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What should we do with emotion AI? Should we regulate, ban, promote, or re-imagine it? Emotion AI, a class of affective computing technologies used in personal and social computing, comprises emergent and controversial techniques aiming to classify human emotion and other affective phenomena. Industry, policy, and scientific actors debate potential benefits and harms, arguing for polarized futures ranging from panoptic expansion to complete bans. Emotion AI is proposed, deployed, and sometimes withdrawn in collaborative contexts such as education, hiring, healthcare, and service work. Proponents expound these technologies’ benefits for well-being and security, while critics decry privacy harms, civil liberties risks, bias, and shaky scientific foundations, and gaps between technologies’ capabilities and how they are marketed and legitimized. This panel brings diverse disciplinary perspectives into discussion about the history of emotions—as an example of ’intimate’ data—in computing, how emotion AI is legitimized, people’s experiences with and perceptions of emotion AI in social and collaborative settings, emotion AI’s development practices, and using design research to re-imagine emotion AI. These issues are relevant to the CSCW community in designing, evaluating, and regulating algorithmic sensing technologies including and beyond emotion-sensing.
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Generative AI Going Awry: Enabling Designers to Proactively Avoid It in CSCW Applications
The rapid development and deployment of generative AI technologies creates a design challenge of how to proactively understand the implications of productizing and deploying these new technologies, especially with regard to negative design implications. This is especially concerning in CSCW applications, where AI agents can introduce misunderstandings or even misdirections with the people interacting with the agent. In this panel, researchers from academia and industry will reflect on their experiences with ideas, methods, and processes to enable designers to proactively shape the responsible design of genAI in collaborative applications. The panelists represent a range of different approaches, including speculative fiction, design activities, design toolkits, and process guides. We hope that the panel encourages a discussion in the CSCW community around techniques we can put into practice today to enable the responsible design of genAI.
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- Award ID(s):
- 2048244
- PAR ID:
- 10623857
- Publisher / Repository:
- ACM
- Date Published:
- ISBN:
- 9798400711145
- Page Range / eLocation ID:
- 125 to 127
- Subject(s) / Keyword(s):
- Generative AI, design, redteaming
- Format(s):
- Medium: X
- Location:
- San Jose Costa Rica
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3678884.3689133
