# Metacognitive Agents for Ethical Decision Support: Conceptual Model and Research Roadmap

arXiv: https://arxiv.org/abs/2202.12039 · HTML: https://mlsanity.com/paper/2202.12039/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 34 references that are in the map.
- First posted on arXiv 24 Feb 2022.

## Builds on (most cited first, 2 of 2)

- [Thinking Fast and Slow: Optimization Decomposition Across Timescales](https://mlsanity.com/paper/1704.07785/) (2017)
- [Implementations in Machine Ethics: A Survey](https://mlsanity.com/paper/2001.07573/) (2020)

## Abstract (arXiv)

An ethical value-action gap exists when there is a discrepancy between intentions and actions. This discrepancy may be caused by social and structural obstacles as well as cognitive biases. Computational models of cognition and affect can provide insights into the value-action gap and how it can be reduced. In particular, metacognition ("thinking about thinking") plays an important role in many of these models as a mechanism for self-regulation and reasoning about mental attitudes. This paper outlines a roadmap for translating cognitive-affective models into assistant agents to help make value-aligned decisions.