on the ethical beliefs of graduate students concerning research’. (Sprague, Daw, and Roberts). Science and Engineering Ethics 7 (4):521-4.
Kligyte, Vykinta, Richard T. Marcy, Sydney T. Sevier, Elaine S. Godfrey, and Michael D. Mumford. 2008. A Qualitative Approach to Responsible Conduct of Research (RCR) Training Development: Identification of Metacognitive Strategies. Science and engineering ethics. 14 (1):3.
Kligyte, Vykinta, Richard T. Marcy, Ethan P. Waples, Sydney T. Sevier, Elaine S. Godfrey, Michael D. Mumford, and Dean F. Hougen. 2008. Application of a Sensemaking Approach to Ethics Training in the Physical Sciences and Engineering. Science and engineering ethics. 14 (2):251.
Korenman, Stanley G., Alan C. Shipp, Aamc Ad Hoc Committee on Misconduct, and Ethics Conflict of Interest in Research. Subcommittee on Teaching Research. 1994. Teaching the responsible conduct of research through a case study approach: a handbook for instructors. Washington, D.C.: Association of American Medical Colleges.
“Through its Ethics and Member Conduct Committee, IEEE aims to: foster awareness on ethical issues; promote ethical behavior amongst those working within IEEE fields of interest; create a world in which engineers and scientists are respected for exemplary ethical behavior.” Review the IEEE Code of Ethics. • Review ethics cases.
“Founded in 1964, the National Academy of Engineering (NAE) [26] is a private, independent, nonprofit institution that provides engineering leadership in service to the nation. The mission of the National Academy of Engineering is to advance the well-being of the nation by promoting a vibrant engineering profession and by marshaling the expertise and insights of eminent engineers to provide independent advice to the federal government on matters involving engineering and technology.”
“The overarching mission of Center for Engineering Ethics and Society (CEES) [27] is to engage engineering leaders in examining the ethical and societal challenges of engineering and bringing them to the attention of the engineering profession and society.”
“The Online Ethics Center (OEC) [28] is maintained by the National Academy of Engineering (NAE) and is part of the Center for Engineering, Ethics, and Society (CEES). The CEES started in April 2007 and plans conferences and other research and educational activities under the direction of the CEES advisory group.”
“Through its Ethics and Member Conduct Committee, IEEE aims to: foster awareness on ethical issues; promote ethical behavior amongst those working within IEEE fields of interest; create a world in which engineers and scientists are respected for exemplary ethical behavior.” Review the IEEE Code of Ethics.
“Founded in 1964, the National Academy of Engineering (NAE) [26] is a private, independent, nonprofit institution that provides engineering leadership in service to the nation. The mission of the National Academy of Engineering is to advance the well-being of the nation by promoting a vibrant engineering profession and by marshalling the expertise and insights of eminent engineers to provide independent advice to the federal government on matters involving engineering and technology.”
“The overarching mission of Center for Engineering, Ethics and Society (CEES) [27] is to engage engineering leaders in examining the ethical and societal challenges of engineering and bringing them to the attention of the engineering profession and society.”
“The Online Ethics Center (OEC) [28] is maintained by the National Academy of Engineering (NAE) and is part of the Center for Engineering, Ethics, and Society (CEES). The CEES started in April 2007 and plans conferences and other research and educational activities under the direction of the CEES advisory group.”
This section of the course will satisfy the requirements of the Scholarship and Research Integrity (SARI) program, covering responsible conduct of research (RCR) issues, such as: the acquisition, management, sharing, and ownership of data; publication practices and responsible authorship; conflicts of interest and commitment; research misconduct (falsification, fabrication, and plagiarism); peer review; collaborative science; mentor/trainee responsibilities; human subjects protections; and animal welfare.
This lesson will take us one week to complete. Please refer to the Course Syllabus for specific time frames and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Read and familiarize yourself with all the Lesson 2 materials. |
Read | Week 2:
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Assignment | Week 2:
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If you have any questions, please post them to our Questions? discussion forum (not email), located under the Discussions tab in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
Scholarship and Research Integrity (SARI) program here at Penn State is an initiative for enriching and expanding education and support for issues facing graduate researchers in every field.
"Penn State is committed to modeling, teaching and promoting responsible conduct of research and scholarship within the University community. All scholars, from graduate students to senior investigators, confront ethical issues in their professions. The issues that require attention are constantly changing. While advances in technology and the ability to interact with colleagues across the globe have opened up vast opportunities for advancement, they have also created new challenges for the responsible conduct of research and scholarship.
Advance discussion of core principles and possible scenarios can help inform choices frequently made under pressure, helping to eliminate poor decisions. Penn State recognizes that we have a unique opportunity —and a responsibility—to address these issues in a proactive and deliberate manner."
The core principles of research integrity concern the avoidance of research fraud. Research fraud can be perpetrated in at least three main ways, namely through the falsification of the research record, the fabrication of data in the research record, and/or plagiarism (the representation of other(s) work without reference as your own). All three of these infractions of research integrity can have damaging results to individuals, even leading to wrongful death in some cases. Further, such situations can corrode overall public trust of scientific research itself, including research institutions.
A familiar scene of falsification of evidence can found while watching a courtroom television drama, where a law enforcement officer is portrayed as having tainted key evidence during the process of investigation and the suspect on trial is let go, even if the suspect may be guilty. Why does this happen? Why should someone, possibly a criminal, be let go because a piece of evidence was falsified, even if the rest of the evidence was not changed? The reasoning is that any conclusions based on or influenced by the falsified evidence cannot be sustained. Further, falsified evidence brings the validity of all of the other evidence in the case into question as well.
A article from the news illustrates the point: "In her order, [the Judge] -- a former prosecutor -- issued a scathing indictment of the prosecutor in that case for hiding evidence that [the murdered] was allegedly, a sexual predator who had molested [the murderer] and other children. [The Judge] said "evidence has plainly been suppressed," and accused former assistant D.A. of engaging in "gamesmanship" and "playing fast and loose." The judge also said [the prosecutor] "had no problem disregarding her ethical obligations" in an attempt to win."
Another way evidence can be falsified is if it is withheld, particularly if it demonstrates a counter argument, such as DNA evidence demonstrating the innocence of a suspect. If this data is available, but withheld, then it is also a form of falsification or misrepresentation of the available data. There are many similar analogies about falsification in law that also carry over to issues about falsification of data in science, engineering, economics, etc. While what ultimately constitutes proof and certainty in a court of law ("beyond the shadow of a doubt") is not the same that constitutes proof or certainty in science (>95%), the impacts and problems of falsification are very similar.
Falsification in sciences and engineering arise from manipulating research materials, equipment, or processes, or changing or omitting data or results such that research observations are not accurately represented in the research record. Falsification often occurs when a researcher chooses to omit data that goes against confirming a hypothesis, such as omitting to report harmful, but rarely observed, side-effects in Phase 1 or 3 trials of testing a new medication. In this context, falsification of data can lead directly to harming individuals who later take the medication.
Other forms of falsification not of the research ethics kind: There are times when data may be false for reasons of instrumental calibration, such as the recent example of the particles that were thought to be traveling faster than the speed of light, when later it turned out to be instrumental calibration issues. This particular issue does not constitute falsification.There is another notion of falsification in the sciences that should not be confused with the falsification of research data, namely, the falsification of a hypothesis. This simply means that a scientific hypothesis has been demonstrated to be logically false based on existing data.
