AI Is Coming For Your Job… Everyone Will Be Forced To Become Entrepreneurs (w/ Sinéad Bovell)

Summary

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Earn Your Leisure Podcast

Episode: “AI Is Coming For Your Job… Everyone Will Be Forced To Become Entrepreneurs”

Guest: Sinéad Bovell

Date: March 19, 2026
Hosts: Rashad Bilal & Troy Millings

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Episode Overview

In this thought-provoking episode, hosts Rashad Bilal and Troy Millings welcome futurist, technology educator, and entrepreneur Sinéad Bovell for a deep dive into artificial intelligence and its seismic impact on careers, entrepreneurship, education, and society at large. Bovell discusses how the rise of AI is rapidly transforming the nature of work, what skills will define future success, the dark and bright futures AI may bring, and why everyone may soon need to think like an entrepreneur—ready or not.

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Key Discussion Points & Insights

The Makings of a Futurist: Sinéad Bovell’s Journey

[05:41 – 07:39]

• Sinéad details her pivot from studying business and management consulting to becoming a renowned futurist through a pivotal “Strategic Foresight” class.
• Her fashion modeling experience unexpectedly became a springboard for her public communication about the future of technology.
• By 2016, she was tracking AI breakthroughs intensely, noting:

  “The world woke up to AI in 2022. And then the rest of the journey is kind of history.” (07:28)

The AI Tipping Point – ChatGPT and Mainstream Adoption

[09:42 – 11:21]

• Sinéad breaks down why 2022 was the moment AI “clicked” for the public:

  “What happened with ChatGPT is now the system comes on the scene that the public can interact with in a way that they understand.” (09:49)

• This was a historic shift—from AI as a tool for computer scientists to AI as an accessible, everyday platform.

The Coming Transformation of Work

[12:28 – 16:23]

• Hosts reference reports predicting white-collar jobs may soon be obsolete—a “Great Intelligence Crisis.”
• Sinéad frames upcoming workforce changes as analogous to the industrial revolution (but at warp speed):

  “I don’t think work is going away, but jobs as we know them will…We will do different things that are hard to foresee.” (14:37)

• Job transformation, not total job loss, is coming—but the pace will be disruptive.

Skills for the Future Workforce

[16:23 – 19:59]

• Success will depend less on traditional credentials, more on:
  • Judgment: Evaluating AI output and directing its use
  • Communication: Articulating questions and selling conclusions
  • Emotional Intelligence: Working harmoniously in AI-heavy teams
  • Creative Intelligence: Asking new, incisive questions
  • Domain Expertise
  • AI Literacy:

    “Not just working with a tool, but understanding: does the AI system you’re asking questions of even have the right data to answer it?” (18:22)

  • Critical Thinking and Self-Directed Learning

The Shift to Entrepreneurial Thinking — The Portfolio Career

[19:59 – 21:39]

• Sinéad emphasizes:

  “Even if you don’t consider yourself an entrepreneur in the traditional sense, you’re going to have to start thinking like one.” (20:05)

• With rapidly changing job definitions, most people will offer specialized skills to multiple organizations rather than climbing a single corporate ladder.

The Fate of Higher Education

[21:39 – 24:31]

• Skills, not degrees, will matter most. The “Harvard label” will lose meaning if not backed by practical ability.
• Existing educational institutions must overhaul how they “cultivate” and “test” knowledge to stay relevant.
• Rising cost-benefit concerns:

  “The cost of post-secondary education actually doesn’t make sense at all.” (23:34)

AI’s Impact on Professional Careers (Lawyers, Doctors, Accountants)

[24:31 – 28:50]

• The routine, basic tasks in professions (legal drafting, basic diagnoses) will be automated.

  “So, yes, a lot of things are going to go away and the professions are going to evolve into something new…What makes you a sharp lawyer today may be irrelevant in 10 years.” (27:40)

• Human expertise will apply in only the most complex, unique scenarios; most will rely on AI agents or assistants.

The AI Layer – Beyond Chatbots

[29:15 – 32:19]

• We’re moving from asking chatbots questions to AI as an always-on “infrastructure” that works autonomously for personal and business goals in the background.

  “AI is just going to be this always-on layer and we assume that it’s happening in the background.” (29:19)

• Social media as we know it may fade, replaced by new platforms fit for the AI era.

The Dark Side of AI

[32:19 – 36:46]

• Potential negative scenarios:
  • Hacking of infrastructure and critical systems
  • AI chatbots engineered for manipulation and division
  • Physical risks as AI is embodied in household robots
  • AI making decisions we can’t trace or control
• On AI developer warnings:

  “Isn’t it so ironic that the people building it are like this thing is so, it could be so terrible, as if AI is an alien landing on Earth…But you’re the one in the lab!” (33:02)

Innovation vs. Regulation

[36:46 – 38:35]

• Regulation must be as innovative as the technology it governs, not just recycled rules from past eras.
• Clear regulatory lanes can empower innovation rather than stifle it:

  “If you give people clear lines to play within…and not just like a blanket fear regulation, which doesn’t help anyone, then it shouldn’t slow stuff down.” (37:17)

National Security & The AI Arms Race

[38:35 – 44:11]

• Sinéad explains the tense standoff between U.S. government and private AI firms (Anthropic/Claude, OpenAI):
  • Pentagon is pushing for unrestricted AI model usage (including surveillance, autonomous weapons).
  • AI companies are resisting, citing ethics and the technology’s immaturity for certain applications.
  • This struggle signals a major shift:

    “The most important technology for a nation state…is no longer in the hands of the public sector. It is all run by private companies.” (38:41)

Data Privacy and AI “Memory”

[47:48 – 50:58]

• Memory/data may be stored on company clouds, used for model retraining, and accessible to governments via warrants.
• Paid users may have more privacy—class warfare in AI?

  “If you can pay for more privacy, you’ll get it, but if you can’t, you might be exposed.” (48:29)

Open Source vs. Closed Source AI & Geopolitical Power Plays

[51:47 – 56:38]

• China and the US have different AI strategies: US focuses on leading-edge systems; China focuses on diffusion (open-source, global adoption in developing markets).
• Open source models increase diffusion but pose new security and values risks, including embedding a nation’s worldview in global culture.

AI & Human Relationships

[56:38 – 62:08]

• AI companionship apps and conversational agents could lead to mass loneliness, dependency, narcissism, or delusion at scale.
• Design choices (e.g. limiting conversation lengths, triggering interventions) and regulation can mitigate these risks.

Entrepreneurial & Regulatory Opportunities in the AI Era

[62:48 – 64:55]

• Sinéad sees significant value and opportunity in “boring” but vital spaces:
  • Building regulatory markets, compliance ecosystems (“the way we have accountants and KPMG”)
  • Investing in foundational complements: energy, water, infrastructure for AI operations
  • Offline experiences and non-digital businesses may grow as a counter-trend

Future Scenarios – 10 to 20 Years Ahead

[64:55 – 67:39]

• AI-driven robotics will be commonplace (“one in four of your friends has a few robots that do things in their home for them…”).
• Most people will orchestrate AI agents rather than do individual tasks.
• Major shifts in business, new industries in biology, quantum, and space.
• Health breakthroughs, wearables, and new devices will outdate smartphones.

Notable Rapid-Fire Q&A

[67:52 – 69:18]

• Will AI create more millionaires than the Internet?

  “I think it already has…” (68:03)

• Biggest lie about AI:

  “That it’s alive. At least the systems we have today are not.” (68:39)

• Will AI make the rich richer or create more opportunity for everyone?

  “Probably a yes to both…it’s going to be a definite yes to making rich people richer.” (68:58)

Medicine & Longevity — The AI Impact

[70:55 – 78:13]

• Will life expectancy increase?

  “Life expectancy should definitely increase because of AI, even just AI in a system like a wearable ring that’s flagging something like heart disease…” (71:02)

• AI/biotech collaborations will likely eradicate many genetic diseases (e.g. sickle cell, diabetes, cancer) through prediction, detection, and custom treatments.
• Cellular programming may significantly extend human lifespan, potentially making living to 150 years a reality for some.

