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Report - UK needs to rethink funding, procurement and infrastructure to take advantage of AI

Stuart Lauchlan Profile picture for user slauchlan April 15, 2018
According to a much anticipated House of Lords Select Committee report on AI, the UK government must to take further action to support AI developments.

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If the UK is to have a post-Brexit AI economy, the government needs to get smarter about funding, procurement and infrastructure. That’s the long-awaited conclusion from the House of Lords Select Committee on AI today.

And basically, right now, while the UK government is talking-the-talk, it’s not walking-the-walk…or at least not well enough. Or as the Committee puts it in its report - AI in the UK - ready, willing and able?

The Government’s leadership in the development and deployment of artificial intelligence must be accompanied by action.

Some background context - last summer, the House of Lords, the upper house of the UK legislature, appointed a Select Committee to examine Artificial Intelligence and its potential impact, positive and negative, on the UK. This included societal, economic, regulatory and ethical considerations.

The cross-party Committee did its homework. Over 22 evidence sessions, it gathered commentary from industry, academia and beyond. Fifty-seven pieces of oral evidence were heard, along with 223 piece of written evidence. While the remit for the Committee was UK-centric, the conclusions and recommendations have applicability internationally as well as nationally.

On investment, the report states:

The challenge for start-ups in the UK is the lack of investment available with which to scale up their business. To ensure that AI start-ups in the United Kingdom have the opportunity to scale up, without having to look for off-shore investment, we recommend that a proportion of the £2.5 billion investment fund at the British Business Bank, announced in the Autumn Budget 2017, be reserved as an AI growth fund for SMEs with a substantive AI component, and be specifically targeted at enabling such companies to scale up.

Further, the Government should consult on the need to improve access to funding within the UK for SMEs with a substantive AI component looking to scale their business. To guarantee that companies developing AI can continue to thrive in the UK, we recommend that the Government review the existing incentives for businesses operating in the UK who are working on artificial intelligence products, and ensure that they are adequate, properly promoted to companies, and designed to assist SMEs wherever possible.

There’s also a need for more urgency to put in place the foundations necessary to support AI tech. While noting the government’s commitment to build out digital infrastructure, the Committee argues:

We are concerned that it does not have enough impetus behind it to ensure that the digital foundations of the country are in place in time to take advantage of the potential artificial intelligence offers. We urge the Government to consider further substantial public investment to ensure that everywhere in the UK is included within the rollout of 5G and ultrafast broadband, as this should be seen as a necessity.

Tackling bias

The Committee has concerns around the push for more open data sets across the public sector which carry information on citizens. This is open to being taken advantage of by larger U.S. tech firms, it warns:

Access to data is essential to the present surge in AI technology, and there are many arguments to be made for opening up data sources, especially in the public sector, in a fair and ethical way. Although a ‘one-size-fits-all’ approach to the handling of public sector data is not appropriate, many SMEs in particular are struggling to gain access to large, high-quality datasets, making it extremely difficult for them to compete with the large, mostly US-owned technology companies, who can purchase data more easily and are also large enough to generate their own.

Furthermore, there’s a real danger that these public data sets are not actually accurate mirrors of society. As such if this data is used to ‘teach’ AI systems, there are unfortunate consequences.

We are concerned that many of the datasets currently being used to train AI systems are poorly representative of the wider population, and AI systems which learn from this data may well make unfair decisions which reflect the wider prejudices of societies past and present. While many researchers, organisations and companies developing AI are aware of these issues, and are starting to take measures to address them, more needs to be done to ensure that data is truly representative of diverse populations, and does not further perpetuate societal inequalities.

Researchers and developers need a more developed understanding of these issues. In particular, they need to ensure that data is preprocessed to ensure it is balanced and representative wherever possible, that their teams are diverse and representative of wider society, and that the production of data engages all parts of society. Alongside questions of data bias, researchers and developers need to consider biases embedded in the algorithms themselves—human developers set the parameters for machine learning algorithms, and the choices they make will intrinsically reflect the developers’ beliefs, assumptions and prejudices. The main ways to address these kinds of biases are to ensure that developers are drawn from diverse gender, ethnic and socio-economic backgrounds, and are aware of, and adhere to, ethical codes of conduct.

To tackle this, the Committee wants to see:

the creation of authoritative tools and systems for auditing and testing training datasets to ensure they are representative of diverse populations, and to ensure that when used to train AI systems they are unlikely to lead to prejudicial decisions. This challenge should be established immediately, and encourage applications by spring 2019. Industry must then be encouraged to deploy the tools which are developed and could, in time, be regulated to do so.

There should also be an overhaul of public sector procurement, says the Committee. That’s a call that many have made before and run into the passive resistance of the ‘not the way we do things here’ government buy-side, but it’s essential according to today’s report:

To ensure greater uptake of AI in the public sector, and to lever the Government’s position as a customer in the UK, we recommend that public procurement regulations are reviewed and amended to ensure that UK-based companies offering AI solutions are invited to tender and given the greatest opportunity to participate. The Crown Commercial Service, in conjunction with the Government Digital Office, should review the Government Service Design Manual and the Technology Code of Practice to ensure that the procurement of AI-powered systems designed by UK companies is encouraged and incentivised, and done in an ethical manner.

We also encourage the Government to be bold in its approach to the procurement of artificial intelligence systems, and to encourage the development of possible solutions to public policy challenges through limited speculative investment and support to businesses which helps them convert ideas to prototypes, in order to determine whether their solutions are viable. The value of AI systems which are deployed to the taxpayer will compensate for any money lost in supporting the development of other tools.

My take

A lot of good stuff here. This is a wide-ranging report that’s had a lot of work put into it. Some of the recommendations are very sound, some are, I fear, rooted into idealism rather than pragmatism, but none the less interesting for that. Now, let’s see what the government decides to do about them…

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