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1. An ethical decision-making framework with serious gaming: a smart water case study on flooding

   https://doi.org/10.2166/hydro.2021.097  

   Ewing, Gregory; Demir, Ibrahim (March 2021, Journal of Hydroinformatics)

   null (Ed.)

   Abstract Sensors and control technologies are being deployed at unprecedented levels in both urban and rural water environments. Because sensor networks and control allow for higher-resolution monitoring and decision making in both time and space, greater discretization of control will allow for an unprecedented precision of impacts, both positive and negative. Likewise, humans will continue to cede direct decision-making powers to decision-support technologies, e.g. data algorithms. Systems will have ever-greater potential to effect human lives, and yet, humans will be distanced from decisions. Combined these trends challenge water resources management decision-support tools to incorporate the concepts of ethical and normative expectations. Toward this aim, we propose the Water Ethics Web Engine (WE)2, an integrated and generalized web framework to incorporate voting-based ethical and normative preferences into water resources decision support. We demonstrate this framework with a ‘proof-of-concept’ use case where decision models are learned and deployed to respond to flooding scenarios. Findings indicate that the framework can capture group ‘wisdom’ within learned models to use in decision making. The methodology and ‘proof-of-concept’ system presented here are a step toward building a framework to engage people with algorithmic decision making in cases where ethical preferences are considered. We share our framework and its cyber components openly with the research community. 

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2. Engineering Ethics Through High-Impact Collaborative/Competitive Scenarios (E-ETHICCS): Initial Results and Lessons Learned.

   Streiner, S; Burkey, D; Young, M.; Cimino, R.; Pascal, J.; Dahm, K. (August 2022, ASEE Annual Conference proceedings)

   Ethics education has been recognized as increasingly important to engineering over the past two decades, although disagreement exists concerning how ethics can and should be taught in the classroom. With active learning strategies becoming a preferred method of instruction, a collaboration of authors from four universities (University of Pittsburgh, University of Connecticut, Rowan University and New Jersey Institute of Technology) are investigating how game-based or playful learning with strongly situated components can influence first-year engineering students’ ethical knowledge, awareness, and decision making. This paper offers an overview and results of the progress to date of this three year, NSF Improving Undergraduate STEM Education (IUSE) grant that aims to (1) characterize the ethical awareness and decision making of first-year engineering students, (2) develop game-based learning interventions focused on ethical decision making, and (3) determine how (and why) game-based approaches affect students’ ethical awareness in engineering and the advantages of such approaches over non game-based approaches. Now in its second year, the authors have conducted a preliminary analysis of first-year students' ethical knowledge and organization via a concept mapping approach and have measured students' ethical reasoning using the Defining Issues Test 2 (DIT2) and Engineering Ethics Reasoning Instrument (EERI). Further, the authors have developed a suite of ethics-driven games that have been implemented across three of the universities, engaging over 400 first-year engineering students. Evaluation data has also been gathered for further game development and to assess initial student engagement and learning. Year 1 has provided insight into where first-year engineering students “are at” in terms of ethical knowledge and reasoning when they come to college, and how game-based instruction can be effective in the development of these students into moral agents who understand the consequences of their decisions. Further results from this investigation will provide the engineering education community with a set of impactful and research-based playful learning pedagogy and assessment that will help students confront social and ethical dilemmas in their professional lives. 

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3. Informing a Robot Ethics Architecture through Folk and Expert Morality

   Surendran, V.; Melo Cruz, A.; Wagner, A.; Borenstein, J.; Arkin, R.; Chen, S. (July 2022, 7th International Conference on Robot Ethics and Standards)

   Ethical decision-making is difficult, certainly for robots let alone humans. If a robot's ethical decision-making process is going to be designed based on some approximation of how humans operate, then the assumption is that a good model of how humans make an ethical choice is readily available. Yet no single ethical framework seems sufficient to capture the diversity of human ethical decision making. Our work seeks to develop the computational underpinnings that will allow a robot to use multiple ethical frameworks that guide it towards doing the right thing. As a step towards this goal, we have collected data investigating how regular adults and ethics experts approach ethical decisions related to the use in a healthcare and game playing scenario. The decisions made by the former group is intended to represent an approximation of a folk morality approach to these dilemmas. On the other hand, experts were asked to judge what decision would result if a person was using one of several different types of ethical frameworks. The resulting data may reveal which features of the pill sorting and game playing scenarios contribute to similarities and differences between expert and non-expert responses. This type of approach to programming a robot may one day be able to rely on specific features of an interaction to determine which ethical framework to use in the robot's decision making. 

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4. Comparing First-Year Engineering Student Conceptions of Ethical Decision-Making to Performance on Standardized Assessments of Ethical Reasoning

   Cimino, R; Streiner, S; Burkey, D; Young, M; Bassett, L; Reed, J (June 2024, Science and engineering ethics)

   The Defining Issues Test 2 (DIT-2) and Engineering Ethical Reasoning Instrument (EERI) are designed to measure ethical reasoning of general (DIT-2) and engineering-student (EERI) populations. These tools—and the DIT-2 especially—have gained wide usage for assessing the ethical reasoning of undergraduate students. This paper reports on a research study in which the ethical reasoning of first-year undergraduate engineering students at multiple universities was assessed with both of these tools. In addition to these two instruments, students were also asked to create personal concept maps of the phrase “ethical decision-making.” It was hypothesized that students whose instrument scores reflected more postconventional levels of moral development and more sophisticated ethical reasoning skills would likewise have richer, more detailed concept maps of ethical decision-making, reflecting their deeper levels of understanding of this topic and the complex of related concepts. In fact, there was no significant correlation between the instrument scores and concept map scoring, suggesting that the way first-year students conceptualize ethical decision making does not predict the way they behave when performing scenario-based ethical reasoning (perhaps more situated). This disparity indicates a need to more precisely quantify engineering ethical reasoning and decision making, if we wish to inform assessment outcomes using the results of such quantitative analyses. 

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5. Comparing First-Year Engineering Student Conceptions of Ethical Decision-Making to Performance on Standardized Assessments of Ethical Reasoning

   https://doi.org/10.1007/s11948-024-00488-y  

   Cimino, Richard_T; Streiner, Scott_C; Burkey, Daniel_D; Young, Michael_F; Bassett, Landon; Reed, Joshua_B (June 2024, Science and Engineering Ethics)

   Abstract The Defining Issues Test 2 (DIT-2) and Engineering Ethical Reasoning Instrument (EERI) are designed to measure ethical reasoning of general (DIT-2) and engineering-student (EERI) populations. These tools—and the DIT-2 especially—have gained wide usage for assessing the ethical reasoning of undergraduate students. This paper reports on a research study in which the ethical reasoning of first-year undergraduate engineering students at multiple universities was assessed with both of these tools. In addition to these two instruments, students were also asked to create personal concept maps of the phrase “ethical decision-making.” It was hypothesized that students whose instrument scores reflected more postconventional levels of moral development and more sophisticated ethical reasoning skills would likewise have richer, more detailed concept maps of ethical decision-making, reflecting their deeper levels of understanding of this topic and the complex of related concepts. In fact, there was no significant correlation between the instrument scores and concept map scoring, suggesting that the way first-year studentsconceptualizeethical decision making does not predict the way they behave whenperformingscenario-based ethical reasoning (perhaps more situated). This disparity indicates a need to more precisely quantify engineering ethical reasoning and decision making, if we wish to inform assessment outcomes using the results of such quantitative analyses. 

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