0:00
Jimmy, welcome to Giant Ideas. Good to be here. Thanks for coming.
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0:02
So, let's start by talking about Wikipedia.
0:03
So many lessons that I'm sure you've learned and the world has learned from the founding of Wikipedia.
0:08
One curious element of it, or very interesting element of it, is that you decided to start it as a non-profit.
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We interviewed Tim Berners-Lee, the creator of the World Wide Web, who created the web for nothing.
0:19
You created a huge part of the World Wide Web, again, without personal gain.
0:25
Do you Do you personally regret any of that?
0:27
Are you happy you did it?
0:28
And then maybe more importantly for the world, do you think it's been a really good thing for Wikipedia that it has been a non-profit?
0:33
Yeah, no, I don't have any regrets.
0:35
I mean, it's it's an an amazing thing to be a part of and my life is unbelievably interesting and fun.
0:42
I also have Fandom, my for-profit wiki company, which has done very well, couple hundred million revenue and all that. So, that's fine. I'm not poor.
0:48
Uh and the um uh you know, the the meaning of Wikipedia, you know, in the long run, I think in 500 years people will look back on this era and say, "Yeah, that that was a bit of a crazy, horrible time and yet these nice people were really good and they were sharing knowledge and and that seems like a useful thing to have done."
1:12
And how is it impacted us?
1:12
I mean, I think the the most important thing is actually not necessarily for-profit versus non-profit, although I do think that is relevant.
1:21
Um but it's it's actually more broadly the business model.
1:26
So, the even if you're a non-profit, you have to have a business model.
1:29
You've got to pay the bills and you've got to sort of you know, make it work.
1:35
And if we had advertising as a business model, I think that would that would be pretty problematic in lots of ways.
1:40
You know, a lot of the stuff that we've seen happen to purely ad-supported journalism, uh where there is a really strong temptation to have clickbait headlines and to think about viral things and and all of that, >> [cough] >> which [clears throat] is fine in certain areas, but really would be a bit odd for Wikipedia.
2:03
It'd be problematic, I would say.
2:06
>> So, sort of a purity to the Wikipedia approach allows you to build some of that trust, I presume.
2:10
Yeah, and and and the organization, so the the Wikimedia Foundation can remain very very uh mission-driven.
2:17
And so, you know, our our goal is a free encyclopedia for every single person on the planet in their own language.
2:25
That's how we make decisions.
2:27
And so, when we have, you know, decisions to make, which even companies that actually do care a lot about that same kind of value system, I would I would say Google does, but Google has to prioritize, of course, the markets where there's big ad revenue.
2:40
You know, they're they're good about trying to support as many languages as they can and and things like that, but obviously, you know, it's like the next million uh users of Google in California are going to be much more interesting and more profitable than the next million in Kenya. Sure.
2:56
Just because that's the way the market is.
2:59
Um whereas for us, it's like, well, that hardly matters.
3:01
And indeed, for our business model, which is donation-based, it's probably those next million in Kenya who people are really more excited about.
3:09
Having built Wikipedia as a nonprofit, you've kept it as a nonprofit.
3:12
Famously, OpenAI started as a nonprofit and is basically not really a nonprofit anymore for all intents and purposes.
3:19
What do you make of that situation and how do you think they should proceed?
3:24
Well, I it's it's very complicated.
3:26
And I I've sort of made a uh sort of amateur study of it as I think many of us in the industry have.
3:34
It's like, what [snorts] the hell what the hell is going on over there?
3:35
Like, it's very like, how do you do that?
3:36
Uh so, it's really, you know, uh it's still, I think, technically owned by the nonprofit at the top of it, but it's got this sort of cap return, blah blah blah.
3:47
You know, it's very complicated.
3:49
Um and apparently, Sam Altman doesn't own any shares, which is also quite interesting.
3:52
I don't know what to make of that either.
3:54
So, I think one of the keys is you know, basically if you think about what what is Wikipedia?
