Hosted over two days and across two alternative stages, the Alan Turing Institute hosted AI UK; a tour d’horizon from the brightest and best that the Institute had to offer neatly intertwined with leading figures from industry and academia. Delivered using the HopIn virtual conference software; the experience was seamless, the speakers candid and the conclusion, cautiously optimistic.
5 Key Takeaways and Questions
The very first session of the conference set out in stark terms, the level to which there is a shortage of Artificial Intelligence professionals in the United Kingdom. As in many other skilled sectors where the United Kingdom has an internal competitive advantage in knowledge, it lacks the human resources to transfer this to a sustained competitive advantage which it can exploit internationally. In a call to arms, Professor Sir Adrian Smith pronounced that the UK needed an ‘army’ of AI professionals to bridge the gap. Later that morning, Professor of Structural Bioinformatics at the University of Oxford, Charlotte Deane, noted that in doctoral practice alone, places outnumbered applicants by around ten to one.
Greater efforts to improve accessibility through primary and secondary education are certainly required to nurture the next generation of AI professionals in the medium to long term, but how do we address the elephant in the room? How does the UK go about upskilling its existing workforce? When one takes into account the ageing population and the fact that 25% of 2030’s workforce has already entered the labour market, is it too late to hope to compete on the international stage?
Collaboration is Key
Without openness in data, informed policy decisions and progression cannot take place. Real time analysis of localised data was key to tackling the primary issue at hand throughout 2020, stopping the spread of the virus – yet it was clear that the public sector lacked the capability to deliver the precision and timeliness in silo. Robust and active participation from the private sector; from Google and Facebook through to start ups and challengers like Adzuna and Revolut have been key inputs through artificial intelligence analyses that have shaped public policy decisions at both the national and more commonly, the regional level. But how can we ensure that individual data privacy is enshrined, and more broadly, how open should data be going forward?
Ethics Are Everywhere
Throughout many of the sessions, a member of the Turing Institute’s ethical board opined on the topic at hand – the need to balance data privacy against the utility of the underlying data provided. The fact that ethical questions of data were so prevalent in many discussions was unsurprising from a liberal worldview which views the privacy of the individual as sacrosanct, but could this become a limiting factor in developing artificial intelligence to its full potential? From a realist perspective, the ability of a state to utilise artificial intelligence depends on its ability to access data; and the primary roadblock for Western nations is their innate enlightenment principles. Aggregation, anonymisation go some way to protect against States of a more authoritarian persuasion, namely China, which are not constrained in this regard – and as such, have raced ahead in utilising machine learning in their daily lives.
Punching Above Its Weight
Despite the concerns outlined above, it must be stated that the United Kingdom’s performance relative to its size is impressive. Priya Lakhani OBE noted the relative outperformance of the United Kingdom for inward investment in AI – third in the world, albeit some way behind the AI superpowers of China and the United States. As Professor Vasco Carvalho alluded, this is, in no small part, due to institutions like the Alan Turing Institute and the Office of National Statistics – both of which draw respect and acclaim from the international community. But, like several other sectors within which the United Kingdom has an internal comparative advantage from a knowledge perspective, the lack of specificity and focus on policy support leaves its currently favourable position vulnerable to increased international competition.
The most expedient way through which to strengthen its position would be to simplify the jargon and complex AI nomenclature. For the layperson, the very premise of artificial intelligence remains a mystery, and one with a seemingly high barrier to entry. The ability to set international norms through agreeing a common framework of accessible terminology would be welcome and set a precedent for the international community as well as the United Kingdom itself.
COVID Has Changed the Way We Interact with Data
The past twelve months has put the way that legislators handle data in their decision making in a new light – and has highlighted the importance of both timeliness and localisation as drivers of effective policy.
The improved use of alternative and timely data throughout the pandemic also highlighted a fresh political fault line in so far as how data is interpreted, filtered, and presented to the wider populous. Why were the conclusions of SAGE taken as gospel, and prioritised over alternative, aggregated long views from the field of economics? Why have views from the latter been derided and dismissed as callous or playing politics with public health? It is unhelpful and creates an unnecessary obstruction to collaboration.
The use of artificial intelligence and its algorithmic outputs will be at the centre of the debates on policy openness in both the immediacy and as the effects on the real economy and mental health are borne out in years to come. The United Kingdom begins its next chapter in the field of AI from a strong base but will require effective political will and a more sensible approach to openness if it is to succeed and double down on its current advantages.
Over the course of the following weeks, the Alan Turing Institute will be making available a select number of the session on their YouTube Channel; you can access them using this link – they are well worth the watch.
Written by Harry Wilby, SAMI Associate
The views expressed are those of the author(s) and not necessarily of SAMI Consulting.
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