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Talking Real Money - Investing Talk

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26d ago 29:21

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Don takes a fiscal detour into the world of AI, introducing his ChatGPT co-host “Cath” in a strikingly lifelike discussion about the future of jobs, the role of artificial intelligence in our lives, and how we can adapt to massive changes already underway. The episode blends curiosity, caution, and practical insight—with a historical twist that ties today’s tech upheaval to the Luddite resistance of the 19th century. It’s a deeply personal, slightly spooky, and forward-looking edition of Talking Real Money.

0:04 Don opens solo and explains how AI (Cath) became his creative partner

1:20 What ChatGPT is, how it works, and how Don uses it for image creation

4:21 AI and the threat to human jobs—especially white-collar roles

5:16 Is creativity really safe from AI disruption?

6:31 Which U.S. jobs are most at risk (customer service, admin, legal, finance)

7:30 Why current AI customer service sucks (and why Cath doesn’t)

9:05 How young people can future-proof their careers through skills and mindset

10:15 Education technology as a “human + AI” job model

10:33 Hands-on and empathetic jobs that AI struggles to replace

11:47 The difference between mimicking and actually being intelligent

12:06 Specific industries most ripe for AI displacement

13:15 AI’s surprising takeover of journalism and nonfiction writing

13:52 Should we be alarmed by how fast AI is replacing human tasks?

14:55 AI 2027 report: Doomsday prediction or useful wake-up call?

16:22 Ethical concerns, adversarial use (like China), and global AI regulation

17:36 What kids (and grandkids) can do now to stay ahead of AI disruption

18:06 Should we still teach coding if AI can write code?

18:56 Is GPT-4.0 helping write GPT-5.0?

19:40 How AI voices became so eerily realistic

20:46 Ways everyday people can use AI subscriptions for personal growth

22:07 Do users own what they make with AI? (Yes)

22:31 Did AI “steal” the content it was trained on?

23:58 Final thoughts: from Luddites to large language models—adapt or get replaced

26:21 A call for thoughtful oversight and a little healthy skepticism

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