The AI Daily Brief: Artificial Intelligence News and Analysis - What People Really Want From AI
Episode Date: March 19, 2026A new Anthropic study based on nearly 81,000 interviews offers a much more nuanced picture of what people actually want from AI: not some clean split between boosters and skeptics, but a messy mix of ...hope, anxiety, productivity gains, emotional complexity, and fears around reliability, autonomy, and jobs. NLW breaks down the biggest findings, why professional ambition and personal quality of life are so tightly linked in how people describe AI, and why dismissing the views of actual AI users is becoming its own kind of bias. In the headlines: AI brings Val Kilmer back for one final film role, Microsoft restructures Copilot again, and Anthropic’s Cowork Dispatch adds Claude Code sessions.For all the links referenced in the show, sign up for the newsletter: https://aidailybrief.beehiiv.com/Brought to you by:KPMG – Agentic AI is powering a potential $3 trillion productivity shift, and KPMG’s new paper, Agentic AI Untangled, gives leaders a clear framework to decide whether to build, buy, or borrow—download it at www.kpmg.us/NavigateMercury - Modern banking for business and now personal accounts. Learn more at https://mercury.com/personal-bankingAIUC-1 - Get your agents certified to communicate trust to enterprise buyers - https://www.aiuc-1.com/Blitzy - Want to accelerate enterprise software development velocity by 5x? https://blitzy.com/AssemblyAI - The best way to build Voice AI apps - https://www.assemblyai.com/briefRobots & Pencils - Cloud-native AI solutions that power results https://robotsandpencils.com/The Agent Readiness Audit from Superintelligent - Go to https://besuper.ai/ to request your company's agent readiness score.The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614Our Newsletter is BACK: https://aidailybrief.beehiiv.com/Interested in sponsoring the show? sponsors@aidailybrief.ai
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Today on the AI Daily Brief, an 81,000 strong study on what people really want from AI.
Before that in the headlines, Val Kilmer comes back for one last role.
The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.
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Well, as you heard in the intro, AI has brought Val Kilmer back to star in one last movie.
The film is called as deep as the grave and features Val Kilmer in the role of Father Fintin.
Kilmer was cast way back in 2020 when production began.
However, by the time the film was being shot several years later,
Kilmer was in the final stages of his battle with throat cancer,
which would ultimately take his life last year.
Now he's coming back thanks to AI to actually star in the movie.
What's generating a lot of discussion around this one is that
as much reflexive antagonism as it's going to get,
and there is plenty of that going around.
it's harder to paint this with the brush of a cynical use of technology to replace human actors.
Instead, in this case, at least according to the people making the film,
it's AI being used to deliver on their original vision.
The character Father Fenton is a Catholic priest and Native American spiritualist
who played a key role in the true story being depicted.
The film's writer and director, Querte Vorhe said,
He was the actor I wanted to play this role.
It was very much designed around him.
It drew on his Native American heritage and his ties to and love of the Southwest.
I was looking at a call sheet the other day, and we had him ready to shoot.
He was just going through a really, really tough time medically, and he couldn't do it.
Now, Kilmer ended up not being able to shoot a single scene for the movie,
so the entire performance was generated using AI tools.
Vorhays created the performance with full permission from Kilmer's estate,
and the cooperation in support of his children.
Said Vorhays, his family kept saying how important they thought this movie was
and that Val really wanted to be a part of this.
He really thought it was an important story that he wanted his name on.
It was that support that gave me the confidence to say,
okay, let's do this. Despite the fact some people might call it controversial, this is what Val wanted.
The film was shot on Navajo land in Arizona and New Mexico and tells the story of archaeologists
Anne-Earl Morris working with the local people in the 1920s to uncover the ancient history of
the Anasazi people. Kilmer has Cherokee ancestry and made his home in northern New Mexico,
so the story about discovering one of the earliest civilizations in the Southwest had a personal
importance. While AI was used to create the on-screen performance, the film uses Kilmer's
actual voice, which was damaged by tracheal surgery in 2015.
That worked for the real-world figure of Father Fenton who suffered from tuberculosis.
At one stage during the movie's production, Vorhe's produced a cut that simply omitted Kilmer's character,
but later realized the character was critical to round out the narrative.
Vorhiz said,
We really figured out that this is a major missing element.
Normally, we would just recast an actor.
I'm all about working with our actors, and we have brilliant performances all throughout this movie.
But we can't roll camera again.
