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1. Engineering Ethics Education for Social Justice

   Douglas, Elliot P.; Holbrook, J. Britt (January 2020, Proceedings Frontiers in Education Conference)

   null (Ed.)

   This Work-in-Progress Innovative Practice paper describes incorporation of social justice into engineering ethics education. Current teaching of engineering ethics pays inadequate general. While many authors have called for a reconsideration of the fundamental canons of engineering ethics, there has been relatively less work on teaching and developing ethics from viewpoints that highlight social justice. We have recently begun a project to address this gap, focusing on curriculum design and collecting preliminary data to demonstrate the efficacy of our approach. In this paper we describe the theoretical foundations for the class, the design principles, and the research approach to determine its effectiveness. 

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2. Engineering Ethics Education for Social Justice

   Douglas, Elliot P.; Holbrook, J. Britt (January 2020, Frontiers in education)

   null (Ed.)

   This Work-in-Progress Innovative Practice paper describes incorporation of social justice into engineering ethics education. Current teaching of engineering ethics pays inadequate attention to social justice, mirroring engineering education in general. While many authors have called for a reconsideration of the fundamental canons of engineering ethics, there has been relatively less work on teaching and developing ethics from viewpoints that highlight social justice. We have recently begun a project to address this gap, focusing on curriculum design and collecting preliminary data to demonstrate the efficacy of our approach. In this paper we describe the theoretical foundations for the class, the design principles, and the research approach to determine its effectiveness. 

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3. How do ethics and diversity, equity, and inclusion relate in engineering? A systematic review

   https://doi.org/10.1002/jee.20571  

   Hess, Justin L.; Lin, Athena; Whitehead, Andrew; Katz, Andrew (January 2024, Journal of Engineering Education)

   Abstract BackgroundThis paper begins with the premise that ethics and diversity, equity, and inclusion (DEI) overlap in engineering. Yet, the topics of ethics and DEI often inhabit different scholarly spaces in engineering education, thus creating a divide between these topics in engineering education research, teaching, and practice. PurposeWe investigate the research question, “How are ethics and DEI explicitly connected in peer‐reviewed literature in engineering education and closely related fields?” DesignWe used systematic review procedures to synthesize intersections between ethics and DEI in engineering education scholarly literature. We extracted literature from engineering and engineering education databases and used thematic analysis to identify ethics/DEI connections. ResultsWe identified three primary themes (each with three sub‐themes): (1) lenses that serve to connect ethics and DEI (social, justice‐oriented, professional), (2) roots that inform how ethics and DEI connect in engineering (individual demographics, disciplinary cultures, institutional cultures); and (3) engagement strategies for promoting ethics and DEI connections in engineering (affinity toward ethics/DEI content, understanding diverse stakeholders, working in diverse teams). ConclusionsThere is a critical mass of engineering education scholars explicitly exploring connections between ethics and DEI in engineering. Based on this review, potential benefits of integrating ethics and DEI in engineering include cultivating a socially just world and shifting engineering culture to be more inclusive and equitable, thus accounting for the needs and values of students and faculty from diverse backgrounds. 

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4. A new approach to grant review assessments: score, then rank

   https://doi.org/10.1186/s41073-023-00131-7  

   Gallo, Stephen_A; Pearce, Michael; Lee, Carole_J; Erosheva, Elena_A (July 2023, Research Integrity and Peer Review)

   Abstract BackgroundIn many grant review settings, proposals are selected for funding on the basis of summary statistics of review ratings. Challenges of this approach (including the presence of ties and unclear ordering of funding preference for proposals) could be mitigated if rankings such as top-k preferences or paired comparisons, which are local evaluations that enforce ordering across proposals, were also collected and incorporated in the analysis of review ratings. However, analyzing ratings and rankings simultaneously has not been done until recently. This paper describes a practical method for integrating rankings and scores and demonstrates its usefulness for making funding decisions in real-world applications. MethodsWe first present the application of our existing joint model for rankings and ratings, the Mallows-Binomial, in obtaining an integrated score for each proposal and generating the induced preference ordering. We then apply this methodology to several theoretical “toy” examples of rating and ranking data, designed to demonstrate specific properties of the model. We then describe an innovative protocol for collecting rankings of the top-six proposals as an add-on to the typical peer review scoring procedures and provide a case study using actual peer review data to exemplify the output and how the model can appropriately resolve judges’ evaluations. ResultsFor the theoretical examples, we show how the model can provide a preference order to equally rated proposals by incorporating rankings, to proposals using ratings and only partial rankings (and how they differ from a ratings-only approach) and to proposals where judges provide internally inconsistent ratings/rankings and outlier scoring. Finally, we discuss how, using real world panel data, this method can provide information about funding priority with a level of accuracy in a well-suited format for research funding decisions. ConclusionsA methodology is provided to collect and employ both rating and ranking data in peer review assessments of proposal submission quality, highlighting several advantages over methods relying on ratings alone. This method leverages information to most accurately distill reviewer opinion into a useful output to make an informed funding decision and is general enough to be applied to settings such as in the NIH panel review process. 

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5. A Systematic Review of Ethics Disclosures in Predictive Mental Health Research

   https://doi.org/10.1145/3593013.3594082  

   Ajmani, Leah Hope; Chancellor, Stevie; Mehta, Bijal; Fiesler, Casey; Zimmer, Michael; De Choudhury, Munmun (June 2023, 2023 ACM Conference on Fairness, Accountability, and Transparency)

   Applied machine learning (ML) has not yet coalesced on standard practices for research ethics. For ML that predicts mental illness using social media data, ambiguous ethical standards can impact peoples’ lives because of the area’s sensitivity and material con- sequences on health. Transparency of current ethics practices in research is important to document decision-making and improve research practice. We present a systematic literature review of 129 studies that predict mental illness using social media data and ML, and the ethics disclosures they make in research publications. Rates of disclosure are going up over time, but this trend is slow moving – it will take another eight years for the average paper to have coverage on 75% of studied ethics categories. Certain practices are more readily adopted, or "stickier", over time, though we found pri- oritization of data-driven disclosures rather than human-centered. These inconsistently reported ethical considerations indicate a gap between what ML ethicists believe ought to be and what actually is done. We advocate for closing this gap through increased trans- parency of practice and formal mechanisms to support disclosure. 

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