Mitigating algorithmic bias in AI systems

In this talk, Dr Nicol Turner Lee will address her research and present the components of her new ratings system as part of her talk.

Introduction
Dr Nicol Turner Lee is a senior fellow in Governance Studies and Director of the Center for Technology Innovation at the Brookings Institution, a global think tank. She researches public policy designed to enable equitable access to technology, and is a sought after speaker in the US on topics such as digital futures, AI and ethics, algorithmic bias, and the intersection between technology and human rights.

This talk is suitable for a general audience.

About the event
From what we buy, to how we learn, AI systems are making predictions that have a huge impact on our lives and livelihoods. Yet, when these AI systems exhibit explicit or implicit biases, it is sometimes too late to reverse the consequences for individual users.

In some instances, the denial of credit or housing can have long-standing implications on the people who apply, especially if they are from more vulnerable populations. But biased technology is not just a problem for the users, developers face massive reputational risks when deploying these biased algorithms.

In her research, Dr Turner Lee is establishing a sociotechnical approach to AI bias, and has been architecting an "energy star ratings" system that integrates high quality technical cadence in model design, appropriate public policy prescriptions, and consumer feedback loops. Her work relies on the argument that best practices among AI developers should predict potential discriminatory outcomes before certain algorithms are implemented and should correct for biases throughout their life cycles.

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