# A Computational Model of Commonsense Moral Decision Making

arXiv: https://arxiv.org/abs/1801.04346 · HTML: https://mlsanity.com/paper/1801.04346/

## Key facts

- Cited by 13 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jan 2018.

## Built on by (most cited first, 13 of 13)

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- [Moral Dilemmas for Moral Machines](https://mlsanity.com/paper/2203.06152/) (2022)
- [A Systematic Literature Review of Human-Centered, Ethical, and Responsible AI](https://mlsanity.com/paper/2302.05284/) (2023)
- [Human-In-The-Loop Machine Learning for Safe and Ethical Autonomous Vehicles: Principles, Challenges, and Opportunities](https://mlsanity.com/paper/2408.12548/) (2024)
- [When Is It Acceptable to Break the Rules? Knowledge Representation of Moral Judgement Based on Empirical Data](https://mlsanity.com/paper/2201.07763/) (2022)
- [Fairness and Sequential Decision Making: Limits, Lessons, and Opportunities](https://mlsanity.com/paper/2301.05753/) (2023)
- [Towards Cognitively-Faithful Decision-Making Models to Improve AI Alignment](https://mlsanity.com/paper/2509.04445/) (2025)
- [The End Justifies the Mean: A Linear Ranking Rule for Proportional Sequential Decisions](https://mlsanity.com/paper/2605.12717/) (2026)
- [Position: We Need Practical AI Alignment Methods to Mirror Human Reasoning](https://mlsanity.com/paper/2608.12372/) (2026)

## Abstract (arXiv)

We introduce a new computational model of moral decision making, drawing on a recent theory of commonsense moral learning via social dynamics. Our model describes moral dilemmas as a utility function that computes trade-offs in values over abstract moral dimensions, which provide interpretable parameter values when implemented in machine-led ethical decision-making. Moreover, characterizing the social structures of individuals and groups as a hierarchical Bayesian model, we show that a useful description of an individual's moral values - as well as a group's shared values - can be inferred from a limited amount of observed data. Finally, we apply and evaluate our approach to data from the Moral Machine, a web application that collects human judgments on moral dilemmas involving autonomous vehicles.