# Responsible Autonomy

arXiv: https://arxiv.org/abs/1706.02513 · HTML: https://mlsanity.com/paper/1706.02513/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Jun 2017.

## Built on by (most cited first, 18 of 18)

- [Auditing large language models: a three-layered approach](https://mlsanity.com/paper/2302.08500/) (2023)
- [Conformity Assessments and Post-market Monitoring: A Guide to the Role of Auditing in the Proposed European AI Regulation](https://mlsanity.com/paper/2111.05071/) (2021)
- [Ethics of AI: A Systematic Literature Review of Principles and Challenges](https://mlsanity.com/paper/2109.07906/) (2021)
- [System Cards for AI-Based Decision-Making for Public Policy](https://mlsanity.com/paper/2203.04754/) (2022)
- [Modulating Language Model Experiences through Frictions](https://mlsanity.com/paper/2407.12804/) (2024)
- [Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning](https://mlsanity.com/paper/2301.08491/) (2023)
- [Hybrid Approaches for Moral Value Alignment in AI Agents: a Manifesto](https://mlsanity.com/paper/2312.01818/) (2023)
- [Value Preferences Estimation and Disambiguation in Hybrid Participatory Systems](https://mlsanity.com/paper/2402.16751/) (2024)
- [Collaborative filtering to capture AI user's preferences as norms](https://mlsanity.com/paper/2308.02542/) (2023)
- [Consent as a Foundation for Responsible Autonomy](https://mlsanity.com/paper/2203.11420/) (2022)
- [AI Alignment Dialogues: An Interactive Approach to AI Alignment in Support Agents](https://mlsanity.com/paper/2301.06421/) (2023)
- [AI for Open Science: A Multi-Agent Perspective for Ethically Translating Data to Knowledge](https://mlsanity.com/paper/2310.18852/) (2023)
- [Personality-Enhanced Social Recommendations in SAMI: Exploring the Role of Personality Detection in Matchmaking](https://mlsanity.com/paper/2509.09583/) (2025)
- [Learning the Value Systems of Agents with Preference-based and Inverse Reinforcement Learning](https://mlsanity.com/paper/2602.04518/) (2026)
- [Towards Algorithmic Transparency: A Diversity Perspective](https://mlsanity.com/paper/2104.05658/) (2021)
- [Streamlining Advanced Taxi Assignment Strategies based on Legal Analysis](https://mlsanity.com/paper/2401.12324/) (2024)
- [Building Altruistic and Moral AI Agent with Brain-inspired Emotional Empathy Mechanisms](https://mlsanity.com/paper/2410.21882/) (2024)
- [Learning the Value Systems of Societies with Preference-based Multi-objective Reinforcement Learning](https://mlsanity.com/paper/2602.08835/) (2026)

## Abstract (arXiv)

As intelligent systems are increasingly making decisions that directly affect society, perhaps the most important upcoming research direction in AI is to rethink the ethical implications of their actions. Means are needed to integrate moral, societal and legal values with technological developments in AI, both during the design process as well as part of the deliberation algorithms employed by these systems. In this paper, we describe leading ethics theories and propose alternative ways to ensure ethical behavior by artificial systems. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems.