This repository provides a curated reading list on ethical, transparent, and fair AI/ML, targeting engineers, designers, policymakers, and researchers. It aims to contextualize AI as a sociotechnical system, offering critical discourse and resources to understand its societal impact beyond technical capabilities.

How It Works

The project is a comprehensive, open-ended collection of academic papers, articles, videos, and books categorized by key themes such as critical AI studies, accountability, transparency, bias, fairness, ownership, ethics, policy, labor impact, social impact, propaganda, design, and auditing. It encourages readers to explore connections between these multifaceted aspects of AI.

Quick Start & Requirements

This is a reading list, not a software project. No installation or specific technical requirements are needed beyond internet access to view the linked resources.

Highlighted Details

• Extensive categorization of resources covering a broad spectrum of AI's societal implications.
• Includes foundational texts and contemporary research from leading academics and institutions.
• Provides links to supplementary materials like "lists of lists" and research initiatives for deeper exploration.
• Features optional sections for further reading on specific sub-topics.

Maintenance & Community

The list is maintained by a single contributor (@irinimalliaraki) with an invitation for suggestions and comments via Twitter or email. It does not appear to have a formal community or development roadmap.

Licensing & Compatibility

The repository itself is likely under a permissive license (e.g., MIT, Apache 2.0, common for GitHub projects), but the licensing of the linked external resources varies significantly and is not specified.

Limitations & Caveats

As a curated list, its comprehensiveness is subjective and dependent on the curator's ongoing efforts. The lack of a structured community or formal maintenance process may lead to outdatedness or unaddressed suggestions.