Activism by the AI Community

Belfield, Haydn

doi:10.1145/3375627.3375814

Cited by 32 publications

(5 citation statements)

References 20 publications

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“…It is further specified in a detailed blog post [9]. Employees could threaten to leave the company or engage in other forms of activism if the company violates its principles [21].…”

Section: Interpreting Ethics Principlesmentioning

confidence: 99%

How to design an AI ethics board

Schuett,

Reuel,

Carlier

2024

AI Ethics

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The development and deployment of artificial intelligence (AI) systems poses significant risks to society. To reduce these risks to an acceptable level, AI companies need an effective risk management process and sound risk governance. In this paper, we explore a particular way in which AI companies can improve their risk governance: by setting up an AI ethics board. We identify five key design choices: (1) What responsibilities should the board have? (2) What should its legal structure be? (3) Who should sit on the board? (4) How should it make decisions? (5) And what resources does it need? We break each of these questions down into more specific sub-questions, list options, and discuss how different design choices affect the board’s ability to reduce societal risks from AI. Several failures have shown that designing an AI ethics board can be challenging. This paper provides a toolbox that can help AI companies to overcome these challenges.

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“…It is further specified in a detailed blog post [9]. Employees could threaten to leave the company or engage in other forms of activism if the company violates its principles [21].…”

Section: Interpreting Ethics Principlesmentioning

confidence: 99%

How to design an AI ethics board

Schuett,

Reuel,

Carlier

2024

AI Ethics

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“…US adults without technical training tend to be less supportive of AI and more concerned about AI governance challenges compared with US adults who have a computer science or engineering degree (Zhang & Dafoe, 2019). Yet, AI/ML researchers are increasingly aware of the dangers and harmful societal consequences of AI systems (Belfield, 2020); furthermore, an international sample of AI researchers -compared with the US public -are less trustful of tech companies to develop and manage AI (Zhang et al, 2021). Future research could test whether knowledge about AI and trust in AI systems follows an inverted-U shape: increasing knowledge increases trust up to a point then decreases as one becomes an expert.…”

Section: Impact Of Experience and Knowledge On Attitudesmentioning

confidence: 99%

Public Opinion toward Artificial Intelligence

Zhang

2023

The Oxford Handbook of AI Governance

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This chapter synthesizes and discusses research on public opinion toward artificial intelligence (AI). Understanding citizens’ and consumers’ attitudes toward AI is important from a normative standpoint because the public is a major stakeholder in shaping the future of the technology and should have a voice in policy discussions. Furthermore, the research could help anticipate future political and consumer behavior. Survey data worldwide show that the public is increasingly aware of AI; however, they—unlike AI researchers—tend to anthropomorphize AI. Demographic differences correlate with trust in AI in general: those living in East Asia have higher levels of trust in AI, while women and those of lower socioeconomic status across different regions have lower levels of trust. Surveys that focus on particular AI applications, including facial recognition technology, personalization algorithms, lethal autonomous weapons, and workplace automation, add complexity to this research topic. This chapter concludes by recommending four new topics for future studies: (1) institutional trust in actors building and deploying AI systems, (2) the impact of knowledge and experience on attitudes toward AI, (3) heterogeneity in attitudes toward AI, and (4) the relationship between attitudes and behavior.

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“…Asilomar features heavily in another example of self-reflection by technologists, but only as part of a broad set of measures undertaken in the AI community "to shape the societal and ethical implications of AI", 32 actions that Belfield terms "activism". While Belfield draws out other ways in which that activism takes shape (worker organising, for instance), what I will focus on here is that of using the "epistemic community" 33 as an engine for self-reflection and norm-setting.…”

Section: Contemporary Case Studies Of Research Culture: Self-governan...mentioning

confidence: 99%

3. Existential Risk and Science Governance

Sundaram

2023

The Era of Global Risk

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As existential risks are deeply related to science and scholars, this chapter proposes a new consideration of scientific governance, self-governance of technologies, and research culture as socio-technical processes opposed to the conventional idea of science as something extrinsic and beyond conditioning. The chapter provides examples of instances where scientists and communities have worked together to improve existing modalities.

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Activism by the AI Community

Cited by 32 publications

References 20 publications

How to design an AI ethics board

How to design an AI ethics board

Public Opinion toward Artificial Intelligence

3. Existential Risk and Science Governance

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