There is an Aesop's Fable you may be familiar with, titled The Boy Who Cried Wolf, about a shepherd boy who shouts out to the local villagers that a wolf was attacking his flock, but when the villagers rushed to the scene, there was no wolf to be found. The boy did this multiple times, and each time, there was no wolf to be found. When a wolf actually did come to attack the boy's flock, the villagers had ignored the cries, thinking that it was a false alarm, and the boy's flock was destroyed by the wolf. The moral of this story is, at its root, about how being caught fabricating observations, in this case about a wolf, will inevitably lead to an erosion of trust in other claims.
Fabrication is making up data or results and recording them in the research record. Fabrication in research typically concerns the construction of data to fit or conform to a given test or confirm a particular hypothesis. Fabrication is no small issue in the sciences, and publishing work or releasing medicines based on fabricated results can bring big rewards. There exist numerous examples of fabrication in science, medicine, and engineering, many of which likely go undetected.
"Biomedical research has become a winner-take-all game — one with perverse incentives that entice scientists to cut corners and, in some instances, falsify data or commit other acts of misconduct," says senior author Arturo Casadevall of Albert Einstein College of Medicine.
The study reviewed 2,047 papers retracted from the biomedical literature through May 2012 and consulted the National Institutes of Health (NIH) Office of Research Integrity and Retractionwatch.com to establish the cause.
And the team found that about 21 percent of the retractions were attributable to error, while 67 percent were due to misconduct, including fraud or suspected fraud (43 percent), duplicate publication (14 percent), and plagiarism (10 percent). Miscellaneous or unknown reasons accounted for the remaining 12 percent.
"What's troubling is that the more skillful the fraud, the less likely that it will be discovered, so there likely are more fraudulent papers out there that haven't yet been detected and retracted," says Casadevall.
Perhaps you are working on writing a paper for a class and are on a serious deadline, plus you have to study for two midterms, and you have caught a cold, so are not feeling your best. While working on the paper, you decide you can save time writing by cutting and pasting large parts of supporting text from a rather obscure website (it was, after all, three pages into a web search.) You reason that the passages you cut-and-paste are quite appropriate to what you are trying to convey, and that it would be rather difficult to improve on what the author already wrote. Being rushed for time, you also "forget to quote" and/or properly cite the material you pasted into the paper. Upon grading the paper, the instructor catches your shortcut and has a meeting with you about this problem. You are informed by the instructor that this kind of shortcutting is called plagiarism and that you are going to receive an F for the course and a mark on your school record. You realize that this is rather problematic, and could even impact your ability to receive student loans. Then, you think that this seems rather harsh for such a minor infraction. Equally, you wonder, why would the penalty for copying answers on a test be met with equally harsh consequences? (Do some pullout work here on ethics spotting. Why do you think that there are ethical issues with copying work? Does it cause harm?)
How eager would you be to take a medicine for an ailment if you were not at all sure if either the medicine would work on your ailment – or if the side-effects of the medication were worse than the disease? How confident would you be in someone you never met saying that they "have your best interests" in mind when making decisions for you, such as ? On one hand, new medicines could not be brought to market if no one was willing to take part in early trials of the medicine. On the other hand, not many people would be eager to be among the first to test out a new drug for an ailment or life-threatening disease, unless the alternatives were definitively worse. Research is often conducted on humans, animals, living systems, and environments in ways that could impact the well-being (positively and negatively) of those subjects of research. Important ethical questions arise when we begin to ask how much those subjects know about the risks of partaking in specific research or how a specific intervention may impact their health. Further, ethical problems are compounded when the subject(s) of research or decision-making cannot speak or make decisions for themselves, such as for an unconscious patient on life support, or even for non-human subjects, like animals, plants, and ecosystems. The main ethical question that arises is whether a subject or stakeholder is able to consent to participating in research and/or decision-making, or what is referred to as "informed consent."
Having the capacity to give consent to being part of research, receiving a medical treatment with known risks (like surgery), and/or having decisions (including policies) about your welfare made on your behalf requires the ability to consent and be informed (and understand that information) well enough to make a well-grounded decision. The idea of informed consent, however, is only applied to humans who can consent. While consent cannot be given by animals, ecosystems, and other non-human subjects, the idea of consent is implicit in trying to come to a decision about the minimization of harms. This consideration of the well-being of non-human subjects unable to consent would widely apply, from animals in a laboratory setting to aquifers in a hydraulic fracturing (fracking) zone, and are typically taken into consideration through existing regulatory processes (such as the Institutional Review Board or Environmental Impact Assessments.)
The main concept to keep in mind here is the idea of consent, whether it be informed consent of a patient or research subject, or a form of representative consent, where a person or organization stands in for the concerns of the non-human subject(s) undergoing research or significant changes.
Each research institution which is able to receive grants from the U.S. Government for human and/or animal research is required to have an Institutional Review Board (IRB) that reviews proposals to assure the protection of research subjects. Examples of and reasons for requiring review of research that involves human subjects are numerous and multiple throughout medical and behavioral research. (History is full of horror stories about the treatment of medical and behavioral research subjects.)
While it may not be bio-medical research, if we are to learn what we can about the many social and behavioral aspects of renewable energy and sustainability systems, we will need to research topics such as patterns of consumption, energy use, patterns of traffic flow, individual psychology, response to risks, etc. Behavioral and social requires the study of research subjects, which will require a review of the research by the institution's own IRB.
Penn State has very extensive Institutional Review Board (IRB) resources as part of the Office for Research Protections (which all research falls under.) This lesson is in no way a replacement for the extensive educational resources and regulatory support. See the following resources for more: Penn State's Institutional Review Board [35] and Penn State's Office for Research Protections [36].
The treatment of research subjects and medical patients can be approached through a basic principle (easy in theory, but not in practice) that subjects ought to be treated how they want to be treated. The difficult part can be in determining whether subjects understand the risks of the procedure or research in which they are partaking. Further, protecting the identity of information and research data about a subject is required (privacy and confidentiality) if no harm comes to the subject from the information generated by the research (such as a pre-existing condition or genetic marker for a specific disease). Subjects that are experiencing conditions that could compromise or coerce subjects into agreeing to research or treatments that may not be in their best interests.
From 1850 to 1920, roughly 85% of the old-growth forests in the United States were cut down. Much of this lumber fed the early iron and steel mills and resulted in the industrial expansion of the United States, and many of these areas have since been reforested. Nevertheless, this expansion impacted or even eradicated the landscapes and ecosystems of many different species. Further, this exact pattern of rapid deforestation has been occurring in the Amazon rainforest since 1972, beginning with the building of interior highways. (By 2013, approximately 800,000 km2 of rainforest will have been cleared since 1970, roughly the size of France and Italy combined.) The loss of respiration from the trees (keeping humidity in the region constant) has resulted in multiple problems in the Amazon river basin, from extreme flooding to droughts. How do we being to judge the loss of such services that the rainforest itself provides? How do we clearly compare the costs of the loss of such ecological services, such as clean water and protection from floods, to the financial benefits and economic developments such activities bring with them?
