In early January 2021, the UK AI council released an AI roadmap that outlined the need for a UK national AI strategy alongside potential direction that strategy can go in. The roadmap affirms the growing recognition by governments of the importance of facilitating the growth of AI and pleasingly held ethical considerations within the report also. Below are the top 16 recommendations alongside the thoughts of Nural Research.

The AI council is an independent committee that provides advice to the UK Government, as well as high-level leadership for the Artificial Intelligence (AI) ecosystem.

Check out the full report below

AI Roadmap
An independent report, carried out by the AI Council, providing recommendations to help the government’s strategic direction on AI.

Top 16 recommendations


Nural Research's Opinion

Below are three particular areas of note that have been drawn out from the report. This is by no means a complete review of the pros and cons of the report created and please get in touch if you would like to discuss further.


Ethical considerations
The importance of ethics when utilising AI systems is noticeably alluded to many times throughout the report and it is good to see these considerations at the highest level. The most powerful treatment comes in the discussion of the need to educate all young people on the inner methodology of AI. In doing so, it will create a generation of people "know what questions to ask, what risks to look out for, what ethical and societal implications might arise, and what kinds of opportunities AI might provide".

The key areas of ethical considerations include: the limitations of sampled datasets, datasets which misrepresent the world we want to live in (despite being accurate), human bias entered in modelling. It is imperative that follow on work has these areas at the forefront.


Moonshot projects
The report also considers the huge potential for AI to tackle moonshot projects and even focused on the two areas of healthcare and climate change as specific example areas. Thus, the potential for AI to tackle long-term problems is becoming increasingly apparent.

A greater analysis of the lanscape necessary to cultivate these projects needs to be developed next. While it can be inferred that greater access to funding, education and awareness are key contributors, a review of the common themes found in successful projects that implemented AI would be invaluable. Throughout this review it must be remembered that the aim is not to successfully implement AI but to successfully solve the grand problem and thus we must not overstretch to fit AI to a problem it is not ideally equipped for.


Lack of tangible, measurable direction
Across the 16 recommendations and within the report, there is a lack of tangibility to the goals outlined. While many of the directions are clear and well thought through, there is a suitable amount of ambiguity over the measurement of the direction e.g. "Committing to achieving AI and data literacy for everyone". However, it may be argued that as this report was purely to guide UK national AI strategy as opposed to create it, it is not in the report's remit to concretely define measurements of success. In any case, these loose directions provide reasonable scope for misinterpreation and to miss the mark regarding the quality of implemnetation and so further work must build upon this.