# A Democratic Platform for Engaging with Disabled Community in Generative AI Development

arXiv: https://arxiv.org/abs/2309.14921 · HTML: https://mlsanity.com/paper/2309.14921/

## Key facts

- No citing papers in the map yet (data through 7 Oct 2026).
- Builds on 3 of its 13 references that are in the map.
- First posted on arXiv 26 Sep 2023.

## Builds on (most cited first, 3 of 3)

- [Toxicity in ChatGPT: Analyzing Persona-assigned Language Models](https://mlsanity.com/paper/2304.05335/) (2023)
- [Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scale](https://mlsanity.com/paper/2211.03759/) (2022)
- ['Generative CI' through Collective Response Systems](https://mlsanity.com/paper/2302.00672/) (2023)

## Abstract (arXiv)

Artificial Intelligence (AI) systems, especially generative AI technologies are becoming more relevant in our society. Tools like ChatGPT are being used by members of the disabled community e.g., Autistic people may use it to help compose emails. The growing impact and popularity of generative AI tools have prompted us to examine their relevance within the disabled community. The design and development phases often neglect this marginalized group, leading to inaccurate predictions and unfair discrimination directed towards them. This could result from bias in data sets, algorithms, and systems at various phases of creation and implementation. This workshop paper proposes a platform to involve the disabled community while building generative AI systems. With this platform, our aim is to gain insight into the factors that contribute to bias in the outputs generated by generative AI when used by the disabled community. Furthermore, we expect to comprehend which algorithmic factors are the main contributors to the output's incorrectness or irrelevancy. The proposed platform calls on both disabled and non-disabled people from various geographical and cultural backgrounds to collaborate asynchronously and remotely in a democratic approach to decision-making.