4:00
Wikipedia is often reported as a tech story.
4:05
But the truth is the actual tech infrastructure is minimal.
4:07
Like it's really you know, if you think about okay, what's the technology of Wikipedia?
4:12
Fundamentally it's a web server, web browser, database, you know, the idea of Wiki.
4:21
It's very basic and all of those things and it's really a community story. It's about the people.
4:25
It's about the humans who are building this thing.
4:29
And so therefore the cost um is not nearly what it cost to do sort of frontier AI models.
4:37
And so I will say like okay, to do open AI as a nonprofit, I don't I can't think of a single way if it were set up as a charity that they would say well okay, we need to invest 120 billion GPUs.
4:50
Yeah, good luck raising that kind of money unless there's going to be some kind of return from investors.
4:55
Like that that's sort of obvious.
4:57
Whereas for Wikipedia, you know, we're trying to raise whatever, couple hundred million and we've got a massive massive audience, you know, it's doable and it's always been doable all all along.
5:07
I mean one of the great things about Wikipedia is it's really bootstrapped in the in that sense, you know, it's like we've never had to go for outside capital and and so forth.
5:17
It's always just been donations and largely small donors.
5:18
So So there is a difference.
5:21
So it's you know, it's very easy for people to sort of tisk tisk at Open AI, but I'm like well you know, go ahead start a charity and raise $2 million and see what you can do with API.
5:32
I mean good luck with with um not API, GPUs, you know, it's going to be quite hard.
5:38
We've talked a bit about your incentives starting a nonprofit versus a profit, but thinking about the incentives of the users of Wikipedia.
5:46
So, you've created arguably probably the biggest historical body of knowledge or certainly one of them without financial incentives for those contributing.
5:53
So, you've had a front row seat for the last 20 years.
5:57
What have you learned about I guess human motivation and and and why people are doing this?
6:01
Yeah, I think this is this is really huge and um you know, so so Fandom is Wiki communities as well and that's ad supported and and so on and it's it's mainly about entertainment, gaming, and so forth.
6:15
And so, you know, one one of the first hypotheses that I had but I wasn't sure about is would people be willing to contribute to I'll give an example the Muppet Wiki.
6:27
Right, which you can't really set up as a charity cuz you can't really convince the government that's a charitable project but it's a community project.
6:33
So, would people contribute um would they contribute unless maybe like social media influencers, maybe they need some sort of deals or whatever. It turns out they do.
6:43
Uh it's because they're they love they have a passion about some area of knowledge or something that they're interested in.
6:52
They have often times a community motive that you wouldn't think of as charitable.
6:55
So, people who are working in a lot of uh gaming wikis they're they're quite proud of their knowledge and they're quite happy to help other people like them who are trying to get through that very complicated level on the game and so on and so forth.
7:07
So, it's interesting that um you know, the you know, when I was raising money for Fandom uh you know, somebody said to me, "Oh, the the VCs must love this that you you know, all these people just do the work for free and so on."
7:23
I'm like, "Actually, the funny thing is VCs are the only people who ever said, 'Why don't you pay people?'"
7:27
They're like, "What if you paid people like a dollar per article or something like that?
7:33
Wouldn't you get more articles?"
7:33
And I was like, "You would get more crap, that's for sure."
7:37
And actually that's another piece of it.
7:39
It's like the people writing Wikipedia aren't doing it for very low pay.
7:42
If you want good quality writing, uh you can either pay good journalists a proper salary, right?
7:50
Or you can get people who are really passionate about it to do it out of the love of what they're doing.
7:57
But if you pay people a very low amount, you're just going to get a bunch of nonsense.
8:00
There was a company called Demand Media, which had a little flurry of a splash.
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I don't know whatever happened to them, but haven't heard about them in a long time.
8:06
But they basically were using algorithms to detect like what people were searching for.
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And they would find quirky search terms that had no coverage, and then they would pay people like a dollar or something, you know, to write, you know, uh instead of just an article about how to wash your dog, it'd be a specific how to wash a Pomeranian.
