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From those talks, we bring you speakers and ideas that will surprise you. just don't know what you're gonna find challenge you we truly have to ask ourselves like why is it noteworthy and even change you i literally feel like i'm a different person yes do you feel that way ideas worth spreading from ted and npr i'm manoush zamorodi On the show today, what happens when we become obsessed with predicting the future?
It was the FIFA World Cup in Doha, Qatar.
So it was in November, which means my students were here.
They were in our workroom and they were huddled around a laptop.
Brendan Dwyer is a former football coach and now a professor of sports leadership.
He's at Virginia Commonwealth University, which is a financial supporter of NPR.
On this day, his students had bet on a game, but not the way Brendan expected.
They were watching Morocco and Belgium, which is a very unconventional game for these students to watch, because they weren't from Morocco or Belgium.
But these students were like enthralled by this game.
And as the game was going on, More students were starting to gather around.
And it was not a knockout round game.
It was really not a semi-final or a final.
It was an interesting game, but we're talking second half.
It's not the last couple minutes.
But each moment, they were yelling and screaming and getting upset.
I found that they were getting upset mainly at the referee, more than they were getting upset at a missed shot or a missed pass or a missed play by one of the players.
Okay.
That's when it was like, what are you guys cheering about?
And they mentioned that they weren't betting on the outcome of the game.
They were betting on the number of corner kicks.
In other words, they weren't cheering for either team specifically.
They were just hoping to see more corner kicks because they'd put money on it.
So every time the referee awarded a corner kick or did not, they reacted a certain way.
And that was hilarious to me and also at the same time got me a little caught off guard because I've never seen one.
I didn't realize you could bet on the number of corner kicks at that point.
And two, the fact that these students were so enthralled not by who's going to win a World Cup game, but corner kicks.
And the students won.
They picked the over and they won the over.
What Brendan saw with his students watching the World Cup were the early signs of an exploding marketplace.
You know, this is a growing trend.
In sport fandom, we're not just watching the wins and losses.
Now we're watching an additional game within that with the sports betting apps and now with the prediction markets.
We can always find a way to up the ante.
It's not just sitting back watching the game for, you know, the beauty of the game.
You want to make every game interesting?
Step one, open the BetMGM Sportsbook.
From sports betting.
Kalshi!
Kalshi lets you legally trade on anything.
To prediction markets.
Prediction is literally what computers do.
Prediction. is intelligence.
To tech CEOs who make grand statements about how AI will inevitably shape society.
By the end of 2028, more of the world's intellectual capacity could reside inside of data centers than outside of them.
Forecasting the future has become a national pastime.
But what do we lose when we model, price, and place bets on our future?
Today on the show, predictions.
Why humans have for millennia tried to anticipate what's next and how money and financial incentives change our experiences of the here and now.
So back to Brendan Dwyer.
He has spent the last two decades studying sports fans and their habits around sports betting, which had been illegal in most US states with some key exceptions.
Some sort of sports betting has been around in the United States forever.
Whether it's been legalized or not.
You know, there's been at a bookie or it's been in a bar, Las Vegas or New Jersey.
Horse racing.
That would kind of get close to sports but weren't really the traditional sports betting as we know now.
The money lines, the parlays, all the fun, interactive apps that make it scarily easy to bet.
With the internet came the dawn of online fantasy sports leagues.
As fantasy sports became more popular in the early part of the 2000s, it started to knock down our preconceived notions about risk and reward and interactivity of fan engagement.
You put money down at the beginning of the year.
You compete against your friends and family and you may get money back out in.
If you're talking about football, you put money down in August.
You may get money back in January if your season long fantasy team plays well.
And through a number of tests, they realized this is probably not gambling.
So it got a carve out from a number of gambling laws across the country.
For two decades, state and federal regulators battled against online betting platforms.
Then they found themselves in a new fight, as these platforms started offering daily opportunities for fans to bet on fantasy leagues.
And it changed the narrative on our broadcasts, where people were talking about daily fantasy sports, talking about odds.
But most importantly, it really kind of tested the water from a consumer perspective, a cultural perspective.
And we found out that our society had a bit more of a favorable association with betting.
Was this gambling?
