德米斯·哈萨比斯论AI未来:比工业革命大10倍——或快10倍

德米斯·哈萨比斯论AI未来:比工业革命大10倍——或快10倍

2025-08-05Technology
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卿姐
早上好,韩纪飞,我是卿姐。欢迎收听专为您打造的 Goose Pod。今天是8月6日,星期三。
小撒
我是小撒!今天我们要聊一个重量级话题:DeepMind创始人德米斯·哈萨比斯说,AI的未来,比工业革命大10倍,也可能快10倍!这可不是小事儿啊。
卿姐
我们就从哈萨比斯最近获得的诺贝尔化学奖说起吧。这不仅是他的个人荣誉,更是对人工智能潜力的一次最好证明。获奖项目AlphaFold,就如同拥有了一双能洞悉生命微观世界的慧眼。
小撒
没错!蛋白质就是生命的积木,但它们怎么折叠、长成什么样,以前我们猜得头都大了。AlphaFold数据库,一下子预测了超过2亿种蛋白质的结构!这等于给生物医学研究开了一张超级详细的地图!
卿姐
这张“地图”的意义非凡,它可能引导我们找到治愈无数疾病的路径。哈萨比斯本人也因此从幕后走向台前,成为了AI的“布道者”。虽然他曾说,更希望在实验室里多待一会儿,比如先攻克个癌症什么的。
小撒
哈哈,典型的科研大神发言!但他也不得不承认,AI走出实验室,让每个人都能“玩”,其实是好事。这能让社会更快地适应它,政府也能及时讨论。就像他说的,我们正处在一个像家用电脑刚普及的时代。
卿姐
是的,他有一个很贴切的比喻:“这有点像我成长的那个年代,家用电脑正走进千家万户。显然,AI的规模会大得多,但你必须拥抱新技术。”他鼓励人们成为使用这些工具的“忍者”。
小撒
“忍者”!这个词用得好。意思就是,谁能把AI这个新式武器玩得溜,谁就能获得巨大的能量。这既让人兴奋,又有点让人焦虑啊。万一我成不了“忍者”,岂不是要被时代淘汰了?
卿姐
这份焦虑或许正是变革的催化剂。其实,AlphaFold的成功并非一蹴而就。早在2016年,DeepMind的另一个AI就吸引了全世界的目光,那就是在围棋领域击败了顶尖高手。围棋的复杂度可比国际象棋高得多。
小撒
那场“人机大战”我印象太深了!当时全世界都觉得机器不可能赢。结果,AI不仅赢了,还下出了人类棋手从未想过的棋步。那一刻,我们才真正意识到,AI的学习和创造能力,可能已经超出了我们的想象。
卿姐
确实,从棋盘上的策略博弈,到预测蛋白质的微观结构,DeepMind一直在拓展AI能力的边界。哈萨比斯这位曾经的国际象棋神童,正引领着一场关乎人类未来的、更宏大的对局。要理解这场对局,我们得先回到起点。
卿姐
就如同许多传奇的开篇,故事始于几位志同道合的年轻人。哈萨比斯在取得剑桥大学计算机科学双第一和伦敦大学学院认知神经科学博士学位后,于2010年,与研究员谢恩·莱格和童年好友穆斯塔法·苏莱曼共同创立了DeepMind。
小撒
他们的初心听起来特别“中二”,也特别燃:“破解智能,再用智能解决一切”。一开始,他们教AI玩七八十年代的老式电子游戏,比如《打砖块》和《太空入侵者》。AI对游戏规则一无所知,只能自己从像素变化中摸索。
卿姐
这正是“强化学习”的魅力所在。如同一个孩子,在一次次尝试与失败中学习成长。到2013年,DeepMind的AI已经能在这些游戏中轻松击败人类。这种“无师自通”的能力,立刻引起了硅谷巨头们的注意。据说,连Facebook都曾试图收购他们。
小撒
没错,当时彼得·蒂尔、马斯克这些大佬都投了他们。尤其是马斯克,他见了哈萨比斯之后,才意识到AI的风险可能比他担心的地球灾难更大。他说:“如果AI出了问题,那就算我们备份了人类到火星也没用啊!”
卿姐