8:26
Uh and it the content was terrible because people are like, "Oh, I'll take a dollar.
8:30
I know nothing about dogs or Pomeranians, but I could I need a dollar, so I'll do it."
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And it it just wasn't good.
8:35
Whereas the Muppet Wiki, let me tell you, >> Very, very good.
8:39
>> People care about Muppets. Uh yeah.
8:39
And you know, the the same is true.
8:41
I mean, that's a it's a fun example, but uh you know, it particularly around geek culture, you can imagine the people who are really deeply knowledgeable about Lord of the Rings and things like that.
8:52
And then the same for Wikipedia, a lot of the people involved in Wikipedia are they're motivated yes, by the charitable vision, yeah, free encyclopedia for everyone.
9:02
That sounds like a worthwhile way of spending your time.
9:05
But they're also very motivated about their their passion around a certain topic.
9:08
So, you know, people who are writing about trains or you know, whatever it might be.
9:14
Um they're they're deeply knowledgeable.
9:16
And I, you know, just count me as any ordinary person who I sometimes stumble across a Wikipedia page, and I'm like, "Who are these people?" It's unbelievable.
9:23
Like, you know, it's like here's some very obscure airplane, um you know, that was in production from 1934 to 1938, and there's this massive article about all the details including specific airframes and which ones are still flying and I'm like, "Wow, this is fantastic."
9:42
But you wouldn't you couldn't pay anybody to do that.
9:44
And it it wouldn't make sense.
9:47
But what does make sense is having a community that's welcoming to that person who's like, "Hey, I know about this. I'm obsessed.
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I'm not going to apologize for my obsession.
9:59
I'm just going to go with it."
10:00
So a combination of sort of contributing to the community but also I guess some self-fulfillment from you know being an expert in something.
10:06
>> Yeah, and and you know one of the the interesting things is you know it it's people you know human beings do like recognition from other human beings.
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That visibility is psychologically valuable.
10:20
And in some cases that uh can be a bad thing.
10:24
Like a lot of times the way social media is designed the way to get visibility and attention is to behave badly.
10:30
Um because you get more followers that way and and this that and the other.
10:34
And the you know the more positive side of it is people who get a huge following because they're actually interesting and they've got good ideas or they are attractive in you know sort of visual social media and things like that.
10:48
But for the Wikipedians nobody's trying to get famous uh and be an influencer and get a sponsorship deal or anything like that.
10:55
But they still do care about the um the feedback from other human beings.
11:01
But actually you know the person who's obsessively writing about the Muppets doesn't really care what any of us think.
11:08
They just want the other Muppet fans to sort of say, "Oh wow, you're you're amazing, you know."
11:13
>> And who are these people?
11:13
Are we talking about a very small number of people who create 80% of it or is it actually across cuz you have to be so niche in these areas to be able to write about it.
11:21
Is it a vast number of writers?
11:21
It's it's it's vast but it it's it's narrower.
11:28
It's hard to really answer that question.
11:29
So I would say um you know there's the really really active contributors.
11:35
So, the people who are the most active are actually probably not the people who are obsessive about a niche.
11:41
They're obsessive about Wikipedia.
11:42
So, they're doing work across the whole thing and they're checking references and they're monitoring incoming stuff for bad behavior and they're being admins and things like that.
11:53
But yeah, I mean one one of the things a lot of people have the idea of Wikipedia that it's 10 million people adding one sentence each, but it's really is a much more narrow group of people who are really very focused on Wikipedia and the the standards and the rules and how it all works.
12:11
Well, that's I think a great segue.
12:13
I mean Wikipedia promises a neutral point of view which sounds ideal, but in reality is it just a reflection of who shows up, who are used [snorts] the most, who cares the most and reflective of that group that you described cuz that is I guess one of the recent criticisms from some people on both the left and right side of the political >> So, yeah.
