Latest / The Road to Accountable AI / Sharon Goldman (Ground Level AI): AI as It Meets the Real World

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Sharon Goldman (Ground Level AI): AI as It Meets the Real World · The Road to Accountable AI

• 0:09
  Hi, I'm Kevin Werbeck, Professor of Legal Studies and Business Ethics at the Warden School of the University of Pennsylvania.
• 0:15
  For decades, I studied emerging technologies from broadband to blockchain.
• 0:19
  Today, AI is promising to transform our world.
• 0:24
  But AI needs accountability, mechanisms to ensure it's developed and deployed in responsible, safe, and trustworthy ways.
• 0:32
  On this podcast, I speak with the experts leading the charge for accountable AI.
• 0:36
  ~
• 0:39
  Jaron Goldman has been a journalist on the AI beat since 2022 and focusing on other areas of tech for a decade before then.
• 0:47
  She recently left Fortune to start her own outlet on, as she describes it, how AI meets the real world.
• 0:53
  We talk about the recent incidents of AI and cybersecurity, data centers, AI and trust, and how to tell stories to people so that they understand what's really going on in the AI
• 1:08
  world today.
• 1:12
  Sharon, thanks for joining me and welcome to the Road to Accountable AI.
• 1:16
  thank you so much, Kevin, for having me.
• 1:18
  Looking forward.
• 1:20
  You
• 1:20
  ~ have covered the the tech industry for a long time.
• 1:24
  But ~ if if I read this right, you started full time on the AI beat in twenty twenty two, just before the whole Chat GPT explosion adventure beat and then fortune.
• 1:35
  Looking back, did you anticipate what the crazy ride the last several years ~ has been?
• 1:43
  Absolutely not.
• 1:44
  That's you know, it's it's funny to think about because in 2022 I had covered AI a little bit.
• 1:52
  I had been covering really more enterprise tech.
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  Like it was really about everything from, you know, ~ software to cloud to mobile.
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  digital transformation was one of the big buzzwords at the time.
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  Big data ~ had been on the scene for several years.
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  And AI.
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  you know, old school machine learning had been part of that.
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  So when I started Adventure Beat and I started covering AI as a daily beat, I sort of figured, you know, I've been there, done that.
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  I couldn't have been more wrong.
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  I immediately probably two weeks in, I discovered that I was like a babe in the woods.
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  There had there was this whole storyline going on that I felt like I had been plopped into the middle of.
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  I really didn't know anything, for example, about
• 2:40
  Open AI and Anthropic had just started the year before.
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  I really didn't have any insight into these sort of frontier AI firms and how quickly things were already accelerating at that time, even before Chat GPT came out.
• 2:56
  So it really was a huge surprise.
• 2:59
  In addition, I must say that when ChatGPT first came out and I received the email ~ about it, I
• 3:06
  didn't really appreciate what it was.
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  I there had been a couple of other chatbots coming out at the time.
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  And so I perceived this sort of in the same vein.
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  I didn't really see it as a momentous occasion.
• 3:19
  And two weeks later, it was everywhere.
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  And suddenly, you know, my mother knew what Chatch ET was.
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  And that was a huge change.
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  So I definitely did not see that coming.
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  But once the roller coaster ride got going, I feel like I kind of got my.
• 3:36
  Got my legs under me.
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  Yeah, what was it like ~ covering this technology at major business publications over the past several years?
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  ~ it it's been a real roller coaster ride.
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  I think partially because people didn't immediately see, as I say, like how quickly it was going to move.
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  And right from the beginning, there was a lot of challenges and controversy, you know, similar to what's being covered today, but it was sort of the beginning of that.
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  People saying that, you know, there were real dangers and different
• 4:11
  you know, open letters about pausing AI and all of that.
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  That that was pretty early on.
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  And and just, you know, how quickly agents came into the game.
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  I I probably started covering AI agents back in 2023, these very early days of that.
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  But you know, there were there were just various milestones along the way.
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  And for a business publication, you know, you're not just covering the latest research and technology.
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  You're also covering
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  how it's being adopted, what companies are coming up.
