DrupalCon Seattle 2019: Erase Unconscious Bias From Your AI Datasets
Channel: Drupal Association
Date: 2019-04-12

Advances in AI techniques like machine learning and deep neural networks have potential to save time and boost productivity. But what if we train these technologies using datasets that exclude large portions of the population?

For example, some facial recognition software doesn’t acknowledge dark skin. Why? People of color were excluded from the datasets that were used to train the software. If AI isn’t designed with inclusion upfront, its rewards won’t equally benefit us all. The good news is that while such unconscious bias is unavoidable, it is not insurmountable.

This talk will share:

What machine bias is

Why it's dangerous for end users

The root cause of machine bias

How to add bias testing to product development lifecycles.

Attendees should have at least basic knowledge of machine learning, classifiers, and other aspects of datasets that are used to train AI-powered products. They will leave my session knowing which actions they can take to add bias testing to product development lifecycles so that they can build more equitable AI products that benefit all end users.