Environmental and ecological systems can be significantly impacted by human intervention. Animals, plants, schools of fish, even entire ecosystems are impacted by human consumption patterns, particularly in the history of energy production. Animals, particularly mice, are continually used to test new drugs, the toxicity of chemical compounds, the potential for cancer from exposure, etc. Further, animals are designed to produce necessary human medicines, such as insulin from pigs, or now even organs in sheep grown with human tissue (20% by genetics) to decrease the chances of organ transplant rejections, and bacteria are being designed to produce ponds of biofuels.
As discussed previously, we can do our best to ensure human subjects and patients are able to consent to take part in research or a medical procedure, or someone who may represent their best interests can typically speak for that person's wishes (such as towards the end of life, when a person may be impaired). However, thinking about consent for something like a lab mouse or a landscape does not make sense. How would a lab mouse want to be treated? (Probably not how most of them are treated.) Is it right to introduce engineered genetics into the environment that could breed into native species of plants, changing the inherited genetic structure of the plant forever, such as genetically modifying corn engineered for biofuels?
For human subjects research, the Office for Research Protections (ORP) requires research to be approved through the Institutional Review Board (IRB). For animal subjects research, the ORP requires review by the Institutional Animal Care and Use Committee (IACUC). For environmental based research, such as for biofuels, an Environmental Impact Assessment (EIA) is typically conducted on the part of the researcher. (Check to see here if there is a review board for this.) Regardless, procedures for assessing environmental factors need to be significantly improved, particularly under the principles and goals of sustainability.
Source: Committee for the Update of the Guide for the Care and Use of Laboratory Animals (2010). Guide for the Care and Use of Laboratory Animals, Eighth Edition.
Source: Based on the United Nations Environment Programme: Abaza, H., Bisset, R., & Sadler, B. (2004). Environmental impact assessment and strategic environmental assessment: towards an integrated approach. Geneva, UNEP.
A stakeholder is an entity which has a specific interest in the outcomes of a given action, such as a project or change in policy. 'Entities' here can refer to individual citizens, organizations, business, groups of people, systems, ecosystems, or even members of future generations. To have a stake in something means to be in some manner or another impacted by the outcomes of the action proposed or completed. Precisely who or what all the stakeholders are in a given action is not necessarily clear before the action is completed and an impact analysis conducted. Nevertheless, there is an obligation based on principles of basic social justice and democratic processes to determine what the impacts of a given action could possibly be and to whom or what.
An action can have a wide variety of impacts. However, those impacts depend on the standpoint of the stakeholder. One stakeholder may have received a very good deal out of the action while for the other stakeholder the outcome was negative. For example, say you have a small house in the woods by a stream which you use to drink and water your garden with on dry days, the excess from which you make a small bit of money. Along comes a gold prospector who, now living up the stream from you, decides to dam the stream up in the search for gold. You now only have access to a small trickle of the water you just had access to the day before. (What would you do?) Obviously, the outcomes of a given action are rather different depending on the stakeholder's standpoint. (Not all outcomes have to be so stark in comparison.) We might call these two individuals primary stakeholders, while those benefiting from the prospector's gold and those who may not be able to any longer purchase the farmer's vegetables may be referred to here as secondary stakeholders. Those individuals who would able to go in and require the prospector to dismantle or at least minimize the impact of the gold mining operation would be referred to here as key stakeholders, who hold power over the outcomes of the action but may or may not be impacted by the action.
Some stakeholders are not able to represent their interests during a consideration of impacts, for example, an endangered environment, ecosystem, or species is obviously not able to represent 'its' interests in human decision-making processes. As such, these kinds of stakeholders require representative proxies for their interests, which often come in the form of special interest NGOs. There are also many groups of individuals (humans) that are unable to properly enter into the decision-making process for reasons of gender, race, class, economic status, social status, or otherwise. Assuring that outcomes and impacts of actions do not adversely affect those stakeholders that cannot represent themselves requires a comprehensive stakeholder analysis and includes representations of those interested that cannot readily represent themselves. Why is this necessary? Because the dominant financial and political forces will almost always work in their own best interests, leverage what power they have. This is, in fact, the crucial difference between stakeholder in an action and shareholder in a company.
The product of a well-conducted stakeholder analysis ought to produce a shared balance of benefits/burdens from a given action and, foremost, not impact those in a weak position or otherwise unable to represent their own interests. A fair process requires the consideration of possible impacts to the primary stakeholders, secondary stakeholders, and key stakeholders. Basic procedural fairness usually necessitates a partially to completely open process where stakeholders are able to give light to their perspective on the impacts from the initial conception of the action. A stakeholder analysis is likely to produce the best results (perceived as fair) when conducted early on in the process of deliberation around a decision or action so engagement with all interested stakeholders can begin. The stakeholder analysis process is a mapping out of people, groups, or systems that hold a stake in the outcome of the action. Initially, a stakeholder analysis can be done by theoretically mapping out the possible impacts on stakeholders of a given decision or action. Mapping out in a real process requires direct representation from the members of the group, i.e., as effective as it may be, it is improper to assume a stakeholder's standpoint is a given. Taking our previous example of the gold prospector and the gardener, it would probably be improper and incorrect for the prospector to assume that if the gardener minded the loss of streamflow, his land could be purchased for a good sum of money.
A significant motivating factor for conducting research and moving it forward is receiving credit for the research and findings. Credit is given to those who play a significant role in shaping the research and/or interpretation of results. Authorship, either of papers, project proposals, architectural plans, etc., is a primary aspect of the distribution of one's work and a necessary aspect of moving a career forward in many fields. In academic research settings, authorship and credit provide the foundations by which a researcher is evaluated. The more prestigious the journal is, the higher the impact the research is likely to be perceived to have, the more prestige the researcher. In business and policy planning, credit and acknowledgment can depend on and be evaluated based more on team and leadership performance than in academic settings. Regardless of the context, "credit where credit is due" seems an apt phrase to describe what it takes to move a career forward.
Acknowledgment comes in many forms, again, depending on the context. In a commercial environment, acknowledgment may take the form of upholding patents, which may be licensed and put to use in other products. In an academic environment, acknowledgment comes in the form of citing previous works and findings upon which the current research is based. In a laboratory environment, acknowledgment may come in the form of providing credit to technicians either through co-authorship or in an acknowledgments section. Acknowledgment sections of books often cite specific examples of how certain individuals helped to shape the author's thinking around a particular point.
"The reward individual scientists seek is credit. That is, they seek recognition, to have their work cited as important and as necessary to further scientific progress. The scientific community seeks true theories or adequate models. Credit, or recognition, accrues to individuals to the extent they are perceived as having contributed to that community goal. Without strong community policing structures, there is a strong incentive to cheat, to try to obtain credit without necessarily having done the work. Communities and individuals are then faced with the question: when is it appropriate to trust and when not?"
Longino, Helen, "The Social Dimensions of Scientific Knowledge [44]," The Stanford Encyclopedia of Philosophy (Spring 2013 Edition), Edward N. Zalta (ed.), URL = <plato.stanford.edu/archives/spr2013/entries/scientific-knowledge-social/>.
Authorship of a publication implies both taking credit as well as responsibility for what is published. This can sometimes be a challenge in interdisciplinary or large team contexts, where trust in others' work is an established necessity. Even though most fields and even different labs will have slightly, if not completely, different standards for deciding on the order of authorship, what constitutes a viable contribution is fairly similar across fields.