12:30
So, it's it's a it's a bit of a yes and a no to answer that.
12:34
So, on the one hand yes, of course we all have our biases and we know about the things we know about and you know very often one of the things I say about bias is that it's often like if you ask a fish about water, the fish will say what water because you're just swimming in it.
12:55
Like you don't really even realize you're biased in many cases and that's because of the media you consume and the culture you live in and so on and so forth. So, that's unavoidable. Kind of unavoidable.
13:07
The other bit is to say like if you have people who have a genuine commitment to neutrality, they can definitely overcome their own personal viewpoint and say actually I do understand you know like we're not here to settle the argument.
13:23
We're here to present all sides of the argument in a fair way and people are actually pretty good at that.
13:28
Not everybody, and some people find it very uncomfortable, and some people are good at it in some areas and not in other areas.
13:33
My My mean, my personal example is I don't ever attempt to edit anything about Donald Trump because the man makes me insane, and I couldn't be a good Wikipedian.
13:44
Uh but broadly, there are people who are quite good at it and and who who do, you know, work to achieve neutrality. And so, is it perfect? No.
13:53
Uh it can be imperfect because people aren't even realizing that they're being biased because they haven't really heard any other perspectives.
14:00
Um it can be imperfect because of very if there's something that's very emotional, uh that makes it a lot harder.
14:09
So, where I see problems around neutrality is generally, um you know, if there's a war on, uh particularly if Wikipedians have been killed and things like that.
14:18
Yeah, we're human beings.
14:19
Like, it's hard uh even when we have a commitment even when the community wants to be neutral, yeah, it's kind of hard to hold onto that um and in those in those times.
14:31
And so, you know, the idea that, as Elon says, Wikipedia's become wokapedia. No, it hasn't.
14:38
Like, I I know the Wikipedians I read Wikipedia a lot, and say, "Look, that's just not true."
14:43
Uh I mean, one sort of little example, there's a a classic kind of uh gotcha question around the whole trans issue, "What is a woman?"
14:54
And I don't know what they think the answer's going to be, but if somebody started coming at me with this question on X, you know, I was like, and I knew a little bit about this, but, you know, and and the the answer there was a like a right-wing documentary about this, and the like the big punchline is, "A woman is an adult human female."
15:09
And they did get a some people on the documentary who were not quite willing to go there and say and sort of waffled in this and that, but I'm like, I can just tell you what it says on Wikipedia. Adult human female.
15:20
Like, then further down the article, of course, it addresses like the questions of trans and that there's a social question and the issues and da da da da da and it's all like, "Yeah, that's fine."
15:28
Like I'm like, "If you're coming at me over that one, I'm like, yeah, we've we've not become, you know, crazy woke."
15:33
Uh on the other hand, if you say, "Yeah, look, Wikipedia has problems of bias."
15:40
Um I'm like, "Yeah, actually I think we probably do."
15:42
And I think that's something we always have to have, you know, to examine and to be open about.
15:49
You know, in my in my book that just came out, Seven Rules of Trust, one of the ones I think is really, really important, particularly in my personal context at this moment in time, is uh be transparent even when you have something to hide.
16:03
And, you know, sometimes like the comms team at the Wikimedia Foundation get a little uncomfortable with the way I approach this, but I'm like, "No, like if if we just go with a PR front and say, 'No, we have absolutely no problems with the bias.
16:16
If you think that's wrong, that's because you're a right-wing lunatic.'"
16:19
Yeah, no, that's that's that's not the right way to answer it.
16:21
The right way to answer it is to go, "Yeah, you know what?
16:23
Actually, there's a few areas where I don't think we quite live up to it and I think we need to work on that.
16:28
There are definitely areas where the media is biased uh and therefore Wikipedia ends up reflecting that. How How severe is that? Good, let's debate that. I don't know.
16:42
Uh usually what I find is that when the media is very biased on an an issue, the Wikipedians tend to tone that down.
