Rumman Chowdhury

  • Professions

    CEO and Co-Founder, Humane Intelligence

  • Languages spoken

    English

  • Travels from

    New York/ Texas, USA

Rumman Chowdhury

CEO and Co-Founder, Humane Intelligence; Responsible AI Fellow, Berkman Klein Center for Internet & Society, Harvard University.

First United States Science Envoy for Artificial Intelligence (Biden Administration); Former Member, Artificial Intelligence Safety and Security Board, U.S. Department of Homeland Security

Dr. Rumman Chowdhury is a globally recognized leader in the fields of artificial intelligence (AI), ethics, and responsible technology. She is CEO and co-founder, Humane Intelligence and co-founder of Bias Buccaneers, a collective working on practical approaches to AI safety, and the former Director of the Machine Learning Ethics, Transparency, and Accountability (META) team at Twitter, where she focused on mitigating algorithmic harms and advancing ethical AI practices. Before that, she founded and served as CEO of Parity AI, a startup dedicated to building solutions for responsible AI, and worked as Global Lead for Responsible AI at Accenture Applied Intelligence. With a background that bridges data science, technology, and policy, she has been at the forefront of conversations on AI fairness, accountability, and transparency worldwide.

Beyond her professional leadership, Dr. Chowdhury is an educator, speaker, and advocate for inclusive and ethical innovation. She frequently advises governments, academic institutions, and industry leaders on the societal impact of AI and emerging technologies. Her work has been recognized by numerous international organizations, and she has been named to several prestigious lists highlighting influential women in technology. Through her research, public speaking, and thought leadership, Dr. Chowdhury continues to shape how AI is developed and deployed responsibly, ensuring it aligns with human values and benefits society as a whole.

SPEAKING TOPICS:

  • Responsible Artificial Intelligence (AI)
  • Algorithmic Fairness and Bias Mitigation
  • AI Governance and Regulation
  • Ethics and Transparency in Machine Learning
  • Human Rights and Social Impact of AI
  • Building Inclusive and Equitable Technology
  • AI Safety and Risk Management