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Creating an innovation ecosystem for AI

Luke Georghiou reflects on how the Alvey programme created an innovation ecosystem for Artificial Intelligence today.

Artificial intelligence (AI) has emerged as a new competitive battleground in nations’ search for technological and economic advantage. However excitement about the opportunities associated with machine learning, deep learning and other core concepts of AI has been matched by concerns about ethical dimensions and social consequences.

While scenarios of an AI-dominated future are regularly presented today, for those with long memories the hopes and the hype being expressed have a somewhat familiar ring. This historic echo was noted in a recent House of Lords report on AI which took the unusual step of commissioning a full appendix on ‘Historic Government Policy on Artificial Intelligence in the United Kingdom’ which focused on events of over 30 years ago.

For this writer it brought to life seven years, from 1983 to 1990, spent with colleagues from the Universities of Manchester and Sussex carrying out a real-time evaluation of the Alvey Programme for Advanced Information Technology. This was a £350m (approximately £940m at today’s value) industry-academic initiative that remains the largest of its kind in the UK.

Alvey programme

Alvey was conceived as a response to Japan’s fifth generation computer programme, whose focus on parallel computing was seen to pose a threat to UK industry. The programme was named after BT executive John Alvey who led the inquiry that led to its formation, although he took no substantive part in the programme itself. The programme was a multi-dimensional initiative with sub-programmes on Software Engineering, Very Large Scale Integration (VLSI) in microelectronics, and Intelligent Knowledge-Based Systems.

Our evaluation judged that its technological objectives had largely been met and to some extent its structural objectives were also achieved in that it formed a template for academic-industry cooperation that was replicated both nationally and in the EU’s archetypal ‘ESPRIT programme’. ESPRIT started shortly after Alvey and instituted the project structures that still run through the EU framework programmes, including the current Horizon 2020.

Benefits today

Despite this, the overall conclusion of the Alvey evaluation was downbeat. However with the benefit of hindsight some long-term benefits can be seen. For instance Alvey’s focus on object-oriented programming was implemented by Microsoft a quarter of a century later. And one of its core projects - a large-scale demonstrator on mobile information systems from the military radio communications company Racal Electronics - was an important step towards the company’s new cellular radio service launched in 1985 as Vodafone.

However Alvey was boxed in by a Thatcherite aversion to any measures seen to be near market. Indeed in that era it was remarkable that an intervention on this scale was supported at all. As a result, little was done to complement it with what, today, would be seen as essential parts of an innovation ecosystem including user engagement, enhancing the supply of trained people, and fostering patient capital.

AI debate

Much of the debate, then as now, was on Alvey’s engagement with AI. Since 1973 the field had been blighted by a highly negative review of its prospects by Sir James Lighthill, Lucasian Professor of Mathematics at Cambridge University.

Lighthill saw real benefits as being at least 25 years away but by 1981 a group of leading AI academics, dubbed by Alvey Programme Director Brian Oakley as the ‘artificial intelligentsia’, was ready to rehabilitate the subject.

Its evaluation acknowledged that the academic research base had been strengthened and that a new competence had been established in UK industry. Less encouragingly it reported that academic participants were particularly critical of their industrial partners and there was a dearth of firms willing or capable of exploiting the results.

Contractual obligations were also a barrier with one project held up by an obligation to use UK hardware in preference to its US counterpart. Staff recruitment and retention also hindered progress, while a general lack of commercial follow-up left a sense of under-achievement and contributed to a second ‘winter’, albeit less explicitly than that induced by Lighthill.

Hope or hype?

In the current AI spring there is reason to hope that the ‘seasonal’ cycle will not be as exaggerated, even if there is an inevitable drawback from some of the hype.

Crucially, there is a far higher engagement by business and much potential in the combination of machine learning, robotics and data analytics. With the Industrial Strategy presenting AI as one of its four Grand Challenges, the key will be to avoid the over-reach of Alvey in trying to progress innovation and industrial development solely with an R&D initiative.

Crucial complementary initiatives in training and skills, substantial user-engagement, greater focus in key centres and institutes, and systematic attention to ethical issues through a responsible research and innovation approach are all necessary components of a sustainable innovation ecosystem for AI.

Luke Georghiou is Deputy President and Deputy Vice-Chancellor at the University of Manchester, and Professor of Science and Technology Policy and Management at the Manchester Institute of Innovation Research at Alliance MBS.

Blog posts give the views of the author, and are not necessarily those of Alliance Manchester Business School and The University of Manchester.

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