16:49
Uh so actually we're better than The New York Times if if The New York Times is pursuing an agenda or something.
16:55
But it's complicated and it's quite hard.
16:57
And actually, you know, there's a lot of detail under the surface.
16:58
You know, like one of the problems that we have right now is um a lot of the right-wing media is quite independently of being right-wing also low quality. Uh and that's a problem.
17:10
You know, like if if you if you're really being serious and thoughtful and you say, "Okay, right.
17:16
I've got uh you know, a story in the New York Times and the Washington Post and I've got a story in Breitbart.
17:24
You're not going to go well, those are about equal.
17:25
Like one of them is actually not very good.
17:27
It's like tabloid and sort of lots of misleading information and a lot of polemics and so on and the other are yeah, slightly left-leaning newspapers which you can grapple with.
17:37
You know, so that's wrong.
17:38
And so my my thing if I you know, say to Elon like why don't you fund a newspaper?
17:42
You know, a seriously a serious intellectual effort to put forward the ideas that you agree with.
17:49
That would be far more helpful to the world than beating on me.
17:52
So We live in a kind of era of of fake news and there's a lot of concern about trust in in AI.
17:59
How do you feel about where we're going with with AI and whether people can trust it?
18:03
How can we learn from Wikipedia to foster more trust?
18:08
Yeah, so I mean huge question.
18:10
There there's so many different elements to that.
18:12
So you know, clearly right now there's a problem with AI and trust because of the hallucination issue which is still quite severe and you know, as new models come out, you know, Sam Altman is I would say a bit of an affair. I like Sam.
18:29
I know Sam but he'll he'll say things like this is unbelievable.
18:35
We've solved the hallucination issue.
18:36
I'm not sure he's ever said we've solved it but he'll he'll hint in that direction. I'm like oh great.
18:40
That sounds fantastic and then I start using it.
18:41
I'm like yeah, actually it's still bullshits like a night I my my latest which will only really make sense I think to British people.
18:50
Um it's like a it's it's very intelligent very knowledgeable a complete bullshitter.
18:58
I'm like it's a 21-year-old Boris Johnson.
19:01
>> going to say you could hire him as an intern.
19:02
>> [laughter] >> Much of the English upper class.
19:06
And you know, and so I think you had a great example of a hallucination if um, when we when we had you at uh at our venture on ideas if you could share that one. >> Oh, yeah, yeah, yeah.
19:15
So, I mean, one of my one of my favorite things to do and I think if I keep talking about it it'll get into the training data and then it'll ruin it.
19:21
But, uh is um I every new AI model that I test and I do a lot I do a lot of local AI cuz I'm really fascinated by what's going on in the open source world.
19:30
And I always ask uh who is Kate Garvey, my wife.
19:34
And it's she's kind of perfect for this because she's not a famous person, but she is known to a degree and she [snorts] she worked for Tony Blair for 10 years and she promotes the sustainable development goals and she's been in the press a little bit here and there, but not a famous person.
19:55
And so, it it always sort of BS's and it and it says things that are generally quite plausible, uh but not true.
20:04
So, once it said uh that she um that she set up a non-profit organization. Yeah, true.
20:11
Uh to promote women's empowerment in the workplace.
20:15
Definitely not true, but it sounds like Kate.
20:17
Um and that she did this with uh Miriam Gonzalez, who's Nick Clegg's wife.
20:20
Um which who we know I mean, I know Nick because of Meta and you know, we've worked together on whatever there and um and our kids go to the same school and you know, like whatever small town London.
20:33
And uh I showed Kate this and she's like, "Wow, like that could have happened.
20:38
Like like have we been sitting together at a dinner party, you know, at a certain time?
20:42
Like that could have actually happened."
20:44
And that's typically a it typically it's things that are plausible cuz then I always the next question I ask is, "And who did she marry?" Yeah.
20:51
Um and that's also generally plausible.
20:53
It's it's because she worked in politics and is sort of a London person, it's generally um members of parliament uh or political journalists in the UK.
