Ethics, Prosperity, and Society: Moral Evaluation Using Virtue Ethics and Utilitarianism

Hegde, Aditya; Agarwal, Vibhav; Rao, Shrisha

doi:10.24963/ijcai.2020/24

Cited by 4 publications

(3 citation statements)

References 6 publications

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“…Social dilemma games, which illustrate the trade-off between self-interested and mutually beneficial choices [Rapoport, 1974], create a useful testing ground for moral agents [Cavagnetto and Gahir, 2014;Cunningham, 1967;Hegde et al, 2020]. In particular, in this work we consider iterated games.…”

Section: Introductionmentioning

confidence: 99%

Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning

Tennant

Hailes

Musolesi

2023

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

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Practical uses of Artificial Intelligence (AI) in the real world have demonstrated the importance of embedding moral choices into intelligent agents. They have also highlighted that defining top-down ethical constraints on AI according to any one type of morality is extremely challenging and can pose risks. A bottom-up learning approach may be more appropriate for studying and developing ethical behavior in AI agents. In particular, we believe that an interesting and insightful starting point is the analysis of emergent behavior of Reinforcement Learning (RL) agents that act according to a predefined set of moral rewards in social dilemmas. In this work, we present a systematic analysis of the choices made by intrinsically-motivated RL agents whose rewards are based on moral theories. We aim to design reward structures that are simplified yet representative of a set of key ethical systems. Therefore, we first define moral reward functions that distinguish between consequence- and norm-based agents, between morality based on societal norms or internal virtues, and between single- and mixed-virtue (e.g., multi-objective) methodologies. Then, we evaluate our approach by modeling repeated dyadic interactions between learning moral agents in three iterated social dilemma games (Prisoner's Dilemma, Volunteer's Dilemma and Stag Hunt). We analyze the impact of different types of morality on the emergence of cooperation, defection or exploitation, and the corresponding social outcomes. Finally, we discuss the implications of these findings for the development of moral agents in artificial and mixed human-AI societies.

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Section: Introductionmentioning

confidence: 99%

Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning

Tennant

Hailes

Musolesi

2023

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence

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“…The interactions in our model are governed by the Continuous Prisoner's Dilemma (CPD; Verhoeff, 1993). These interaction types have recently been shown to be successful in modelling and understanding other social phenomena such as ethical behaviour (Hegde et al, 2020) and egocentric bias (Sreenivas & Rao, 2019) in individuals. Our agent society contains two social structures, groups and factions.…”

Section: Introductionmentioning

confidence: 99%

Modelling prejudice and its effect on societal prosperity

Mohan

Verma

Rao

2022

Journal of Simulation

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Existing studies of the multi-group dynamics of prejudiced societies focus on the socialpsychological knowledge behind the relevant processes. We instead create a multi-agent framework that simulates the propagation of prejudice and measures its tangible impact on prosperity. Levels of prosperity are tracked for individuals as well as larger social structures including groups and factions. We model social interactions using the Continuous Prisoner's Dilemma (CPD) and a new agent type called a prejudiced agent. Our simulations show that even modeling prejudice as an exclusively out-group phenomenon nonetheless generates implicit in-group promotion, leading to higher relative prosperity of a prejudiced population. This skew in prosperity is seen to be correlated to factors such as size difference between groups, and the fraction of prejudiced agents in a group. Our model is a step towards a deeper understanding of the origins, propagation, and ramifications of prejudice through simulative studies grounded in apt theoretical backgrounds.

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“…The interactions in our model are governed by the Continuous Prisoner's Dilemma (CPD) [11]. These interaction types have recently been shown to be successful in modeling and understanding other social phenomena such as ethical behavior [12] and egocentric bias [13] in individuals. Our agent society contains two social structures, groups and factions.…”

Section: Introductionmentioning

confidence: 99%

Modeling Prejudice and Its Effect on Societal Prosperity

Mohan¹,

Verma²,

Rao³

2021

Preprint

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Existing studies on prejudice, which is important in multi-group dynamics in societies, focus on the social-psychological knowledge behind the processes involving prejudice and its propagation. We instead create a multi-agent framework that simulates the propagation of prejudice and measures its tangible impact on the prosperity of individuals as well as of larger social structures, including groups and factions within. Groups in society help us define prejudice, and factions represent smaller tightknit circles of individuals with similar opinions. We model social interactions using the Continuous Prisoner's Dilemma (CPD) and a type of agent called a prejudiced agent, whose cooperation is affected by a prejudice attribute, updated over time based both on the agent's own experiences and those of others in its faction. Our simulations show that modeling prejudice as an exclusively outgroup phenomenon generates implicit in-group promotion, which eventually leads to higher relative prosperity of the prejudiced population. This skew in prosperity is shown to be correlated to factors such as size difference between groups and the number of prejudiced agents in a group. Although prejudiced agents achieve higher prosperity within prejudiced societies, their presence degrades the overall prosperity levels of their societies. Our proposed system model can serve as a basis for promoting a deeper understanding of origins, propagation, and ramifications of prejudice through rigorous simulative studies grounded in apt theoretical backgrounds. This can help conduct impactful research on prominent social issues such as racism, religious discrimination, and unfair immigrant treatment. This model can also serve as a foundation to study other socio-psychological phenomena in tandem with prejudice such as the distribution of wealth, social status, and ethnocentrism in a society.

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Ethics, Prosperity, and Society: Moral Evaluation Using Virtue Ethics and Utilitarianism

Cited by 4 publications

References 6 publications

Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning

Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning

Modelling prejudice and its effect on societal prosperity

Modeling Prejudice and Its Effect on Societal Prosperity

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