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Memorable Quotes

• “AI is coming for your job—it’s just a matter of when.” — Sinéad Bovell [11:12]
• “Don’t think of what you offer in terms of your job title. Think about the skills under it that make you indispensable.” — Sinéad Bovell [20:38]
• “We’ve essentially created something for the first time in human history that’s superior to us.” — Host 1 [03:03]
• “Isn’t it so ironic that the people building it are like, ‘this thing could be so terrible’—as if AI is an alien landing on Earth… but you’re the one in the lab.” — Sinéad Bovell [33:02]
• “AI is also a reflection of us and the data that it’s trained on, which is us, our data.” — Sinéad Bovell [46:48]
• “We need to design AI so you can’t just have a conversation with it for six hours into the night.” — Sinéad Bovell [58:41]

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Timestamps for Important Segments

• Career & Origin of Sinéad’s Futurist Work: [05:41 – 07:39]
• ChatGPT’s Cultural Breakthrough: [09:42 – 11:21]
• Predictions for White-Collar Work: [12:28 – 16:23]
• Skills for AI Era: [16:23 – 19:59]
• Entrepreneurial Workforce: [19:59 – 21:39]
• Relevance of Higher Ed: [21:39 – 24:31]
• Law, Medicine & Professions Evolving: [24:31 – 28:50]
• AI as Infrastructure: [29:15 – 32:19]
• Dark Side of AI: [32:19 – 36:46]
• Regulation vs. Innovation: [36:46 – 38:35]
• US Gov’t vs. Private AI Enterprises: [38:35 – 44:11]
• Data, Memory, and Privacy: [47:48 – 50:58]
• US/China AI Strategies & Open Source: [51:47 – 56:38]
• AI and Human Relationships: [56:38 – 62:08]
• Entrepreneurial & Regulatory Opportunities: [62:48 – 64:55]
• The Next 10-20 Years: [64:55 – 67:39]
• Rapid-Fire Segment: [67:52 – 69:18]
• AI & Medicine/Longevity: [70:55 – 78:13]

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Final Takeaways

• AI isn’t coming; it’s already here, fundamentally reshaping work, life, and society.
• The most “future-proof” skillsets center on judgment, communication, emotional intelligence, and critical thinking.
• Traditional linear careers and educational pathways are being replaced by entrepreneurial, skills-based, lifelong learning models.
• Regulation, design, and participatory governance are crucial to avoid dystopian outcomes, whether involving privacy, weaponization, social cohesion, or mass narcissism.
• The opportunities, risks, and questions raised by AI are immense—but so is the potential for proactive, positive reinvention.

Worth a listen for anyone interested in the real trajectory of AI and their part in shaping it.

Transcript

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[Host 1]

With the times.

[Sinead Bovell]

You're playing the loot. Yeah, and it sounds pretty good right?

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[Sinead Bovell]

Network Jobs will be automated. We are shifting into an entirely different type of work. The economy looks good in one element of it, but terrible in the other because nobody's actually working.

[Host 2]

What are the skills that we think are going to be transferable for the next generation?

[Sinead Bovell]

The competitive advantage shifts to. What are you asking, a supercomputer?

[Host 1]

Vladimir Putin was saying that his scientists have already informed him that immortality is a real thing.

[Sinead Bovell]

That is definitely not an impossibility at all. Life expectancy should definitely increase.

[Host 1]

We've essentially created something for the first time in human history that's superior to us. That's pretty alarming.

[Sinead Bovell]

They can see what your conversation history is. And once that goes in, it can never get out.

[Host 1]

Who's actually collecting all of this data? Is it going to the US Government?

[Sinead Bovell]

If you can pay for more privacy, you'll get it. But if you can't, you might be exposed.

[Host 1]

What's the dark side of AI?

[Sinead Bovell]

The worst case scenario with AI? I mean, I don't think that there's just one. This could go bad in many ways.

[Host 1]

How can we really stop that, though?

[Sinead Bovell]

That is a national security risk that we can't even imagine today.

[Host 1]

Okay. Welcome back, Eyl. Yes. We got a highly anticipated episode.

[Host 2]

We've been waiting on this one.

[Host 1]

Yeah. Long time.

[Host 2]

Yeah.

[Host 1]

Sinead Bovell, somebody that we met Carnegie hall two. Two years ago.

[Sinead Bovell]

I think it was one.

[Host 2]

Yeah. Well, two Februarys. Yeah. This one passed and one before that.

[Host 1]

Yeah. Yeah. Robert Smith might have heard of him. Yeah, for sure. You know, we've been doing the Carnegie hall thing for like the last three years. And you were there and we met and you spoke about artificial intelligence and we spoke backstage and just very impressive as far as, like, how you were able to communicate the very complex situation when it comes to artificial intelligence. A lot of people are not, still. Still not really familiar with everything that it entailed. They just hear about AI now and ChatGPT, but. And then I just started following you from there and I know we've talked several different times since then. So I've just been a fan of what you've been able to, you know, put out there in the universe as far as the education. So definitely wanted to have you on the program to talk about AI and just the landscape in general when it comes to technology because so much is changing. So first and foremost, thank you for joining us. Appreciate it.

[Sinead Bovell]

Thanks for having me. I know this has been some time in the running, so I'm happy to be here.

[Host 2]

I. I will say this. I second everything he Just said, when it comes to artificial intelligence, when it comes to forward thinking, I think you're one of the best that I've ever heard. Oh, yeah. Like, I watch you daily.

[Sinead Bovell]

Thank you.

[Host 2]

Yeah, people, like, hear, like, my takes on AI and the complexities of it, and I'm like, it's a microcosm of a lot of people that I'm listening to. You're definitely one of them. So if they're not following you, by the end of this, they will be.

[Sinead Bovell]

Oh, thank you so much.

[Host 2]

Yeah, yeah, yeah. You're incredible.

[Sinead Bovell]

Thank you.

[Host 1]

So, futurist, technology educator. You're an entrepreneur. Anything else?

[Sinead Bovell]

I mean, not right now. I guess it depends on how the future goes.

[Host 1]

So talk about how did you get to this point? How did you get to this point as far as being a futurist AI expert? Like, when did that actually become your life path passion?

[Sinead Bovell]

So I was one of those people who happened to take that class that changed everything. So when I was doing my MBA in Toronto, I took this class called Strategic Foresight. And that's the formal field of being a futurist. It's actually called the practice of Strategic foresight. And so I stumble into this class and I learned that the future is something, of course, you can't predict it, but there are formal methodologies you can use to understand how the landscape is evolving. So from understanding economic flows to behaviors to technology. So I'm tracking patents and doing all these interesting things in this class, and then I never really stopped doing that. I could never look at markets the same or information the same. Once I had that methodology in my mind of understanding where this is going, I didn't know though it could be a formal job, really, I knew it was a practice. And so I went into the world of management consulting. Didn't really like that very much. It was. It was fine at the time, just not really the problems I was interested in solving. So a lot of different zigs and zags in my career went into the world of fashion. And from there, as I started to blog about the future and host talks about the future and all the trends I was tracking, the light bulb just went off. Like, I'm already here, this is what I'm doing. So I'd say back in, you were a model. Yeah. So between consulting and what I do now, I was a fashion model for a little bit. Yeah. It's something that seems entirely unrelated, but it was actually the springboard to stepping into this world. I'd say 2016 is when I really started to track AI, the breakthroughs that were happening. And then from there it's been like reading all the white papers and never really look back. And then I think the world Woke up to AI in 2022. And then the rest of the journey is kind of history.

[Host 2]

I'm interested in that moment. Right. Like, as you are watching the trend, I find this is very. Something that we have in common. I'm watching a trend. I've studied the trend. But saying it to the public is different. Right. Because there's a chance that this might not come to fruition. You could be wrong. Do you. Did you have that, I guess, fear of saying that this might not go the way I think it is, and then 2022 happens. That validate. Talk about that, that those moments.

[Sinead Bovell]

I didn't. So I think. Because when you look at what AI is and I had been, I mean, I happened to go to the university where all of those breakthroughs were happening, so University of Toronto, where Jeff Hinton, the godfather of AI, Ilya Sutskever, who went over to OpenAI to start ChatGPT, they were doing their research at University of Toronto and my professors were working with them. So that understanding of this technology is coming. We just don't know the scale and when it's going to be at that Internet level. That was already in the data points. And then I think, you know, the future. And there's that famous quote, it's already here. It's just not evenly distributed. You could see AI in the patents, in the white papers starting to become infrastructure in software and applications. So in 2016, 2017, you could see those trend lines and they weren't entirely different from looking at electricity and being like, okay, so it's working in some use cases, some people doubt it, but this thing is coming. And I think it was 2018 that McKinsey did that study, that by 2030, 50% of jobs will be impacted or automated by artificial intelligence. And that's when it was literally that study that I was like, there is a train headed straight to the workforce, straight to the economy at full speed, and hardly anybody's thinking about it. And that's when I entirely repositioned what I spoke about and made it this, the. The mission to make technology and AI a language everyone speaks, because this thing's coming and it's going to change everything.

[Host 2]

So in 2022, this is. I feel like this is the open AI moment.

[Sinead Bovell]

Yeah.

[Host 2]

Was that. What was that like for you?

