Joshua Kroll

Chevron down

Responsible AI for Good

AI has the potential to provide solutions to many serious problems facing the world. But just as normal, commercial uses of AI raise concerns about the relationship between technology, people, and society, so do uses "for good". AI for good requires careful thought about responsibility, and a careful weighing of the costs and benefits of the technology as it is applied in the world. AI technology can reinforce existing social structures, distribute benefits in an unjust way, assault the autonomy, dignity, and privacy of those it aims to help, or be abused for purposes its controllers and developers did not foresee. Starting from three principles for the responsible use of AI, this talk examines how to think about what responsible AI deployment requires when that use is intended for a beneficial use. Specifically, it will address how to uphold the intended values, such as fairness, ethics, privacy, and the beneficence of the use considered.

Joshua A. Kroll, PhD, is a computer scientist and leading expert recognized internationally for his work on responsibility and accountability in computer systems, especially automated decision-making systems and systems that use data science, machine learning, and artificial intelligence. As a Postdoctoral Research Scholar at the School of Information at the University of California, Berkeley, he studies how technology fits within a human-driven, normative context and how it satisfies goals driven by ideals such as fairness, accountability, transparency, security, privacy, and ethics.

Joshua has helped to develop and lead the field of fairness, accountability, and transparency in computer systems. His paper "Accountable Algorithms", published in the University of Pennsylvania Law Review (Vol. 165, 2016-17) received the Future of Privacy Forum's Privacy Papers for Policymakers Award in 2017. Joshua has also organized related research venues, including the Workshop on Fairness, Accountability, and Transparency in Machine Learning (FAT/ML) and the Conference on Fairness, Accountability, and Transparency (FAT*).

Joshua holds a Bachelor's degree in physics and mathematics from Harvard College as well as a Master's degree and a Doctorate in computer science from Princeton University. His previous research work spans accountable algorithms, cryptography, software security, formal methods, Bitcoin, and several aspects of technology policy.

Buttontwitter Buttonlinkedin
This website uses cookies to ensure you get the best experience. Learn more