UK public sector failing to be open about its use of AI, review finds

A report into the use of artificial intelligence by the U.K.’s public sector has warned that the government is failing to be open about automated decision-making technologies which have the potential to significantly impact citizens’ lives.

Ministers have been especially bullish on injecting new technologies into the delivery of taxpayer-funded healthcare — with health minister Matt Hancock setting out a tech-fueled vision of “preventative, predictive and personalised care” in 2018, calling for a root and branch digital transformation of the National Health Service (NHS) to support piping patient data to a new generation of “healthtech” apps and services.

He has also personally championed a chatbot startup, Babylon Health, that’s using AI for healthcare triage — and which is now selling a service in to the NHS.

Policing is another area where AI is being accelerated into U.K. public service delivery, with a number of police forces trialing facial recognition technology — and London’s Met Police switching over to a live deployment of the AI technology just last month.

However the rush by cash-strapped public services to tap AI “efficiencies” risks glossing over a range of ethical concerns about the design and implementation of such automated systems, from fears about embedding bias and discrimination into service delivery and scaling harmful outcomes to questions of consent around access to the data sets being used to build AI models and human agency over automated outcomes, to name a few of the associated concerns — all of which require transparency into AIs if there’s to be accountability over automated outcomes.

The role of commercial companies in providing AI services to the public sector also raises additional ethical and legal questions.

Only last week, a court in the Netherlands highlighted the risks for governments of rushing to bake AI into legislation after it ruled an algorithmic risk-scoring system implemented by the Dutch government to assess the likelihood that social security claimants will commit benefits or tax fraud breached their human rights.

The court objected to a lack of transparency about how the system functions, as well as the associated lack of controlability — ordering an immediate halt to its use.

The U.K. parliamentary committee that reviews standards in public life has today sounded a similar warning — publishing a series of recommendations for public-sector use of AI and warning that the technology challenges three key principles of service delivery: openness, accountability and objectivity.

“Under the principle of openness, a current lack of information about government use of AI risks undermining transparency,” it writes in an executive summary.

“Under the principle of accountability, there are three risks: AI may obscure the chain of organisational accountability; undermine the attribution of responsibility for key decisions made by public officials; and inhibit public officials from providing meaningful explanations for decisions reached by AI. Under the principle of objectivity, the prevalence of data bias risks embedding and amplifying discrimination in everyday public sector practice.”

“This review found that the government is failing on openness,” it goes on, asserting that: “Public sector organisations are not sufficiently transparent about their use of AI and it is too difficult to find out where machine learning is currently being used in government.”

In 2018, the UN’s special rapporteur on extreme poverty and human rights raised concerns about the U.K.’s rush to apply digital technologies and data tools to socially re-engineer the delivery of public services at scale — warning then that the impact of a digital welfare state on vulnerable people would be “immense,” and calling for stronger laws and enforcement of a rights-based legal framework to ensure the use of technologies like AI for public service provision does not end up harming people.

Per the committee’s assessment, it is “too early to judge if public sector bodies are successfully upholding accountability.”

Parliamentarians also suggest that “fears over ‘black box’ AI… may be overstated” — and rather dub “explainable AI” a “realistic goal for the public sector.”

On objectivity, they write that data bias is “an issue of serious concern, and further work is needed on measuring and mitigating the impact of bias.”

The use of AI in the U.K. public sector remains limited at this stage, according to the committee’s review, with healthcare and policing currently having the most developed AI programmes — where the tech is being used to identify eye disease and predict reoffending rates, for example.

“Most examples the Committee saw of AI in the public sector were still under development or at a proof-of-concept stage,” the committee writes, further noting that the Judiciary, the Department for Transport and the Home Office are “examining how AI can increase efficiency in service delivery.”

It also heard evidence that local government is working on incorporating AI systems in areas such as education, welfare and social care — noting the example of Hampshire County Council trialing the use of Amazon Echo smart speakers in the homes of adults receiving social care as a tool to bridge the gap between visits from professional carers, and points to a Guardian article which reported that one-third of U.K. councils use algorithmic systems to make welfare decisions.

But the committee suggests there are still “significant” obstacles to what they describe as “widespread and successful” adoption of AI systems by the U.K. public sector.

“Public policy experts frequently told this review that access to the right quantity of clean, good-quality data is limited, and that trial systems are not yet ready to be put into operation,” it writes. “It is our impression that many public bodies are still focusing on early-stage digitalisation of services, rather than more ambitious AI projects.”

The report also suggests that the lack of a clear standards framework means many organisations may not feel confident in deploying AI yet.

“While standards and regulation are often seen as barriers to innovation, the Committee believes that implementing clear ethical standards around AI may accelerate rather than delay adoption, by building trust in new technologies among public officials and service users,” it suggests.

Among 15 recommendations set out in the report is a call for a clear legal basis to be articulated for the use of AI by the public sector. “All public sector organisations should publish a statement on how their use of AI complies with relevant laws and regulations before they are deployed in public service delivery,” the committee writes.

Another recommendation is for clarity over which ethical principles and guidance applies to public sector use of AI — with the committee noting there are three sets of principles that could apply to the public sector, which is generating confusion.

“The public needs to understand the high level ethical principles that govern the use of AI in the public sector. The government should identify, endorse and promote these principles and outline the purpose, scope of application and respective standing of each of the three sets currently in use,” it recommends.

It also wants the Equality and Human Rights Commission to develop guidance on data bias and anti-discrimination to ensure public sector bodies’ use of AI complies with the U.K. Equality Act 2010.

The committee is not recommending a new regulator should be created to oversee AI — but does call on existing oversight bodies to act swiftly to keep up with the pace of change being driven by automation.

It also advocates for a regulatory assurance body to identify gaps in the regulatory landscape and provide advice to individual regulators and government on the issues associated with AI — supporting the government’s intention for the Centre for Data Ethics and Innovation (CDEI), which was announced in 2017, to perform this role. (A recent report by the CDEI recommended tighter controls on how platform giants can use ad targeting and content personalisation.)

Another recommendation is around procurement, with the committee urging the government to use its purchasing power to set requirements that “ensure that private companies developing AI solutions for the public sector appropriately address public standards.”

“This should be achieved by ensuring provisions for ethical standards are considered early in the procurement process and explicitly written into tenders and contractual arrangements,” it suggests.

Responding to the report in a statement, shadow digital minister Chi Onwurah MP accused the government of “driving blind, with no control over who is in the AI driving seat.”

“This serious report sadly confirms what we know to be the case — that the Conservative Government is failing on openness and transparency when it comes to the use of AI in the public sector,” she said. “The Government is driving blind, with no control over who is in the AI driving seat. The Government urgently needs to get a grip before the potential for unintended consequences gets out of control.

“Last year, I argued in parliament that Government should not accept further AI algorithms in decision making processes without introducing further regulation. I will continue to push the Government to go further in sharing information on how AI is currently being used at all level of Government. As this report shows, there is an urgent need for practical guidance and enforceable regulation that works. It’s time for action.”