We don't have the budget, we're not a big studio film.
So we had to think of innovative ways to do it, and we realized the technology is there for us.
Vorhays followed all SAG guidelines on the use of AI and compensated the Kilmer estate for his appearance.
He says he hopes the film can be a model of the ethical use of AI in filmmaking.
Now, this was not Kilmer's first rodeo with AI.
He previously supported the use of AI to recreate his voice for his reprisal of the Iceman character and Top Gun Maverick,
which was the last time he appeared on screen.
He said at the time that he was grateful to the company who produced the effect, commenting,
As human beings, the ability to communicate is the core of our existence, and the side effects
from throat cancer have made it difficult for others to understand me. The chance to narrate my story
in a voice that feels authentic and familiar is an incredibly special gift. Said Kilmer's daughter
Mercedes about the new film, he always looked at emerging technologies with optimism as a tool
to expand the possibilities of storytelling. This spirit is something which we are all honoring
within this specific film, of which he was an integral part. Now, it's not worth going through,
like I said, the reflexively negative comments.
Sitting at 5.5 million views on Twitter,
the variety story is much more viral
than anything they produced for some time.
One of the more nuanced versions of the critique
came from Raymond Arroyo who wrote,
This digital necromancy is a very bad idea.
First of all, what makes a great actor
is their unexpected inspired choices
in a given role, a glance, a grimace,
and extended phrase.
The AI Val Kilmer will be denied
all of those uniquely human and very personal choices.
It will be an extended facsimile of an actor
without his fire or ingenuity,
a hollow show. In addition to which the deceased to Kilmer will be saddled with a performance
and a role he has no agency over. This is a violation of his dignity and his work as a living
artist. Now on the second part, we don't really have any other way as society to respect the
wishes of the dead unless they made those wishes explicitly known, or in the absence of that,
we rely on their family, and given that his family is very clearly on board, I'm not sure
what to say about that second one. On the first one, I think there is much more truth there.
But if it is true, we'll see that in practice and I think the market will vote with
their feet. In any case, like I said, this one is sure to be very controversial, and it'll be
interesting to see how the discussion shakes out. Moving back to the core of the AI industry,
it's Microsoft's turn to shake up their AI organization with the restructure of their co-pilot
teams. Microsoft is making several big changes to make their AI efforts more coherent. The team
working on the consumer and commercial versions of copilot will be combined, allowing the products
to be brought more in line with one another. Customer surveys from earlier in the year
showed the multiple different versions of copilot were a major source of confusion.
This combined co-pilot team will be led by product experience executive Jacob
Andrew, who has been promoted to a new role as EVP of co-pilot.
Andrew will now report directly to CEO Sachi Nadela, rather than AI CEO Mustafa Sullyman,
giving Nadella more direct oversight of co-pilot.
With responsibility for co-pilot removed, Seliman will now focus on leading Microsoft's
proprietary model training and superintelligence efforts.
There has been very little progress made on this front over the past year,
with Microsoft last releasing a foundation model in August.
Nadella's announcement makes it seem as though this move is about building out additional leadership
for each aspect of Microsoft's AI efforts.
He wrote,
We are bringing the copilot system across commercial and consumer together as one unified effort.
This will span four connected pillars,
co-pilot experience, copilot platform, Microsoft 365 apps, and AI models.
This is how we move from a collection of great products to a truly integrated system,
one that is simpler and more powerful for customers.
Now, in his own note,
Sullyman said that removing co-pilot from his portfolio was designed to, quote,
enable me to focus all my energy on our superintelligence efforts
and be able to deliver world-class models for Microsoft over the next five years.
Sullyman seems to believe this is the big future bet for Microsoft,
telling CNBC, I'm genuinely thrilled about this change
precisely because most of the future value is going to accrue to the model layer,
and my job is to create highly cogs-optimized, highly efficient enterprise-specific model lineages
for Microsoft over the next three to five years.
That is singularly the objective precisely because the model is the product, right?
That is the future direction of all the IP.
Now, there are a few big takeaways from the shakeup.
Primarily, it resolves the issue that co-pilot didn't have a single owner within Microsoft.
The product was nominally under Sillyman's leadership, but in practice it seemed like a fragmented effort implemented across multiple product teams.
The move also reinforces that AI is a critical business unit at Microsoft that requires more resources and a more structured approach.
