AI and society: a virtue ethics approach

Farina, Mirko; Zhdanov, Petr; Каримов, Артур Равилевич; Lavazza, Andrea

doi:10.1007/s00146-022-01545-5

Cited by 15 publications

(2 citation statements)

References 94 publications

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“…While our work is only preliminary and certainly partial it nevertheless holds some value as one of the first exploratory attempts in the literature. Specifically, it appears to be beneficial because it aims to coherently synthetize current research while offering a springboard for future inquiries and progresses in the field (Farina et al, 2022 ).…”

Section: Discussionmentioning

confidence: 99%

ChatGPT in society: emerging issues

Farina

Lavazza

2023

Front. Artif. Intell.

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We review and critically assess several issues arising from the potential -large-scale- implementation or deployment of Large Language Models (LLMs) in society. These include security, political, economic, cultural, and educational issues as well as issues concerning social biases, creativity, copyright, and freedom of speech. We argue, without a preconceived pessimism toward these tools, that they may bring about many benefits. However, we also call for a balance assessment of their downsides. While our work is only preliminary and certainly partial it nevertheless holds some value as one of the first exploratory attempts in the literature.

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Section: Discussionmentioning

confidence: 99%

ChatGPT in society: emerging issues

Farina

Lavazza

2023

Front. Artif. Intell.

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“…These theories include Act Utilitarianism [7,91,128], Kantianism [105,187,236], Virtue Ethics [131,171,216], Norm-based systems [82,120], The Veil of Ignorance [138,167], Divine Command Theory [37], The Golden Rule [167], and Prima Facie Duties [8,216] among others. In addition to these applied works, there have been many more theoretical pieces examining when and why particular ethical frameworks ought to be used [76,89,103,142,178,186,187,225,244,254]. However, these systems are still largely imagined, and we are not aware of any real-world systems yet in operation, in contrast to "fair" predictive systems which we know operate in a variety of public settings already.…”

Section: Conceptualizationsmentioning

confidence: 99%

Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities

Nashed¹,

Svegliato²,

Blodgett³

2023

Preprint

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As automated decision making and decision assistance systems become common in everyday life, research on the prevention or mitigation of potential harms that arise from decisions made by these systems has proliferated. However, various research communities have independently conceptualized these harms, envisioned potential applications, and proposed interventions. The result is a somewhat fractured landscape of literature focused generally on ensuring decision-making algorithms "do the right thing". In this paper, we compare and discuss work across two major subsets of this literature: algorithmic fairness, which focuses primarily on predictive systems, and ethical decision making, which focuses primarily on sequential decision making and planning. We explore how each of these settings has articulated its normative concerns, the viability of different techniques for these different settings, and how ideas from each setting may have utility for the other.Finally, given the optimal value function * ( ), the optimal policy * ( ) can be calculated in the following way: * ( ) = arg max ∈ * ( ).

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