Local founders reveal how AI is seeping into legacy industries
John Derrick, Knoxville-based Founder of Authentrics.AI joined the panel at the annual "3686 Conference" in Nashville.
The “3686 Conference” joined entrepreneurs, founders, investors, and technologists from across the state to discuss the latest trends and showcase Southeast innovation. One of the panels was “AI for legacy industries” and it brought together four of the brightest minds in artificial intelligence (AI) in the state: John Derrick, Charles Alexander, Grace Hanson, and Kate O’Neil. All four are leaders of cutting-edge companies harnessing the power of AI.
Notably, Derrick is the Founder of Authentrics, which is based in Knoxville, and a portfolio company of Market Square Ventures. His company is focused on monitoring the data that goes into what he calls the “AI Blackbox.”
“What I do is help companies see where their AI comes from,” Derrick said in the panel. “Companies can open it up, trace it back, and get rid of any wrong, biased, or misinformed data.”
The panel primarily discussed how the biases of AI could impact existing corporations. For example, O’Niel is the Chief Executive Officer (CEO) of a start-up in the realm of Human Resources technology. Her company, Opre, uses AI to scan employee reviews for manager biases.
“Humans are full of good biases and bad biases and that affects our performance reviews, and ultimately maybe our employment. Our system identifies those biases to help prevent companies getting sued for wrongful termination of employees,” she explained.
It goes both ways, humans can be biased and therefore AI will be biased if it’s fed biased data made by humans. Make sense?
Take for example what happened with the roll-out of Google’s Gemini. Derrick used this as an example. The AI was programmed for inclusivity; and thus could not create historically accurate generated images.
“It’s one thing to build AI with good intentions, but it’s another thing to leverage it and control it for public use,” Derrick explained, sharing th importance for corporations to be careful with their deployment of AI in the public sector too fast.
He drew parallels between AI and research papers. Researchers must spend hours double and triple-checking their facts. Then, it goes through a peer-review process. It should be the same with AI data sets.
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