"The list of authors establishes accountability as well as credit. When a paper is found to contain errors, whether caused by mistakes or deceit, authors might wish to disavow responsibility, saying that they were not involved in the part of the paper containing the errors or that they had very little to do with the paper in general. However, an author who is willing to take credit for a paper must also bear responsibility for its errors or explain why he or she had no professional responsibility for the material in question."
(pg. 37) National Research Council. On Being a Scientist: A Guide to Responsible Conduct in Research: Third Edition. Washington, DC: The National Academies Press, 2009.
John Hardwig (1985) articulated one philosophical dilemma posed by such large teams of researchers. Each member or subgroup participating in such a project is required because each has a crucial bit of expertise not possessed by any other member or subgroup. This may be knowledge of a part of the instrumentation, the ability to perform a certain kind of calculation, the ability to make a certain kind of measurement or observation. The other members are not in a position to evaluate the results of other members' work, and hence, all must take one anothers' results on trust. The consequence is an experimental result, (for example, the measurement of a property such as the decay rate or spin of a given particle) the evidence for which is not fully understood by any single participant in the experiment."
Agree on the order of authorship beforehand, if at all possible. Sometimes authors get pulled into a publication later in the process, but even then some agreement on the order of authorship ought to be arrived at before sending off a manuscript for review.
Contribution. Authorship is generally limited to individuals who make significant contributions to the work that is reported. This includes anyone who:
Steneck, Nicholas H. 2007. ORI Introduction to the Responsible Conduct of Research [45]. [Rockville, Md.]: Dept. of Health and Human Services.
When credit as a co-author is not appropriate for a given publication, extended collaborators and external advisors will often be given credit in an acknowledgment section, usually at the beginning of a paper and at the end of a book. Robert Day provides a helpful description here which provides some excellent rules of thumb for how to approach an acknowledgments section in a publication. These rules of thumb are proper to consider for a variety of contexts which require extending the social courtesy of acknowledging the contribution of another's input.
First, you should acknowledge any significant technical help that you received from any individual, whether in your laboratory or elsewhere. You should also acknowledge the source of special equipment, cultures, or other materials. You might, for example, say something like "Thanks are due to J. Jones for assistance with the experiments and to R. Smith for valuable discussion."
Second, it is usually in the Acknowledgments wherein you should acknowledge any outside financial assistance, such as grants, contracts, or fellowships.
A word of caution is in order. Often, it is wise to show the proposed wording of the Acknowledgment to the person whose help you are acknowledging. He or she might well believe that your acknowledgment is insufficient or (worse) that it is too effusive. If you have been working so closely with an individual that you borrowed either equipment or ideas, that person is most likely to be a friend or a valued colleague. It would be silly to risk either your friendship or the opportunities for future collaboration by placing in public print a thoughtless word that might be offensive. An inappropriate thank you can be worse than none at all, and if you value the advice and help of friends and colleagues, you should be careful to thank them in a way that pleases rather than displeases.
Furthermore, if your acknowledgment relates to an idea, suggestion, or interpretation, be very specific about it. If your colleague’s input is too broadly stated, he or she could well be placed in the sensitive and embarrassing position of having to defend the entire paper. Certainly, if your colleague is not a coauthor, you make them a responsible party to the basic considerations treated in your paper. Indeed, your colleague may not agree with some of your central points, and it is not good science and not good ethics for you to phrase the Acknowledgments in a way that seemingly denotes endorsement." Day, Robert. “How to Write and Publish a Scientific Paper: 5th Edition” Oryx Press, 1998.
Remember, there is nothing really scientific about the Acknowledgments section, it is simply about courtesy.
The motivation for credit and acknowledgment is a significant driver behind the push to publish or patent from research. With rapid communications that support the dissemination of research, new findings can propagate quickly. Digital communications combined with increasingly competitive environments create further pressure to disseminate findings quickly. In circumstances of urgency, such as with an infectious disease, timing is critical, but so is accuracy in data and interpretation. In most cases, research and development occurs within a predictable cycle, perhaps dictated in the terms of the grant or business cycle. Research findings ought to be submitted in a timely manner and, for federally funded research, made available along with the data. Different funders have different expectations for what to do with findings. For companies, much is often not shared due to what they may argue is protection of trade secrets, which makes it more difficult to review certain claims.
Submitting research findings for peer review is one way journals and researchers check the work of their colleagues. While the peer review process is a quality check of the work, it is not a foolproof process, and errors can get through. For multidisciplinary teams, the lead author may not be able to evaluate the validity of certain sections of a paper, in which case the lead author ought to find a colleague capable of giving feedback on such content.
"Investigators are expected to promptly prepare and submit for publication, with authorship that accurately reflects the contributions of those involved, all significant findings from work conducted under NSF grants. Grantees are expected to permit and encourage such publication by those actually performing that work, unless a grantee intends to publish or disseminate such findings itself.... Investigators are expected to share with other researchers, at no more than incremental cost and within a reasonable time, the primary data, samples, physical collections and other supporting materials created or gathered in the course of work under NSF grants. Grantees are expected to encourage and facilitate such sharing. Privileged or confidential information should be released only in a form that protects the privacy of individuals and subjects involved. General adjustments and, where essential, exceptions to this sharing expectation may be specified by the funding NSF Program or Division/Office for a particular field or discipline to safeguard the rights of individuals and subjects, the validity of results, or the integrity of collections or to accommodate the legitimate interest of investigators."
National Science Foundation Award and Administration Guide [46]
A conflict of interest can arise when there are competing interests in a particular project or line of research that hinder the capacity for clear judgment and unbiased analysis. We want to avoid conflicts of interest to avoid social favoritism (cronyism and nepotism), the preference of familiar people and things (the mere-exposure effect), favoritism towards funding sources (funding outcome biases), bias in review of other projects based on competing interests, self-favoritism (egotism), internal review (self-policing), etc. Bribery, described in further detail below, presents an immediate conflict of interest.
Bribery means to take or offer something in exchange for favoritism. Bribery presents a very immediate and obvious conflict of interest that requires a “gift” in exchange for preferential treatment. These kinds of “gifts” can come in various forms, such as kickbacks for accepting a bid; money, goods, services, or favors for “looking the other way”; use of information to blackmail someone; using knowledge for personal financial gain, such as insider trading; and use of position of authority for personal gain, particularly in government-related positions.
Gifts and bribery do not always come in the form of money or forms of obvious payment. Basically, if you would not feel comfortable in people knowing about the transaction or favor, then it is probably not a good idea to engage in the exchange.
Disclosure is the primary means for addressing possible conflicts of interest, for similar reasons to those in our disclosure to Subjects and Stakeholders (Lesson 2, Part 2 [50]). It might be obvious to state that the easiest way to avoid COIs is to be able to know about them in advance. This is why identifying and disclosing known COIs is the best way to avoid the mistrust that may come from them. In other words, information and access to that information about possible conflicts of interests is still the best way to avoid them.
The external perception of a conflict of interest, even if it feels as though none exists, is enough to put projects, CEOs, and/or entire companies at risk. Integrity is typically based on a person or company’s record for avoiding conflicts of interest and in “fair dealings.”