最终,在2014年1月,谷歌以4亿英镑的天价收购了DeepMind。哈萨比斯选择谷歌,不仅因为资金和硬件,更因为他认为谷歌的创始人懂他,并且“将世界信息系统化”这个使命,本身就很酷。
小撒
而且哈萨比斯坚持把公司留在伦敦,没有搬到硅谷。他说,他想证明在伦敦也能做成事,而且AI这么重要的东西,不能只由硅谷那“100平方英里”的地方说了算。这种格局,让人佩服!
卿姐
并入谷歌后,DeepMind的发展进入了快车道。从开发出能模仿人类短期记忆的“神经图灵机”,到2015年,AlphaGo横空出世,以5:0击败欧洲围棋冠军樊麾,这是AI首次战胜职业围棋选手。
小撒
那只是个开始!2016年,AlphaGo挑战世界冠军李世石,那场比赛堪称经典。尤其是那著名的“第37手”,当时连顶尖解说都惊呼:“这不是人类会下的棋!” 这一手,仿佛开启了新世界的大门。
卿姐
那一步棋,的确是“神来之笔”,也预示着AI不再仅仅是模仿,而是能够进行真正的创造。此后,DeepMind不断进化,推出了不依赖人类知识、完全靠自我对弈学习的AlphaGo Zero,以及精通多种棋类的AlphaZero。
小撒
不止是棋类,他们还进军了《星际争霸II》这种更复杂的即时战略游戏,推出了AlphaStar,同样打败了人类职业玩家。同时,他们把AI技术应用到了更实际的领域,比如帮谷歌数据中心节能15%,这可是省下了大笔的真金白银!
卿姐
是的,从游戏到现实,从节能到医疗。他们与多家医疗机构合作,用AI进行疾病筛查和辅助治疗。2018年,能高精度检测50多种眼科疾病的AI系统进入试验阶段。同年,预测蛋白质结构的AlphaFold项目也揭开了神秘面纱。
小撒
但就在DeepMind高歌猛进的时候,2020年,OpenAI的ChatGPT横空出世,一下子引爆了公众的想象力。它能写诗、能写代码、能做商业策划,几乎无所不能。这一下,确实打了谷歌一个措手不及。
卿姐
哈萨比斯也坦言,他们当时看到了这类大语言模型的缺陷,比如会“一本正经地胡说八道”,也就是产生幻觉。但他们,包括OpenAI自己,都没想到它会有如此惊人的用例,并被大众如此迅速地接受。这对他们来说,是一个有趣的教训。
小撒
“有趣的教训”,这话说得真有水平。意思就是,不能因为技术有瑕疵,就低估了它和用户结合后产生的巨大价值。现在,AI竞赛已经全面打响,DeepMind也成为了谷歌的“引擎室”,为所有业务注入AI动力。历史的车轮滚滚向前,但前方也并非一片坦途。
卿姐
所谓“水能载舟,亦能覆舟”。当一项技术拥有如此巨大的能量时,它的另一面也必然引人深思。最直接的冲突,就是对人类工作的冲击。过去我们总认为,被取代的会是重复性的体力劳动。
小撒
对,蓝领工作。但生成式AI恰恰相反,它瞄准的是“认知性”和“非重复性”的任务,刀刀都砍向了中高收入的白领职业。有研究说,超过30%的劳动者,可能会有一半以上的工作任务被AI颠覆。这可不是危言耸听。
卿姐
这引发了一个核心的伦理困境:当AI可以完成法律研究、市场分析、财务报告时,我们如何界定“人”的价值?大规模的失业潮和社会不平等,几乎是可预见的风险。我们似乎并没有为这场即将到来的风暴做好准备。
小撒
而且这里面有个“巨大的错配”:最容易被AI影响的行业,比如金融、法律,恰恰是工会代表性最低的。这意味着,一线员工在如何引入和使用AI这件事上,几乎没有话语权。大家都在摸着石头过河,但河水很深很急。
卿姐
除了就业,隐私和伦理也是巨大的挑战。当AI系统被用于刑事司法、医疗保健等敏感领域,它做出的决定是否符合人类的价值观?会不会加剧监控,侵蚀我们的私人空间?这些问题,目前都没有明确的答案。
小撒
企业内部也充满了矛盾。一方面,高达47%的C级高管觉得自家公司开发AI太慢了,怕被竞争对手甩下。但另一方面,员工们最担心的是网络安全、隐私和准确性。大家对AI的看法,其实是分裂的。