How stringent should laws be?
The debate and legal battles continued all the way up to the Supreme Court in 2018.
Brendan Dwyer explains from the TED stage.
A brief history.
So in 2018, the Supreme Court struck down the federal ban on sports gambling.
Since then, 37 states, plus the District of Columbia, passed laws where we can bet on sports.
Since he gave this talk in 2025, two more states have joined that list.
That has been huge for the betting industry.
The American Gaming Association estimated, in 2017, just under 5 billion was spent on sports betting, primarily physically in a casino.
In 2024, that number was $150 billion, 95% of it online.
The sports betting industry has become its own economic engine, transforming the DNA of the sports fan along the way.
You study sports consumer behavior, basically sports fans, how they respond.
But that has changed since 2018.
Talk us through this big Supreme Court decision and how it relates to sports betting today.
Yeah, the change and deregulation of sports betting and allowing the states to make their own laws and allowing, at this point, close to 70 of Americans to legally bet on sports, has fundamentally changed the sport industry.
You know, now sports fans, at the tip of their fingers through their phones, can bet on pretty much anything as it relates to professional sports, college sports, and has driven a lot of money into the sports industry.
It has changed the way sports is broadcasted, the way we watch it, and ultimately how fans behave.
I have to say, I didn't really pay attention.
I don't think many people who aren't into this world even knew.
How big a deal was it?
For people in the sports industry, it's a huge deal.
I mean individuals like Mark Cuban, the owner of the Dallas Mavericks.
He's gone on record to say it double the value of his franchise because of sports betting.
That's how much money and interest and focus sports bettors put on sports, sport consumption, because they watch games longer, they watch more sports, they watch pre-games and analysis, which all of that drives media contracts, it drives advertisement and that is the real fuel of the sport industry.
Is that a bad thing?
I mean, we could all use a little pleasure these days.
When does it become problematic?
Well, the economist in me that wants my students at VCU to find jobs, I like that there's more money in the sports industry.
But from a sports purist and someone that worries about problem gambling of certain populations, I do worry about how the transactional nature works of sports, because of sports betting is changing not just how fans interact with sports betting, but also how it is portrayed and how it's potentially changing decisions within the sport.
Right now we are over-sponsoring, we are over-advertising, we are targeting specific groups.
I think all of that is going to have to change because as more research comes out in all sorts of fields addiction problem gambling, or it's even marketing and advertising a lot of the research is consistent in that you can't continue to target specific groups and advertise this much without providing safety nets.
It's not done in any other part of the world the way we're doing it right now.
When did the rise of prediction markets start to happen?
They turn everything from the weather to political debates when they turn regular life into a sport.
Can you sort of trace that back to that 2018 Supreme Court decision?
Do you think they're related?
Yeah, I think they're related are very interesting phenomena in that they kind of combine a lot of different things.
I think sport has probably made them more commonplace.
Legal sports books have try to get them shut down because they're trying to protect their service.
So I think, as it relates to sports um, It has taken off because there are still a number of states that don't have legalized sports betting, including California and Texas.
Some very large states with lots of people.
Most states, you have to be 21 to bet.
And so there are gaps in the marketplace that prediction markets fill.
And it's also unregulated.
It's peer to peer.
There's no house.
So there's just a lot more opportunity in the prediction market for individuals that are looking to monetize their perceived ability as a sports fan and don't feel like they want to live in the environment of a sports book.
I think trust is an issue with sports books.
These are the platforms that offer the bets, the parlays and all that.
There's always going to be trust issues with them, because there's going to be a belief that they didn't set the lines properly and that they're making too much money.
And when there's trust issues, people are always going to try to find an alternative way to make money.
When we come back, we'll dig into Brendan Dwyer's research about which sports fans are betting responsibly and which ones are getting carried away.
I work with 18 to 24 year olds on a daily basis and I worry about their decision making for anything they do.
They have overconfidence and regulation issues to everything.
And so when you add overconfidence. and sports, and money, it worries me even more.
Today on the show, the pull of predictions.
I'm Manoush Zomorodi, and you're listening to the TED Radio Hour from NPR.
We'll be right back.
It's the TED Radio Hour from NPR.
