Over the last year, our attention has been focused on a series of issues that are of global importance. Last year, Extinction Rebellion pushed climate change to the top of the agenda. This year, COVID-19 has made effective public health monitoring a priority. In recent weeks, anger at systemic racial injustice has fuelled public protests.
While these are very different issues, they share something in common: they will not be addressed if we do not use data-driven technologies to understand, monitor and improve complex systems - whether that is the healthcare system, the justice system or the energy grid.
This week the CDEI published its AI Barometer, a major analysis of the key risks, opportunities, and governance challenges associated with AI and data use in the UK. The conclusion we came to, after engaging with 120 experts, is that there are significant barriers that will prevent the UK from using AI and data-driven technology to overcome the complex challenges its facing.
The problem is often not with the technology itself, but a failure to harness it. As identified in the CDEIs AI Barometer, game changing opportunities related to the use of AI and data often have common characteristics, which make them challenging to realise.
They require coordination across organisations, they involve the use of large scale complex data about people, and they affect decisions that have a direct and substantial impact on peoples lives.
The good news is that, despite these challenges, we can break through the technological impasse. In order to realise the game changing opportunities identified in the CDEIs AI Barometer, policymakers, industry and other decision-makers must tend to three areas.
Firstly, we must improve access to - and the sharing of - high quality data. AI which is trained and tested on poor quality or biased data may result in unfair and erroneous outcomes. The CDEI will soon be reporting on bias in algorithmic decision-making, including the difficulty organisations face in accessing data to measure and mitigate bias.
Equally, the concentration of data in the hands of a small number of companies, the unwillingness or inability to share data, and the difficulty of transitioning data from legacy and non-digital systems to modern applications, can all stymie innovation.
Secondly, we must improve the clarity and consistency of data governance. Guidance around AI and data use in the UK is often highly localised, with different police forces setting their own policies for facial recognition technology use, for example. The application of existing regulatory standards in an AI context can be unclear and can vary between and even within sectors. This can lead to confusion among both those deploying and overseeing technology.
Improved data governance will not only mean that the public can have confidence that effective regulatory mechanisms are in place, but that public servants, businesses and innovators have the clarity and confidence to use data in ways that are not just legal, but also responsible.
Thirdly, we need to improve transparency around the use of AI and data. Private firms and public sector organisations are not always transparent about how they are using these technologies or their governance mechanisms. This prevents scrutiny and accountability, which could otherwise spur responsible innovation.
All three areas need to be addressed if we are to foster public trust in the use of AI and data-driven technology by institutions, the importance of which has been demonstrated during the COVID-19 response.
Policymakers, industry and regulators need to work together - including through the UK Governments forthcoming National Data Strategy - to address these issues. Steps need to be taken to create a governance environment that enables responsible innovation and commands public trust. With a coordinated national response, we can begin to realise the transformative potential of AI and data-driven technology.
Roger Taylor is Chair of the Centre for Data Ethics and Innovation
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The UK has only just begun to see the transformative potential of AI - Telegraph.co.uk
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