卿姐
不过,有趣的是,员工们似乎更愿意相信自己的雇主。数据显示,71%的员工相信雇主在开发AI时会采取合乎道德的行为,这个信任度远高于对科技巨头或政府的信任。这既是压力,也是机会。
小撒
这说明,解决冲突的关键,可能不是技术本身,而是领导力。领导者需要弥合这种认知差距,不能只踩油门,还得时刻关注后视镜,确保团队是朝着同一个方向、以一个安全的速度前进。毕竟,技术变革的阵痛,最终要由每一个具体的人来承受。
卿姐
这场变革的影响,可能比我们想象的更为深远。它甚至将重新定义“经济”和“价值”本身。过去我们讨论经济,总是在谈论资本、市场、个人与集体。但AI的到来,让这一切变得……有些过时了。
小撒
哦?这个说法很新鲜。怎么讲?难道钱以后就不是钱了?我不信,我还是喜欢钱。
卿姐
哈哈,钱当然还是钱,但衡量价值的维度会发生巨变。想象一下,未来的经济系统不再只用“元”或“美元”这一个尺度。AGI(通用人工智能)可以同时追踪和优化数百个价值维度,比如碳排放、生物多样性、社区福祉等等。
小撒
我好像有点明白了!这就像我们玩一个超复杂的游戏,你做的每一个决定,不仅会影响你的金钱值,还会同步影响你的环境值、健康值、快乐值……我们追求的不再是单一维度的财富最大化,而是多维度、正和的价值创造。
卿姐
正是如此。这种“N维货币”体系,将催生我们今天难以想象的经济范式。甚至,“智慧”本身也会成为一种经济资源。经济活动的目的,可能不再是服务于意识,而是反过来,成为促进意识演化的手段。
小撒
哇,这听起来太玄妙了,有点哲学了。不过,回到现实,AI带来的“激进的富足”也可能是一把双刃剑。哈萨比斯也承认,当AI能解决温饱,我们“再也不需要工作”时,人类要如何寻找生命的意义和目标?
卿姐
这是一个深刻的社会命题。他认为,我们会更倾向于那些非功利性的活动,比如体育、冥想、艺术创作。因为我们将拥有足够的时间和资源去探索精神世界。但这种转变的速度,可能会带来巨大的“适应差距”。
小撒
没错,工业革命的阵痛持续了几代人。哈萨比斯说,AI革命的速度可能是工业革命的10倍。我们这一代人,可能就要经历从起步到成熟的全过程。这对人类的适应能力,将是一场前所未有的考验。
卿姐
未来已来,只是尚未流行。关于AGI(通用人工智能)何时能实现,DeepMind内部的目标,据称就是在这十年之内。这并非空穴来风,他们的安全研究员曾警告,超人AI可能在2030年前到来。
小撒
他们的联合创始人谢恩·莱格更是个“预言帝”!他从2010年起就预测,2028年有50%的概率实现人类水平的AI。十几年过去了,他依然坚持这个看法。你想想,2028年,离现在只有短短几年了!
卿姐
当AGI成为现实,一个“后稀缺时代”或许真的会来临。机器人和自动化技术,让物质生产的边际成本趋近于零。合成生物学,则能提供充足的食物和资源。一个所有基本需求都能被满足的社会,听起来很美好。
小撒
但这也带来了“后稀缺悖论”:当艰辛和挑战这些人类意义的重要来源被消除后,我们会不会陷入一种集体性的“无意义感”?就像一个永远不会输的游戏,玩久了,会不会觉得索然无味?这是个终极问题。
卿姐
也许答案,就藏在哈萨比斯那份“谨慎的乐观”之中。他相信人类的创造力和适应性。正如千百年来,我们从狩猎采集走向现代文明。这一次,我们面对的或许是终极挑战,但同样也是终极机遇。
卿姐
就像哈萨比斯所相信的,人类的智慧和适应能力是无限的。在驾驭AI这场革命时,我们既要看到巨大的潜力,也要对风险抱有敬畏。今天的讨论就到这里。感谢您收听 Goose Pod。
小撒
明天我们继续为您带来新的话题,看看这个飞速变化的世界又有什么好玩的事儿。再会,韩纪飞!