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  So it it became such a vast and broad beat that, you know, I'm I'm certain everyone can appreciate that as a reader, ~ seeing the headlines, you know, just more and more every
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  day to the point that you're like, I would really rather watch sports than see another AI headline.
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  But as a reporter, it it was it's just completely overwhelming.
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  And and many times over the past few years I've had to like make decisions about, you know, what
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  am I gonna cover, what am I not, what's important, what's not important, how do I see different sides of an ongoing debate?
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  And it's it's never boring.
• 5:21
  I can definitely say that.
• 5:23
  Yeah.
• 5:24
  And I want to get on to what you're doing now, but but I just want to follow up on that a little.
• 5:28
  How do you make those decisions?
• 5:29
  How do you think about what stories to tell?
• 5:32
  I think you you have to certainly think about the audience that you're dealing with.
• 5:37
  So Adventure Beat, for example, this was a little bit more of a technical audience.
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  At least that's how I perceived it.
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  So I did feel a little bit freer to go into the weeds and not have to explain every technical term.
• 5:52
  At Fortune, that that was quite different.
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  You know, I was constantly being told by my editors, no, you need to explain what inference is or
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  you know, just other jargony words that I was already taking for granted.
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  You know, people are not gonna understand what you're talking about.
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  And I appreciated that because I did it didn't really occur to me that a a business audience, you know, a broad business audience, really quite different from, you know, a
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  little bit more technical audience.
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  ~ and so, you know, I had to make my decisions there.
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  For and you know, at Fortune, I was really tasked
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  much of the time to be covering the biggest players.
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  You know, they really wanted to cover what's the latest at OpenAI, what's the latest in anthropic, is Google in the lead?
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  Is Meta in the lead?
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  Who's leading?
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  Who's losing?
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  What's the race?
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  you know, and in a little bit of a way, I I feel like I realized that there were other stories that I wanted to tell that didn't fit quite neatly into the fortune space.
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  Sometimes they did.
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  Like I did, I was very interested in covering
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  the AI data center boom ~ last year.
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  ~ you know, even before it started becoming such a discussion point, I I felt like it was so fascinating.
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  And I was lucky enough that fortune was very supportive of that and sent me to several ~ data center sites in different states to cover that.
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  ~ but you know, that wouldn't necessarily have traditionally been a fortune story.
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  So I I felt, you know, gratified that I could get in there.
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  ~ but you know, Venture Beat had a had a very different angle.
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  So, you know, partially it's what I'm personally interested in, but always thinking about the publication's audience as well.
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  And you recently left Fortune to go out on your own.
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  What what are the stories that you want to tell at Ground Noble AI?
• 7:43
  Yeah, so ground level AI is a publication and platform I launched on Substack.
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  It's a newsletter and a podcast.
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  ~ I launched in mid-June, ~ right after I left Fortune.
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  And the idea is it in my mind, I I think of it as like AI as it meets the real world.
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  That can mean a lot of different things, but to me, it's a real focus in going beyond some of the headlines that are really just about open AI or anthropic and the models
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  themselves.
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  You know, the latest capabilities, the latest gossip.
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  You know, I'm like, there's so much more like on the ground type of things underneath the models that are so important, you know, like the the infrastructure, both digital and
• 8:27
  physical, the security, cybersecurity and and governance and ~ safety and security, policy issues ~ that you know are a wide swath of.
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  of angles around that and even the the geopolitics which can kind of cross into all of those lanes and then too some of the consequences of of AI around workplace adoption and
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  communities affected and stuff like that.
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  So that still is quite a wide broad swath, but still it was a way for me to at least wrap my mind around the beat a little bit more because it's changed.
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  AI is now ever any reporter covering anything
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  in a way is is covering the AI bead.
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  So if I'm going to do that, I'd like to kind of like put a little bit of boundaries about around it.
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  Are there common themes among those areas that you're interested in?
• 9:23
  Yeah, I mean, I do think that so much of the discourse is around trust.
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  So I feel like the various issues of trust and security are issues that sort of cross all of those lines.
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  You know, if you're talking about enterprise adoption, for example, you're talking about things that, you know, other people might think are not very sexy.
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  They're the the governance, the risk.
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  you know, the the the compliance, all of those things to me are really interesting because that's how it's going to get adopted and that's how it's going to be used securely in your
• 10:03
  in your firm.
