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July 15, 2020 33 min
"First is the worst, second is the best, third is the one with the treasure chest." Some of you may recognize this old children's poem, variations of which can be found on the internet that replace the last two words "treasure chest" with....well, I'll leave it up to you to find out. Though quaint, this rhyme is actually quite germane as shorthand for the many iterations AI projects must cycle through before they start delivering trusted data, trusted decisions, & trusted outcomes. The worst results are at the beginning, but as time goes on and the AI continues learning & improving, the results can be quite good, and for organizations who stick with it, very successful. When it comes to AI projects, significant time often passes between inception and dividends, due to the many steps which must be taken to get things right. Our guest Matt Sanchez argues that in order to protect customer’s trust in your brand, there should be no short cuts taken along this route. In fact as Founder & CTO of CognitiveScale, a company focused on helping clients to pair humans with machines, he advocates for “responsible AI” as a framework to ensure that AI never breaches customer trust. Matt joins us for a broad-based discussion that taps into his wide-ranging insights on AI dating back to his days as a Leader of IBM’s Watson Labs. In this episode, we'll learn about the 6 key components that make up responsible AI, why data needs to be "nutritious, digestible, and delicious", and the bottomline proof that leaves him so optimistic about AI's future.
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