Veteran Microsoft reporter and senior editor at The Verge Tom Warren commented,
it's hard not to also read this as an admission that Microsoft's efforts to separate the
co-pilot experience for consumers and businesses has failed over the past couple of years.
Now, to be fair to Microsoft, they are certainly not alone in taking a few iterations to get their
AI organization right. Google undertook a major restructuring in late 2024 to set themselves up for
a massive comeback the following year. Meta has been constantly reshuffling their teams over
the past year in order to get their efforts back on track. And more recently, Alibaba has also
restructured their AI teams to focus on product and business. And that's not even counting OpenAI's
new focus and removal of side quests. Given how many users are basically forced to use copilot
by virtue of their company's policies, I hope nothing more that this leads to great things.
Lastly today, just one day after launching Co-Work Dispatch, Anthropic is updating the tool
to add support for Claude Code sessions. Co-work Dispatch is Anthropics tool for kicking
off and monitoring co-work tasks from a mobile device. Claude code has its own separate equivalent
known as remote control, but as of today, the line between Co-work and Claude Code is getting a lot more
Blurrie. Announcing the new feature, Anthropics Felix Reesberg posted, by popular demand,
dispatch can now launch Claude Cod Code sessions, ask it to build, make, or improve something.
One user asked Reesberg if this feature is a replacement of remote control for Claude
to which he responded, we have some things in the works to make remote control overall a
smoother experience, but this is using the same underlying primitives as Claude Code's remote
control. I think the question will be, how much over the next call it year, Anthropics
synchronizes the experience of co-work in Claude Code. Do they?
become one suite? Do they remain separate but have pretty clear feature parity with just different
interfaces? There's an argument that Claude Co-work, as Claude Code for all the other types of
knowledge workers, might be the most important product line of their immediate future. For now,
though, that is going to do it for the headlines. Next up, the main episode. All right, folks,
quick pause. Here's the uncomfortable truth. If your enterprise AI strategy is, we bought some tools,
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Welcome back to the AI Daily Brief. As the conversation about artificial intelligence gets more
fraught and heightened, there's a lot of people making a lot of assumptions and a lot of people putting
words into each other's mouths. And the party's guilty of doing this come from all sides of the
AI debate, from those who are extremely against AI to those who are extremely pro-AI. There's a
temptation to reduce people to simple, clear attitudes when for the vast majority of people, many of the
issues surrounding this technology and its impact in the world and its impact on their jobs and on
education and on their kids' lives is complicated and nuanced. And so I was interested when Anthropic
released their latest research, which was a massive study of nearly 81,000
and people who are asked in Anthropics' words to share how they use AI, what they dream it could
make possible, and what they fear it might do. The interview was conducted with Anthropic
interviewer. It's basically a version of Claude that is specifically designed for this type of
conversational interview and research. So I want to talk first about what the study actually found,
and then we'll talk about the various reactions to it. The study was conducted last December,
which it is worth noting that although that is recent by social science standards, it was only at the
very beginning of this transitional second moment, as I've called it, and I'd be really interested
to see this study again, as people fully digest the transformation that's happened over the course
of the last three months or so. The study was truly global. People responded from 159 countries
using 70 languages. As an aside, that leads Anthropic to believe that this represents the largest
and most multilingual qualitative study ever conducted. And at the very front and center of the findings,
and cutting to the quick of why nuance is required as we're having these conversations, is the fact
that people didn't so much divide themselves into different groups, but experienced the full range
of emotions in and of themselves. The way that they framed it, across interviews, hope and alarm
didn't divide people into camps so much as coexist as tensions within each person. Disruption
anthropologist Jasmine's son pulled out this section as well. Anthropic writes, what people want
from AI and what they fear from it turned out to be tightly bound. So let's talk first about what
people want from AI. Anthropic used Claude to break responses into different overarching categories
and found that number one was professional excellence. About 18.8% of the responses around what people
hoped for had to do with professional excellence in some way. Other versions of professional impact
showed up lower on the list as well. Entrepreneurship came in at number seven with 8.7%. And financial
independence, although I think you could argue that that sort of sits in between professional
and personal, came in at number five at 9.7%. More personal goals, however,
were even more prevalent. The number two most common category of response after professional
excellence was personal transformation, representing 13.7% of responses. Life management was just after that
with 13.5%. Time freedom, basically winning back time from professional pursuits and from other
adult constraints towards more personal pursuits, came in at number four at 11.1%. Learning in
growth came in at number eight at 8.4%, which admittedly could be both personal and professional, which is the
same for number nine creative expression, which came in at 5.6%.
