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S4 E22 - Dr. Jabe Bloom - Navigating the Myths and Realities of AI with Pragmatism

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Innehåll tillhandahållet av John Willis. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av John Willis eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

In this episode of The Profound Podcast, I sit down with Dr. Jabe Bloom, a researcher and expert in systems thinking, AI, and digital transformation. We explore Eric Lawson’s book The Myth of AI, tackling the contentious debate around artificial general intelligence (AGI). Dr. Bloom offers insights from his dissertation and divides the ongoing discourse on AI into two camps: dogmatists and pragmatists. Dogmatists believe AGI is inevitable, while pragmatists focus on the practical impacts of current AI technology, such as large language models (LLMs), and how these will reshape businesses, education, and society.

Throughout the episode, Dr. Bloom explains his framework for thinking about AI, touching on proactionary versus precautionary approaches to its development and regulation. He also draws connections between these ideas and W. Edwards Deming’s principles, especially around abductive reasoning—a concept that links back to Dr. Bloom’s past discussions about AI’s potential in problem-solving.

The conversation takes a critical view of AGI's feasibility, with Dr. Bloom emphasizing the current challenges AI faces in replicating abductive reasoning, which involves making intelligent guesses—a capability he argues machines have yet to achieve. We also dive into examples from fields like DevOps, healthcare, and city planning, discussing where AI has shown great promise and where it still falls short.

Key takeaways from the episode include the importance of addressing present AI technologies and their immediate impacts on work and society, as well as the ongoing need for human oversight and critique when using AI systems.

  continue reading

82 episoder

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iconDela
 
Manage episode 447115587 series 3568163
Innehåll tillhandahållet av John Willis. Allt poddinnehåll inklusive avsnitt, grafik och podcastbeskrivningar laddas upp och tillhandahålls direkt av John Willis eller deras podcastplattformspartner. Om du tror att någon använder ditt upphovsrättsskyddade verk utan din tillåtelse kan du följa processen som beskrivs här https://sv.player.fm/legal.

In this episode of The Profound Podcast, I sit down with Dr. Jabe Bloom, a researcher and expert in systems thinking, AI, and digital transformation. We explore Eric Lawson’s book The Myth of AI, tackling the contentious debate around artificial general intelligence (AGI). Dr. Bloom offers insights from his dissertation and divides the ongoing discourse on AI into two camps: dogmatists and pragmatists. Dogmatists believe AGI is inevitable, while pragmatists focus on the practical impacts of current AI technology, such as large language models (LLMs), and how these will reshape businesses, education, and society.

Throughout the episode, Dr. Bloom explains his framework for thinking about AI, touching on proactionary versus precautionary approaches to its development and regulation. He also draws connections between these ideas and W. Edwards Deming’s principles, especially around abductive reasoning—a concept that links back to Dr. Bloom’s past discussions about AI’s potential in problem-solving.

The conversation takes a critical view of AGI's feasibility, with Dr. Bloom emphasizing the current challenges AI faces in replicating abductive reasoning, which involves making intelligent guesses—a capability he argues machines have yet to achieve. We also dive into examples from fields like DevOps, healthcare, and city planning, discussing where AI has shown great promise and where it still falls short.

Key takeaways from the episode include the importance of addressing present AI technologies and their immediate impacts on work and society, as well as the ongoing need for human oversight and critique when using AI systems.

  continue reading

82 episoder

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