'There's this deep mystery of what, actually, is this thing?': the philosopher inside Google DeepMind AI Since 2017, Iason Gabriel has worked at the tech giant, trying to anticipate - and think through - the impact of AI. But as commercial and geopolitical pressures escalate, can ethicists make any difference? In 2017, a 33-year-old political philosopher named Iason Gabriel was told by a friend that he ought to apply for a job at DeepMind, the London-based subsidiary of Google where much of its AI research was concentrated. The suggestion was not an obvious one. Gabriel was a cheerful but intense junior academic with a passion for Vipassana meditation and what his brother calls "enthusiastic" rock climbing. At the University of Oxford, where he was a fellow at St John's College, Gabriel taught courses on political theory and wrote papers on the moral contortions of "yuppie ethics" and the ethical blind spots of effective altruism. When he wasn't there, he did crisis work for the United Nations Development Programme in Sudan and Lebanon. DeepMind, meanwhile, was the world's leading AI research lab. In part, this was because it had the financial and computational backing of Google, which had bought the company in 2014 for $650m. In part, it was because DeepMind had recently shown it could put those resources to stunning use. In Seoul, in 2016, a DeepMind system called AlphaGo defeated Lee Sedol, a South Korean Go champion, in a five-game match. The victory was significant not least because of Go's legendary complexity; the game has more possible configurations than there are atoms in the universe. Thanks to the fuss around AlphaGo, Gabriel was aware of DeepMind.

Models that are learned from real-world data are often biased because the data usedtotrainthemisbiased.

This article aims to demonstrate how the approach to computing is being disrupted by deep learning (artificial neural networks), not only in terms of techniques but also in our interactions with machines. It also addresses the philosophical tradition of hermeneutics (Don Ihde, Wilhelm Dilthey) to highlight a parallel with this movement and to demystify the idea of human-like AI.

The G7 has just agreed a (voluntary) code of conduct that AI companies should abide by, as governments seek to minimize the harms and risks created by AI systems. And later this week, the UK will be full of AI movers and shakers attending the government's AI Safety Summit, an effort to come up with global rules on AI safety. In all, these events suggest that the narrative pushed by Silicon Valley about the "existential risk" posed by AI seems to be increasingly dominant in public discourse. This is concerning, because focusing on fixing hypothetical harms that may emerge in the future takes attention from the very real harms AI is causing today. "Existing AI systems that cause demonstrated harms are more dangerous than hypothetical'sentient' AI systems because they are real," writes Joy Buolamwini, a renowned AI researcher and activist, in her new memoir Unmasking AI: My Mission to Protect What Is Human in a World of Machines.

AI researcher and activist Joy Buolamwini is best known for a pioneering paper she co-wrote with Timnit Gebru in 2017 which exposed how commercial facial recognition systems often failed to recognize the faces of Black and brown people, especially Black women. Her research and advocacy led companies such as Google, IBM, and Microsoft to improve their software so it would be less biased and back away from selling their technology to law enforcement. Now, Buolamwini has a new target in sight. She is calling for a radical rethink of how AI systems are built. Buolamwini tells MIT Technology Review that, amid the current AI hype cycle, she sees a very real risk of letting technology companies pen the rules that apply to them-- repeating the very mistake that has previously allowed biased and oppressive technology to thrive.

I can tell Buolamwini finds the cover amusing. She takes a picture of it. Times have changed a lot since 1961. In her new memoir, Unmasking AI: My Mission to Protect What Is Human in a World of Machines, Buolamwini shares her life story. In many ways she embodies how far tech has come since then, and how much further it still needs to go.

When I visited the Victoria and Albert Museum in London in early June, a fabulous drag cabaret was in full swing. Across seven small screens and a large wall projection, a rotating cast of performers in an array of bold looks danced and lip-synced their hearts out to banger after banger. Highlights included Freedom! 90 by George Michael, Five Years by David Bowie and Beyoncé's Sweet Dreams. Then the whole thing started again. But this wasn't just a video installation running on a loop: it was an elaborately engineered deepfake.

The best advice I can give you for 2023 is to familiarize yourself with the concept of "artificial intelligence" and its impact on our everyday lives. And in the wrong hands, this technology can wreak havoc on society. To me, social media platforms have been the clearest example of this. Twitter and Facebook feeds, powered by artificial intelligence and controlled by some of the world's wealthiest people, have bombarded users with politically opportunistic conspiracy theories, misinformation, and hatred. These days, I tend to see the misery evoked by social platforms as an opportunity to highlight the potential dangers of artificial intelligence.

A computer scientist who said she was pushed out of her job at Google in December 2020 has marked the one-year anniversary of her ouster with a new research institute aiming to support the creation of ethical artificial intelligence. Timnit Gebru, a known advocate for diversity in AI, announced the launch of the Distributed Artificial Intelligence Research Institute, or DAIR. Its website describes it as "a space for independent, community-rooted AI research free from Big Tech's pervasive influence." Part of how Gebru imagines creating such research is by moving away from the Silicon Valley ethos of "move fast and break things" -- which was Facebook's internal motto, coined by Mark Zuckerberg, until 2014 -- to instead take a more deliberate approach to creating new technologies that serve marginalized communities. That includes recognizing and mitigating technologies' potentials for harm from the beginning of their creation process, rather than after they've already caused damage to those communities, Gebru told NBC News.

Sight is a miracle-- the relationship of reflection, refraction, and messages decoded by nerves within the brain. When you look at an object, you're staring at a reflection of light that enters your cornea in wavelengths. As it enters the cornea, the light is refracted, or bent, toward the thin, filmy crystalline lens that further refracts the light. The lens is a fine-tuner: it focuses the light more directly at the retina, forming a smaller, more focused beam. At the retina, the light stimulates photoreceptor cells called rods and cones.