52 min

AI Failure Series - Overpromising and Underdelivering AI Today Podcast: Artificial Intelligence Insights, Experts, and Opinion

    • Technology

AI is not new - in fact the term was coined in 1956. Why then, if it's been around for decades, and we are now on our third major wave of AI interest and hype, do we keep making the same mistakes that have brought us to two previous AI Winters? Are we still overpromising what AI can deliver? In this podcast hosts Kathleen Walch and Ron Schmelzer will discuss why we are still overpromising and underdelivering on what AI can do, how we can address this, and what can be done to set realistic expectations to ensure AI project success.








Show Notes:










CPMAI Methodology







AI Today podcast: AI Failure Series- AI projects are NOT like traditional software development projects







AI Today Podcast: AI Failure Series – ROI Misalignment







AI Today Podcast: AI Failure Series- Data Quality Issues







AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues







AI Today Podcast: AI Failure Series – Not Understanding the Model & Data Lifecycle







AI Today Podcast: AI Failure Series – Believing Vendor & Industry Hype







AI Today Podcast: AI Failure Series – The Real World Mismatch







AI Today Podcast: AI Failure Series – Iteration Time & Proof of Concept vs. Pilots







AI Today Podcast #005: The AI Winters







AI Today Podcast #67: AI in the museum: Interview with Kristi Delich, Deputy Director, Office of Visitor Services, Smithsonian Institution

AI is not new - in fact the term was coined in 1956. Why then, if it's been around for decades, and we are now on our third major wave of AI interest and hype, do we keep making the same mistakes that have brought us to two previous AI Winters? Are we still overpromising what AI can deliver? In this podcast hosts Kathleen Walch and Ron Schmelzer will discuss why we are still overpromising and underdelivering on what AI can do, how we can address this, and what can be done to set realistic expectations to ensure AI project success.








Show Notes:










CPMAI Methodology







AI Today podcast: AI Failure Series- AI projects are NOT like traditional software development projects







AI Today Podcast: AI Failure Series – ROI Misalignment







AI Today Podcast: AI Failure Series- Data Quality Issues







AI Today Podcast: AI Failure Series – Data Quantity & Data Understanding Issues







AI Today Podcast: AI Failure Series – Not Understanding the Model & Data Lifecycle







AI Today Podcast: AI Failure Series – Believing Vendor & Industry Hype







AI Today Podcast: AI Failure Series – The Real World Mismatch







AI Today Podcast: AI Failure Series – Iteration Time & Proof of Concept vs. Pilots







AI Today Podcast #005: The AI Winters







AI Today Podcast #67: AI in the museum: Interview with Kristi Delich, Deputy Director, Office of Visitor Services, Smithsonian Institution

52 min

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