Research on human biases in AI learning earns best student paper award

By | May 26, 2020

The project demonstrated that a certain bias in humans who train intelligent agents significantly reduced the effectiveness of the training.

A team of researchers working to more effectively train autonomous agents earned the Pragnesh Jay Modi – Best Student Paper at the International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS 2020). Led by second-year Ph.D. student Divya Ramesh, the project demonstrated that a certain bias in human trainers significantly reduced the effectiveness of an agent’s learning.

Intelligent agents promise to save us time spent on repetitive, menial tasks, freeing us up for more creative and meaningful work. But to do that they need to be able to work with us effectively. That means that they must be attuned to a user’s strengths and weaknesses, and able to navigate our complex working environments.

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Author: News Staff

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