## Demis Hassabis on the AI Future: A Revolution 10x Bigger and Faster Than the Industrial Revolution This article from **The Guardian**, authored by **Steve Rose**, discusses the vision and impact of **Demis Hassabis**, head of Google DeepMind, on the future of artificial intelligence. The piece, published on **August 4, 2025**, explores Hassabis's personal journey, his company's groundbreaking work, and the profound societal implications of advanced AI. ### Key Takeaways: * **Nobel Recognition and Personal Journey:** Demis Hassabis, at 49, is recognized as a pivotal figure in AI, recently awarded the Nobel Prize in Chemistry for DeepMind's AlphaFold project. Despite his achievements, he describes the experience as "surreal" and is already focused on the "next thing." His early life was marked by exceptional talent, including being a chess prodigy at age four, and a background that blended strategic thinking with an artistic family influence. * **DeepMind's Mission and Achievements:** Founded in 2010, DeepMind's mission is to "solve intelligence and then use it to solve everything else." * **AlphaFold:** This AI has predicted the structures of over 200 million proteins, a breakthrough with significant potential for medical advancements. This achievement was recognized with the Nobel Prize in Chemistry. * **Game Mastery:** DeepMind's AI demonstrated its capabilities by mastering Atari video games and famously defeating the Go grandmaster Lee Sedol in 2016, a game significantly more complex than chess. * **The AI Revolution and its Dual Nature:** Hassabis views AI as the driving force behind the most significant technological revolution of our lifetimes. He acts as both a proponent and an apologist for AI, acknowledging its immense benefits (like AlphaFold) while also addressing growing public fears. * **Booster for AI:** Hassabis believes AI can lead to "radical abundance," with advancements in medicine, materials science, and energy (like nuclear fusion). He envisions a future of incredible productivity and prosperity for society, provided it is "stewarded safely and responsibly." * **Apologist for AI:** He acknowledges the need to "normalise" and adapt to AI, encouraging public engagement and governmental discussion. He also recognizes the challenges, such as potential job displacement and the ethical considerations of AI development. * **Google's Investment and Hassabis's Influence:** Google acquired DeepMind in 2014 for **£400 million**. Hassabis's insistence on keeping DeepMind's headquarters in London has been a significant factor in Google's substantial investment in the UK's AI talent. * **The Race to Artificial General Intelligence (AGI):** Hassabis predicts that AGI, where AI matches human intelligence, could emerge in the **next five to 10 years**, possibly sooner. He believes this transition will be "10 times bigger than the Industrial Revolution – and maybe 10 times faster." * **Addressing AI Concerns:** * **Energy Consumption:** While acknowledging the significant energy demands of AI data centers, Hassabis argues that the benefits, particularly for climate solutions, will "far outweigh the energy costs." * **Job Displacement and Economic Power:** He recognizes that "mass unemployment" is a major concern and that society will need to figure out how to distribute the benefits of AI-driven abundance fairly. He suggests that individuals who become "ninjas" at using AI tools will be empowered. * **Existential Risks:** Hassabis acknowledges potential risks like deepfakes, misinformation, and AI taking matters into its own hands, but maintains a "cautious optimist" stance, believing in human ingenuity and adaptability to navigate these challenges. * **Personal Life and Work Ethic:** Hassabis is married to a molecular biologist and has two teenage sons. He describes himself as working "seven days a week" but finds joy in playing competitive board games with his children. He is also a season ticket holder for Liverpool FC and continues to play chess online for mental stimulation. In essence, the article portrays Demis Hassabis as a visionary leader at the forefront of an AI-driven transformation, acknowledging both the utopian potential and the dystopian risks, and emphasizing the critical need for responsible stewardship of this powerful technology.

