Is AI Turning Us All into the Same Person? | Sandra Matz | TED
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TL;DR
Sandra Matz discusses the impact of AI on human decision-making, emphasizing the risk of becoming unoriginal and the importance of balancing exploration and exploitation.
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People worry about AI for all kinds of reasons. It's polarizing, it spreads misinformation, it's coming for our jobs. And those are all good reasons to be nervous. But what really keeps me up at night is something else. Something that feels more personal and perhaps even more concerning for the human experience itself.
I worry that AI will make us boring. You, me, all of us. That's because the more we outsource our decisions to AI, the more we surrender something deeply human. Our capacity to explore,
to take risks, to stumble into the unknown, and sometimes surprise even ourselves. I worry that without the potential for discovery, for serendipity, we risk becoming more shallow and unidimensional versions of who we are and who we could be, not just as humans, as individuals, but as humanity.
Now let me make this idea a bit more concrete and take you somewhere perhaps unexpected, but also totally relatable. Imagine walking into a Baskin-Robbins. What you'll see is an illustrious assortment of 31 different ice cream flavors.
There's chocolate chip, pistachio, almond, lemon sorbet, and many more. You're now facing a difficult choice. Are you going to go with an old favorite, chocolate maybe, or are you going to take a risk on something funky and new, like wild and reckless sherbet?
And yes, it's a real flavor. (Laughter) The choice you're facing is a classic human dilemma scientists call the exploitation- exploration trade-off. Are you going to play it safe and capitalize on what you like, or are you going to take a risk
with the hope of finding something even better? And our lives are full of these trade offs. Stick with your favorite restaurant or try the fancy new spot on the corner. Keep your usual haircut or ask for something new and edgy. Stay in your stable job or finally try to become a pickleball champion?
(Laughter) We all differ in our appetite for exploitation versus exploration. But we're also all hardwired by evolution to strike a certain balance between the two, because for our ancestors on the African savanna,
the trade-off was pretty simple. Stick too closely to what's safe and you risk starvation when the grove runs dry. Stray too far into the unknown and you might get poisoned or eaten by lions. Luckily for you and me, the trade offs we face today are far less about survival.
But our choices are still governed by this instinct to balance caution with curiosity. If all you ever did in life was play it safe and exploit, you'd never get disappointed, but you'd also never get a chance to advance and grow.
If all you did instead was discover and explore, you'd collect endless experiences, but you'd also never get a chance to capitalize on your learnings. So it's really this balance between exploitation and exploration that fuels our growth,
not just as a species, but also as individuals. But that's exactly where AI throws a wrench into the works, because AI hates risk. And that's not because of its algorithmic DNA. It's because the systems we rely on to navigate our world,
from Spotify to Netflix to ChatGPT, are overwhelmingly trained to optimize for exploitation. Or more specifically, for short-term engagement and satisfaction. Did you click the link, watch the video, like the song? If yes, AI gets a clap on the shoulder.
If no, it gets a slap on the hand. Risk, discovery and exploration are simply not part of their programming. Think back to Baskin-Robbins. If 60 percent of people preferred the flavor pralines and cream, then that's what the AI is going to recommend.
It's not that AI lacks imagination. It lacks incentive. Safe bets protect against disappointment, which in turn reduces customer churn. So instead of taking this risky gamble that helps you explore, companies tend to err on the side of exploitation
when training their AI systems. And to be clear, there's nothing inherently wrong with that. I've spent the last 15 years as a computational social scientist working at the intersection of psychology, computer science, and business. And I know that rewarding AI in that way can be extremely valuable.
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