When the algorithm runs everything around you, it’s important that the people behind it reflect you.
Matthew Finney is a guru when it comes to all things surrounding the process or set of rules that calculate how humans navigate the world through technology. As a data scientist and strategy consultant at Harvard, he is responsible for developing AI decision systems that help large organizations make noise when it comes to some of their most challenging business and mission problems.
He joined AfroTech’s Will Lucas to discuss how there is still bias when it comes to the algorithm and how having more people who look like us in the data science industry can move mountains for us in the long run.
Life As A Data Scientist
“My job is to develop artificially intelligent decision systems that help large organizations make an impact on their most challenging business and mission problems,” Finney shared during the latest episode of Black Tech Green Money.
He further explains the nuances that come with the advancements of technology and the effect it has on the work he’s passionate about.
“I can sometimes be a reluctant technologist. Don’t get me wrong, in the last decade we have made some amazing feats with artificial intelligence,” he continued. “We’ve been able to figure out what you want to buy before you knew what you want. We can have a self-driving artificial intelligent electric car, and if that wasn’t enough, we put it in space. We’ve trained AI to read mammograms with particular skill at diagnosing a set of highly invasive cancers that radiologists missed, but we still haven’t figured out how to make our technology treat others the way that we would want to be treated.”
Combating Algorithmic Bias
In order to tackle an issue, it must first be identified and defined. Finney explains why this is imperative when it comes to the way the world approaches algorithmic bias and the steps needed to address it.
“First, we’re going to define and measure algorithmic bias, then we’re going to figure out how we can isolate the root cause of poor algorithmic behavior,” he said. “And finally, we’re going to learn how we can take action to make algorithms more fair.”
Listen To The Full Episode Here
Finney doesn’t just stop at the definition of algorithmic bias, but he proceeds to use the conversation to teach folks the best way to approach it in order to create a society that is better for people who look like us.
Listen to the full Black Tech Green Money episode below.