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  ~ I also really do in enjoy covering AI and cybersecurity.
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  And funnily enough, it's become headline news over the past few months.
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  I never could have imagined that.
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  I thought it was like this, you know, side thing that most people aren't very interested in.
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  But, you know, I I
• 10:23
  go out every year to the Black Hat Security Conference.
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  ~ and that's when OpenAI made its big briefing announcement about hugging face.
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  And I posted immediately about that.
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  And, you know, it kind of went viral.
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  And that's just an example of how, you know, these these parts of the AI story and evolution as it really affects people is is is something that everyone wants to hear
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  about.
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  It's not just a
• 10:52
  you know, a small audience anymore.
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  But yeah, so I feel like ~ that's some I I do sort of circle a lot of themes.
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  Like I really do enjoy getting into some of the nitty-gritty stuff around infrastructure, like how are these data centers built?
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  Or like just today I was posting about like how do we understand even what makes up the whole technology stack?
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  Like people think of just the models, but there's
• 11:22
  software and applications, there's energy, there's data centers, there's the s the racks themselves, there's the servers, there's the networking, there's so much.
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  ~ and on the policy side, I must say I'm very interested in in following what's happening around this year's election and how AI issues are are, you know, everywhere around the
• 11:47
  election.
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  It's become incredibly political.
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  Absolutely.
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  How do you translate those those technical elements for a broader audience?
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  Is you as you talked about cybersecurity, everyone has known it's important for a long time, but most people's eyes glaze over when you get into the the details of the
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  mechanics.
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  And, you know, the hugging face incident was fascinating, ~ but you need to have some understanding about the the technology to to get what happened.
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  So, you know, how do you think about presenting that in a way that that doesn't lose the the accuracy?
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  I think, you know, that's where I feel like for me, you know, there are a lot of substacks out there covering tech.
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  There's a lot of people that do things in different ways.
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  But I'm not, you know, I do write an my own analysis or essay type pieces, but I'm also speaking to a lot of people and I'm interviewing experts.
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  Like I'm not a cybersecurity expert.
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  I think the most important thing in covering a story like that is asking.
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  the expert people, what they think about it.
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  So I think if you, you know, if you hear from people on that wall about whether or not they, you know, what they really are concerned about and what they aren't, and sort of in
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  a in a basic way that what they would compare it to or how they could explain it to you, that's a way of imparting, you know, you don't need to get that deep in the weeds to
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  understand that that was a serious incident.
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  But you also don't need to get that deep in the weeds to understand that, you know, people have different opinions about it.
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  And and there isn't one, you know, one opinion that, you know, that, you know, has everything in it.
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  You know, you you you there's different ways to explain it.
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  It's a nuanced issue, is what I should say.
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  And I feel like that's what I'm covering at ground level AI, is really nuanced issues.
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  And that isn't always as viral or popular as
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  you know, headline making scary news about AI.
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  ~ I think that's very popular.
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  It definitely gets a lot of clicks.
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  And not that I'm not trying to get clicks too, but I try to offer a little bit more nuanced where I'm asking different people for their opinions and sort of putting it in
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  perspective for people.
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  Which, you know, sometimes, you know, I'll be introducing concepts that if you're not in cybersecurity, you not
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  encounter on a daily basis, but you might find interesting to know that that's what these people are thinking about.
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  So yeah.
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  You mentioned ~ the issue of trust.
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  And this is also something I've thought about a lot and written about in in different contexts.
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  What does that really mean?
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  Because we see all these polls where people say I don't trust AI and and you you hear that reaction a lot, but what what is exactly the trust gap that you see in this area?
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  I was just talking to several people about that this morning.
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  I'm gonna be moderating a panel in a couple of weeks on this topic.
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  And that's the thing.
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  It means so many different things to different people and you can come at it from a lot of ways.
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  But I feel like for one thing, there's trust in the technology itself.
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  You know, do you feel that, you know, these this technology is trustworthy that
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  People understand it.
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  And generally, people know that the answer to that is in many cases, no, that there's a lot of things we don't understand about LLMs.
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  Even the researchers building them don't understand that it's a a little bit of a black box, ~ even to them, and that there isn't enough transparency there.