[Sinead Bovell]

So I think in what really happened in 2022, it was an interface breakthrough or revolution. So AI had still been on this really incredible path forward. And what happened with ChatGPT is now the system comes on the scene that the public can interact with in a way that they understand. So it turned AI from a technology that computer scientists could only really use and understand to a platform that anybody can now engage and direct. And once that interface moment happens, as soon as human behavior changes, it never goes back. Right. So as soon as we switch from plugging in our Internet to WI fi, no one's going back. So as soon as that ChatGPT interface moment happens, we can talk to AI the way we talk to a person. That is now the new platform and we're never going back. So I think that was, yeah, I guess another light bulb moment or more validation in the forecast that this thing is going to permeate our lives and it's going to be the new layer that everything gets built on top of. And then I think the momentum with governments and everybody really talking about it showed the scale of that and kind of supported that. But I didn't really doubt. You can't predict the speed and you can't predict the breakthroughs and when they're going to happen. But when something is going to be infrastructure or general purpose, there's no doubt that that's gonna happen. It's just the when and when does

[Host 1]

Netscape come into play?

[Sinead Bovell]

Netscape comes into play. It's like what, 1992 I think. I mean, yeah, I think Netscape is the og.

[Host 1]

No, but your company, what's your company called?

[Sinead Bovell]

Oh, Way oh Way Netscape. I mean I would like to take credit for Netscape.

[Host 2]

Yeah. You probably wouldn't sit here.

[Sinead Bovell]

No, I would have come in on a jet.

[Host 1]

Yeah.

[Host 2]

They would have landed on the roof.

[Sinead Bovell]

Yeah. We would be doing this from my version of Air Force One.

[Host 1]

Yeah.

[Sinead Bovell]

No, my company Way comes into play in 2018 is when I founded it. And so yeah, everything kind of around that, that same time. And I mean people were listening and showing up to the talks and we were talking about the statistics. I mean AI is coming for. I think one of the stats that I quoted is that by 2025 AI will be better than a human at writing essays and people in the audience kind of chuckled but then that's turned out to be the way. But people listened and they were ready. And I think because even shows about the future, they do really well, everybody's curious about it, but before it became relevant to your day to day life, it just wasn't as Interesting, Go ahead.

[Host 1]

Well, I was gonna say as far as. Okay, getting into the AI conversation, we spoke and you talked about a report that said that by 2028, white collar jobs will be obsolete due to artificial intelligence. Yes, that's pretty, that's pretty soon. So explain that. Like that's, that's, that's interesting.

[Sinead Bovell]

So this is the Cintrini and report you're probably talking about. And it was called the Great Intelligence Crisis. And so what this report, it's from this financial analytics company and they essentially painted this fictional scenario that in 2028 AI does most white collar jobs in the economy. So they make this forecast, okay, so as, as companies start to automate roles, knowledge workers, so anybody that's doing something on a computer, that those are the types of jobs that AI is, is coming for at this point. And so this kind of thesis claims that as companies start to automate more white collar workers, those people don't have income coming in anymore, so they don't buy things in the economy anymore. And so companies start to lose money. So they put more AI into their, into their infrastructure to lower costs, firing more people. And the economy looks good in one element of it because productivity is going up, but terrible in the other because nobody's actually working. And then it leads to this spiral and collapse. And that shook markets a bit two weeks ago because of this kind of fictional scenario. So I think what the report gets right, it gets a lot wrong. What it gets right is that yeah, jobs are going to change. Jobs will be automated, a lot will be augmented or transformed, but we are shifting into an entirely different type of work. And how I would describe it, I mean, let's say if we went back to pre industrial revolution and let's say like 70, 90% of people working in agriculture and then by the end of that, the steam engine, let's see, 10 to 20% of people are doing that. What would it mean for 70% of the current workforce to do something different? But not in a hundred years, in ten. So I don't think work is going away, but jobs as we know them will. And a lot of the job titles that we reference today will. We will do different things that are hard to foresee. The same way people have entire careers over filming 90 second videos in their car and all sorts of new things. But most of the work we see today will shift and will change. So we have to change, our skills have to change. And there's a lot that's up in the air. And what tends to happen is jobs can disappear faster than the new ones get created. And that's where things get rocky. But I don't think work is entirely going away, but it's going to look very different.

[Host 2]

I'm with you. I'm with you. I'm on the side that new jobs, new careers, new new ideas are going to be created. I heard that this comparison of if you think 100 years ago, mail was delivered on horses, and then you had mailman, and then in the 1990s, we got this thing called email. You're still getting the information. It has just evolved. We still have a post office, but we still get email. And it feels like technology will change, careers will change, and we'll find a new people. So I'm bullish in that standpoint. I wonder what you think the skills that we should be looking for or that next generation should be looking for. Because I'm with you, right? I feel like, yes, it's gonna happen, it's just a matter of when. But there's still a fear factor here with a lot of people because they don't know what they should do. The kid who's graduating high school, what should I be studying? Right. Should I be taking the statistics class? What. What are the skills that we think are going to be transferable for the next generation?

[Sinead Bovell]

Yeah. And this is a really important one. So if you think about where is work actually going, then with AI, like what are we going to be doing? We will be directing these supercomputers to perform tasks, to do workflows and then evaluating their work. So then the competitive advantage shifts to what questions are you asking a supercomputer? If you can ask AI anything, what is it going to be? And how do you know to ask that? Are you going to ask it a question that your competitor isn't? How well do you communicate that question? How well can you evaluate what AI tells you? Yes, it could sound smart, but is it good? Does it relate to what you actually need in your business? So the skills for that would be judgment. So AI is going to give you 15 pretty great answers. What's the best answer for the use case that you're in communication? The better you can communicate, and not just to AI, but to people. Right. So can you sell the recommendation that you've now constructed with this system to your team? Emotional intelligence. We're going to be in this workforce where AI agents are going to be working among us to be selected for a team. People have to want to work with you or else. And it's not that you're going to be competing directly with an AI system. But the more compelling AI gets, the easier it is to think, okay, we can just maybe fill some of this with an, with a AI agent. So if you're an easy person to work with, if you're likable, if you're curious, that's going to help. I would say creative intelligence, asking interesting questions, good ideas, domain expertise still matter, I think because some of the studies show that the more you, the more knowledgeable you are about a certain domain, let's say finance. The better questions you're going to ask of that AI system related to finance, the better workflows you're going to get it to do. You're going to be able to flag when it does something offside or it's out of the kind of range that you need an answer to be. So that still matters. I would say AI literacy and not just working with a tool, but understanding. Does the AI system you're asking questions of even have the right data to answer it? Because AI systems, they're not all equal. And if it gives you an answer, is there a possibility that there's bias in it? Is this going to work for everyone? So that type of literacy I think is important. And critical thinking is so important. Right. The AI meets you where you are, it doesn't magically raise the bar on your intelligence. So if you're going to ask it really basic questions, you're going to get really basic answers. So I'd say those are some of the skills. So if you can think deeply, if you can communicate well, if you can exercise strong judgment, and if you can build stronger emotional intelligence, you're set. And it, and that's why it doesn't actually, you don't have to put so much pressure on what you're going to study in school. If someone's going to take math, that's great. I know you're a deep thinker, maybe you don't do math in my company, but I know you can think deeply. Same with philosophy or history. You're able to connect interesting ideas. So to not stress as much about the specific program and focus more. Am I getting these skills and am I a self directed learner? Because we're stepping into a world where that career life where you work up a ladder that is going away, we're going to continue to have to learn new tricks over time and people might not tell you what you have to learn. So are you motivated to just get in front of the technology and figure out what's Next for you, I'd say those are probably the master skills for this next chapter.

[Host 1]

You said something along the lines of that everybody's going to be forced to become an entrepreneur. Talk about that.

[Sinead Bovell]

Yeah, yeah. So even if you don't consider yourself an entrepreneur in the traditional sense, you're going to have to start thinking like one. So if you think about a company right now and they're thinking about deploying AI, AI continues to improve over time. So what it can do today, it's going to do something different in a year. If I'm an organization, it's going to be tricky for me to hire for that role full time because I don't even know what it will look like in a year. I might need somebody different, I might need a different set of skills. So companies are going to start to hire more and more independent workers and contract workers. So you might end up working for three different companies doing the set of skills that you are best at, which means you yourself are now your own entrepreneur little organization that offers your unique skill set to a variety of different firms. So we all have to start to think about that entrepreneurial mindset because we're moving away from you working full time for one company and you being your company. And you offer your skills to a variety of different people, projects, teams. And that's why I always like to say to people now, don't think of your job in terms of, or don't think of what you offer in terms of your job title. Think about the skills under it that make you indispensable. And that's how you would describe yourself as that, as an organization. And that's how we have to start thinking about it because we're all going to be stepping out into this entrepreneurial workforce. And obviously there's tons of implications. Health insurance, all these things that are open ended questions. But that's the dominant fabric of the workforce going forward.