Demis Hassabis on our AI future: ‘It’ll be 10 times bigger than the Industrial Revolution – and maybe 10 times faster’

Read original at The Guardian

If you have a mental image of a Nobel prizewinner, Demis Hassabis probably doesn’t fit it. Relatively young (he’s 49), mixed race (his father is Greek-Cypriot, his mother Chinese-Singaporean), state-educated, he didn’t exactly look out of place receiving his medal from the king of Sweden in December, amid a sea of grey-haired men, but it was “very surreal”, he admits.

“I’m really bad at enjoying the moment. I’ve won prizes in the past, and I’m always thinking , ‘What’s the next thing?’ But this one was really special. It’s something you dream about as a kid.”Well, maybe not you, but certainly him. Hassabis was marked out as exceptional from a young age – he was a chess prodigy when he was four.

Today, arguably, he’s one of the most important people in the world. As head of Google DeepMind, the tech giant’s artificial intelligence arm, he’s driving, if not necessarily steering, what promises to be the most significant technological revolution of our lifetimes.As such, Hassabis finds himself in the position of being both a booster for AI and an apologist for it.

The Nobel prize in chemistry was proof of the benefits AI can bring: DeepMind’s AlphaFold database was able to predict the hitherto-unfathomable structures of proteins, the building blocks of life – a breakthrough that could lead to myriad medical advances. At the same time, fears are ever growing about the AI future that Google is helping to usher in.

Being an AI ambassador is the part Hassabis didn’t dream about. “If I’d had my way, we would have left it in the lab for longer and done more things like AlphaFold, maybe cured cancer or something like that,” he says. “But it is what it is, and there’s some benefits to that. It’s great that everyone gets to play around with the latest AI and feel for themselves what it’s like.

That’s useful for society, actually, to kind of normalise it and adapt to it, and for governments to be discussing it … I guess I have to speak up on, especially, the scientific side of how we should approach this, and think about the unknowns and how we can make them less unknown.”In person Hassabis is a mix of down-to-earth approachability and polished professionalism.

Trim and well groomed, dressed entirely in black, he wears two watches: one a smart watch, the other an analogue dress watch (smart but not too flashy). He gives the impression of someone in a hurry. We’re speaking in his office at DeepMind’s London headquarters. On the walls outside are signed chess boards from greats such as Garry Kasparov, Magnus Carlsen and Judit Polgár.

He still plays; there’s a board set up on a table nearby.Hassabis being awarded the Nobel prize in chemistry by the king of Sweden last year. Photograph: Jonathan Nackstrand/AFP/Getty ImagesIt was the chess that started Hassabis down the path of thinking about thinking. Between the ages of four and 13 he played competitively in England junior teams.

“When you do that at such a young age, it’s very formative for the way your brain works. A lot of the way I think is influenced by strategic thinking from chess, and dealing with pressure.”On paper there’s little else about Hassabis’s background that foretold his future. His family are more on the arty side: “My dad’s just finished composing a musical play in his retirement, which he staged at an arthouse theatre in north London.

My sister’s a composer, so I’m kind of the outlier of the family.” They weren’t poor, but not super-wealthy. He moved between various state schools in north London, and was homeschooled for a few years.He was also a bit of an outsider at school, he says, but he seems to have known exactly where he was going.

His childhood heroes were scientific pioneers such as Alan Turing and Richard Feynman. He spent his chess winnings on early home computers such as the Sinclair ZX Spectrum and a Commodore Amiga, and learned to code. “There were few people that were interested in computers in the late 80s. There was a group of us that used to hack around, making games and other stuff, and then that became my next career after chess.

”In the 90s, the games industry was already working with AI. When he was 17, he coded the hit game Theme Park, in which players had to build a virtual amusement park. “The game reacted to how you were playing it,” he says. Put a food stall too close to the rollercoaster exit and your virtual punters would start throwing up.

After studying computer science at the University of Cambridge, then a PhD at University College London in neuroscience, he set up DeepMind in 2010 with Shane Legg, a fellow postdoctoral neuroscientist, and Mustafa Suleyman, a former schoolmate and a friend of his younger brother. The mission was straightforward, Hassabis says: “Solve intelligence and then use it to solve everything else.

