Julia Angwin
Pulitzer Prize–Winning Investigative Journalist & Authority on Data & AI Accountability
Julia Angwin is an investigative journalist whose work has reshaped how organisations understand data power, algorithmic decision making, and accountability. A Pulitzer Prize–winning reporter and the co-founder of The Markup, she is best known for exposing how data driven systems affect fairness, privacy, and civil rights, often long before regulators or executives recognise the risk.
Julia’s investigations reveal how algorithms behave in the real world, where bias, opacity, and unintended harm surface at scale. As AI systems increasingly influence hiring, pricing, policing, and access to opportunity, she helps leaders understand what actually happens when automated decisions meet people.
Her talks are rigorous, compelling, and grounded in facts. They focus on what leaders must know before deploying AI systems, how risks emerge, where oversight fails, and how confidence is built through transparency, testing, and accountability rather than assumption.
Signature Keynotes
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How data-driven systems behave once deployed in the real world.
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Why transparency and testing matter more than intent.
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What investigations reveal about fairness at scale.
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How unintended harm enters algorithmic systems.
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Why independent scrutiny strengthens innovation.
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How AI moves from laboratories into collective meaning.
The Angwin Effect
Accountability becomes a prerequisite for trust.
Audiences leave ready to:
Understand how algorithmic harm emerges in practice
Recognise where data-driven systems fail silently
Ask better questions before AI is deployed at scale
Build oversight that detects risk early, not after damage
Lead with evidence rather than reassurance
Why Book Julia
Julia Angwin brings rare credibility from the investigative front line of AI and data accountability. Her insight resonates with boards, executives, and policymakers operating in high-trust, high-risk environments where mistakes are public and costly.
Book a speaker who reframes artificial intelligence as something leaders must verify, not simply adopt.
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