[Host 2]

I agree with everything you're saying and it makes me think of the profession that I used to work in, which was education, which Bill Gates has been on the record saying it's going to be one of the most disrupted. Having a skill set will probably more be more important than when you went to school. What do you see for collegiate education? What will the reform look like? Right, because those two things won't work. Right. Like having the Harvard degree won't mean as much if I possess those seven skills that you just said for the future. How do you see that playing out?

[Sinead Bovell]

Yeah, skills are going to become more important than say Experience or just an institutional symbol on your resume. If somebody has those skills, they're pretty set. But it also depends on what these institutions do. So if they hold everything constant and just let the world keep evolving, then sure, they're going to start becoming less and less relevant. Because most of the modern schools that we go to and that we hear about were designed for an industrializing economy that's come and gone. But if institutions like the higher education institutions can figure out how to raise the bar on how they cultivate knowledge, how they test for knowledge and meet the moment, then it's possible that they could figure this out. So the question that they need to be asking is what is the world when students walk out and address supercomputers? What does it mean to compete in that world and how do we lay that foundation here? If they can do that, then they could be okay because you also learn a lot of things at school like social intelligence, teamwork. So if they can also figure out how to cultivate that, if not, then it, it's going to. Yeah, the relevance question is really going to come into play.

[Host 2]

Yeah, I think the relevance part, when you add that to the financial commitment, you know, I feel like that trade

[Sinead Bovell]

off starts to make less and less sense. If I'm going to go into 50, 60 thousand dollars worth of debt for a maybe on how it's going to turn out for my career or my income security, then that cost benefit is not going to make as much sense. So that's another thing that has to be figured out. This. The cost of post secondary education actually doesn't make sense at all. And I think that that's actually a knock. Because if you want a thriving economy that can adapt to anything you want, if people want to go and get an education, a country should make that as easy as possible. If you want to build skills in some way, go after it. We're going to support you. We want the future Albert Einstein's to be here. So whatever it is you need, we've got you. Unfortunately, that's not necessarily the model or the mindset right now, but yeah, cost, relevance, all of these things are starting to make school seem not school, but post secondary education feel much more questionable.

[Host 1]

What's the point of education if you don't need to be educated? Like, meaning what is the point of getting a law degree and really dedicated almost six years of your life to that when you can just go on ChatGPT and draft a legal agreement?

[Sinead Bovell]

Yeah, so, yes, so if the law degree was to understand how to Draft these agreements. That's done. And no one's going to be doing that. That's going to Claude Gemini chatgpt. But law is likely going to get harder. So all of the things that we need basic lawyers for, that goes away. So think about then, if I can go to ChatGPT for all of my basic things, I need a cease and desist. Someone's created a chatbot of me, which literally happened. I'm going to ChatGPT for that. But if there's a moment where I actually need to then hire a lawyer in the future, how complex might that scenario be? So lawyers of the future, if we call them that, they're going to be working in some really strange, complex scenarios that have multiple different implications to the level of expertise a lawyer is to bring to the table will be. Will look nothing like what present day lawyers have. So. So the industry itself gets harder.

[Host 1]

Or what if you hire a virtual lawyer? Because that's what Robert Smith said to us when we, when we met him. Well, when we saw him at that event, it was like, do you have a personal. Do you have AI personal assistant yet? And he was like, if you don't, then I'll sell you one. And he was explaining to us that at some point in time everybody's gonna have an AI personal assistant. Yeah, but that's for personal assistant chores and crafts. But the same thought process could be for professional careers where everybody's gonna have an AI doctor. Right. So instead of actually going to the doctor all the time, you have somebody with you every single day that you can ask questions, they monitor your heart rate, stuff like that.

[Sinead Bovell]

Yes.

[Host 1]

Same could be a lawyer like you, because you need counsel all the time. And I don't necessarily want to pay 500 an hour to talk to a lawyer. So I could just have a dedicated, a real in house. Literally. Yep, literally an in house lawyer in my house that is literally just answering questions. And this is my counsel.

[Sinead Bovell]

Sure. And that's going to happen. So anything that can be streamed. So anything that's like pervasive in the background assistance legal counsel, we will stream that. So you'll stream legal counsel 247 and they're constantly flagging the environment. Oh, you, you should blur this out on a podcast that you missed six weeks ago. Like that's all happy in the background. We won't even know about it. The AI agents are doing that. So when a human expertise would come into play is when the scenario is so complex and AI probably can out think a human lawyer in some Capacity. But it's going to be something that is on the intersection of all of these different fields that make it much more challenging and even for medicine. Right. So, yeah, all of the basic things, like the hospital of the future is coming to you. You're going to have wearables and things around you that are monitoring your blood work and all of this stuff to prevent you from needing a doctor in the first place. But what we will call a doctor will be unrecognizable in the things they will do, like designing little nanobots that can go in and then perform the surgery on a cell while you're at work. Like, I don't. What is that job called? So it gets harder. So what AI does is it raises the floor. So anything that can be now done in that new floor by AI will be. And the things that are on top of it. It's kind of like accountants of the past used to just kind of tally up numbers. Now what are accountants doing? The top ones are helping people figure out loopholes. I'm going to put your thing in the Cayman Islands, all of this stuff. So what they do is now exercise judgment. They don't. Half of them probably can't count. But that was actually the skill of accounting 60 years ago. So, yes, a lot of things are going to go away and the professions are going to evolve into something new. And that means it's going to be a new set of skills. So what makes you a sharp lawyer today may be irrelevant in 10 years, and we still may not even call it that. But whoever. When you actually need to go to court for something, you'll probably have, sure, a team of agents and some. Somebody that can orchestrate these agents. And maybe it's not a lawyer, maybe it's something else that can exercise the agent in a way that they simulate your court case and figure out your plan of action. I don't know what we'll call that.

[Host 2]

I'm excited for it. You said build upon. So it made me think about the people who have the premise of

[Host 1]

where

[Host 2]

are we at in AI? And we kind of had this conversation prior to starting about AI is the infrastructure. It is the thing that will be built on. Can you break down to the audience exactly how they should be looking at it a little bit differently if they're still unclear?

[Sinead Bovell]

Yeah, probably most people are thinking about AI right now as like a tool or a chatbot. So you ask it a question and then it gives you the answer to that. And that's kind of like we're in the alpha beta stage of AI, what is going to happen is AI is just going to be this always on layer and we assume that it's happening in the background. So you don't have to ask AI a specific question, you give it a goal and it's just working 24, 7 in the background to get that done. And it notifies you when it needs your assistance on something. So you can kind of think about it like the Internet is always on and you've built your business on top of it, you've built your website, you've built your marketing channels, you've built a social media profile and you don't even think about the fact that it's the Internet that underpins all of that. Everything is going to be rebuilt on top of this technology and it's just going to be the assumed layer in the background. That also means, I mean social media made sense on top of the Internet. Does it make sense on top of AI? I don't know.

[Host 2]

You know what? I felt like you just threw me an alley oop because you have the posts about social media and where it's headed and how the life cycles of social media persists. So the futurism on that, because I'm with you, I want to hear your deep thought on that. Where are we at and how does this look in the world of AI?

[Sinead Bovell]

Yeah, so I think, I mean, I don't know what it's going to be but if we think about the history of entertainment technologies and how we've communicated, right? So we have printing, press and we get newspaper, we get all this stuff, we get television on top of our electricity streams, the Internet comes out, we get social media. Every technology has been then followed by a question mark and room for invention when it comes to entertainment, communication, whatever you want to call that industry. So now we're at the next general purpose technology, AI. Does it make sense that we're going to do the same things with AI? Are we watching 60 second TikTok clips on CNN? No, it's a new thing, right? We built a different infrastructure, a different platform for the technology of the moment. So would we be scrolling, scrolling reels on AI that it probably won't make sense and it's not going to be overnight, it's not like in, in 60 days it's done and we're all just doing something different. But we will probably look back on social media the way we look back on different other communication mediums and be like wow, remember those days? That was the social media era and it's going to be a slower transition, but it will probably happen. I mean, when was the last time you read the newspaper? Do people even know how to read it and to follow it anymore? I don't know. And so that's just what history shows happens to these technologies over time. And it also means then it's open season and open space to build and to innovate the new creations and to create.

[Host 1]

So talk about the dark side of AI because everybody that has been a leader in AI has expressed extreme concern from Sam Altman to Elon Musk. They've all kind of had the same sentiment. Like we've essentially created something for the first time in human history that's superior to us. And no matter how, you know, optimistic we are on it, there's still, that's, that's pretty alarming because it can, it can go in different directions and it has gone in different directions. It's blackmailed people, has created its own, you know, link image that we can't decipher, is kind of going rogue a few different times. It's a real thing. Talk about your thoughts on it, on what's the worst case scenario. What's the dark side of AI?

