Probably not a game: Playing with the AI in the ritual of taking pictures on the mobile phone

Neumayer, Christina; Sicart, Miguel

doi:10.1177/14614448231158654

Cited by 4 publications

References 45 publications

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Governing AI through interaction: situated actions as an informal mechanism for AI regulation

Papyshev

2024

AI Ethics

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This article presents a perspective that the interplay between high-level ethical principles, ethical praxis, plans, situated actions, and procedural norms influences ethical AI practices. This is grounded in six case studies, drawn from fifty interviews with stakeholders involved in AI governance in Russia. Each case study focuses on a different ethical principle—privacy, fairness, transparency, human oversight, social impact, and accuracy. The paper proposes a feedback loop that emerges from human-AI interactions. This loop begins with the operationalization of high-level ethical principles at the company level into ethical praxis, and plans derived from it. However, real-world implementation introduces situated actions—unforeseen events that challenge the original plans. These turn into procedural norms via routinization and feed back into the understanding of operationalized ethical principles. This feedback loop serves as an informal regulatory mechanism, refining ethical praxis based on contextual experiences. The study underscores the importance of bottom-up experiences in shaping AI's ethical boundaries and calls for policies that acknowledge both high-level principles and emerging micro-level norms. This approach can foster responsive AI governance, rooted in both ethical principles and real-world experiences.

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Governing AI through interaction: situated actions as an informal mechanism for AI regulation

Papyshev

2024

AI Ethics

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The Future of Generative AI: How GenAI Would Change Human-Computer Co-creation in the Next 10 to 15 Years

Huang

2023

Companion Proceedings of the Annual Symposium on Computer-Human Interaction in Play

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Explainable Artificial Intelligence: Importance, Use Domains, Stages, Output Shapes, and Challenges

Ullah,

Khan,

De Falco

et al. 2024

ACM Comput. Surv.

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There is an urgent need in many application areas for eXplainable ArtificiaI Intelligence (XAI) approaches to boost people’s confidence and trust in Artificial Intelligence methods. Current works concentrate on specific aspects of XAI and avoid a comprehensive perspective. This study undertakes a systematic survey of importance, approaches, methods, and application domains to address this gap and provide a comprehensive understanding of the XAI domain. Applying the Systematic Literature Review approach has resulted in finding and discussing 155 papers, allowing a wide discussion on the strengths, limitations, and challenges of XAI methods and future research directions.

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Probably not a game: Playing with the AI in the ritual of taking pictures on the mobile phone

Cited by 4 publications

References 45 publications

Governing AI through interaction: situated actions as an informal mechanism for AI regulation

Governing AI through interaction: situated actions as an informal mechanism for AI regulation

The Future of Generative AI: How GenAI Would Change Human-Computer Co-creation in the Next 10 to 15 Years

Explainable Artificial Intelligence: Importance, Use Domains, Stages, Output Shapes, and Challenges

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