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These are the tech CEOs young people trust most and least when it comes to AI

The finding was part of a poll conducted by CNBC with Generational Lab. Participants aged between 18 and 34 were given the names of nine tech leaders and asked whether they trust them to act responsibly on AI. Read Entire Article

These are the tech CEOs young people trust most and least when it comes to AI

A recent study conducted by CNBC and Generational Lab has revealed that young people, aged 18 to 34, have a significant lack of trust in tech CEOs when it comes to AI. The poll asked participants to rate their trust in nine tech leaders regarding responsible AI actions. Satya Nadella, Microsoft's CEO, was the most trusted with 35% of the respondents believing in his intentions for AI.

Sam Altman, CEO of OpenAI, came in second with a 31% trust rating. Elon Musk, Mark Zuckerberg, Jensen Huang, Sundar Pichai, and Dario Amodei rounded out the top ten list, all with trust ratings lower than 30%.

The study highlights the growing unease among younger individuals regarding the actions of these tech giants. Palantir, with Chairman Peter Thiel and CEO Alex Karp, received the lowest trust ratings of 21% and 19%, respectively. This is due to Palantir's involvement in various controversies connected to AI, such as aiding US immigration authorities and providing AI-powered military targeting systems to the Pentagon.

Additionally, the poll found that 45% of young people believe AI will have a negative impact on their careers, with only 10% expecting it to help.

The respondents also voiced their opinions on AI regulation, with 45% favoring federal government rules and 36% preferring an independent expert body. Only 8% thought AI should not be regulated, while 60% called for slowing data center expansion. Apart from AI-related concerns, 26% of the polled young individuals admitted they had not traded on a prediction market like Kalshi in the past 30 days.

Written by urgent.news from TechSpot's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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