Challenge Algorithmic Bias

Objectives

Learn how algorithms impact decisions in finance, jobs, and justice. Support efforts to audit and regulate biased algorithms.

Advocate for transparency in automated decision-making. Educate others about the risks of algorithmic discrimination.

Demand accountability from companies using AI and automation.

Encourage the development and use of algorithms that are inclusive, fair, and regularly reviewed for bias.

Read reports like ProPublica’s study on predictive policing or MIT’s Gender Shades project exposing facial recognition bias.

Try Elements of AI or Data Ethics, AI, and Responsible Innovation (University of Edinburgh, free online).

Back the Algorithmic Justice League, Data & Society, or AI Now Institute, which audit and challenge biased systems.

When interacting with schools, employers, or agencies, ask if decisions involve automated systems and request explanations.

Support initiatives like the AI Audit Toolkit or laws requiring regular bias audits for companies deploying AI.

Highlight and share projects like Google’s skin-tone scale research or Inclusive Images dataset to improve representation.

Encourage developers and organizations to use open-source toolkits like Aequitas, Fairlearn, or AI Fairness 360 for bias testing.

Support regulations like the Algorithmic Accountability Act (U.S.) or the EU AI Act that require transparency and fairness in AI.