Penn State, like most major research universities, has an extensive COI policy. For the full policy and requirements for individual reporting, you can read through Penn State's Research Administration Policies Research Protections [51]. All researchers receiving federal funds must report any possible financial conflicts of interest at least once per year, and within thirty days if one does arise. Penn State defines the purpose of the policy as the following:
"The purpose of this Policy is to maintain the objectivity and integrity of Research at The Pennsylvania State University (the “University”) and to ensure transparency in relationships with outside Entities and individuals as they relate to the academic and scholarly mission of the University. Among its many missions, the University seeks to foster interactions between the private sector and academia, as interdisciplinary and translational research is of ever-increasing importance in transforming newfound knowledge into useable technologies and scholarship that benefit the public. There is, however, the potential for financial conflicts of interest in such collaborations. In most cases those conflicts can be managed appropriately, rather than eliminated, thereby enabling those involved in University Research to engage in that Research objectively and with integrity and at the same time maintain acceptable financial relationships with outside Entities and individuals. Disclosure of financial interests to the University will protect both investigators and Penn State from potential criticism or even government sanctions in the event such relationships are subsequently called into question."
As you will see in the following example, corporations also have a significant interest in keeping conflicts of interest from occurring.
Let us look at what the company ArcelorMittal defines as conflicts of interest in its Code of Business Conduct [52].
ArcelorMittal recognizes that we all have our own individual interests and encourages the development of these interests, especially where they are beneficial to the community at large.
However, we must always act in the best interests of the Company, and we must avoid any situation where our personal interests conflict or could conflict with our obligations toward the Company.
As employees, we must not acquire any financial or other interest in any business or participate in any activity that could deprive the Company of the time or the scrupulous attention we need to devote to the performance of our duties.
We must not, directly or through any members of our families or persons living with us or with whom we are associated, or in any other manner:
We must inform our supervisor or the Legal Department of any business or financial interests that could be seen as conflicting or possibly conflicting with the performance of our duties. If the supervisor considers that such a conflict of interest exists or could exist, he or she is to take the steps that are warranted in the circumstances. If the case is complex, the supervisor is to bring it to the attention of the Vice-President of his or her division, the Chief Executive Officer or the General Counsel.
We must not profit from our position with ArcelorMittal so as to derive personal benefits conferred on us by persons who deal or seek to deal with the Company. Consequently, accepting any personal benefit, such as a sum of money, a gift, a loan, services, pleasure trips or vacations, special privileges or living accommodations or lodgings, with the exception of promotional items of little value, is forbidden.
Any entertainment accepted must also be of a modest nature, and the real aim of the entertainment must be to facilitate the achievement of business objectives. For example, if tickets for a sporting or cultural event are offered to us, the person offering the tickets must also plan to attend the event. In general, offers of entertainment in the form of meals and drinks may be accepted, provided that they are inexpensive, infrequent, and, as much as possible, reciprocal.
As these instructions cannot cover every eventuality, we are all required to exercise good judgment. The saying «everybody does it» is not a sufficient justification. If we are having difficulty deciding whether a particular gift or entertainment falls within the boundaries of acceptable business practice, we should ask ourselves the following questions:
Is it directly related to the conduct of business? Is it inexpensive, reasonable, and in good taste? Would I be comfortable telling other customers and suppliers that I gave or received this gift? Other employees? My supervisor? My family? The media? Would I feel obligated to grant favours in return for this gift? Am I sure the gift does not violate a law or a Company policy?
In case of continuing doubt, we should consult our Supervisor or the Legal Department.
This lesson will cover the basic principles of global climate change and how the warming of the climate is driving the push towards innovation and adoption of renewable energy technologies, processes, policies, and cultures. This lesson will look at the push for renewables as a necessary condition for beginning to address the climate problem at its main source, namely, greenhouse gasses emitted as a byproduct of the burning of fossil fuels and other industrial processes. The call to address climate change is, at its root, an ethical imperative which further underpins the drive for renewables.
This lesson will take us one week to complete. Please refer to the Course Syllabus for specific time frames and due dates. Specific directions for the assignment below can be found in this lesson.
Requirements | Assignment Details |
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To Do | Familiarize yourself with all the Lesson 3 Readings and assignments. |
Read | Week 3:
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Assignment |
Week 3: Post questions and comments in the discussion forum. To post, go to the course in Canvas, click on Lesson 3 folder, and post to Lesson 3 Discussion. Complete Ethics Matrix 2 and Stakeholder Analysis Worksheet. To submit, go to the course in Canvas, click on Lesson 3 folder, and click on Submit Ethics Matrix 2b and Stakeholder Analysis Matrix. |
If you have any questions, please post them to our Questions? discussion forum (not email), located under the Discussions tab in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
The links between energy use and the global warming of the atmosphere are significant. In 2011, the global total output of CO2 from energy production was 32,579,000,000 metric tons (32.6 Gigatons) or 71,824,400,397,211 pounds. That is just for one year, for energy consumption alone.
First, read Chapter 1 of the IPCC report on Renewable Energy (RE) and climate change.
This is a rather complex document with a significant amount of data and figures, and it is sometimes easy to lose the thread of the argument. This document expects you to already know something about how climate change works. For a quick background on how the greenhouse effect works, please have a look at HyperPhysics [58] and University Corporation for Atmospheric Research (UCAR) [59].
In Chapter 1 of the IPCC RE Report:
In Part 1, you read about the linkages between energy, renewables, and climate change. Now, read the International Energy Agency's Methodology for the "450 Scenario" and Chapter 8 of 2012 World Energy Outlook.
This report by the IEA works through various energy policy scenarios based on requirements to meet certain targets.
Biofuels are fuels generated through the processing of biomass for energy. They can be solids, in the form of biofuels like wood derivatives (pellets, paper, charcoal, etc.), digested biomass (like cow dung). They can be liquids, like biodiesel, ethanol, and methanol. Or they can be a gas, like methane. The advantage to biofuels is that they can be a very useful way to store and transport (solar and chemical) energy that is immediately available for use, like fossil fuels. As well, biofuels present possible opportunities for zero-carbon emissions (over the lifecycle). The difficulties biofuels present are mainly that: biofuels are more processing intensive and expensive than fossils; biofuels also require significant land and resources that can compete with needs for food crops, thus driving up prices on food; and that biofuels, if not managed correctly, can produce very little reduction in overall emissions for a significant cost. In this module, you will learn about the various types of biofuels, learn of reasons why a lifecycle analysis is required to determine the value of a biofuel process, and investigate.
This lesson will take us two weeks to complete. Please refer to the Course Syllabus for specific timeframes and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Familiarize yourself with all the Lesson 4 Readings and assignments. |
Read |
Week 5: Week 6:
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Assignment |
Week 5: Draft of Ethics Matrix 2b (Broader Social and Environmental Impacts) and the Stakeholder Analysis Matrix. Post questions and comments in the discussion forum. To post, go to the course in Canvas, click on Lesson 4, post on Lesson 4 Discussion. Week 6: Apply Ethics Matrix 2b (Broader Social and Environmental Impacts) and the Stakeholder Analysis Matrix in an analysis of biofuels. That is, fill out the matrices and use them to help you identify significant stakeholder and ethical issues and write up an analysis that broadly identifies ethical considerations in the three main categories and discusses the relationship of those issues to the stakeholders. This should be roughly 600-750 words in length. To submit, go to the course in Canvas, click on Lesson 4, submit to Assignment 4 - Analysis of Biofuels. |
If you have any questions, please post them to our Questions? discussion forum (not email), located under the Discussions tab in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
Biofuels are fuels generated via a biological/metabolic process. Biofuels can be in a solid, liquid, or gas form. (Fossil fuels are basically very old, i.e., fossilized, biofuels.) Biofuels are actually the oldest among all fuels used by human populations, readily available in forms such as burning wood and dung. Liquid biofuels, such as ethanol and biodiesel, are particularly appealing because they are intended to replace traditional fuels, like gasoline and diesel. Unlike fossil fuels, biofuels are renewable in that they can be grown, for the most part, on demand (within typical biological constraints.) Depending on the method, biofuels are typically "carbon neutral" in that the CO2 released during their burning is CO2 that was captured and stored as a carbohydrate (through photosynthetic respiration). The "carbon neutral" aspect, along with the useful (transportable) form of liquid fuels, makes biofuels quite appealing as part of a broader renewable energy strategy.
