Friday, 03 November 2017

Our fear is that a GM-style public backlash to AI might lead to a clampdown on its use in the public sector – leaving private companies to use it unchecked

Fresh breakthroughs in artificial intelligence come thick and fast these days. Last month, Google’s DeepMind revealed its latest Go-playing AI which mastered the ancient game from scratch in a mere 70 hours. AI can spot cancer in medical scans better than humans, meaning radiotherapy can be targeted in minutes, not hours. We may soon use the technology to design new drugs, or repurpose existing ones to treat other, neglected, diseases.

But as we begin to realise these opportunities, the potential risks increase: that AI will proliferate, uncontrolled and unregulated, in the hands of a few increasingly powerful technology firms, at the expense of jobs, equality and privacy. Already, mistakes over the sharing of patient records between DeepMind and the Royal Free Hospital in London have raised public concerns about technology firms being involved in digital healthcare.

As the Guardian reported this week, the danger of a public backlash to AI, similar to that seen with the introduction of genetically modified crops, is very real. There are similarities – the concern about unforeseen consequences, the complexity of the new technology, the need for public engagement and, above all, the role of industry.

With GM crops, businesses initially reaped the benefits, while society bore the risks and the same may well apply to AI. But there are also significant differences. The barriers to introducing AI are much lower than for GM crops, where trials must be approved, as must the sale of seeds and products. Online, there are no borders, and national regulation is either non-existent or difficult to enforce.

So the real worry about a public backlash is that the response will not be widespread regulation of the whole marketplace, but instead a clampdown on the use of AI in the public sector. Private companies will continue to use AI, unregulated, to improve the targeting of products. But in the public sector where there could be life-changing benefits, over-regulation will mean the opportunities will be lost.

That is not to say that AI should be allowed to spread uncontrolled in the NHS. But it does emphasise why it’s so important to get this right. AI can only be introduced successfully in the NHS if the public, patients and healthcare professionals have confidence in the system, including clear oversight and accountability.

Transparency is essential, and so too is a meaningful conversation with the public – something that was lacking with the failed programme and the DeepMind partnership with the Royal Free. Having an early discussion about the value of data, and finding a way for the NHS to realise that value when using services based on algorithms requiring patient data, is crucial. Finally, the implications for the patient and clinician, and issues of fair access and benefit, must be fully addressed.

While there is a risk that a GM-style backlash could prevent the appropriate application of AI in healthcare, we should not give up hope. As the Information Commissioner has recently emphasised, it does not need to be a choice between privacy or innovation.

The example of embryo research and the recent approval of mitochondrial donation – so-called “three parent babies” – shows that the UK has learnt from the mistakes of GM crops. New technologies can be introduced with public confidence if done carefully, with clear oversight, a robust regulatory framework, wide-reaching debate about the ethical and social implications, and, above all, meaningful public consultation.

We must follow the same approach with AI, to ensure that, ultimately, it is the patient who wins the game.

Nicola Perrin is head of Understanding Patient Data, an initiative that supports better conversations about the uses of health information and Danil Mikhailov is head of digital strategy at Wellcome.

This article was originally published on The Guardian.

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