Another 9.4% hope for some sort of societal transformation.
Now, what was interesting is that when you dig even into the professional goals,
they often get very blurry, very quickly with the personal.
Anthropic writes, many started the interview talking about productivity,
but after Anthropic interviewer asked about their underlying hope behind it,
what realizing this vision would enable for them, other priorities surfaced.
It wasn't about doing better work, but increasing their quality of life outside of it.
Using AI to automate emails became, in actuality, a desire to spend more time with family.
A white-collar worker in Columbia wrote,
With AI, I can be more efficient at work.
Last Tuesday, it allowed me to cook with my mother instead of finishing tasks.
A freelancer in Japan said, I want to use less brainpower on client problems and have more time to read more books.
Cutting across all nine clusters, Anthropic argues that there are actually three meta-clusters that they all fit within.
They write, roughly a third of visions are about making room for life, more time, money,
mental bandwidth, by using AI to alleviate current burdens. Another quarter revolves around using
AI to help people do better, more fulfilling work, not escaping work, but getting more out of it.
About a fifth are about becoming someone better, learning, healing, and growing, and a smaller
share want to make something, or fix the world. Summing up, they say the nine clusters may look
disparate, but they are underpinned by recognizably human desires. Now, digging into the societal
transformation piece, as sort of this group that feels a little bit apart from the others, even those are
more personal than they appear at first. Anthropic writes,
Those that wanted societal transformation from AI often cited a vision for health care.
People wanted AI to detect cancer earlier, accelerate drug discovery, or enable broad access.
Often these desires stemmed from personal experience of losing family members, living with chronic
illness, or watching loved ones receive wrong or delay diagnoses.
Similarly, in the societal transformation category, the next most common vision was around
transformation of education. Quote, respondents in low and middle income countries were quick
to cite the possibility that AI might break the association between educational quality and wealth.
The point is that across all of these desires, they are very common core human pursuits,
newly expressed through the opportunities that AI represents.
When people were asked then, if AI had taken a step towards their stated vision,
81% said yes, anthropic grouped those experiences of AI delivering into six categories.
By far the most dominant was productivity, with 32% overall saying that it had delivered
productivity gains, the next most common way in which it had delivered,
anthropic called cognitive partnership. Said one academic, it's like having a faculty,
colleague who knows a lot, is never bored or tired and is available 24-7.
Closely related was learning, represented by a student in India who said,
My professor teaches 60 people and won't entertain many questions. I can ask AI anything
even at 2am, including the dumb ones. Other ways in which AI has delivered on their vision
include technical accessibility, research synthesis, and emotional support. Although
notably emotional support was the lowest reported category with just 6.1% of responses.
That might be, though, because emotional support is sort of embedded in the way that AI delivers
in the other areas. For example, one response that was counted in the learning category came from
a white-collar worker in Brazil who said it's much easier for me to learn without being judged,
just friendly feedback. It's harder with friends or family to get that. Now, it makes sense why
Anthropic would classify that as learning, but there is certainly an element of emotional support there as
well. Anthropic wrote that while emotional support comprised only 6% of responses, they were among
the most affecting they encountered. There were many stories they write of people using AI to process grief.
Said one woman, Claude is like a sponge gently holding and catching my longing and guilt
towards my mother. Unlike real people, Claude has unlimited patience to listen to me,
understands my pain and helplessness. And yet in this category, we also start to see the duality.
A respondent from South Korea said, my relationship with a friend became strained,
and I talked more with Claude then, because Claude understood my thoughts and stories well.
But it was a stupid choice. I should have talked with that friend, not Claude. That's how I lost that friend.
It's clear why this is going to be one of the complicated areas for AI. Anthropic writes there is
real ambiguity in how to interpret the diversity of stories we heard, as wins for human well-being,
as double-edged swords, or as band-aids for broader institutional failures. In truth, they write,
it's probably some combination of all three. So what then are people concerned with?
This area of questioning I find super interesting, especially in the context of the larger and ever more fraught
conversation around AI disruption that we're having on a societal level. Are AI users worried about
AI coming to life and X-risk? Are they worried about losing their jobs? Interestingly, Anthropics
said that while the positive visions for AI seemed to come from a few core desires like more time,
more autonomy, and more personal connection, concerns were much more varied but also more concrete.
At the top of the list was unreliability, representing 26.7% of responses when people asked what they were worried about.