This lesson focuses on the Nuffield Council on Bioethics report on the ethics of biofuels. Within this report, you should gain an understanding of the history of biofuels, how biofuels are produced, why biofuels are appealing, different biofuels pathways for current and future production, and the main ethical issues that arise in the production of biofuels.
In the Nuffield Report, you need to pay particularly close attention to the various ethical arguments laid out in chapters four and five. Each of the six ethical principles suggested in the Nuffield Report, (Human Rights, Environmental Sustainability, Climate Change, Just Reward, Equitable Distribution of Costs and Benefits, and Duties) is an example of a broader social and environmental impacts issue. (Note: These categories correlate to EDSR matrix 2b.)
Corresponding reading: Pages 8 - 43 of the Nuffield Report on Biofuels.
What should be apparent from reading the Nuffield Council on Bioethics Report on Biofuels is that all biofuels pathways require us to think about the wide variety of possibly significant impacts that growing and processing feedstocks could have on populations and environments. All of these impact factors need to be taken into proper consideration when making an argument for a particular biofuels pathway. (Note: For those thinking about nonmarket aspects of biofuels, evaluation of the various impacts is essential to putting forward any sound strategy.)
This course presents you with a few tools for identifying the range of possible broader impacts that could emerge from any large systems project, such as increasing biofuels production. Of course, there are a wide variety of broader impacts that may not present any ethical problems; but, here, we are going to focus on those impacts that do, or could present ethically significant issues in the consideration and evaluation of any renewable energy or sustainability strategy.
In Lesson 1.2, you were introduced to the concept of Broader Social and Environment Impacts as part of the EDSR framework. In Lesson 2.1, you were introduced to questions concerning the ethical treatment of stakeholders and nonhuman subjects, which includes the idea of a system as a subject. (The reason why the treatment of stakeholders and nonhuman subjects is considered a professional integrity issue is that these considerations ought to be a normal part of professional practice. In other words, the consideration of stakeholders and nonhuman subjects should be considered in terms of a direct impact and not necessarily a broader impact.) For this lesson, you will evaluate across the three dimensions of systems ethics (Matrix 1) and conduct a stakeholder analysis (Stakeholder Matrix).
This is an example of the applying the Broader Social and Environmental Ethics Matrix (2b) to the case of U.S. Corn Ethanol production. This example attempts to find something for every subcategory here; however, some of these subcategories may not be relevant for all cases. For your own assignments, try to identify at least the most ethically relevant of the subcategories.
Public education about biofuels requires the explanation of methods, benefits, impacts, and trade-offs in using the fuels. More public platforms to learn about biofuels ought to be made readily available. My suggestion would be to engage NASCAR, here in the U.S., and try to convince them to run their races only on biofuels, which their own team would need to "brew." This way, fans could likely be interested enough to learn about the various aspects of biofuels. (Of course, now the stock cars would be running the "moonshine" in their tanks instead of running it in their trunks.) Stock cars aside, biofuels are still the most significant form of energy consumed by 3/5 of the human populations. Biofuels are used, most significantly, in rudimentary cooking and heating applications throughout the world. While we can think about second and third generation biofuels, much of the world uses some form of rudimentary biofuel as part of their daily routine.
Advancement of learning and understanding while promoting teaching ought to, first and foremost, consider the needs of those populations most dependent on biofuels for their daily survival. We ought to, as well, do better about educating "ourselves" about the needs of those groups (depending on more rudimentary biofuels) and educating those societies dependent on more industrialized forms of energy production and consumption about how their practices impact other's access to rudimentary biofuels. Corn biofuels are especially problematic, even under the most ideal of conditions. Corn biofuels require significant inputs of CO2 intensive fertilizer production and fresh water. (~100 gallons of water to grow a gallon of fuel.) Reaching out to communities that may be impacted by corn biofuels ought to learn the trade-offs that need to be made.
In conducting a stakeholder investigation, we can see many possible areas where underrepresentation of particular groups is likely to pose a significant ethical issue. Public participation in the decision-making process is essential to bringing to light the challenges and problems that the spectrum of groups may face, but without a specific process that gives voice and credence to minority interests, most minority perspectives would go unconsidered. Many environmental injustices are based on social and economic status. In terms of corn ethanol, a wide variety of farming communities could be impacted. As well, indirectly, those communities that consume corn as a main food staple could be impacted. Bringing together and voicing these various perspectives beforehand could lead to better, i.e., less impactful, decisions on the front end. At the very least, typically underrepresented communities ought not be negatively impacted by the cultivation and processing of corn for use as biofuels.
In terms of corn based biofuels, research and education can be readily observed in action through agricultural extension programs, such as those at Penn State. International biofuels research networks have been established to support rapid knowledge and technology transfers. As well, there are industry specific organizations, such as aviation, that are seeking to understand the best way to integrate biofuels to meet their needs. Once a biofuel pathway is established, a commitment is implicitly made to maintain education and innovation.
How well is research about the latest developments in biofuels being disseminated? If the latest research happens to demonstrate that corn based ethanol is neither sustainable nor all that economically viable? If the research ends up in academic journals, is it getting in front of the right audience? Are the results of the research being "translated" into terms that a lay audience may understand?
Corn biofuels present a variety of economic benefits to the corn farmers, fertilizer producers, the seed industry, and others that would see economic gains from a move to corn ethanol. However, there are many significant problems with corn based biofuels, covered in other sections below.
Regulatory support via farming and energy based subsidies for corn based biofuels can prove problematic for other biofuel strategies. Overall, regulations are going to be necessary if biofuels are to be adopted. Regulations will typically affect some aspect of the transport industry to change fuel standards such that a certain percentage of biofuels are mixed in with regular fossil based fuels. The airline industry in the U.S., for example, is committed to trying to achieve a 20% biodiesel mix for all short haul passenger flights. (This is near the maximum that the current generation of engine technology can take.) Corn based ethanol will likely be de-emphasized as a regulatory priority once cheaper and less land-use / water-use intensive processes become readily available.
Adopting corn biofuels requires accepting certain application and infrastructure commitments that may not have been made explicit in the decision-making process about adoption. There are ethical implications to requiring secondary stakeholders to take on certain commitments, from car companies whose engines need to be able to accept the higher ethanol based fuels to the farmers who have to grow a corn in a way that requires buying into the "big agricultural" system or face not being competitive.