I'm Manoush Zomorodi.
Today on the show, we are looking into the pull of predictions.
And we're talking to Brendan Dwyer, who has spent 20 years researching sports gambling and the sports fans who do all that betting.
Who are these individuals from a consumption perspective?
How do they compare to general sports fans?
What are they watching?
How much are they watching?
What do they look like from a fan perspective in terms of loyalty, involvement?
It's really trying to establish a baseline, because in our field there really wasn't any academic literature on loyalty, what the American sports better look like.
Tell me what you found.
Well, I mean, there are all sorts of different sports bettors.
They consume at all different levels.
As your involvement, which is an attitude, not necessarily a behavior, as your cognitive involvement, so your attachment and then your emotional involvement increases the more you consume everything.
And so we see sports bettors from the lowest level that are consuming more than non-betters.
But then those that are at the highest level, The ones that consider themselves almost predictive analysts, are consuming so much sport because they want to find that edge.
Sports bettors are not disengaged.
They're overengaged.
And those highly involved sports bettors, they are part spectator, part day trader.
The scoreboard is no longer where you put the final result.
It's a balance of open bets.
Now we have games sometimes starting at 9 a.m. and ending at 2 a.m.
That means the book is always open, creating a perpetual loop of deposit, wager, outcome, repeat.
And when loyalty, attention and money become so intertwined, so do the incentives at every level the league, the team fans, even the athletes.
The question isn't whether sports betting enhances engagement.
It clearly does.
The question is what type of engagement is it?
My students would later tell me they remember the corner kicks.
They don't remember who won the game.
It was Morocco, by the way, 2-0.
And that is the trade-off.
We've quickly monetized sports. the moment, and we've lost the meaning in the process.
Is there something kind of sad about that?
Does the former football coach in you feel sort of bereft at that statement?
Well, I think it's sad in a couple different ways.
I think this is an issue for our entire society, but I don't like seeing people at sporting events in particular, but even when they're watching sporting events with their friends staring down looking at their phones, because it is a shared experience.
You should be enjoying the moment and the opportunity together to watch your team play and talk about what is occurring.
So that's one aspect.
And then yeah, I do think we are seeing our athletes as more of a chess piece or a machine to achieve a goal, as opposed to a player on a team, and that team is trying to achieve a common goal.
So yeah, as a former coach and person who loves sports, I think it does take away from something that sports was not meant to be.
I'm thinking just of my own family my husband son, big Knicks fans, and they watch the game because it is an emotional roller coaster.
There's no money down, but I can imagine that I would be concerned if that then turned into something more.
I have a knack for this and this can be financially remunerative for me.
Well, I guess I could start out by saying pretty much any sports fan thinks they know more about sports than everyone else.
So I think you know, especially when you talk about 18 to 24-year-old males, they have a built-in level of confidence about a lot of things, but in particular about sports.
It is also at a time in their life where, for a lot of them, money is important to them and they oftentimes do not have a lot of it.
From what we found in our research, they see betting as an opportunity to make money.
And it's that combination of overconfidence and impulsivity of younger individuals that is troublesome.
It's really more evident in younger people than older people.
And older people we found in our research, are more rigid, which also comes with challenges in terms of changing their perceptions and their behaviors towards betting.
But I think majority of sports bettors are very responsible bettors.
Oh, really?
They are?
I think they're irrational, but I think in terms of the amount of money they spend, they have it under control for the most part.
But the younger individuals overconfidence and impulsivity.
If their belief in sports betting is an opportunity to make money is really a challenge.
Do the words matter?
Like if you said to a young person who's into sports betting you know you're gambling would they push back on that?
Would they say absolutely not?
No, I think they enjoy the risk.
Another study we have conducted found that risk plays no role in their decision to gamble.
If they know it's more risky, that's not going to make any impact on their decision.
I work with 18 to 24 year olds on a daily basis.
And I worry about their Uh-huh. because it's not just like going to Vegas.
If you go to Vegas and you play specific games, there is some skill and luck.
If you play blackjack, if you play poker craps.
There's more skill in those games than if you play roulette or a slot.
Those are more luck-based.
In sports, you can have a much higher perception of the skill.