Speaking of that duality that we've talked about running through this, this makes intuitive sense in the fact that as people become more reliant on AI,
they understand that the risk of it being wrong or leading them astray becomes higher.
Now, when it came to jobs in economy, they were an important concern as well.
Number two, after unreliability representing 22.3% of worries. A loss of autonomy and agency was number three at 21.9%.
and closely related cognitive atrophy represented 16.3%.
Societal issues were a little bit farther down the list, but definitely there.
Jobs and economy is a hard category to tell how much of that is personal versus societal,
but there were concerns like misinformation, which came up 13.6% of the time,
surveillance and privacy, which came up 13.1% of the time,
and malicious use, which came up 13% of the time.
Existential risk did make an appearance, but it was at the bottom of the list,
representing around 6.7% of conversations.
One really interesting area that I find wildly underrepresented in the larger conversation is a concern
about over-restriction. In other words, excessive safety measures, paternalistic content filtering,
and blocking legitimate use cases. A quote from one respondent in the U.S.,
the threat isn't that AI becomes too powerful, it's that AI becomes too timid, too smooth, to optimize
for avoiding discomfort. Notably, there were also 11% of people who expressed no concern, and while you
might assume those were the Super Bowl accelerationists, they actually just tended to see AI as a neutral tool,
akin to electricity or the internet. They tended to be more confident than their peers that when
problems inevitably arose, they could be solved through adaptation. Now, notably on this list,
you didn't hear a lot of the things that dominate the media conversation. Things like copyright
concerns or risks to kids. Those did show up, but in the long tail. Five percent of concerns were
around bias and discrimination. Four percent were around IP and data rights. Four percent were around
environmental costs. Three percent were around harmed children and other vulnerable groups. And three
percent were concerned around democracy and political integrity. This certainly strike me as the biggest
divergence, either A, between media reporting about concerns and actual express concerns, or B,
and this is something we'll talk about a little bit more in just a minute, the difference between
the concerns of users and non-users of AI. Now, as Anthropics said at the beginning, hopes and fears
were not evenly divided into different camps. They were present together in most people. In fact,
they found five recurring tensions between directly competing benefits and harms, leading to
this idea that what people want from AI and what they fear from it are tightly bound. One is a tension
between using AI to learn and growing so reliant on it that you stop thinking for yourself. Another is
people finding solace in AI, but worrying about AI standing in for human connection. On the productivity
front, people save time on some tasks, only for, as Anthropic writes it, the treadmill to speed up
on others, and of course they dream of economic freedom, while at the same time having fears around
being displaced at work. They did note that across most of these tensions, the benefits
side is more grounded in experience while harm liens hypothetical. For example, they write,
33% of people mentioned AI's benefit for learning, while 17% expressed worry about cognitive
atrophy from AI use. Ninety-one percent of those who mentioned learning benefits said that they
had actually realized those gains in some ways, as opposed to 46% of those who are worried about
atrophy who had seen it firsthand. In other words, basically double the number of people who
hoped for learning benefits had actually seen them than those who were worried about
learning atrophy had seen those effects.
The strongest co-occurrence of light and shade in the same person was around the positive
and negative impacts of emotional support.
Anthropics said that there was actually triple the baseline co-accurrence rate there.
On the other end of the spectrum, they write that the economic mobility tension between
those yearning for economic empowerment from AI and those fearing displacement from it is the
most speculative, with the highest rate of hopes and hypothetical fears.
It's also the area where co-occurrence of upside and downside in experience is weakest.
In other words, people who are actually experiencing a lot of the financial benefits of AI,
are not simultaneously experiencing job displacement.
Now, cutting a little bit deeper here,
economic benefits are definitely accruing to the more nimble.
They write that those benefits skew heavily towards independent workers,
like entrepreneurs, small business owners, and even people with side projects.
They report real economic empowerment
and more than triple the rate of institutional employees.
Interestingly, employees with side projects benefited the most,
with 58% stating some form of real economic gain.
Freelancers, they found, as the most exposed middle.
freelance creatives were the group where the upside and downside most nearly cancelled out.
23% had lived the benefits, but 17% had lived the downside.
As Anthropic puts it, AI is both their tool and their competitor.
Now, I want to talk about some people's responses to the survey, but the last thing that I'll
note is that this once again found similar patterns that we've seen elsewhere, with Western
and developed countries having average or below average sentiment towards AI, and southern
and developing economies, having more above average sentiment towards AI.