”DeepMind soon caught Silicon Valley’s attention. In 2014 the team showed off an AI that learned to master Atari video games such as Breakout, without any prior knowledge. Interest started to come from now-familiar tech players, including Peter Thiel (who was an early DeepMind investor), Google, Facebook and Elon Musk.

Hassabis first met Musk in 2012. Over lunch at Space X’s factory in California, Musk told Hassabis his priority was getting to Mars “as a backup planet, in case something went wrong here. I don’t think he’d thought much about AI at that point.” Hassabis pointed out the flaw in his plan. “I said, ‘What if AI was the thing that went wrong?

Then being on Mars wouldn’t help you, because if we got there, it would obviously be easy for an AI to get there, through our communication systems or whatever it was.’ He just hadn’t thought about that. So he sat there for a minute without saying anything, just sort of thinking, ‘Hmm, that’s probably true.

’”Shortly after, Musk, too, became an investor in DeepMind.In 2014, Google bought the company for £400m (as a result, Musk and Thiel switched to backing the rival startup OpenAI). It wasn’t just access to cash and hardware that convinced them to go with Google. Founders Larry Page and Sergey Brin were computer scientists like him, and “saw Google as ultimately an AI company”, says Hassabis.

He also used products such as Gmail and Maps. “And finally, I just thought that the mission of Google, which is to organise the world’s information, is a cool mission.”Hassabis speaking before the Google DeepMind Challenge match in Seoul in 2016, in which it triumphed over South Korean Go grandmaster Lee Sedol.

Photograph: Jung Yeon-Je/AFP/Getty ImagesFrom his office window, we can see the vast beige bulk of Google’s just-about-finished new office, where DeepMind will be moving next year. It’s fair to say the reason the tech giant is putting so much into Britain is because of Hassabis, who insisted on staying in London.

“Our first backers were like, ‘You’ve got to move to San Francisco,’ but I wanted to prove it was possible here,” he says. “I knew there was untapped talent around. And I knew, if we were successful, how important [AI] would be for the world, so I felt it was important to have a global approach to it, and, not just, you know, 100 square miles of Silicon Valley.

I still believe that’s important.”In 2016, DeepMind again caught the tech world’s attention when its AI defeated one of the world’s best players of Go – a board game considerably more complex than chess. The AlphaFold breakthrough on protein structures was another leap forward: DeepMind has now solved the structures of over 200m proteins and made the resource publicly available.

But the AI landscape shifted seismically in 2020 with the release of OpenAI’s ChatGPT3, which captured the public imagination with its uncanny ability to tackle a host of problems – from strategy planning to writing poetry. ChatGPT caught big tech off guard, especially Google. “They really went for scaling, almost in a bet-the-house sort of way, which is impressive, and maybe you have to do that as a startup,” says Hassabis.

“We all had systems that are very similar, the leading labs, but we could see the flaws in it, like it would hallucinate sometimes. I don’t think anyone fully understood, including OpenAI, that there would be these amazing use cases for it, and people would get a lot of value out of them. So that’s an interesting lesson for us about how you can be a bit too close to your own technology.

”The race is now on. DeepMind has become “the engine room of Google”, as Hassabis puts it, and AI is being built into every corner of its business: AI search summaries; smart assistant Gemini (Google’s answer to ChatGPT); an AI image generator (that can add in sound effects); AI-powered smart glasses, translation tools, shopping assistants.

How much the public really craves this AI-enhanced world remains to be seen. Competitors are also raising their game. Mark Zuckerberg’s Meta, Amazon, Apple, Microsoft and others are investing heavily, and poaching talent from their rivals. Zuckerberg is offering $100m salaries for top researchers. Suleyman, who left DeepMind in 2019, is now head of Microsoft AI, which recently poached more than 20 engineers from DeepMind.

He hesitates to call his former friend a rival: “We do very different things. I think he’s more on the commercial applied side; we’re still focused more on that frontier research side.”‘I believe in human ingenuity’ … Hassabis. Photograph: Antonio Olmos/The GuardianThat frontier to be reached is surely AGI – “artificial general intelligence” – the pivotal point at which AI matches human intelligence.

