Improving Prediction in Human Behavior Using Behavior Modifications

Improving Prediction in Human Behavior Using Behavior Modifications

Thursday 27 August, 12pm-1pm AEST via Zoom webinar.

Professor Gatil Shmueli, National Tsing Hua University, Taiwan

In this lecture, Professor Shmueli will discuss several dilemmas, challenges, and trade-offs related to behavioral big data.  Internet platforms with vast amounts of behavioral data commonly predict human behaviors. Predictions are sold to third parties who utilize them for personalisation, targeting and other decision-making. Because better predictions translate into higher financial value, platforms are incentivised to reduce prediction errors. Beyond improving algorithms and data, platforms can stealthily achieve 'better' predictions by 'pushing' users' outcomes towards their predicted values, using behavior modification techniques, thereby demonstrating more certain predictions. This strategy is absent from the machine learning and statistics literature. Professor Shmueli’s team integrate causal inference notation with correlation-based prediction in order to formalise and analyse how behavior modification results in 'improved' prediction errors. Their discoveries should alert data scientists and purchasers of prediction products, and raise moral, and societal concerns.

Register here: https://bit.ly/3fOM7Q3