Now, interestingly, the two sides of the takes were themselves in some ways, the light and shade opposites of one another.
For some, the methodology itself represented something of a triumph.
Drag AI Labs writes,
81,000 responses is a dataset that actually means something.
What stands out is the methodology.
Using Claude itself as the interviewer at that scale,
removes the interviewer bias problem that kills most qualitative research.
The model can hold a consistent interview structure across 159 countries and 70 languages simultaneously.
No human research team gets anywhere close to that coverage.
On the other side is this take,
represented by Berkeley Haas Professor Abashak Nagaraj who wrote,
I'm very bullish on the role of AI qualitative interviewers,
but all the results from this exercise should have a big asterisk
around what the specific sample is and what it says about AI in general.
Who are these 81,000 users around the world that are responding to this call?
Is this telling us something about how AI is generally perceived?
Or what the 81,000 clawed users think about AI?
We already know that clawed users are likely to be quite different than the
average user on the consumer side, let alone how this selection varies across countries' occupations
and continents. Survey research scholars have written entire textbooks about sample selection,
but I saw very little discussion on this topic or any disclaimers in this report, except for a
paragraph below the appendix. This, I think, is the fair-ish version of the critique. Now, I don't
think Anthropic is trying to hide the fact that this is a survey of 81,000 clod users. They didn't
go to pains to say that everyone should only treat this then as the opinion of clod users,
but they also didn't bury that lead or pretend that this was anything other than that.
In fact, they highlight, at the very top of their tweet thread about it, among other places,
the methodology that had these interviews conducted with the Anthropic interviewer.
The version of this critique that I'm not only less convinced by, but I also think is actually quite pernicious,
is represented by anonymous Twitter user librarian Shipwreck.
They write, I'm sorry, but inviting AI users to share their opinions on AI is going to provide
you with significantly skewed results.
There are some interesting things in here, but it needs to be emphasized that these
are the views of AI users, and it isn't a shock AI users are largely pro-AI. This survey may be useful
for telling you what clawed users think of AI, and maybe you could jump from that to make
broader assumptions about other AI users, but this doesn't really tell us much about broader
attitudes towards AI. So here's my issue with this. On the one hand, yes, absolutely, if we're just
extrapolating out what we should take from this, it is completely reasonable to say that to the extent
that we want to make broader assumptions about AI attitudes, we should perhaps limit the boundaries
of those broader assumptions to other AI users, as opposed to everyone. And I agree with this in the sense
that I would not try to extrapolate general attitudes towards AI from, for example, the percentage
of users in this survey that had a positive attitude towards AI. I don't think those things would hold.
But what's pernicious about this discourse is that it reveals something that is much more prevalent,
which is an implicit idea that somehow the opinions of AI users are less legitimate and less
relevant when it comes to understanding the quote-unquote overall perception of AI, then are the
experiences and perceptions of non-AI users and people who are inherently negative towards AI.
In fact, you can almost see this among many of the AI critics, who basically, without being
so clear about it, are effectively arguing that the only opinions that should matter when it comes
to, for example, making AI policy are the people who are against AI and not using AI.
There is a presumption in many cases of some sort of moral superiority of that position, as though
not having an informed opinion, in some way makes it a more pure opinion. This, of course, is
intellectual nimbism masquerading as methodology critique. And it just doesn't carry water in a world
where billions of people are using AI every week. We are heading into a period where we are going
to be having big, important societal discussions about the role of AI. And I want them to be as
informed as possible. And what's more for any AI critics who are worried that AI users are going to
represent some monolithic, unconsidered mass, just look at for how many people in this study,
real concerns coexist with the real feeling of opportunity. Now, obviously, I don't want to be
guilty of what I'm critiquing and paint with too broad a brush. There are plenty of AI critics
who are not trying to discount or dismiss and disenfranchise the opinion of billions of AI users.
But I do find this sentiment, this dismissal, for example, of this type of study, as illegitimate
because it is of AI users, it's more prevalent than I'd like. Just something to keep an eye on as we go
deeper into these conversations. For now, though, I think it's a really fascinating study. I think
the implications of being able to interview 81,000 people in a week are super cool and go way beyond
just figuring out what people think about AI. And I'm excited to see what Anthropic do next with their
interviewer. For now, however, that is going to do it for today's AI Daily Brief. Appreciate you
listening or watching as always. And until next time, peace.