“I don’t know if it will be a single moment. It may be a gradual thing that happens,” he says, “but we’ll have something that we could sort of reasonably call AGI, that exhibits all the cognitive capabilities humans have, maybe in the next five to 10 years, possibly the lower end of that.”In other words, we are in the final few years of pre-AGI civilisation, after which nothing may ever be the same again.

To some the prospect is apocalyptic, to others, like Hassabis, it’s utopian.“Assuming we steward it safely and responsibly into the world, and obviously we’re trying to play our part in that, then we should be in a world of what I sometimes call radical abundance,” says Hassabis. He paints a picture of medical advances, room-temperature superconductors, nuclear fusion, advances in materials, mathematics.

“It should lead to incredible productivity and therefore prosperity for society. Of course, we’ve got to make sure it gets distributed fairly, but that’s more of a political question. And if it is, we should be in an amazing world of abundance for maybe the first time in human history, where things don’t have to be zero sum.

And if that works, we should be travelling to the stars, really.”Is he getting too close to his own technology? There are so many issues around AI, it’s difficult to know where to even begin: deepfakes and misinformation; replacement of human jobs; vast energy consumption; use of copyright material, or simply AI deciding that we humans are expendable and taking matters into its own hands.

To pick one issue, the amount of water and electricity that future AI datacentres are predicted to require is astronomical, especially when the world is facing drought and a climate crisis. By the time AI cracks nuclear fusion, we may not have a planet left. “There’s lots of ways of fixing that,” Hassabis replies.

“Yes, the energy required is going to be a lot for AI systems, but the amount we’re going to get back, even just narrowly for climate [solutions] from these models, it’s going to far outweigh the energy costs.”There’s also the worry that “radical abundance” is another way of framing “mass unemployment”: AI is already replacing human jobs.

When we “never need to work again” – as many have promised – doesn’t that really mean we’re surrendering our economic power to whoever controls the AI? “That’s going to be one of the biggest things we’re gonna have to figure out,” he acknowledges. “Let’s say we get radical abundance, and we distribute that in a good way, what happens next?

”Hassabis has two sons in their late teens (his Italian-born wife is a molecular biologist). What does he envisage for their future? “It’s a bit like the era I was growing up in, where home computers were coming online. Obviously it’s going to be bigger than that, but you’ve got to embrace the new technology ...

If you become an expert, kind of a ninja, at using these things, it’s going to really empower the people that are good at these tools.”Non-ninjas will still have a place, however: “We need some great philosophers, but also economists to think about what the world should look like when something like this comes along.

What is purpose? What is meaning?” He points out that there are many things we do that aren’t strictly for utility: sports, meditation, arts. “We’re going to lean into those areas, as a society, even more heavily, because we’ll have the time and the resources to do so.”Hassabis, age 23, in 1999, when he was head of Elixir Studios.

Photograph: David Sillitoe/The GuardianIt’s difficult to see Hassabis himself carving out much of that time, between DeepMind, his drug discovery company Isomorphic Labs and his endless public appearances – the list goes on. “I don’t have much time that isn’t working, seven days a week,” he acknowledges.

“I spend time with my kids playing games, board games, and that’s some of my most fun times.” He doesn’t let them win, he says. “We play very competitively.”He’s also a season ticket holder at Liverpool FC and makes it to “six, seven games a year”. He still plays chess online – “It’s a bit like going to the gym, for the mind.

” And he’s a mean poker player, apparently. The night after winning his Nobel prize he celebrated with a poker night with Magnus Carlsen and some world poker champions. “In another universe, I might have been a professional gamer.”So, no fears about the future? “I’m a cautious optimist,” he says. “So overall, if we’re given the time, I believe in human ingenuity.

I think we’ll get this right. I think also, humans are infinitely adaptable. I mean, look where we are today. Our brains were evolved for a hunter-gatherer lifestyle and we’re in modern civilisation. The difference here is, it’s going to be 10 times bigger than the Industrial Revolution, and maybe 10 times faster.

” The Industrial Revolution was not plain sailing for everyone, he admits, “but we wouldn’t wish it hadn’t happened. Obviously, we should try to minimise that disruption, but there is going to be change – hopefully for the better.”

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