21:05
Uh but my favorite is actually not that plausible.
21:09
I would say it it said that she married Peter Mandelson.
21:13
>> [laughter] >> And then I said to this was chat GPD and I said but isn't Peter Mandelson you know quite famously gay and then it got very woke with me and it says it's not appropriate to speculate about people's personal sex lives and gay people can get married in the United Kingdom.
21:27
I was like yeah okay not really my point but >> Amazing.
21:30
Is there a reality Jimmy Wales test like the the Turing test >> [laughter] >> So so when you when you say that and you you think okay well could Wikipedians use chat GPD to help write Wikipedia's like well no like if you say you know write an encyclopedia article about Taylor Swift who is a famous person it actually you know it's actually not bad although there will be a few zingers in there in my experience.
21:58
But if you the more obscure the topic the more likely it is to hallucinate. Right.
22:04
And we don't need help writing about Taylor Swift. We've got that covered.
22:06
You know it's the it's the more obscure things.
22:09
It's actually I I recently looked and I don't know how often they update but I looked at Grokopedia. Mhm. Kate Garvie as an entry.
22:16
I was checking because she just got an OBE like a British honor and um Wikipedia was updated not because it was her but because we have some obsessives who when the list comes out they immediately go and update everybody.
22:30
So Wikipedia was updated within a couple of hours.
22:31
I was like oh I wonder how quickly they will pick that up and they didn't pick it up but also it's first time I'd actually read it. And it was it was wild.
22:38
It was it was much longer than the Wikipedia entry sort of longer than it should be because she's not a famous person.
22:46
But further down it it started to go on and on sort of in a very AI sort of way about there's not much known about her private life because she's not a very public person.
22:56
Yeah which means you can stop now because you're an encyclopedia but and then it linked that to the sort of message discipline and the secrecy of the Blair administration.
23:09
I'm like, yeah, it's really not got anything to do with that.
23:11
It's just like she's not famous, you know. Right.
23:13
[laughter] Yeah, yeah, yeah.
23:15
So it takes Like her personal life isn't of much interest to anybody. So, yeah.
23:18
So, uh so anyway, at the same time, I think we have to say like the anything you say about AI today, >> [snorts] >> in 6 months' time, you really have to re-evaluate. >> Sure. Sure.
23:32
>> And certainly, you know, when I look at it and I'm playing with things, uh particularly when once you give [snorts] yourself a huge token budget and you don't just do a simple chatbot where you ask the question, but you actually sort of in an agentic way, you go through multiple passes to improve and so on, uh I think it's interesting and I think there's more and more use cases that the Wikipedia community might find helpful.
23:58
On that note, I mean, AI is I mean, a lot of these uh chatbots are being trained in large part on Wikipedia.
24:03
Of course, the the LLMs are trained on the internet.
24:05
AI [snorts] is kind of becoming in some ways the new interface for for knowledge and truth for a lot of people in a way that Wikipedia and Google were in the previous era.
24:13
How do you feel about Wikipedia's role in this?
24:14
Is this going to be sort of the what just one part of the library infrastructure that feeds into the AIs or yeah?
24:20
Yeah, so I mean, all of the every model trains on Wikipedia data.
24:26
It's a huge part of the the training component.
24:28
Um I think by numbers the the you don't always know because they don't reveal everything.
24:33
They're all busy competing with each other, but uh it seems like in terms of quantity, like Reddit number one and Wikipedia number two. >> Reddit is number one?
24:41
Yeah, but Reddit is bigger than Wikipedia in terms of sheer volume of words uh because, you know, like there's a lot of Reddit posts every day.
24:50
What I always say is >> Reddit leans very specifically to a certain kind of demographic, too. So, It certainly does.
24:55
Yeah, yeah, sort of a nerdy, I would say somewhat left, uh nerdy left. >> male, I think, right? >> Extremely male.
25:02
Even more male than Wikipedia, yeah.