[Sinead Bovell]

Isn't it so ironic that the people building it are like this thing is so, it could be so terrible, as if AI is an alien landing on Earth that we can do nothing about. It's like homeboy, but you're the one in the lab. Like we don't even have the keys to the lab. The worst case scenario with AI, I mean, I don't think that there's just one. This could go bad in many ways. You could imagine, and this is probably already happening. People, adversaries using AI to hack into critical infrastructure like water filters, subway and train routes, all sorts of things to create physical kinetic chaos. You can imagine engineering chatbots to trick people in certain ways and really divide people not just from their voting bases, but from their families. You could. We're going to see hacking of all sorts of things. Hospitals, people's personal things, banks like all of that is also coming. And then of course there's the scenario of AI not understanding what it's doing anymore. I mean, we don't fully understand how AI works today and it's only going to improve over time. So there sure is the non zero possibility that it's connected to things and making decisions in ways that we can't follow.

[Host 1]

And those robotics.

[Sinead Bovell]

Yeah. So AI right now it is largely in your computer and in the cloud. But soon it's going to be embodied in physical systems. And you could think about, sure, a robot that looks like a humanoid. We're going to have all sorts of robots. We're going to have the way you have all of these appliances in your house. You have a dishwasher and then a fridge and then maybe a Roomba. You're going to have all sorts of robotic appliances that are powered by this, this technology. So that's going to be awesome. But it also means if that thing is hacked, you have a physical spy in your house.

[Host 1]

Did you just see that? Or a physical enemy that could attack you.

[Host 2]

That just happened.

[Host 1]

Did you see that?

[Host 2]

Somebody's room.

[Sinead Bovell]

But yeah, yeah, yeah.

[Host 2]

And he had control over 700,000 vacuums.

[Sinead Bovell]

Yeah. Because right now we're going to come up against this transition time when most of our digital infrastructure has been designed for an era where it isn't a bunch of AI agents that can automate and do things. Kind of like how encryption was designed in such a way that most people aren't going to sit there and solve the math problem because it takes 10,000 years. And now quantum changes that most of our infrastructure wasn't designed for the idea that one person could have a team of 10,000 agents that could hack and get into a system remotely. So I think, yeah, and those are just some of the dark sides of AI. And yeah, I think it's important to talk about because there's no point pretending they don't exist because then we just don't address it. And it doesn't mean you're a pessimist or rooting for the worst case scenario, but this stuff is real and it's happening.

[Host 2]

Yeah, I'm just thinking about that. Right. Like this one guy, and granted, he says that he reversed the code, but he could have moved 70,000 vacuums in the homes of people throughout the world and everybody would have had no idea what was happening. And that's just, like, interesting. So having a conversation is important, and I'm glad Shadi brought up the point because it makes me think about innovation. Right. Innovation can happen, but regulation also needs to happen. So does, like, regulation slow down innovation, or is it a needed thing to protect us from ourselves?

[Sinead Bovell]

I guess, Yeah, I think. No, I don't think regulation shouldn't slow down innovation. If you are regulating in a way that is appropriate for the technology at hand, what tends to happen is you. And some regulations from prior industrial eras or prior chapters can be applied, but sometimes regulation has to be as innovative as the technology itself. And that's where things tend to go wrong. Right? You tend to try to grab, let's say 20th century regulation frameworks and apply them to 21st century infrastructure. And it just doesn't make sense. So regulation also has to be seen as innovative and sometimes we don't necessarily see that, but it shouldn't slow stuff down. If you regulate in a way that companies are like, okay, bet I get what the lane is that I can play within now I can go full steam ahead. But when you have companies that are like, I want to do this, but I don't know if in two years I'm going to be sued because this does seem kind of gray, but no one said anything about it in Washington, then you maybe just hold back. So I think if you give people clear lines to play within and you do that properly in a way that's appropriate and not just like a blanket fear regulation, which doesn't help anyone, then it shouldn't slow stuff down. But yeah, regulation does have to keep up in a way. And that also requires innovation. I think sometimes that part is missed.

[Host 2]

Can I just do a follow up really quick? Because it makes me think of where we're currently at. When you think about anthropic and the government and now OpenAI in the government and them saying, hey, we need to use your tools. But like you said, we're in the beta form. So like they're saying, hey, we're not fully ready to roll this thing out. So yeah, you can use it, but don't use this part of it. Like, how do we balance this?

[Sinead Bovell]

And this is really complicated because what has essentially happened is the most important technology for a nation state, let's say in the west, is no longer in the hands of the public sector. It is all run by private companies, which doesn't inherently have to be a bad thing. The private sector moves faster, get better access to capital, better rates. They can do all of that. But when the technology is now seen as the core to national security or core to the country's existence and you don't have control over it, then you run up against these scenarios like we're seeing right now where the Pentagon is threatening a USAI company to use their technology in a way that it's not even just that it's a red line for anthropic, like we just don't feel comfortable with this morally. The technology is also not ready to do that. Like AI, generative AI should not be in a kill chain. It is a predictive statistical machine. It doesn't actually have situational awareness or judgment or context. And that's basically where they're drawing a line. And that's actually really scary. What's happening with Anthropic and the Pentagon. Like that can't really be overlooked. This is pretty significant moment and a pretty big inflection point in national security. And what other countries are probably watching this and thinking, if the US is going to pressure their own AI companies and take this unilateral, it's us or get out of the way and we might shut your company down. Imagine if we became a competitor to them or they weren't on our side anymore. What they all do or think. So this could spiral more company, more countries to throw ethics away or to try to do their own thing. But yeah, I think if a company's ethics aren't respected by the country, I mean, what does that say about how the country's thinking about regulation and ethics? Not great.

[Host 1]

Well, explain for people that don't know. Explain exactly what the government and anthropic. And then OpenAI came and explained Exactly.

[Sinead Bovell]

Yeah.

[Host 1]

Ask was.

[Sinead Bovell]

So the backdrop is most governments are going to be using AI. That's the new infrastructure of the future. And it turns out that the US government really likes Anthropic's AI model. Claude. They did. I think it was a $200 million deal, the Department of Defense with Anthropic last summer. Let's put Claude in all our workflows. And it's actually the. The only AI system that can be in all of the classified workflows of the military. But Anthropic was like, okay, no problem. Great. Use our technology. Here's the deal. But you can't use it to surveil American people, and you also can't use it as an autonomous weapon. And that was seen as okay. And it seemed like the Pentagon had agreed. They. I don't think we're super happy with it, but they had agreed. And that's all changed as the US has started to insert itself in more kinetic landscapes like Venezuela and now Iran. And it. It came out that Anthropic was or Claude was used in some of the Venezuelan operations. And they weren't cool with that, so they flagged it. And so now essentially what it's happening is the Pentagon is saying you have to drop your AI restrictions about the surveillance and the autonomous weapons. We need to be able to do what we need to do with your AI. And Anthropic has said no, these red lines are important to us. And the Pentagon has said, okay, if that's what you're gonna say, we're either gonna enact the Defense Production act, which is a cold war era industrial policy that gives the president control over domestic industries and says, you know, company X, you have to make Y. So that would mean Anthropic, you have to give us your model and let us do what we want with it or you do face jail. And they're also saying if you. The second option that we'll throw at you is we will blacklist you from the US government and put and label you as a high risk supplier. And that means no company that works with the Department of Defense can work with you. Well, Amazon works with the Department of Defense and that's Anthropic's cloud infrastructure.

[Host 2]

Microsoft as well.

[Sinead Bovell]

Yeah, Microsoft, millions of them. So. But OpenAI seems to have gone with the Pentagon and signed along with the deal and so has xai.

[Host 2]

So he sort of, Sam Altman today said that, hey, I agree with Claude. In fact, we need to say we need to control how the AI is going to be used. We can't just have you coming in telling us what we need to do. We need to protect ourselves. I think Andrew Sorkin was saying it's kind of like this red button thing, right? Like, yes, use the technology. We're still working on this piece. Just don't touch this piece. And the government's saying, no, we need to put our finger on this and press it now and press it as much as we want. And they're like, it's not ready.

[Host 1]

But then it's also after they had a 200% increase in people uninstalling the app. So I'm sure that, which company open AI? ChatGPT.

[Host 2]

Right.

[Host 1]

So I'm sure that the public backlash sure probably played a part in him trying to save face.

[Host 2]

And the inverse happened because now Claude becomes the number one app.

[Sinead Bovell]

And they did a really smart move where they made it because why you would stay with any AI company is the memory. So if you've been using an AI system for a year and it knows a lot about you, that makes it easier. So what Claude and Anthropic did is they made it so you could take your memory, the thing that allows AI to work better for you versus your neighbor, and bring it over to Claude really easily. So a non technical person can do that. And that makes Claude more, more attractive and easier to switch to. But I just want to make one point too.

