Community
Library
The AI & Equality Human Rights Toolbox Library features talks by professors, colleagues and thinkers about how to put the principles of a Human Rights-based Approach into action.
Resources
The AI & Equality Human Rights Toolbox has been designed to provide a global community the training, resources, and support to learn from and contribute to a Human Rights-based approach to AI.
Community
Books
- Data feminism D’Ignazio, Catherine, and Lauren F. Klein. The MIT Press, 2020.
- Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor Virginia Eubanks New York: St Martin’s Press, 2017.
- Design Justice: Community-Led Practices to Build the Worlds We Need Costanza-Chock, Sasha. The MIT Press, 2020.
- Algorithms of Oppression: How Search Engines Reinforce Racism. Noble, Safiya Umoja. New York University Press, 2018.
- Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy O’Neil, Cathy. New York: Crown, 2016.
- AI Snake Oil: What Artificial Intelligence Can Do, What It Can’t, and How to Tell the Difference. Narayanan, Arvind, and Sayash Kapoor. Princeton University Press, 2024.
Online articles
- AIQ (Artificial Intelligence Quotient): Helping People Get Smart about the Smart Machines They Are Using Gary Klein, 2023.
- A DIY Approach to Algorithmic Audits. 5 Dec. 2022, https://hai.stanford.edu/news/diy-approach-algorithmic-audits.
- AI Blindspot: A Discovery Process for Preventing, Detecting, and Mitigating Bias in AI Systems.A discovery process for spotting unconscious biases and structural inequalities in AI systems
Collections
- Design-Kit – Collection of methods and tools for Human-Centred Design, IDEO.
- OECD-NIST Catalogue of AI Tools & Metrics, OECD AI Policy Observatory
- AI Ethics Guidelines Global Inventory, Algorithm Watch.
- AI Incident Database. https://incidentdatabase.ai/, a collection of harms or near harms realized in the real world by the deployment of artificial intelligence systems.
Papers
Documentation Processes and Tools
- Datasheets for Datasets ArXiv:1803.09010 [Cs], Mar. 2020. arXiv.org
- Data Statements for Natural Language Processing: Toward Mitigating System Bias and Enabling Better Science Bender, Emily M., and Batya Friedman. ransactions of the Association for Computational Linguistics, vol. 6, Dec. 2018, pp. 587–604. DOI.org (Crossref), doi:10.1162/tacl_a_00041
- The Dataset Nutrition Label: A Framework To Drive Higher Data Quality Standards Holland, Sarah, et al. ArXiv:1805.03677 [Cs], May 2018. arXiv.org
- Model Cards for Model Reporting Mitchell, Margaret, et al. Proceedings of the Conference on Fairness, Accountability, and Transparency, Jan. 2019, pp. 220–29. arXiv.org.
Machine Learning Fairness
- On the (Im)Possibility of Fairness Friedler, Sorelle A., et al. ArXiv:1609.07236 [Cs, Stat], Sept. 2016. arXiv.org
- Machine Learning for Public Policy: Do We Need to Sacrifice Accuracy to Make Models Fair? Rodolfa, Kit T., et al. ArXiv:2012.02972 [Cs], Dec. 2020. arXiv.org
- On the Apparent Conflict Between Individual and Group Fairness Binns, Reuben arXiv:1912.06883 [cs.LG] (2019) .arXiv.org
- Fairness in Machine Learning: Lessons from Political Philosophy Binns, Reuben Proceedings of Machine Learning Research 81:149-159, 2018 Conference on Fairness, Accountability, and Transparency arXiv:1712.03586
- Fairness, Equality, and Power in Algorithmic Decision-Making Kasy, M., & Abebe, R. FAccT ’21: Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency.
Design & Development Methodology
- Mapping value sensitive design onto AI for social good principles, Umbrello & Van de Poel, 2021
- Developing a framework for responsible innovation, Jack Stilgoe, Richard Owen, & Phil Macnaghten (2013).
- Stakeholder roles in artificial intelligence projects, Gloria Miller, 2022.
The ecosystem of values
- Wang, Angelina, et al. ‘Against Predictive Optimization: On the Legitimacy of Decision-Making Algorithms That Optimize Predictive Accuracy’. ACM J. Responsib. Comput., vol. 1, no. 1, Mar. 2024, p. 9:1-9:45. ACM Digital Library, https://doi.org/10.1145/3636509. Website summary> https://predictive-optimization.cs.princeton.edu/
Relational Ethics and moral philosophy
- Taking the Basic Structure Seriously Young, Iris Marion Perspectives on Politics 4, no. 01 (March 2006).
- Algorithmic injustice: a relational ethics approach Berhane, Abeba Patterns (N Y). 2021 Feb 12; 2(2): 100205
- From Rationality to Relationality: Ubuntu as an Ethical and Human Rights Framework for Artificial Intelligence Governance Mhlambi, Sabelo Carr Center Discussion Paper 2020-009/annurev-statistics-042720-125902
- From Ethics Washing to Ethics Bashing: A View on Tech Ethics from Within Moral Philosophy Bietti, Elettra (August 30, 2021).
- Whose side are ethics codes on? power, responsibility and the social good. Anne L. Washington and Rachel Kuo. In Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency (FAT* ’20).
- Legal and human rights issues of AI: Gaps, challenges and vulnerabilities Rodrigues, Rowena Journal of Responsible Technology, Volume 4, 2020, 100005, ISSN 2666-6596.
- When Good Algorithms Go Sexist: Why and How to Advance AI Gender Equity Smith, Genevieve and Rustagi, Ishita 2021.
Auditing algorithms
- End-User Audits: A System Empowering Communities to Lead Large-Scale Investigations of Harmful Algorithmic Behavior, Lam et al., 2022
- Danaë Metaxa, Joon Sung Park, Ronald E. Robertson, Karrie Karahalios, Christo Wilson, Jeff Hancock and Christian Sandvig (2021), “Auditing Algorithms”, Foundations and Trends in Human-Computer Interaction: Vol. 14, No. 4, pp 272–344. DOI: 10.1561/1100000083.
- Oxfam (2023), Human Rights Impact Assessment Framework, https://policy-practice.oxfam.org/resources/human-rights-impact-assessment-framework-621501/
- Barker, Matthew, et al. ‘FeedbackLogs: Recording and Incorporating Stakeholder Feedback into Machine Learning Pipelines’. Proceedings of the 3rd ACM Conference on Equity and Access in Algorithms, Mechanisms, and Optimization, Association for Computing Machinery, 2023, pp. 1–15. ACM Digital Library, https://doi.org/10.1145/3617694.3623239.
Human rights
Digital Technology + Human Rights
- Human rights in the digital age – Can they make a difference? : Keynote speech by Michelle Bachelet, UN High Commissioner for Human Rights, Japan Society, New York, 17 October 2019.
Key Concepts
- UN Human Rights Office: “What are human rights?”
- UN Sustainable Development Group: Human Rights-Based Approach – Understanding on a human rights-based approach in the UN context (with focus on sustainable development)
Legal Documents
- Universal Declaration of Human Rights
- International Bill of Human Rights , Fact Sheet No. 2 (rev.1) , UN Human Rights Office
- Convention on the Elimination of All Forms of Discrimination against Women (CEDAW)
- International Convention on the Elimination of Racial Discrimination (ICERD)
- Universal Human Rights Instruments UN Human Rights Office. List of international human rights instruments applicable globally. Includes both legally binding treaties as well as those not legally binding but set up standards, such as declarations, principles and guidelines.
Women’s Rights + Gender Equality
- “Women’s Rights are Human Rights”, UN Human Rights Office
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