# Documentation Practices of Artificial Intelligence

arXiv: https://arxiv.org/abs/2406.18620 · HTML: https://mlsanity.com/paper/2406.18620/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 35 references that are in the map.
- First posted on arXiv 26 Jun 2024.

## Builds on (most cited first, 17 of 17)

- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [Model Cards for Model Reporting](https://mlsanity.com/paper/1810.03993/) (2018)
- [Data Cards: Purposeful and Transparent Dataset Documentation for Responsible AI](https://mlsanity.com/paper/2204.01075/) (2022)
- [Towards Accountability for Machine Learning Datasets: Practices from Software Engineering and Infrastructure](https://mlsanity.com/paper/2010.13561/) (2020)
- [Interactive Model Cards: A Human-Centered Approach to Model Documentation](https://mlsanity.com/paper/2205.02894/) (2022)
- [CrowdWorkSheets: Accounting for Individual and Collective Identities Underlying Crowdsourced Dataset Annotation](https://mlsanity.com/paper/2206.08931/) (2022)
- [Assessing Language Model Deployment with Risk Cards](https://mlsanity.com/paper/2303.18190/) (2023)
- [The Dataset Nutrition Label (2nd Gen): Leveraging Context to Mitigate Harms in Artificial Intelligence](https://mlsanity.com/paper/2201.03954/) (2022)
- [Data Readiness Report](https://mlsanity.com/paper/2010.07213/) (2020)
- [AI Usage Cards: Responsibly Reporting AI-generated Content](https://mlsanity.com/paper/2303.03886/) (2023)
- [Use case cards: a use case reporting framework inspired by the European AI Act](https://mlsanity.com/paper/2306.13701/) (2023)
- [The Journal Coverage of Web of Science and Scopus: a Comparative Analysis](https://mlsanity.com/paper/1511.08096/) (2015)
- [Experiences with Improving the Transparency of AI Models and Services](https://mlsanity.com/paper/1911.08293/) (2019)
- [Aspirations and Practice of Model Documentation: Moving the Needle with Nudging and Traceability](https://mlsanity.com/paper/2204.06425/) (2022)
- [fAIlureNotes: Supporting Designers in Understanding the Limits of AI Models for Computer Vision Tasks](https://mlsanity.com/paper/2302.11703/) (2023)
- [Unlocking Model Insights: A Dataset for Automated Model Card Generation](https://mlsanity.com/paper/2309.12616/) (2023)
- [Towards an Interface Description Template for AI-enabled Systems](https://mlsanity.com/paper/2007.07250/) (2020)

## Abstract (arXiv)

Artificial Intelligence (AI) faces persistent challenges in terms of transparency and accountability, which requires rigorous documentation. Through a literature review on documentation practices, we provide an overview of prevailing trends, persistent issues, and the multifaceted interplay of factors influencing the documentation. Our examination of key characteristics such as scope, target audiences, support for multimodality, and level of automation, highlights a dynamic evolution in documentation practices, underscored by a shift towards a more holistic, engaging, and automated documentation.