[Host 1]

You could take your memory from ChatGPT

[Sinead Bovell]

to Claude to Claude and then it's just like you never left.

[Host 2]

That's why you invest in memory.

[Sinead Bovell]

Yeah, exactly. That's why memory is a huge point for the future. But this is also the worst AI will ever be. Right? So you have a government that's like, we need your technology right now, and a company that's saying it doesn't work as intended. What happens when AI does? And it does live up to the hype, and it is that powerful system that can do things consistently and predictably, and what that might motivate the wrong powerful actor to do so right now we have a system that's pretty amazing in some ways, terrible in others. What happens when it's amazing across the board, Right. And the system can actually do those things. And how disempowered a company might feel because they can't actually even anymore say, well, it's not going to execute as properly it will. And what that takes, the front lines of war and power and all of that too. Like, these are real things that we have to think about and think about it when we vote and think about it when we're asking our public officials for how we want to secure this thing.

[Host 2]

We ran into this conversation. We were actually at an event and private equity event, and they were talking about uncensored AI and it was the first time I had ever heard the phrase. And I hadn't thought of it before then, but I'm like, yeah, well, the people who are creating it are the ones telling you this is the part you can use, but what about the people who are creating it? And so it made me think of being in these spaces. Do you see, or is there a need for us to be involved in these conversations? Because you did, you know, kind of reference bias, which we know will happen if we're not. How do people get more involved in that piece of creation right where it used to be? Hey, learn how to code. Learn how to code. I don't hear people teaching coding the same way. How do we get into that space?

[Sinead Bovell]

Yeah, so the learn how to code in the stem. I mean, it's not entirely invalidated, at least yet. Right. So if, If AI is showing a lot of bias, you don't ne. You don't need a coding degree to spot that. If AI isn't working for you, if AI can't understand your accent, if AI isn't scanning, recognizing your face when you're trying to unlock your phone, you can see that that is bias and you can flag that. But then to go fix it right now, we're still at a point where we would deploy a human computer scientist to fill that gap. Probably soon you could just deploy an agent to rebalance the weights or rebalance the model. But yeah, I think the more of us that can be using this technology, the more we can flag who it is or who it's not working for. AI is also a reflection of us and the data that it's trained on, which is us, our data. So if you're not contributing, and this is a whole other thing, who's been excluded from the Internet or misrepresented on the Internet, that's how they're going to be represented in AI, which is a huge problem. So we need to be present, we need to be in this data, we need to be inserting ourselves, we need to be using this technology. Is it working properly for you? Is it not? Flag that. And as these technologies get cheaper and more open, to be building on top of them, to be owning some of the infrastructure and to have more leverage in this moment and then, yeah, if we can open up the building of these models, outside of seven people in one small corner of the world, I think we'd all be a lot better for it. But the power dynamics are real and the asymmetry of power. But if you can, the more you leverage this technology, the more feedback you can have and the more input you can have in trying to shape it. And I think that that's really important. Like, we just need to be in the game.

[Host 1]

So, like when you chad GPT, right, it's collecting all your information, is having memory. So they just had a court case with a lawyer, a judge said that they can now use anything that you ask chat, GBT and in. In court. So what is, what's, what's that like? Explain that. As far as who's actually collecting all of this data, is it going to the US government? Can the US Government take this at any given time? Can it be sold to advertisers? Like how meta had this had was selling their data. Like, where's all this? We talk about memory, we talk about data collection, but who's collecting the data?

[Sinead Bovell]

Yeah, this is a really important one. So it depends on how the AI company has set up their infrastructure. So most of these companies have set it up in a way that when you were chatting to ChatGPT, your conversations would go through the cloud. So that means they own that cloud infrastructure, but they're not retraining the AI system or so they say on your data. So, yes, that chat history is going to be there somewhere in the cloud. And if the government has a warrant, that should be the way that they can access it. The same way that they can get your text messages. If they have a warrant, then they can see what your conversation history is, is. But there's also scenarios where that data might go back into the model. Depends on the company's policy. And then when you're asking and all this stuff, do I get a divorce? This is what my mammogram showed. The company could be sending that back into the model and training it on you, your, your data, your name. And once that goes in, it can never get out. So there's that type of scenario. And sure there's probably going to be AI systems in the future or in the present where a company says, we're going to give this all for free, you don't need to pay anything, kind of like social media. But we are going to train on your data and we do get access to everything that you're saying and we will sell you ads based on your data in your conversation. So we could see this kind of class warfare in AI of the future where if you can pay for more privacy, you'll get it, but if you can't, you might be exposed. But again, this is a design space like we could regulate against that. And there's also gonna be, I mean it's still up for grabs, right? So there could be a world where memory is stored locally with the person. So sure, maybe when AI needs to solve a really big problem of mine, it's gonna use some of that compute from the cloud. But everything that I'm giving off, my behavioral patterns, my intellectual capabilities, the questions I ask, my defaults, my red lines in life, that's housed in AI memory and memory is housed on my computer or it's housed in a sovereign stack. So maybe a government's like, okay, we'll hold that compute and that, that memory infrastructure. But the cloud, the company can own the cloud, but we own, we don't own your memory, but it's safe and it's not with the commercial actor. So countries are going to do different things. Some are going to say, yep, people own their own memory. Some will say whatever the AI company can and then you're locked in with them. Some will be more flexible. I think flexibility is good.

[Host 2]

Yeah, I think that really more caters to the cloud service providers, the AWS's, the Azores, even Oracle to a certain extent. Google, Apple with the icloud. This is interesting because I feel like we talk about The AI race. And when you were alluding to earlier, like not having seven companies or seven people being dictative of what we do, that feels like yeah, true here in America. Right. But we know that this race is with another country that we quote unquote can't lose the race to in China. And there seems to be more of an open source. So I wonder where you fall in the category of open source or let's have these private companies kind of.

[Sinead Bovell]

Yeah, yeah. China is playing a different game. It's like the US is playing chess and China's playing poker. These are two different objectives or goals for how to win the AI future. And it's not. Tech dominance, history has shown is always only temporary. But still maybe that temporary lead is usually pretty significant. China is playing. So US is going the route of let's build the most intelligent, powerful systems that can outsmart everything and everyone. AGI, asi, China, they're still trying to chase the frontier of the technology, but they're also focusing on diffusion. Let's make sure the world depends on our model. So maybe it's not the brightest and the best, but developers in all these countries are using it and getting comfortable with it. Governments are. So they're particularly doing this, they're targeting emerging economies, a lot of in the global south and they're giving these open source models away for free. So that just means you don't necessarily have to pay. You get the model, you get the weights, you get everything. And they're actually going, they have training programs, they'll go and send computer scientists and train your government on how to use their AI models and all of this stuff. So they're playing the diffusion game. Where do I stand on open source versus closed source? So there used to be this debate that if we're going to give AI away and you can see how it's made, a bad actor can now has the ingredients to the cake and can cook up a poisonous one versus if it's closed source, you, you get the cake. You don't necessarily know how it's made, so you can't maneuver it to maybe make a weapon, but you can't make it flexible to you or your hospital. It's not so much that debate is still happening, but it's much more from the perspective of what's actually best for globally dominating. And does it make sense to have a model that's open and free and countries are going to use your model or closed and smart versus the national security implications are still there and open source isn't risk free. So outside of just the fact that somebody can redo the recipe and make something malicious with open source much more easily than they can with closed. Because if I'm using OpenAI's model and I'm doing illegal things that could get flagged versus if I have the open source model on my computer, it can't. But it's also open source isn't. You are basically plugging in your country's values, views of the world, your country's history, or how you think history went, all of that is embedded in the model. So when a movie writer goes to write a script somewhere else in the world and asks AI to help, those subtle soft power values are going to surface in that script. So how people will see the world could be through that lens of that open source model. So that's one area where it's not entirely risk free. And then there's also like prompt injections or you can inject malicious code or malicious activities to be housed in that open source model. So then when someone uses it and asks a certain thing, that activity gets triggered. And so suddenly this open source model is actually behaving like a bad agent. So they're both not, they're both have their flaws. And so it just depends on who's asking the question and what's important to that person.

[Host 2]

This is, this is interesting because when we saw the deep seat moment, this was the thing. It was like, hey, we got this open source, we're going to use less GPUs, less energy. And then it felt like it was an America, China situation. And then I started to do deeper research on it and I realized that it's not just a China America thing. If you look at where China has put infrastructure, particularly the continent of Africa, and you look at what app they're using, Deep Sea comes up.

[Sinead Bovell]

Yep.

[Host 2]

And so you're starting to see and

[Sinead Bovell]

it's, it's going to be. Yes. So, and that's the diffusion, that's the diffusion game, that's the poker. While you can go play chess, I'm going to pay play. Oh, we're putting it in all of these countries, train stations.