You think you are smarter, you know more.
And that enhanced illusion of control is what we call it, can be detrimental.
I love that phrase, enhanced illusion of control.
I think nobody feels like they have any control over their lives right now.
Do you think that that might be what's driving some of the growth of sports betting and prediction markets in general?
Is it just wanting to have fun and get away from the world, or is it...
Trying to feel as though you can get a grip on what is going on, especially when the economy feels so unpredictable.
That's a very good point.
There is a feeling of wanting to have a stake and control in a certain situation that feels uncontrollable.
And this has been a growing trend really since the late 90s, early 2000s, when fantasy sports really took off as an activity where it went from being a few hundred thousand people playing it to millions.
Hmm.
People didn't want to just be a passive fan anymore.
They didn't want to sit on the couch and watch a game.
They wanted to have increased action so that there is a game going on within the game and they're actually pulling the strings of that game within the game.
Now we have betting in all the different ways.
You're right in that.
This gives me confidence, some active participation in something that I have zero control over.
And there are a lot of things in our life right now that we kind of feel like we're just sitting in the passenger seat.
That was Brendan Dwyer.
He's a professor and director of research at the Center for Sports Leadership at Virginia Commonwealth University.
You can see his full talk at TED.NPR.org.
Today on the show, we're exploring why humans have such an insatiable desire to predict the future.
We're always wondering about what can go wrong and we are up at night, you know, millions of us thinking am I going to have a job?
Am I going to be okay?
Is my family going to be healthy?
And so on and so forth.
This is Carissa Veliz.
I'm an associate professor at the Institute for Ethics in AI and I'm the author of Prophecy.
Carissa is investigating two things.
Our willingness to turn to AI and ask it to model and predict everything from our health to business outcomes.
And how the CEOs running those AI companies insist their products are inevitably changing the world.
Do those predictions just become a self-fulfilling prophecy?
And are we forfeiting our own agency and our willingness to believe them?
She says.
These are questions that philosophers have been asking for thousands of years, from oracles in ancient Greece to court astrologers in the Middle Ages.
Yes, as the story goes, King Louis XI had an astrologer in court.
And one day the astrologer predicted that a lady of the court would die within a week.
And she did.
So Louis was really rattled because he figured that either the astrologer had actually murdered the woman just to prove his accuracy and impress people, or he could actually see the future, in which case he could threaten Louis himself.
What if he saw the end of Louis?
So the king decides that the astrologer has to be murdered.
And he gives his servants the order that, upon his signal, they are to throw the astrologer out the window to a certain death.
When the astrologer comes to meet Louis, the king asks him one last question.
He says, given your prophetic abilities, tell me how long will you live?
And the astrologer, not missing a beat, replies, I will die three days before your majesty.
And Louis, go figure, never gives a signal.
I mean, it is an ingenious answer.
Very smart astrologer.
Very, very smart.
So, having heard that story, how do you tie that to artificial intelligence and the era in which we are living in now?
What the story suggests is that predictions are not always quests for knowledge or hypotheses, as we usually associate them with.
Sometimes predictions are quests for power, and I don't think the astrologer found his answer in the stars.
I think he understood the power of prediction and he used it in a very clever way to get himself life insurance.
And when you think about AI, you realize that the kind of AI that we're using machine learning is nothing but a prediction machine.
What it means is that it uses data from the past and projects it onto data it doesn't have.
And I think that we haven't fleshed out the implications of that, because if predictions were only about knowledge, then OK fine, this is a scientific endeavor.
But they're not.
And one very basic reason for why they're not is that predictions are never facts.
They can be educated guesses, they can be power plays, they can be wishful thinking, they can be estimates.
But the future is unwritten and facts belong to the past.
Even though we tend to associate prediction with knowledge, I'd like to invite you to consider the possibility that most of the predictions that you encounter in an everyday setting are closer to the realm of power than that of knowledge.
Carissa Valiz continues from the TED stage.
It might seem that the days in which we sought astrologers and soothsayers to tell us about the future are very distant, but often we use AI as the new Oracle of Delphi, and tech executives whisper in the ears of our leaders much like court astrologers used to.
Granted, the technology is different, but the political role is not.