When it comes to new and innovative methods for producing biofuels, is there an obligation to transfer those methods to other countries, particularly those most in need of energy development opportunities? On the other hand, is there also an obligation to make sure that any such technology being transferred is indeed appropriate for the location and context? For example, would it be a good idea to try to get countries where corn is the main food staple to also try to invest heavily in corn biofuels? If technology does get transferred (such as genetic technology of the corn, the fermenting and refining facilities, and the biochemistry of the catalysts), then is the appropriate knowledge and training also transferred so that local populations can run the corn ethanol systems?
What scientific, technical, and economic research on corn ethanol is being used to make decisions? Is the research produced by a company, by academic researchers, public/private partnerships, think-tanks, etc? Is the research being used appropriate to the decision-making context (climate, soil conditions, water resources, trained experts)?
Is research being used at all when decisions are being made about corn ethanol pathways? Does the evidence about the viability of corn ethanol support the decisions being put forward? Is the evidence being used representative of all the research, or is the evidence being "cherry-picked" by those advocating a certain policy direction? (Think of the spectrum of lobbying interests here.)
Corn ethanol presents significant distributive justice concerns in terms of land-use impacts, water resource impacts, and food vs. fuel considerations. For example, when the price of corn in the U.S. climbed rapidly due to a new regulatory emphasis on corn ethanol production, this directly affected the price of white corn which also went up quickly in Mexico, due to NAFTA regulations. As white corn is the main food staple for a large majority of the Mexican population, poorer populations were finding it difficult to purchase enough white corn for tortillas to feed themselves. This was also due to the fact that many Mexican farmers decided to grow yellow corn because they could get much more for the yellow corn on the North American market than they could for the white corn on the local market.
Decisions get made through a process, but who gets included in that process? While there really is no perfect procedure that can take into account every single perspective when making a decision, there is an ethical obligation to identify the stakeholders (including the 'silent stakeholders') most likely to be impacted and include those voices in building consensus towards a decision. How inclusive of various stakeholder perspectives were the decisions that were made about supporting the adoption of corn ethanol in the U.S.? Were the decision-making procedures influenced mainly by Congressional lobbyists? Or, were there public hearings and attempts to survey public opinion before commitments were made?
How far along in duration does the consideration of impacts extend? Selecting and committing to corn ethanol would not only set up commitments for current populations, but also for future generations. Does corn ethanol provide enough CO2 reductions to improve climatic conditions for future generations, or are there other biofuels options that could address these needs better?
Two forms of retributive justice can be considered in the context of corn ethanol. First, the production of corn ethanol did make it difficult for some families to be able to afford enough of their staple food. Market interventions by the president allowed for subsidies of white corn production, even though it went against NAFTA free trade agreements. Second, do companies in the corn ethanol conduct certain practices that go against regulations? Emissions can come at a variety of points throughout the production process. Are those industrial firms correctly reporting all emissions? If not, and they get caught, are they being punished at a rate high enough to discourage further emissions?
For the most part, nothing really changes for those who use liquid fuels for transportation. Corn ethanol is appealing to many because there is so little difference to the end user between it and what they already use. People may seek out corn ethanol on a preferential basis, but there are no significant transformations in how business is done. Those that may be most impacted on a day to day basis are the farmers that are most likely to be impacted by a significant shift to corn based biofuels.
Corn biofuels do not readily present a different and evolutionary take on energy systems that would take us away from dangerous levels of emissions. Other biofuels do this much better, such as large biodigesters located in a densely populated area which could significantly improve public understanding and appreciation of turning waste into energy while at the same time capturing the CO2 that would otherwise be emitted. Again, unless there was a radical public information campaign (such as NASCAR intentionally adopting corn ethanol as its fuel) corn ethanol does not present significant outreach opportunities that improve the chance of other more effective biofuels.
Does corn ethanol present enough of an energy solution that it will likely change how we go about procuring and using energy? Based on the overall energy and CO2 payback of corn ethanol, it does not seem likely shifts would be coming to our energy economy. In fact, if you begin to look at longer-term trends in automobiles, you see that a shift to electric cars is relatively inevitable, depending primarily on a transformative shift in battery storage solutions. There will be a move away from liquid fuels for ground transportation purposes within the next decade. (Most urban transport in the U.S. runs on either electric or CNG.)
Corn ethanol presents a series of risks ranging from eutrification and other forms of pollution to local water sources and overuse of water resources, particularly where fossilized (non-replenished) water is being used for agricultural purposes in corn farming, such as in regions of the U.S. Southwest. Risks of continuing dependence on natural gas resources in the production of nitrogen fertilizers via the Haber process. Risks are also present in the politics and economics of GMO crops, where genetic content is transmitted via pollen to non-interested parties, and, to make matters worse, that pollen can produce seed that is genetically licensed, so is subject to copyright and intellectual property laws. Who identifies and assesses the risks presented by corn ethanol? Are those risks being taken seriously? Are the risk assessments being conducted by non-interested parties?
The principle essentially states that, in the face of uncertainty about outcomes, one must proceed with caution. For the most part, corn ethanol does not present many uncertain risks in its production and consumption. The risks of corn ethanol, as mentioned above, are relatively well known. This does not mean, however, that one should roll out a massive biofuels plan based on corn ethanol. Many uncertainties do remain, such as the long-term impacts of turning away from other biofuels pathways.
For corn biofuels, an emerging risk would be increased problems due to water consumption. Further, climatologists are currently predicting a massive 1000-year drought coming for the West and Midwest, i.e., much of the corn belt. If all our "eggs" were put into the corn ethanol basket, such a drought would likely cripple that part of the energy economy. This is an emerging risk that requires our close attention now. This goes for all biofuels being grown as crops in that region.
While not entirely exhaustive, this represents a fairly thorough sketch of the wide variety of possible broader social and environmental impacts presented by corn ethanol pathways. Ideally, each of these issues would have a form of resolution that could be designed and planned for as part of a way to improve the outcomes of corn ethanol systems.
Innovations in solar energy, specifically photovoltaics, have seen significant progress in efficiency and installation area over the past decade. The further production of photovoltaics is a necessary component for any sustainable energy portfolio. Industrial choices of raw materials, their use, flows, and wastes are central to many aspects of industrial ecology. In the case of solar materials, there are significant broader impacts questions around strategic mineral availability, mining impacts, toxicity in manufacturing, and material lifespan and end of use. The determination of system boundaries for material life cycle analysis require significant considerations of issues such as selection of cognitive values when choosing sustainability indicators, classification of boundaries (closure of sets), and framework assumptions about how materials are consumed and circulated.
This lesson will take us one week to complete. Please refer to the Course Syllabus for specific time frames and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Watch and familiarize yourself with all the Lesson 5 materials. |
Read and Watch | Week 7:
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Assignment | Week 7:
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If you have any questions, please post them to our Questions? discussion forum (not email), located under the Discussions tab in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
Examine possible correlations between independently acquired datasets dynamically using open source methods and sources.
This lesson will take us one week to complete. Please refer to the Course Syllabus for specific timeframes and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Read and familiarize yourself with all the Lesson 6 materials. |
Read | Week 9: Read the following articles, in order:
(Note, yes, you are supposed to reread the Science article "Impact of Shale Gas Development on Regional Water Quality" at the end.)
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Assignment | Week 9:
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If you have any questions, please post them to our Questions? discussion forum (not email), located under the Discussions tab in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
We will begin to identify potential ethical issues in the language of science in the article titled "Impact of shale gas development on regional water quality" which appeared in the May 16th, 2013 issue of the journal Science.
