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In this workshop, we seek to facilitate a shared understanding regarding the role of ethics and values in design practice and research, using this shared understanding to develop methods to investigate ethical decision-making. While existing study of ethics and values has largely focused on design methods for implementation in practice in an explicit and structured way (e.g., value-sensitive design, values at play), our focus is on the ways in which values might be discovered and generatively explored through qualitative and critical means, both by researchers and practitioners. Through collaborative activities and discussions, workshop participants will be engaged in analyzing existing design artifacts and processes, critiquing them through ethical lenses, and subsequently visualizing their process of value discovery. Outcomes from this workshop are expected to further deepen existing methods for uncovering ethics and values in a design process, highlighting potential opportunities for supporting practitioners’ work and ethical awareness.
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Workshop Report: C-Accel Track Recommendation: Ethical Design of AIs (EDAIs) Executive Summary
A Workshop on the Ethical Design of AIs was convened in September and October 2022. Workshop participants hailed from a wide range of disciplines and application domains, and expressed interest in establishing partnerships across academia, industry, and government agencies, to address the challenges that were identified during the event. One of the outcomes of the workshop was a recommendation for a 2023 Convergence Accelerator Track on the Ethical Design of AIs (EDAIs). Suggested recommendations of themes and goals for the EDAIs Track include the following: (1) Human Centered Design methodologies around Values and Measures and Incentives. (2) Proto Ethical AIs: Algorithms or Systems or Pipelines across multiple domains. (3) Best Practices for the design of ethical AIs. (4) Workforce development and education and training. This report documents the activities of the EDAIs Workshop
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- Award ID(s):
- 2232404
- PAR ID:
- 10538189
- Editor(s):
- Pazzani, Michael; Raschid, Louiqa
- Publisher / Repository:
- NSF Public Access Repository
- Date Published:
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
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