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As we hand over more of our lives to artificial intelligence systems, keeping a firm grip on their ethical and societal impact is crucial. For DeepMind, whose stated mission is to “solve intelligence”, that task will be the work of a new initiative tackling one of the most fundamental challenges of the digital age: technology is not neutral.

DeepMind Ethics & Society (DMES), a unit comprised of both full-time DeepMind employees and external fellows, is the company’s latest attempt to scrutinise the societal impacts of the technologies it creates. In development for the past 18 months, the unit is currently made up of around eight DeepMind staffers and six external, unpaid fellows. The full-time team within DeepMind will swell to around 25 people within the next 12 months.


Headed by technology consultant Sean Legassick and former Google UK and EU policy manager and government adviser Verity Harding, DMES will work alongside technologists within DeepMind and fund external research based on six areas: privacy transparency and fairness; economic impacts; governance and accountability; managing AI risk; AI morality and values; and how AI can address the world’s challenges. Within those broad themes, some of the specific areas addressed will be algorithmic bias, the future of work and lethal autonomous weapons. Its aim, according to DeepMind, is twofold: to help technologists understand the ethical implications of their work and help society decide how AI can be beneficial.

For DeepMind co-founder Mustafa Suleyman, it’s a significant moment. “We’re going to be putting together a very meaningful team, we’re going to be funding a lot of independent research,” he says when we meet at the firm’s London headquarters. Suleyman is bullish about his company’s efforts to not just break new frontiers in artificial intelligence technology, but also keep a grip on the ethical implications. “We’re going to be collaborating with all kinds of think tanks and academics. I think it’s exciting to be a company that is putting sensitive issues, proactively, up-front, on the table, for public discussion.”

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To explain where the idea for DMES came from, Suleyman looks back to before the founding of DeepMind in 2010. “My background before that was pretty much seven or eight years as an activist,” he says. An Oxford University drop-out at the age of 19, Suleyman went on to found a telephone counselling service for young Muslims before working as an advisor to then Mayor of London Ken Livingstone, followed by spells at the UN, the Dutch government and WWF. He explains his ambition thusly, “How do you get people who speak very different social languages to put purpose ahead of profit in the heart of their organisations and coordinate effectively?”

“We want these systems in production to be our highest collective selves” Mustafa Suleyman, DeepMind


Understanding the implications of artificial intelligence systems isn’t an exercise in chin-stroking. In 2015, Google’s AI-powered Photos app started automatically labelling some photos of black people as “gorillas”. More damningly, an algorithm used in the American criminal justice system has been found to be biased against black people. Earlier this year, a facial recognition research group from Stanford University claimed its AI could distinguish between gay and heterosexual people based on their facial features. "Gay men had narrower jaws and longer noses, while lesbians had larger jaws,” the researchers claimed. In London, a startup called RAVN developed an AI that can sift through dull legal paperwork with little-to-no human assistance.

“The topics that we’re concerned with are how do you scrutinise an algorithm; how do you hold an algorithm accountable when it’s making very important decisions that actually affect the experiences and life outcomes of people,” Suleyman says. “We want these systems in production to be our highest collective selves. We want them to be most respectful of human rights, we want them to be most respectful of all the equality and civil rights laws that have been so valiantly fought for over the last sixty years.”

DMES is separate to the firm’s secretive internal ethics and safety board, which has been in operation since around the time DeepMind was acquired by Google for £400 million in September 2010. Suleyman says the board, which has some external representation, has been “reasonably successful”, but further experimentation with how DeepMind explores the ethics of AI has always been the plan. “The ethics board is focussed on [artificial general intelligence],” he explains. “That was always longterm, over ten, 20, 30 years, as we build systems which are more and more autonomous, which are genuinely capable of real human skills. That body is there to help us navigate the challenges that arise specifically from general intelligence.”

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While little is known about the ruminations of DeepMind’s internal ethics and safety board, DMES is intended to be open and transparent. All its research will be published online in full and its six external fellows – who include economist professor Diane Coyle; philosopher and existential risk expert professor Nick Bostrom; international diplomat Christiana Figueres; and economist professor Jeffrey Sachs – have not signed any non-disclosure agreements.


“I can say what I like about anything, anywhere, there’s no constraining agreement,” professor Coyle tells me. She describes her role as a fellow to DMES as conducting academic reviews on research, taking part in workshops and giving feedback. She adds that concerns about DeepMind in-housing crucial AI research are broadly unfounded. “DeepMind is obviously owned by Google now. But you can be too cynical about it. I think they are sincere and genuinely want to achieve some understanding and do some very good research. And I think if a lot more companies did it we’d be in a better place.”

Such cynicism might be founded on DeepMind’s collaboration with the NHS Royal Free Trust to develop an app used to detect acute kidney injury. An investigation into the data-sharing agreement between the firm and the NHS by the Information Commissioner’s Office found that the Royal Free had failed to comply with the data protection act when it handed over details of 1.6 million patients to DeepMind. At the time, a DeepMind spokesperson said the firm “underestimated the complexity of the NHS and of the rules around patient data”. The ICO warned that such work should never be “a choice between privacy or innovation”.

