AICYHCLGDec 29, 2023

Culturally-Attuned Moral Machines: Implicit Learning of Human Value Systems by AI through Inverse Reinforcement Learning

arXiv:2312.17479v14 citationsh-index: 109PLoS ONE
Originality Incremental advance
AI Analysis

This addresses the problem of aligning AI with diverse human cultures for developers and ethicists, though it is incremental as it builds on existing IRL methods.

The paper tackles the challenge of creating culturally-specific moral codes for AI by proposing inverse reinforcement learning (IRL) to implicitly learn values from human behavior, showing that AI agents can acquire altruistic traits reflective of a cultural group and generalize them to new scenarios.

Constructing a universal moral code for artificial intelligence (AI) is difficult or even impossible, given that different human cultures have different definitions of morality and different societal norms. We therefore argue that the value system of an AI should be culturally attuned: just as a child raised in a particular culture learns the specific values and norms of that culture, we propose that an AI agent operating in a particular human community should acquire that community's moral, ethical, and cultural codes. How AI systems might acquire such codes from human observation and interaction has remained an open question. Here, we propose using inverse reinforcement learning (IRL) as a method for AI agents to acquire a culturally-attuned value system implicitly. We test our approach using an experimental paradigm in which AI agents use IRL to learn different reward functions, which govern the agents' moral values, by observing the behavior of different cultural groups in an online virtual world requiring real-time decision making. We show that an AI agent learning from the average behavior of a particular cultural group can acquire altruistic characteristics reflective of that group's behavior, and this learned value system can generalize to new scenarios requiring altruistic judgments. Our results provide, to our knowledge, the first demonstration that AI agents could potentially be endowed with the ability to continually learn their values and norms from observing and interacting with humans, thereby becoming attuned to the culture they are operating in.

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