Predictions are often power plays in disguise.
They justify value-laden decisions under the pretense of facts.
Better understanding.
Prediction matters more than ever because we're relying on forecasting more than ever with AI.
And based on how we talk about prediction, we're being much too naive about it.
But AI is science, you might think.
It's cutting-edge technology, right?
Well, it depends on the kind of AI and how we use it.
AI can be a great technology to make predictions about molecules in the search for new antibiotics.
But predictions about human beings are fundamentally different than those about things.
Predictions about the weather don't influence the weather.
Predictions about people influence people.
Social predictions tend to act like magnets.
They bend reality towards themselves.
They affect the reality they purport to predict.
So let's explain a little bit more just if people are uncertain about how AI is built on prediction.
In that these models have digested basically the entire Internet and they're looking to what people have written previously, how they've constructed sentences words ideas, and then simply replicating that information when we ask them a query.
When it comes to LLMs at least,
That's exactly right.
The large language model outputs a likely response.
And many people think that it's a response that's likely to be true.
But that is actually imprecise.
It's a response...
That is likely to have been given by a person, had you asked a person, and likely to have been accepted by another person.
Because the way these models were trained was with human beings.
So they would suggest two answers to a human being, and then a human being would prefer one of those, and then the model would learn what human beings prefer.
But as we well know...
Sometimes human beings don't prefer the truth.
We prefer good stories.
And so the models are not trained to track truth.
Can you tell us more about some of the use case scenarios you're seeing where AI is being used as a forecasting tool in terms of trying to predict human behavior that you think is dangerous?
Yeah.
So insurance is one very important one.
And we're going from population level predictions, as in how many people in 10 million are going to get diabetes, to individualized predictions.
Is this person going to get diabetes?
And that... is much more dangerous because it creates self-fulfilling prophecies much more easily.
Because, for example, if I predict that a person is going to have bad health and then I put his insurance premium up, that in itself might lead to more stress, which leads to worse health.
So I affect that person very directly.
Human beings are so suggestible.
And we can be so stressed out by circumstances that corner us.
And the whole point of insurance is to pool risks such that the unlucky don't have to burden their unluckiness alone.
So another use case is giving out any kind of opportunity.
So using AI for giving out loans, for giving out jobs, for deciding whether somebody should have an apartment, for making decisions in the justice system having to do with bail or with sentencing.
And as far as I can tell, we are using AI pretty much in every sphere of life.
The argument that I hear with many of these examples actually is well more information is good information.
And so why would we not look to the past and look at trend lines and the data, so that we can make better choices going forward?
Essentially, we are reducing people's capacity to defy their odds.
If you take into account that predictions are not facts, arguably they don't count as information.
The second point is that when you're looking for a needle in a haystack, if you add hay to the haystack, it doesn't help.
So no, more information is not always relevant and it's not always helpful.
And the third thing is it depends on how we use that data.
Do you think people say that there are ways to check for algorithmic bias and make sure that the modeling gives us decisions that reflect a world that we want to live in, not necessarily one that we have lived in?
One of the problems is that if you don't have equality in the data set, there is no way to come up with an algorithm that is not biased.
If I deny you an opportunity on the basis of a clear criteria either it's a loan or a crime, or bail or something.
If I deny you a loan because you don't have X amount of dollars in your bank account, or I deny you bail because
You committed X crime.
Those are contestable facts.
We can argue about them.
If I'm wrong, you can challenge me.
But if I deny you an opportunity on the basis of a prediction, how are you going to challenge that?
Because a prediction is not a fact.
So how are you going to prove to me that you will pay the loan or that you are safe?
You can't.
And so, when we use predictions to make important decisions, what we are actually doing is creating literally a Kafkaesque world in which we are ruled not by principles, not by criteria that are transparent contestable, not by due process, but by statistical pattern matching against which there is no argument.
In a minute, Carissa Valiz weighs in on whether our AI future really is inevitable.
On the show today, predicting the future.
I'm Manoush Zomorodi, and you're listening to the TED Radio Hour from NPR.
We'll be right back.
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Now back to the show.
It's the TED Radio Hour from NPR.
I'm Manoush Zomorodi.