In this article, we will be looking for potential ethical issues that could arise from the scientific study of the impact of shale gas on regional quality water quality.
We will look specifically at the language used in the article to help us locate issues worth further ethical consideration. Later on, we will use the Ethical Dimensions of Scientific Research approach to help us think about where else to look. There is potential for significant ethical issues because the article deals with two issues of immediate importance to contemporary society, namely, development of the energy sector and water quality.
The first sentence of the background indicates to us that natural gas is of significant concern to various regions around the world because of its ability to be a relatively clean energy source as well as reducing dependence on energy imports. As such, we are immediately told that this issue we are about to look at has significant political and environmental importance, often linking us to a variety of ethical considerations. As a transition fuel, methane is also important because it helps is to reduce emissions of CO2 from fossil fuels, various criteria pollutants (NOx, O3, CO, SO2, pm, Pb), and mercury emissions from coal burning, specifically.
Hydraulic fracturing as a way of extracting difficult to reach methane sources has the further appeal of being economically feasible. The process of hydraulic fracturing is a high-pressure process intended to crack rock about 1km below the surface and, as such, this process presents environmental risks to underground water reservoirs through possible gas migration via fractures, the later discharge of the wastewater initially used as hydraulic fluid, and accidental spills in the management of wastewater. What goes unsaid in stating these environmental risks are what these risks also pose to people exposed to such contaminants, but understand that environmental risks are almost always linked to risks to human health, livelihoods, and wellbeing.
As it is stated in the advances in paragraph, the most common problem is with faulty seals around the well casing to prevent leakage of methane. However, the incidence rate of faulty seals is in the range of 1-3% of installed wells. Methane has been detected in areas around well drilling, but there is controversy as to whether or not the methane that was detected was due to the drilling or other natural processes. Without data as to what the conditions were before drilling, what they refer to here as a pre-drilling baseline, it is difficult to determine current conditions from "normal" conditions, as methane has been known to enter into the water table naturally in some of these areas before drilling occurred. As we will see in this article, methods of measuring methane isotopes were used to help answer some of these questions.
Wastewater management of the used hydraulic fracturing fluids is going to dominate environmental debate because wastewater contains both significant chemical additives for the fracturing process as well as vast quantities of heavy metals and radioactive contaminants brought up to the surface from deep underground. As wastewater can only be reused so many times, and as fields mature, there will be growing pressure on finding better strategies for managing the wastewater.
Looking more specifically at the contaminants found in used fracturing fluid, the urgency and risks associated with wastewater management become readily apparent. According to the article, waste management can be more effective through improving three significant areas of research, that is: better modeling of what happens to contaminants of concern, increased long-term monitoring of the wells, and the dissemination of data (which includes improving transparency in the fluid contents). The paper identifies three significant impediments, however, to peer-reviewed research into the environmental impacts of well drilling. First, confidentiality requirements dictated by trade secret laws and what is legal during investigations keep information hidden. Second, the expedited rate of development is making it difficult to conduct studies within a reasonable timeframe, and the limited funds available for research into the impacts of horizontal well-drilling for shale gas. This becomes a problem because the burden becomes to prove harm is being done by this process by a wide range of stakeholders local to drilling sites, as opposed to the burden of having to prove that no harm is being done, which would be put on the drilling and energy companies.
Now, you will want to work through the entire article, reading in a close manner such as this.
These articles provide significant insight into the water pollution risks concerning wastewater from hydraulic fracturing, focusing mainly on the Marcellus Shale region. You will see some common findings emerge in these three readings that pose some concern and elicit recommendations from the authors. Pay attention to these findings.
These articles provide significant insight into the risks concerning methane migration into groundwater from hydraulic fracturing, focusing mainly on the Marcellus Shale region. Like the articles from the prevision section, you will see some common findings emerge in these three readings that pose some concern and elicit recommendations from the authors. Pay attention to these findings.
Sustainability Indicators (SI) are a tool used in an attempt to measure the status of a system for which we have no endogenous terms of success, i.e., "the sustainable state." The primary purpose of SI is to provide a measure for the effectiveness of decisions, both as a measure of previous decisions and as a projection of current decisions into the future. With obvious applications for public and corporate policy, SI are used in a variety of specific contexts that can determine the limit of their applicability in other contexts, i.e., what is a measure of sustainability in one context may not be valid under another context or definition of sustainability. This lesson will take you through some of the historical details in the development of Sustainability Indicators (SI), how SI developed as an integral part of sustainability research, and specifically, how SI are being used to measure the sustainability of cities.
This lesson will take us one week to complete. Please refer to the Course Syllabus for specific time frames and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Read and familiarize yourself with all the Lesson 7 materials. |
Read |
Week 11:
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Assignment |
Week 11:
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If you have any questions, please post them to the General Questions discussion forum (not email), located under the Discussions or the Lesson tab in Canvas. Your instructor will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you are able to help out another student.
Sustainability Indicators (SIs) emerged for the purposes of Sustainable Development as a product of ecological studies quantifying the value of certain parts of an ecosystem in an attempt to provide policymakers with a system for comparing the potential value or harm of one policy over another, i.e., understanding the trade-offs. SIs also provide decision makers with a means for measuring progress over time (e.g., improvement or decline in the system or part of the system.) A simple example is that pollution levels in water resources could indicate whether certain efforts to regulate those pollutants were effective. However, the measure of pollution levels alone does not indicate whether an action is sustainable. It is only in the context of a broader set of indicators (of parts of the system) that the measure of pollution levels would begin to inform us about the sustainability of an action or set of actions.
Urban systems studies are an area that has seen significant attempts at creating comprehensive sets of Urban SIs, as you will encounter in Chapter 3. Many researchers in sustainability and/or urban studies consider the challenge of making our cities sustainable as the main hurdle to achieving a sustainable society. This is for various reasons, including the projected growth of human populations between now and at least 2100 will be in urban centers, where more than 50% of the world's population currently lives, roughly two-thirds of which are in developing countries. Yet, for all of the projected growth, urban living (per capita) provides the best opportunity for a low-impact lifestyle (e.g., per capita, residents of NYC have the lowest greenhouse gas footprints in the U.S.) This is because of high-density living with efficient and readily available public transportation.
Thus far, you have learned various ways to think about ethics in the context of coupled human-energy-environment systems and have put to work tools to help you conduct various types of ethical analyses. You will now look to your own interests in your career or RESS program and attempt to identify a topic that will further inform your interests. This is something you may have identified already in the course (by Week 10 or 11), or you may have come up with an entirely new topic. Either way, if you get stuck, please contact me and we can discuss.
This lesson will take us the rest of the semester to complete. Please refer to the Course Syllabus for specific time frames and due dates. Specific directions for the assignment below can be found within this lesson.
Requirements | Assignment Details |
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To Do | Read and familiarize yourself with all materials and instructions for the Final Case Study. Be sure to clarify with the instructor any confusion or questions you may have. Comments and responses to any queries cannot be guaranteed < 48 hours prior to the due date time of the assignment. |
Read |
Week 12:
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Assignment |
Week 12:
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If you have any questions, please post them to our Questions? discussion forum (not e-mail), located under the discussions tab in Canvas. I will check that discussion forum daily to respond. While you are there, feel free to post your own responses if you, too, are able to help out a classmate.
Links
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