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  So there's the trust in the technology.
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  Of course, then you have the trust in the people building the technology, and there too.
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  There's so many challenges.
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  You know, I I recently wrote a piece where I spoke to my nephew, who's a 22-year-old Gen Z guy, and he uses AI.
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  So he's not against it.
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  What he doesn't trust are the people building it.
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  He really hates the companies themselves, the billionaire CEOs.
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  So you have a lot of that, you know, the the trust in the companies building it.
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  And then follow from that.
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  you know, the trust in the companies using it.
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  So if you're at work, you know, do you trust that your company is using it in a good way?
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  Are you worried about your job?
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  Are you worried about the security of your data, you know, personally too in your personal use?
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  So the the outcomes, you know, the output of the models is also a trust concern.
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  and I find all of that really interesting.
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  I find the all those areas of trust
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  really interesting and equally challenging.
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  I'm not sure at the moment how how you know all of that can be solved, but I I'm always heartened by the number of people in all three of those areas that I do think are working
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  on it.
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  You know, even if if if it they're not successful yet, there there are a lot of efforts in all of those areas to boost trust.
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  But, you know, in in this
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  In this world environment we live in, I feel like it's it's difficult.
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  Absolutely.
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  No, and I I speak to a lot of ~ you know, enterprises and executive education groups about AI governance.
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  And and I always make the point that that trust is important and you should want to be trusted and be trustworthy.
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  ~ but I'm I'm curious, you know, what your experience is like, you know, talking to companies, talking to people, how much that actually matters.
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  It's it's easy to say, yes, sure, sure.
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  We don't want something to blow up.
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  We, you know, we don't want to get sued.
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  ~
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  But I I feel like there's often ~ a a skepticism that this is really going to matter and it's worth making the investments.
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  Yeah, I I that's one thing I worry about.
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  I worry that there's a waiting for the one big bad thing to happen before everyone jumps in with the bigger investments in trust or security or safety.
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  because there's still so much FOMO around this.
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  I'm sure you hear that from executives as well.
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  And right, FOMO does seem to override some of this sometimes.
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  ~ but I do think that the open AI hugging face incident, as well as like methos and fable and and sort of the pace of change that we're seeing now does have executives more on edge
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  about needing to to and and also maybe seeing the the hate coming back at the like you know if they're
• 18:38
  If their, you know, employees or their customers hate AI, you know, that needs to be a wake-up call to how they deal with it.
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  ~ so I'm interested to see how that plays out.
• 18:53
  And you mentioned the the reporting you've done on on data centers.
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  Obviously this has become a huge, you know, political issue, a huge area of concern.
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  You know, how much do you think this is really a story about the energy usage, the water usage, the things on the ground versus really a proxy for all these vague anxieties that
• 19:13
  we've talked about?
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  Yeah, it's really interesting because when I first started covering this, this was about a year ago.
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  and at first I really did see it as kind of a local issue for the communities involved.
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  I definitely said to myself, wow, I wonder why we're not hearing more about this.
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  Like this is, you know, you're taking these what the equivalents of big cities being built in the these rural areas.
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  It's just
• 19:45
  Astounding, like you can't even comprehend the scale.
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  And these communities were mostly taken aback, you know, by the by what has transpired in both good and bad ways, to be fair, but ~ in a lot of really challenging ways.
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  But then as the months passed by, I definitely started seeing just so much more pushback, a lot of misinformation, a lot of, you know.
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  Just swirling and and just growing this massive pushback that's turned very political.
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  I do think that it is a proxy for a lot of things that people just hate or feel uncertain about around AI.
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  you know, it's sort of like a physical yucky manifestation of everything you hate.
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  Like you just couldn't, you know, cinematography better for a movie than having some.
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  you know, spewing gas generator, Elon Musk data center in Memphis, you know, to serve as an example of the excess of AI ambitions for billionaires.
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  That said, you know, even though there is misinformation around some of the impacts, because part of it is that some of the impacts are as yet unknowable.
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  Most of these ~ mega data center sites have not
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  become fully operational yet.
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  So a lot of what you're talking about is people speaking about ~ smaller data centers or ones that have been retrofitted in some way.
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  But you know, but on the other hand, there there are.