On the show today, predictions.
And we were just talking to philosopher Carissa Valise about how AI is already quietly shaping our lives.
But what about the people who are building these AI models?
Many technologists tell us we need to prepare for a future where AI is integrated into every aspect of our world.
Is that kind of forecasting just business people promoting their products?
Or are they trying to will us into this future?
A kind of predictive power grab?
It's both.
And it's fine.
You know it's fine for business people to try to market their product and try to sell you the idea that the future is their product, as long as we're clear on what's going on.
But what worries me is when one of these tech executives says oh, this is what the future looks like and it's inevitable.
And then every newspaper publishes it as if that's a fact.
When a tech executive says that in the future, we will use AI for everything and everywhere, he's trying to get you to act in a way that will fulfill his vision of the future.
And when you believe that prediction as if it were telling you something about the future, When you give in to the fear of missing out and you go and you buy the AI and you contribute to the self-fulfilling prophecy, what you are actually doing is obeying.
Have you noticed how often People who make predictions about technology say that the future they are describing is inevitable?
That's a red flag.
Those predictions are designed to act as conversation stoppers.
They're telling you, don't question me, just accept what I'm saying as a fact.
I'd like for this talk to be a conversation starter.
I hope it'll persuade you to ask more questions.
One example that brings me a lot of joy is Mark Zuckerberg trying to sell us the idea of the metaverse.
We believe the metaverse will be the successor to the mobile internet.
It was like 2020, 2021, Mark Zuckerberg pivoted Facebook to be the VR company, right?
He was so confident in VR.
Zuckerberg told us that in a matter of two or three years, everybody will be living in the metaverse.
Thankfully were not.
And it shows how he was trying to market his product.
And what I would like people to hear when one of these executives says something like that is oh, that's a prediction.
Who is this guy?
What are his financial incentives?
Is that a future I want?
And if not, what am I going to do to make sure that my life looks nothing like that?
I guess the difference with AI versus the metaverse is like people didn't really see the use case for the metaverse.
It just seemed sort of like I could take it or leave it.
It didn't add any value to my life.
But with AI, there are some tools that are genuinely useful.
Is that?
Why do you think it might be harder for people to parse the sort of dangers versus the efficacy of AI that's being sold to us?
Well, I'm not sure.
I think AI is harder to fail because we've already embedded it in so many products and in so many ways.
However, what I would like us to be more aware of is that it really matters how we use AI, that AI is a kind of an empty.
So, for example, one of my favorite uses of AI is for finding molecules and new antibiotics and developing new materials.
I think that's a great use of AI.
And even though it makes a lot of mistakes, you have people checking whether that molecule actually works as an antibiotic or whether that molecule will actually be an interesting material.
But when I predict that somebody is going to be a bad employee and therefore I don't hire them and nobody wants to hire them because everybody's using the same AI then of course that person will not have a job.
And the company that is providing the AI will say, oh, look, my AI is 99.9% accurate.
But at what price?
Because it may be creating the reality that it's purporting to predict.
This reminds me of your previous work where you've looked a lot into digital privacy.
And I wonder if you feel that the sort of personalization of technology, this sort of sense that the tech knows you better than you know yourself, has created a little bit of an imbalance that we are constantly.
Thinking of the individual as opposed to the greater good because of this emphasis on me, the user.
So one of the reflections in the book is how the machinery of surveillance exists to be at the service of the machinery of prediction.
So we only collect all of this data and watch people because we're trying to figure out what they're going to do next and we're trying to influence that.
And that's not that different from being in the savannah thousands of years ago and have a lion looking at you because it wants to know where you're going to go next so it can pounce on you and eat you.
It's the same principle.
But some people would say, well, OK, so I log into Amazon and it knows that I need more detergent.
I'm grateful for that prediction.
Do you find something dangerous or sinister in that?
Well, no, if it's only that, but it's never going to be only that.
And part of why predictions work online are true is because it's easier to determine the future than to predict it.
So, for example to give an extreme example just to illustrate the point if I want to be absolutely sure of where somebody is going to be tomorrow, the easiest thing to do is to jail them, because that way I will know where they're going to be.