When I raise the issue with Suleyman, he counters that DeepMind created a panel of independent reviewers to scrutinise its work with the NHS, adding the company took “serious measures” to be open and transparent. “There's so much more that we need to do when it comes to interacting with this kind of data in the NHS. And that is really, really challenging,” he says. “It is ambiguous, a lot of the texts are very tough to navigate when it comes to regulation and a lot of it is emerging and trying to catch up with the technology.” If it works as DeepMind hopes, one role for DMES could be to spot similar issues and tackle them in the open based on input from all parties.

“I think having a forum where you can bring a lot of disciplinary views to bear is one of the really attractive things about this” Professor Diane Coyle

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The launch of DMES comes little-over a year after the launch of the Partnership on AI, a consortium of technology firms, activist organisations and academic institutions focussed on establishing best practises for developments in artificial intelligence. DeepMind was a founding member, alongside Amazon, Google, Facebook, Microsoft and IBM. For Suleyman, it was necessary to establish DMES alongside the Partnership to tackle the size of the challenge the industry faces. “The objective of DMES is to start to do the work ourselves that I don't see happening elsewhere. The more people doing this research the better. We want there to be lots of orthogonal approaches on this work.” One of the challenges for the Partnership, Suleyman continues, is persuading “all the companies and researchers to get on board with the direction of travel”.

As well partnering with organisations such as the Royal Society and Leverhulme Centre for the Future of Intelligence, DMES will also work closely with the Partnership on AI. Such work will often involve funding interdisciplinary research. While the existence of DeepMind funding will always be made public, the amount of funding may sometimes remain secret. “I think DeepMind should be applauded for taking the initiative to extend its engagement with questions of ethics and social impacts of AI,” says professor Bostrom. “Of course, if there were only one voice speaking on these issues it would be concerning – and maybe equally concerning whether that one voice was a cooperation, a government, or some nutty academic. Fortunately that is not the world we are living in.” He describes DMES as an effort by DeepMind to expose itself to “a larger set of critical economic and ethical perspectives”. DeepMind will also launch “other initiatives” looking into the ethical and societal impacts of AI in 2018, Suleyman says.

The Partnership on AI itself has raised eyebrows over a perceived lack of activity. Suleyman says the group now has a growing staff and that he expects it to be “commissioning lots of similar research” to DMES. But he says that for DeepMind to realise its ambition of cracking general intelligence, it needs an interdisciplinary approach to AI. “We need to have in-house the very best anthropologists, sociologists, specialists on lethal autonomous weapons, specialists on bias and discrimination in machine learning systems, working with both our researchers and applied software development teams so that they can give them feedback and guidance and introduce them to new modes of critical thinking, which you can't get from encouraging someone to read a paper that's been published outside of the organisation.”

Such an assertion raises questions about in-housing, of a Google-owned company stockpiling the best talent, both technical and academic. But Coyle says that need not be the case. “It's quite hard to get off the ground in the academic world because of the incentive structures,” she argues, pointing out that the interdisciplinary nature of artificial intelligence research and scrutiny can struggle inside the constraints of academia. “All the reward and incentive structures, and in fact most research funding, is very much geared towards staying inside one discipline and career path. So I think having a forum where you can bring a lot of disciplinary views to bear is one of the really attractive things about this.”

“Over time, we should give more attention and respect to those that actually produce useful research” Professor Nick Bostrom

Suleyman is very much aware of the criticism that might be levelled at DeepMind. “If we are to be successful as a civilisation in the next two, three, four decades, it’s absolutely critical that we move beyond the default sector-based way of thinking, where academics criticise government for not listening enough, where government criticises companies for not understanding their perspective and where companies dismiss the other. We just all go around this cycle of basically playing the institutional role we’re in and hating on one another. And that has to stop,” he says.


But DeepMind, and Suleyman, have also had to learn. The collaboration with the NHS, which now extends to several trusts, put in sharp relief the level of scrutiny the company is under. “I might sit here with hindsight, as I did with the independent reviewers on DeepMind Health, in a year and be like, ‘Yup, this isn’t right, that’s not right’. And I’m sure we probably will be because this is surprising to people and they are going to ask odd questions like, ‘Isn’t this just in-housing’ and all the other normal concerns that people are going to raise. I think we have to be a little bit resilient to that default scepticism. I respect it, I know the usual characters will have the same old concerns, which I also have. My heart is in their place.”

Crucially, DeepMind does not have a monopoly on artificial intelligence technology, nor will it on artificial intelligence research. As Bostrom puts it, “The more the merrier”, but with a caveat: “Over time, we should give more attention and respect to those that actually produce useful research.” For Suleyman, coming to terms with the ethical and societal issues raised by developments in artificial intelligence is ultimately a matter of scale. “Algorithms are going to be central to our ability to build a better world over the next two decades. We need ten times more academic resource in thinking about these problems. No organisation can do it alone.”

DeepMind will be hosting a series of talks on the societal and ethical challenges posed by artificial intelligence at our annual WIRED Live festival in London on November 2. To find out more, and to book tickets, click here.