# Unraveling the Nuances of AI Accountability: A Synthesis of Dimensions Across Disciplines

arXiv: https://arxiv.org/abs/2410.04247 · HTML: https://mlsanity.com/paper/2410.04247/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Oct 2024.

## Built on by (most cited first, 2 of 2)

- [No One to Blame: A Framework of Constitutive AI Unaccountability](https://mlsanity.com/paper/2608.12104/) (2026)
- [Follow the Norm: Accounting for Fine-Tuning and Prompt Effects on Model Rationales](https://mlsanity.com/paper/2608.13250/) (2026)

## Abstract (arXiv)

The widespread diffusion of Artificial Intelligence (AI)-based systems offers many opportunities to contribute to the well-being of individuals and the advancement of economies and societies. This diffusion is, however, closely accompanied by public scandals causing harm to individuals, markets, or society, and leading to the increasing importance of accountability. AI accountability itself faces conceptual ambiguity, with research scattered across multiple disciplines. To address these issues, we review current research across multiple disciplines and identify key dimensions of accountability in the context of AI. We reveal six themes with 13 corresponding dimensions and additional accountability facilitators that future research can utilize to specify accountability scenarios in the context of AI-based systems.