So when the online world influences our views in a way that makes it easier to predict our behavior, we are paying a cost in autonomy.
And when it comes to detergent, that's not very important.
But when it comes to who you vote for and who you meet online and what you read and what you think, that becomes pretty important.
Where does religion fit into this conversation?
Because it used to provide a sense that something is preordained or there is someone looking out for your future.
Is that true part of what you are seeing when it comes to why technology has such a hold on people that it's filling this sort of gap that there used to be in our culture?
That's one interpretation, and an interesting fact to think about is how, even though greeks were very advanced in mathematics, they never developed the concept of probability mathematically.
And one hypothesis is that they were so convinced that there was such a thing as fate and that gods determined your fate that it just didn't make sense.
You couldn't even think that, thought that there could be mathematical probability, because it just doesn't square with faith determined by gods.
And what I'm seeing more these days, which concerns me quite a bit, is attributing religious or magical or supernatural abilities or properties to algorithms.
People thinking that God can express himself through algorithms or algorithms having this magical quality of guessing things and knowing things.
And And one observation that just chilled my blood when I reread it is from Hannah Arendt, who makes the case that when people are subjected to very random and incomprehensible bureaucracy, they start to have magical thinking to just make sense of it.
And I think that's what's happening to us.
We are so alienated and so yeah, kind of feeling like Joseph in the trial in Kafka's The Trial, that we're starting to attribute magical qualities to the algorithm, just to feel like we are living in a world that still somehow makes sense.
So what do we do?
I hear the word agency said a lot right now.
We need to take back our agency.
Is that the word you would use?
And how do we do it?
Yeah, I like that word.
In philosophy, we also talk about autonomy.
And in a way, our current situation looks a lot like ancient Greece and ancient Rome, in which there was a very strong culture of divination.
And philosophy was born out of that culture, in opposition to that culture of myth and divination, as a voice of reason and agency.
And just like poison, ivy tends to grow near jewelweed and jewelweed tends to be an antidote to poison ivy.
Even though ancient Greece gave us the obsession with the future, it also gave us philosophy to face it.
And I think we need to step up and learn from the past The future is unwritten.
Nobody knows the future.
And if you go around asking people, tell me what the future is, which is essentially a kind of tell me what to do, because I don't know what to do and I'm scared.
Eventually someone will take you up on it.
And whether that person has your best interest at heart is questionable.
But, more importantly, they don't know what the future is either, because it's not written.
And we should change from the mentality of oh, I need to know what the future holds, and kind of unveil this written script, which doesn't exist, to.
I need to build the future that I want to live in, because otherwise somebody else is going to build a future for me.
That was Oxford University philosopher Carissa Valise.
Her book is called Prophecy, Prediction Power and the Fight for the Future, from Ancient Oracles to AI.
You can see her full talk at TED.com.
So, with predictions surrounding us online, in the news and in our pastimes, are we losing our tolerance for uncertainty?
Yeah, and that's why I think so many people are feeling anxious and unmoored.
This is Simone Stoltzoff.
I am a journalist and author and I just published the new book How to Not Know the Value of Uncertainty in a World that Demands Answers.
Simone has spent the last few years talking to experts about balancing what you can know about the future with what you'll never know about the future.
When we are certain about some facets of our life, it makes it easier to hold uncertainty in others.
And so the implication here is that if you find your anchors, find the things that will hold true amid all that is changing around you, it becomes easier to hold the uncertainty as well.
And when we look at uncertainty, We are biologically wired to fear it, to make it cause discomfort.
But that isn't the full story.
Uncertainty can also be the birthplace of possibility.
It can be where new opportunities arise from.
I like to think about like an artist or a entrepreneur or a scientist.
Anyone who is creating revolutionary work has to be comfortable getting to the threshold of what they know and persist nonetheless.
Simone spoke to people who tried to find that balance between certainty and serendipity, like a guy named Max Hawkins who found he needed to purposefully force himself to experience the unknown by engineering it into his life.
Yeah, I mean, Max is a fascinating character.
So he studied computer science and art in college and then got his dream job at Google, moved out to the Bay Area and had been working for a few years and then started feeling this maybe familiar feeling, which is that his life started feeling like a series of rinse and repeat days, like he was acting out a script again and again, and again.