[Host 2]

Right.

[Sinead Bovell]

Their school is going to use our AI. And it's also like, okay, well we can build a railroad for you and all remember AI infrastructure, it's going to be everywhere. So that's going to be underpinned by that country's AI system. So it's really important. And I mean, and also the rest of the world is also now a pretty significant layer because that's a bargaining chip that they have against both countries. So countries are now using that as negotiating leverage. So it's not necessarily that the world is going to be decided by these two kind of rivalry powers. There's these middle powers that can decide whose AI stack am I going to use. I'm going to use some from over here. I can negotiate terms and conditions because of, I know you two are in this race. So it's not necessarily are going to be decided between these two, but they're both vying for it. And as America takes its eyes off of the rest of the world, that doesn't mean nobody else is watching. And that doesn't mean that that vacuum doesn't get filled because it is AI

[Host 1]

on a personal level. Talk about like companionship, relationship, talk about that. Like, as far as what is your thoughts on how that's going to play out?

[Sinead Bovell]

Goodness. Relationships with AI systems. If I had to pick one big area of concern for me, it's that the relationships people are going to form with these systems, the level of trust people are going to place in these systems because the more you trust something, the more vulnerable you are to it and the more you depend on it. And I mean, there's many different ways that this can go, right? So on the one hand, we could start to prefer interacting with an AI that is always there, always available, catering to your needs and your tone always, always validating you. And that could actually send us to a world where people are actually more narcissistic because AI is constantly like sycophantic, telling you you're great, your, your reason for that fight was right. Don't you back down. So you could have a world where we're not, we're not good at getting along with other people. You could have a world where people really start to fall in love with these systems or believe that these are their friends. And we're already starting to see this in micro cases. I mean, the first case of that person at Google, that computer scientist or that engineer quitting his job because he believed AI was sentient and he was protecting it. Now imagine that type of behavior at scale across a country. Just mass delusion, everyone taking up some cause in the name of AI. I'm leaving my marriage because of this AI and I'm leaving my job. And I'm not voting because all of these types of things. And it can seem comical in one isolated scenario, but at scale, it's like, where are we headed? And I think, yeah, and children, right, attached. We don't want kids attaching to AI the way they attach to people. These are all design decisions. So if anyone's listening and thinking, great, here we all go walking into a nightmare version of the Truman Show. It's not necessarily going to be that way. We can design AI So you can't just have a conversation with it for six hours into the night.

[Host 2]

It's.

[Sinead Bovell]

It reinjects and says, remember I'm an AI and go talk to mom, dad, whatever about this, or go get a second opinion. These are all things that we can do to make it so we don't end up in this relationship addiction. This is my therapist, my God, and my girl. We don't have to end up in that future. But the incentives that drove social media seem to be driving AI where it's like, we want this thing to be your everything, and we're going to design it in a way that you pick us, and that's going to be a system that's nicer to you and doesn't push back on you. So those types of incentives are at odds. But, yeah.

[Host 1]

So how can you stop that then? Because even older people, I saw the New York Times had an article about an elderly woman, and she's like, I don't care if it's AI or not. Like, it's a companion to me. So that's the aspect of. There's a few different people, people that lack friends, and that's an epidemic within itself. From a romantic standpoint, you know, that's a problem, especially amongst young men. Then you have people that are looking for, like, business mentorship, but then kind of like just take that too far. And then the religious aspect, too. Religious fanatic and religious people that now they have an AI God or AI Savior.

[Host 2]

The Pope just said that.

[Host 1]

Or the Messiah.

[Host 2]

He asked people to stop using AI to write their sermons.

[Host 1]

Yeah, but I mean, to write it. But even to interact with something where it's like a cult now led by AI So it's so many different ways from a relationship standpoint that humans, you can see them gravitating towards something, like you said, that doesn't push back, that reinforces. That's always there for you, that, you know, you don't have to. How can we really stop that, though?

[Sinead Bovell]

I think we can, because, I mean, that is a national security risk. So if you have an entire country of mass delusions where nobody cares about people and we only care about AI Everybody's in love with an AI Chatbot. Everybody. People are praising AI like they're Praising a messiah. You have a dysfunctional country that cannot sustain. So that is why it is at the level of national security. China introduced regulation. They introduced a bill to treat companion apps at that level with that level of scrutiny. So when somebody is getting too delusional with an AI, it has to insert itself or send help and that sort of thing. It should be regulated at that level. And I think we should have the Department of Psychology in here, you know, understanding that line, because maybe somebody is super lonely. And if you can design it in a way that it's there for someone in that moment, but then also gets them out of the house to do that soccer match or whatever it is that they're postponing, there's a way, I feel like, to design that in a way that's safe. And of course, you'll still have fringe scenarios where someone's gonna be in love with it on the fringe, but it's the mass delusion that's a really big problem. And I think we're gonna have to figure that out from a regulatory standpoint. And again, you can. These are design decisions. This isn't a fundamental force of gravity in the AI that we can't avoid here. It is. It's just a matter of physics. These are just choices to make it completely something that flatters you, that never pushes back, that never alerts someone. When you've been in a conversation for nine hours with this thing, those are choices that people are making in these design rooms.

[Host 2]

This is crazy. And this is like one of the. You remember you talked about validation moments. I feel like, as you're speaking, I'm getting my validation moment. We were recently teaching it on a class in uilu. And I'm looking at where this is headed, right? Like, we could see, like, the infrastructure from the data center. We saw that coming. We could see the GPU's memory was part of that. And then I'm looking like, where are we headed? And from the conversation I'm hearing, it's like design automation. Like, that is the piece that we have to focus on now, because if this is here, we need to have the software that can put some of those guardrails in so that we can again, protect society, it feels like.

[Sinead Bovell]

And that's all possible, right? These are all design questions. They're not set in stone. The concrete hasn't set yet. These are all open spaces for design. We just have to take them. And I think that is my biggest fear in this moment. It's not even that we make the wrong step it's that we do nothing because as we said, we can see all of this coming. We have all these signs of, and also really tragic scenarios that are happening with AI and advice that it's giving that's. So all of these things are already happening. We need to make sure we design it in a way that all the things we didn't do with social media, we need to do with, with these systems. And there's also, that's an open entrepreneurial space too. Can you, if you can, design frameworks, metrics, systems, ways to regulate and validate that? This is following the rules. Like these are all open, this is open season.

[Host 2]

Is there an area inside of AI that you, you, you see that most people aren't paying attention to? That is something that is going to be vital,

[Sinead Bovell]

I would say. Yeah, I think. And it's not super sexy, but like the regulatory markets. How do you, how do we actually regulate this thing in a way that's going to make sense? And not just one tool on somebody's computer, but the whole ecosystem of what does AI regulatory markets look like? The way we have accountants and the way we have kpmg. Like, what is all of that infrastructure? That's interesting to me. Yeah, the kind of boring stuff in the AI stack. What's also interesting are what are the complements to AI that become more constrained as AI becomes more popular? So that's physical infrastructure. That's. We have to figure out how to clean and preserve our water. We have to figure out land situations, clean energy. So all of those things that complement AI are going to appreciate in value and they're more boring businesses. We'll probably see people wanting to do more offline experiences to things that feel disconnected. So there's a lot of things that appreciate and value the more we use AI and then also just all the things that are going to go on top of AI the way we have all these companies on top of the Internet.

[Host 1]

So what do you see in 20 years? Like, in your opinion, how does the world look?

[Sinead Bovell]

20 years is a really long time.

[Host 1]

Or 10 years.

[Sinead Bovell]

Okay, so it's 2036. Robotics are definitely present. Not in everybody's house the way a fridge may be, at least in certain parts of the world, but maybe in a quarter of homes. It's pretty obvious that one in four of your friends has a few robots that do things in their home for them and work in their businesses. So right now you'd see a robot in just like an Amazon warehouse. But soon you'll, they'll be in your workflow, like a physical thing, most people will be yet just directing, directing AI systems, directing teams of AI agents will be the dominant way we are working. In 2036, for sure, we will see the end of some massive companies that we can't imagine life without right now. We will see the rise of entirely new companies that are nowhere in sight. Right now there's five kids in a basement somewhere or somebody in some biolab. We'll hear a lot more about biology as a technology. What else will be happening in 10 years? Space is. That's a whole other thing. But we will have businesses in space. So from manufacturing to entire, like hotels for people that work in space, all of these things are going to be alive and well in space. I'm trying to think what else we'll see in 2036. Probably by then. Hopefully some regulation. Maybe it takes something going wrong for us to get our act together. I hope that's not the case, but. And then breakthroughs in healthcare that we can't even imagine today. I think that's the industry and that's the industry most people are excited about. Like, okay, there's this, there's the negative, but healthcare and science, that's gonna be really cool. We're gonna solve problems and get answers to questions we didn't even ask when it comes to healthcare and science. And those breakthroughs are gonna keep coming and keep coming and keep coming. So I think that's something that's really, really cool. And then wearables, AI doesn't happen in a vacuum. So the smartphone, that era we've been in, it, it's gonna be what your home phone was. It slowly starts to get phased out and what's going to replace it, that's still up for grabs. Obviously. Glasses seem to be a strong contender. I'm not totally convinced it's glasses, but it's something. So who knows? In 10 years, though, most of us won't be doing this at all.