25:03
But anyway, it's a huge part of the training data.
25:06
And but what I would say is they read Reddit to find out how humans talk, and then they read Wikipedia to find out information, but um so it's a huge part of the training data, but I think the the the real question is you know, what is our place in the consumer internet ecosystem?
25:24
You know, traditionally our place was, you know, if you if you ask uh Google "How old is Tom Cruise?"
25:33
I and 20 years ago you type "How old is Tom Cruise?"
25:37
into Google, Google had no idea how old Tom Cruise is, but it knew where to find that.
25:40
So it linked to Wikipedia and you would come to Wikipedia and find out.
25:44
Now Google knows, but Google is always been good about attribution, so it'll say right at the top, you know, source Wikipedia, and then we're still the first link and then we're in all the knowledge graph and all that. Loads of links to us.
25:56
And [snorts] so we we have seen in the last year an 8% drop in human traffic, even though our traffic has gone up.
26:02
We got a lot of bot traffic these days.
26:03
Um and we believe, but that it's hard to really tease out, that a lot of that is that really quick answer short traffic, where you're asking a very simple question, you know, uh "What's the capital of France?"
26:20
Well, probably nobody asked that.
26:21
I mean "What's the capital of Azerbaijan?"
26:23
And uh you get the answer and you're you're you're done.
26:28
So you don't go to Wikipedia because you already got the answer.
26:32
And then but what you might do is you might say, "Okay, that's interesting.
26:33
I want to know more about that place."
26:35
So then you click the link when it says source Wikipedia and you go and you read about that place.
26:40
So we still have that long-form reader traffic.
26:41
We still, you know, people are generally aware that you can't really trust AI.
26:47
And I think in particular um you know, the the Google um sort of AI summaries at the top of search, I don't think that Google would put them there were it not for the competitive pressure they're under.
27:02
I think if they didn't have everybody nipping at their heels, I just think it's not in their nature to put a product up that's so insane because it gets things wrong a lot. Right.
27:14
>> Uh things you would think would be right and you're like, "Oh my god, like you've gone a little crazy there, Google."
27:20
>> Um but that's good in a way.
27:20
It's good that if people are like, "Oh, okay, hold on. It's AI."
27:24
I mean, my children are good, you know, that teenage girls and they roll their eyes about AI quite a lot cuz they they or they'll they'll search something up and they'll give an answer uh to me, you know, I'll say, "Oh, what's this?
27:37
Can you look that up for me?"
27:38
And they're like, "Yeah, yeah, but but it's just AI answering, you know, so we're like we're not sure." And I'm like, "Great.
27:42
That's let's hold on to that for a little while until it gets better."
27:46
But it is getting better and I I don't know how fast.
27:48
Like that's that's one of the open questions I would say at this moment in time.
27:54
Um if you talk to Gary Marcus, a big AI researcher who's sometimes is thought of as an AI opponent or AI skeptic.
28:00
He isn't really either of those, but I think he is he's a large language models.
28:05
He thinks we've hit a plateau and that scaling, more training, and so on isn't actually giving us very much incremental increase. Yeah.
28:14
I think he's probably right about that.
28:16
Um which means are we at a plateau that's going to like are we stuck and we're going to be here for 20 years?
28:23
Are we stuck and we're going to be here for 6 months? Uh I don't know yet.
28:25
Like I think that's a super interesting issue.
28:30
Wikipedia, you guys are one of the most viewed websites in the world.
28:34
Do you think in 5 or 10 years' time, do you think people at scale will still be opening up their phone or laptop and going on websites to go on things like Wikipedia or newspapers or whatever else or will it still mostly then be going through sort of chatbot interfaces and and so like that's one question.
28:49
The other question I'd love to get your view on is kind of which types of websites will survive cuz people think for example social media is like you can't really replicate that with with AI necessarily.
28:58
So people think some form of social media will stick around.