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  I mean, that some of the impacts are clear.
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  Like you, you, you do have, you know, in incredible amounts of construction going on that's total chaos in Richland Parish, Louisiana.
• 21:36
  You know, yes, there are some winners, but you have people being evicted.
• 21:40
  There's definitely rising rents, there's not enough housing.
• 21:45
  you know, I visited a town ~ near the site, an area near a block near the site where you know there were eight houses on the block, and now there are 2,000 people living in RVs.
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  I mean, it's crazy.
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  So I feel like there's a lot of legitimate, you know, impacts there, but on the other hand.
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  I do think that a lot of people who don't are not the communities particularly impacted, they don't live there, but they're just against data centers are definitely bringing in a
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  lot of their own other concerns.
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  Do you think that there's any likelihood that we'll see an actual pause or or a moratorium on development?
• 22:29
  Well, there is already in some st in in several states, they've already passed data center moratoriums at the state level or it could be at the county level.
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  ~ so that's definitely happening.
• 22:42
  I have to say that I don't really think so because there are communities that will accept them and it is good news for some communities.
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  And also, like I do feel that.
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  Many of these are just going to get billed by Hooker by Crooks.
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  So ~ I would like to see more, you know, clear benefits for the communities involved and that they should be more I I just feel like there's a better way to do this whole thing,
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  but you know, I'm not a developer, but I feel like ~ it could be more of a win-win.
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  And I do think many of these will still be built.
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  because there's a lot of
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  political wherewithal to make that happen.
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  and so much investment capital and and all that investment capital.
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  AI labs are right in terms of the scaling loss continuing to hold.
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  They exactly.
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  Choice.
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  Exactly.
• 23:39
  Let's go back to the cybersecurity issue.
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  you know, how how worried are you about what's coming next in terms of these threats?
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  Because when I speak to cybersecurity people that I respect, they are.
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  That doesn't necessarily mean what some people think it means.
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  It doesn't mean that these people think that AI is gonna kill us all or that, you know, rogue agents are gonna take over the world.
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  But the issue is the speed and scale of what's happening now and whether the defense can catch up.
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  It's really like.
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  Cybersecurity has always been this kind of offense-defense thing.
• 24:18
  You know, you're you're playing offense to keep the hackers away, but you're also defending your own systems.
• 24:27
  So it's always been like that, but you know, you might have time to catch your breath.
• 24:32
  You might have ~ you know, ~ in mind a certain period of time that you can take to patch vulnerabilities, for example, or pen test your systems.
• 24:44
  But now that's really up-ended because the the speed to which company ~ hackers can do some very bait, like typical hacker things, not even like rogue agents, but just like
• 25:00
  crazy amounts of phishing.
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  You know, they can take phishing emails to the max, for example, or new things that can be done at scale.
• 25:10
  Like I'm particularly weirded out by
• 25:13
  Deepfakes in the enterprise where and where hackers will like make phone calls that sound just like your boss's voice or ~ Zoom calls where it looks like your, you know, your
• 25:24
  boss's face or something, or or a customer's face.
• 25:27
  ~ but as far as the higher the the more even scarier stuff, like what the reason they took mythos, ~ kept mythos to just a few companies to work with and took Fable.
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  kind of offline for a while was because of these higher level cybersecurity capabilities that attackers could use to find vulnerabilities everywhere in your system before you
• 25:53
  could possibly patch them.
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  But those same systems can be used to find them and patch them too.
• 25:59
  So if you have access to them, you could catch up kind of.
• 26:03
  So that's a lot of what the discourse is now is about let us have access to these more powerful systems so we can catch up.
• 26:11
  But then you have the people saying, but if we let more people use them, the hackers can find them.
• 26:16
  So it's kind of a weird dichotomy.
• 26:21
  But ~ some people I speak to think that the attackers need time to catch up too.
• 26:28
  So there might be this little window we're in where we still do have a chance to catch up.
• 26:33
  But the worry is we may not have enough time.
• 26:37
  So that so I I would say I am worried.
• 26:41
  And I'm I'm really relying on smart people to help us catch up.
• 26:47
  You did a a piece recently talking about how ~ AI safety and cybersecurity were coming together.