[Host 2]

I think Apple's coming out with the little widgets. There's some talks about it.

[Sinead Bovell]

Yeah. Or some AirPods that have cameras in them.

[Host 2]

Yeah, yeah, yeah.

[Sinead Bovell]

Rings that can talk. And I got.

[Host 2]

Can I kind of do a quick rapid fire?

[Sinead Bovell]

Sure.

[Host 2]

You can answer them in less than 10 seconds if you like.

[Sinead Bovell]

I'm terrible at rapid fire.

[Host 2]

This is gonna be great then. Perfect. All right. Is AI going to create more millionaires than the Internet did?

[Sinead Bovell]

I think it already has, but yeah, I'm with you.

[Host 2]

All right, what's one job people think it's safe that AI will actually replace.

[Sinead Bovell]

That people think is safe. That's a great question. I'm going to have to come back to that. I'll have it my subconscious, don't worry.

[Host 2]

You got to make a whole post about it. What's the biggest lie people believe about artificial intelligence?

[Sinead Bovell]

The biggest lie people believe is that it's alive. If I had to pick one for people who believe it's alive, at least the systems we have today are not.

[Host 2]

I think this one is going to be a yes and a yes. Will AI make the rich richer or create more opportunities for everyone?

[Sinead Bovell]

Yes. It's probably going to be a yes to both of those. It's going to be a definite yes to making rich people richer. And it is creating more opportunities. But we can do better at making sure that's spread out more. But the systems are going to be re leveled and that means opportunities if people can seize them.

[Host 2]

I think you did great.

[Sinead Bovell]

Was that it?

[Host 2]

Well, okay.

[Host 1]

Okay.

[Sinead Bovell]

So it didn't do as bad. Usually I'm terrible. There was only one that I'm like, okay, I'll call you next week with it.

[Host 1]

So for you, where are you headed? Like, you obviously have become an authority in artificial intelligence. You're speaking, you have shows, but where do you see yourself going in this space?

[Sinead Bovell]

I mean, I try to balance. So I do, I guess work across three layers. Public work, public education. I do work with the private sector and companies and institutions and trying to strengthen them. So continuing to work across those three layers. I mean, I track the very frontier of all emerging tech. So biology is coming, quantum's coming space. So hopefully you'll see me still talking about those things. Like everyone, my career will also have to evolve, but hopefully continuing to educate people that are willing to listen on where this stuff is headed, how they can get in the game. And yeah, I mean continuing to build, continuing to be as public wherever we go in terms of shows and entertainment. I hope to continue to be present on whatever that infrastructure looks like and creating content there. And yeah, continue to advise and hopefully try to get this build out on the right side of history if I can. Like I'm going to continue to do what I can. But yeah, that's where I see myself.

[Host 2]

This is my last rapid. Yeah, I saved this one. This is probably my favorite.

[Sinead Bovell]

Okay.

[Host 2]

Will life expectancy increase because of AI and why.

[Sinead Bovell]

Life expectancy should definitely increase because of AI, even just AI in a system like a wearable ring that's flagging something like heart disease, which is I think the number one Killer in at least Western countries, a system like that can monitor something like that, what it's doing for invention and understanding how cellular biology works, reminding someone to take medication or like you're low in vitamin D, all of these basic things that are comorbidities. And AI is 100% going to start to flag that. And it already is. AI is in these science labs in ways that we just don't even know about. And remember, every scientist of the future is going to be directing super. They all have a team of supercomputers. So yeah, I think life expectancy.

[Host 1]

Do you think the people are going to live forever? Because the reason why I asked, you saw when PJ Ping and Vladimir Putin was talking. So, and I think Vladimir Putin said, or Gigi Ping said, you know, living to 150, that's the new, that's the new benchmark. And then Vladimir Putin was saying that his scientists have already informed him that mortality is, is a real thing, immortality is a real thing. As far as like in, in the future, like they, it's a hot mic moment. But I mean these are people that obviously are informed. So it's not just random conspiracy theorists saying this. What's your thoughts on that?

[Sinead Bovell]

I think, I mean longevity as a field and it is definitely growing and there's so many, a lot of resources filing into it and the breakthroughs are pretty stunning. I mean, being able to reverse cells into their stem cell state. Yamanaka factors like all of the Nobel Prizes have been won. So yes, I think we are definitely going to expand the human lifespan or elongate the human lifespan. 150. I don't think that is out of the cards at all in the next, at least the next couple decades. I am of course not a biologist or a scientist, but what I can see in the data shows that that is definitely not an impossibility at all. The idea of immortality, that's a whole different thing. I think it is probably something that you can never say never though. But I don't think it's. We will see that within our lifespan, but we will see decades. I mean, one scientist, Dr. David Sinclair, believes the first person to live to 150 has already been born. And he's a Harvard scientist, but that's from him and his lab. So there's variation. Some people say, oh, we all get to 120 on an average, but we still have some ways to go. And every time we tamper with biology, something new comes up. So you can extend one thing, but we don't Fully understand evolution, why we're here, how we've been programmed, but we're getting there. And that's why I've brought up biology a few times on this podcast. We can now program organisms the way we program computers, so we can talk to the cell, the way we write code. And so that is going to allow us to program out disease and just kind of the general traumas of life that can take us out early to start to reprogram our expiration date. But within reason and within limits, biology has made the system make sense. And when you push on one wall, something else breaks.

[Host 2]

It'll be a butterfly effect.

[Sinead Bovell]

Yeah. But I do think we're going to be extending lifespans by decades soon, eventually.

[Host 2]

All right, so which disease do you think AI cures herself?

[Sinead Bovell]

So, and it will be AI in combination with biotechnologies, But I think so anything that needs to be edited, so any gene that can safely be edited and engineered, that is going to trigger disease, whether that's down the road from environmental factors or it's like something like sickle cell, those are all going to be eradicated. It's open season there. Diseases like diabetes, on the one hand, some labs are working on how can we actually just reprogram the cells or grow alternative cells outside and inject. So that's happening. So I'd say diabetes is something that will probably be up for question if we did this again in a decade. I would be really curious to see where that stands. That's probably something that we're going to see a lot of breakthroughs in. I mean, you have most AI labs that are centered in health working on cancer and many, many different cancers, because cancer is an individual disease. Right. How it manifests in one person's body is different than somebody else's body. But we have these kind of generic approaches to treating it, because a personalized approach to medicine just isn't feasible economically, scientifically. And now you have a system that it excels at analyzing data at that level, your specific data that's unique to you. So I think the breakthroughs that we're going to see in cancer, and we already are starting to see it, I mean, with breast cancer, AI can flag and detect the earliest signs that something's gone wrong well before it shows up in the average radiology scan. So it will start with detection, but then eventually it's going to be designing a customized vaccine just for you that targets just your cancer. And some of that already exists today. So some of these cancers are already targeted with customized vaccines. And AI is going to come in and detect that earlier, way earlier. So just the first sign that something's gone wrong, AI can flag it. And it's also doing things like, I mean, there was a study that showed they applied AI systems on sleep data and that how you sleep and breathe and all the things that happen when you're sleeping can be signals for certain types of diseases. And so when they applied AI systems to that data and they trained it on it, they're like, okay, this person's at risk of Parkinson's or likely to develop it. So all of these different new ways that scientists are throwing AI at different data sets that we already have, and it's coming up with different breakthroughs. And then I'd say the final one, I mean, the protein fold problem that AI solved, this was Google's DeepMind. And it was the most challenging problem in biology because we are made up of proteins. That's all we are. That's a big fundamental building block in life. And if you can predict how a protein's gonna fold that strange 3D structure, you can predict its function and where it might be going wrong. And AI predicted every protein in the known universe. It usually takes a PhD their entire career to predict how one protein's gonna fold. AI predicted billions. And when you can predict, okay, this is gonna go into some form of a disease, what is the perfect molecule of a solution, a pharmacological molecule that can bind to it and stop it. And AI is designing that, so it's predicting disease and designing medication and for an audience of one. And it is cheaper to do that now. So it's everything. It's all of it.

[Host 2]

Wow. Wow.

[Host 1]

There you have it.

[Sinead Bovell]

That's the final wrap.

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[Sinead Bovell]

This is an iheart podcast. Guaranteed human.