The stories of bias in AI are everywhere: Amazon’s recruiting tool, Apple’s credit card limits, Google’s facial recognition, and dozens more. The quick solution is just to blame the algorithm and its designers. But it’s not a question of whether or not you have bias in your institution, but rather how you plan to handle it.
In part 2 of 2 of this latest Data Science Central podcast, ‘How to Start Tackling AI Bias, Part 2: Building Fair AI’, Jett Oristaglio, Data Science Product Lead of Trusted AI at DataRobot, will take a deeper dive into how to tackle AI bias, including:
How machine learning can highlight the implicit bias of an institution and how AI is a new toolset to measure and change it
A practical plan that you can implement to improve your AI development and increase trust in your AI
Jett Oristaglio, Data Science Product Lead of Trusted AI – DataRobot
Sean Welch, Host and Producer – Data Science Central