• 26:53
  And I wonder if you could talk a little bit more about that and what's what's the gap between those two communities?
• 26:59
  Yeah, so when I first started covering AI, this was one of the most confusing things to me because if you think of AI safety, isn't cybersecurity about safety?
• 27:10
  But in the world of AI, if you're talking about people in Silicon Valley and just in the AI world, they think of AI safety as the safety within the models themselves as far as
• 27:25
  their capabilities and and making sure that models
• 27:29
  The models themselves are aligned with what you do or don't want them to do.
• 27:34
  And so any fixes there would be within the models themselves.
• 27:39
  Whereas cybersecurity has always been more about keeping things in control and in bounds, even if something is doing something that you don't want it to, which happens all the time
• 27:51
  with hacking, that you can keep your system safe and not let anyone in.
• 27:57
  It's also just two different cultures.
• 27:59
  You know, you have a real Silicon Valley philosophical belief system culture around AI safety that some people, you know, might find off-putting or just very academic and
• 28:15
  research oriented.
• 28:16
  Whereas cybersecurity has been around for decades.
• 28:19
  It's really hands-on and like, you know, in the in the enterprise, for example.
• 28:25
  ~
• 28:26
  So I have found in my coverage and going to different conferences that these groups of people don't tend not to understand each other.
• 28:35
  You know, the AI safety people feel like the cybersecurity people are not taking the model risk seriously enough.
• 28:42
  And the cybersecurity people think the AI safety people are just kind of like in a cloud, like not really understanding that you need to like control and put boundaries around.
• 28:56
  ~ scary things and that you can.
• 28:59
  So it's really interesting to see these two groups coming together now, which they do have to because AI security is a little bit of a different thing.
• 29:09
  You're not just talking about, you know, software, you're talking about these models and having AI agents that are reaching out to different applications and potentially working
• 29:22
  autonomously.
• 29:23
  which is quite different and again at a speed and scale that we haven't seen before.
• 29:28
  So, you know, everyone I speak to that I respect that kind of falls in the middle of this says, We need both folks on that wall, you know, to to make this work.
• 29:39
  Yeah, ironically, it it may be that these scenarios that sounded like science fiction, rogue agents finding a way to communicate, breaking out, hacking, the fact that that's now
• 29:49
  something real and tangible that has happened in in some way opens the door, I think, to the people who are dealing with on the ground issues all the time getting involved and
• 30:01
  saying, Okay, let's let's practically figure out what to do about this as opposed to just theorizing.
• 30:06
  Right.
• 30:06
  And I I think the reverse is true as well.
• 30:09
  Like if you're dealing in your enterprise or in a cybersecurity standpoint about with AI agents that can escape their bounds and do things they're not supposed to, you might be
• 30:21
  grateful if a if a model company made sure that the models were more quote unquote aligned with with human values and and all of that.
• 30:31
  So it it does feel like two sides, you know.
• 30:34
  These things both have to happen, it sounds like to me.
• 30:39
  And last question, what are the stories or or or even one story that that you think ~ is not being covered enough around AI?
• 30:49
  It's probably an unfair question because you're gonna go and cover it at ground level, but what do you think people are not paying enough attention to?
• 30:59
  that is a really good question.
• 31:02
  I I guess I do feel that most people aren't quite understanding how quickly things are changing.
• 31:12
  Because I do think that in a lot of ways it seems like it isn't.
• 31:17
  In our daily lives, I'm not sure that most people are feeling tremendous change in their lives from these things.
• 31:27
  And it can seem like nothing's happening.
• 31:30
  ~ and not that you need to pay attention to everything and it's not meant to, you know, be off-putting, but there is, I feel, a real speed and and scale change to what's going on.
• 31:43
  So I do feel like how that kind of like floats out to the rest of the world is something that I'm keeping an eye on and I think people need to pay more attention to.
• 31:58
  All right.
• 31:58
  Well you you're doing a a great job in terms of telling those stories and it's it's great to have ~ you out there as as a voice.
• 32:04
  So Sharon, many thanks.
• 32:06
  Appreciate the conversation.
• 32:07
  Thank
• 32:07
  you so much, Kevin.
• 32:10
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• 32:12
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• 32:19
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