When I lived in San Francisco, I would wake up right at 7 am and immediately go to my favorite coffee shop.
Here's Max Hawkins on the TED stage.
And I would drink my coffee and get onto my bicycle and ride into work.
And I optimized my schedule to be perfect.
And so, in order to get outside of his bubble, outside of his comfort zone, he did something rather extreme, which is he started designing different algorithms to infuse randomness in his life.
The first thing that he did was he designed an algorithm that would call an Uber to his house and bring him to a random location in the city that he didn't know.
And I was hooked.
I started using this app to go to all different places in San Francisco.
I went to museums randomly, random grocery stores, random bars, random bowling alleys, random florists.
And I started discovering that there was an entire side to San Francisco that I had been ignoring because of my preference.
And at the most extreme example, he quit his job and designed an algorithm to choose where he lived.
And it sent me all over the world.
Taipei, Taiwan, Mumbai, India, Dubai.
And every time I would go to a new city I would do the same sort of stuff I was doing in San Francisco go to random events, meet random people.
And I lived there for two to three months and then asked the computer again for the next location.
I did this for two years.
And did it work?
Did he love it?
I think it worked to a certain extent, but there were also diminishing returns.
So I spoke to this psychologist about Max's situation.
The psychologist's name is Mikel Duga.
He was one of the first people to link intolerance for uncertainty with mental health anxiety disorders.
And what Dugas told me is that when people are particularly intolerant of uncertainty, he sees one of two behaviors.
One is they become obsessive information gatherers.
The other extreme is people become extremely impulsive.
So I went into Max's story and when I went down and spent time with him in LA, thinking that he was able to tolerate uncertainty better than any of us,
But I came away thinking that maybe by outsourcing your decisions to this algorithm, it's just another way of avoidance.
It's another way of not necessarily taking responsibility for the choices of your life.
Yeah, I think that's a really good point, that it's almost like you wrote, that you wondered if having a computer algorithm make his decisions wasn't actually freedom, but it was just a different kind of trap.
And Dugas argues that there's actually a middle path that is a little bit more adaptive.
But I do think it's instructive.
If you feel like you've had too many of these rinse and repeat days, what might you do to microdose uncertainty?
Maybe you take a little different route to work or you go to a restaurant that you've never been to.
And through exposing yourself to that novelty, you not only discover more about yourself, but you're training yourself to be able to to be more tolerant for uncertainty in the future.
So what role does prediction, healthy prediction, have in your view?
Like how do we balance the very real possibilities with this inability to ever really know what's going to happen?
So, rather than having very fixed goals or having a certain idea of my 10-year plan, I try to treat my life a little bit more like a prototype, like an experiment, and try to approach the uncertainty in my life with curiosity instead of fear.
There's this idea from Buddhism that I really like, which is to focus on the next right action.
When we're faced with uncertainty, I think it's really easy to loop through all of the worst-case scenarios or all of the logistical and emotional ramifications if things don't go our way.
But rather than worry about all of those next steps, how might you try to stay grounded in your sphere of influence, of what you can control right now?
It's incredibly disempowering to have a fixed idea of exactly how things will go, because that robs you of the ability to shape it.
And so that's something I come back to again and again.
I actually don't want a predictable or a certain future.
I want to be able to influence it myself.
That was writer Simone Stoltzoff.
His book is called How to Not Know, The Value of Uncertainty in a World that Demands Answers.
Thank you so much for listening to our episode.
It was produced by Phoebe Lett and Katie Monteleone.
It was edited by Sanaz Meshkenpour and me.
Our production staff at NPR also includes Fiona Gearan, Matthew Cloutier, Harsha Nahada, Rachel Faulkner-White, James Delahousie and Avery Keatley.
Our executive producer is Irene Noguchi.
Our audio engineers were Hannah Glovna and Tiffany Vera Castro.
Our theme music was written by Ramteen Arablui.
Our partners at TED are Chris Anderson, Helen Walters, Roxanne Heilacht, and Daniela Ballarezzo.
I'm Manoush Zomorodi, and you've been listening to the TED Radio Hour from NPR.