29:02
Yeah, I it's a really good question and I think it's particularly if we think about journalism it's a really crucial question for society because we need journalism.
29:14
Like and there is no substitute.
29:16
There's no AI substitute for a reporter on the ground gathering facts.
29:21
I mean maybe someday we'll have sort of humanoid journalists >> all knowing humanoid journalists like monks recording in a in a perfect way, you know, everything that they see and I that's that's science fiction fantasy but and so the business model of journalism is obviously been a problem for a long time now.
29:43
I would say I would argue even going back into the 90s.
29:46
You know, that we we had problems and fractures were going on there.
29:53
And I don't have an answer to that unfortunately. I wish I did.
29:54
But I do I do think that we will definitely still have journalism and we will still have people who want to read a story that's written by human of something that happened today.
30:09
I think that we'll see some dynamics around paywalls and things like that we're already seeing battles break out between you know, information producers journalism and scientific journals and things like that and AI crawlers and bots and sort of reusing content and I think some of that is is potentially quite dangerous.
30:37
Like one of my concerns is that you know, at this time obviously the the traditional media still have an enormous amount of political power.
30:46
And I can tell you there are definitely scientific publishers who would love to change the law so that facts are copyrightable.
30:52
Right now, facts are not copyrightable.
30:56
Um and to say you can't use any facts from our scientific articles unless you pay a license fee.
31:00
I mean, that would be horrific, right?
31:01
Uh it'd be horrific if you couldn't report on any news if someone else reported on it first.
31:06
Like all these things are really bad ideas.
31:10
Even though, uh you know, these questions about like what happens if people stop going to news sites entirely cuz they just rely on an AI summary.
31:21
Yeah, okay, that's interesting.
31:21
Like that's potentially very problematic.
31:22
I I also I don't I'm not so sure it's all that likely.
31:26
I mean, I think that chatbot interfaces are um useful in some ways, but they're not really always what people want.
31:34
I mean, one of the things that I do uh on my phone, mainly because I took social media off my phone because I don't think it's healthy for me.
31:44
But now, I don't know if this is any healthier, but now I just read the news.
31:47
>> [laughter] >> Uh but I use the uh I have an Android phone, so there's the Google app, and you just scroll and it it it knows you and so on and it So I I get a lot of stories about AI and things like that that I'm interested in. And I I like that.
31:58
And one of the reasons I like that as a human is I don't know what I'm not I'm not in search mode.
32:04
I'm not in I have a question and I want to get an answer to my question.
32:07
So, if you give me a blank chatbot screen, I don't there's nothing I have at the moment.
32:13
Often though, I read a news story and then I switch over and I'm like, "Oh, hold on, I'm going to go ask Jim and I about that."
32:17
Um but you still want that serendipity of just some a feed, you know?
32:22
And I do think uh you know, social media, although the I think social media's well due for some new competition because >> Yes.
32:33
Um I think a lot of people are like me, sort of saying, "Actually, I don't I'm not It's not benefiting my life in a way, and even though it can be quite addictive, it's you know, it's it's not actually good for me.
32:45
And so, you know, I I I feel the same way about um short-form video.
32:49
Um actually, one of my I have very, you know, I love Google, but I have so few complaints, and one is on YouTube, it's very hard to turn off shorts. Yes.
33:00
>> I'm like, I I don't really want shorts because I know I'll click on them, and I know I'll waste 20 minutes flicking to the next, flicking to the next.
33:06
That's not really what I want to do with my time.
33:08
But, I do want to go to YouTube and sort of get an algorithmic feed of of longer videos, and actually click on something, and spend 20 minutes watching and learning something.
33:17
Anyway, that's just a little complaint.
33:18
If anybody from Google is listening.
33:21
>> [laughter] >> Speaking of watching very interesting videos on YouTube, this has been a fascinating [clears throat] part one.
33:26
We're going to come back for part two next week to talk more about trust, and also your journey as well.
33:30
Thanks so much for joining Giant Ideas, Jimmy.