COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |
University of Cambridge > Talks.cam > C.U. Ethics in Mathematics Society (CUEiMS) > Ethics for the working mathematician, Seminar 4: Fairness and impartiality in algorithms and AI
Ethics for the working mathematician, Seminar 4: Fairness and impartiality in algorithms and AIAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact Sae Koyama. Algorithms run the world, and mathematicians are designing them. Algorithms decide what people read, what they buy, and when then can get a loan. We often design these systems to remove human subjectivity from decision making processes and to make them impartial, as is being done with predictive policing algorithms and prison sentencing algorithms. But how impartial, or fair, can a system designed by humans ever be? Moreover, the internet and big data have given rise to massive new potential, from targeted political advertising as done by Cambridge Analytica, to AI technology such as deepfake videos and self-driving cars. Our ‘solutions’ in these instances can bring about a whole new set of problems. This talk is part of the C.U. Ethics in Mathematics Society (CUEiMS) series. This talk is included in these lists:
Note that ex-directory lists are not shown. |
Other listsBrain Training: secrets, drugs and analysis. Engineering Structures Seminar Series Inference Group SummaryOther talksArm relaxed systems semantics Proof-oriented Programming: Foundations, Systems, & AI What can Arctic staircases tell us about ocean mixing? Q&A Session First integrals for solutions of the conformal Mercator equation Cyber Security in the Era of Quantum Computing |