Why not stop building roads and start building robots?

David Reed, director of research and editor-in-chief, DataIQ

If you were reading The Guardian (print edition) on Monday, 20th March, you might have noticed a telling juxtaposition of two news stories on the business pages. The first explained why future infrastructure spending plans are not focused on the right type of project. The second described how conventional spending on infrastructure has not delivered the expected results. Taken together, they can be seen as a call for a fresh approach that recognises the centrality of data and its enormous economic potential.

The CBI launched a campaign calling on the Government to increase research and development spending on technology to 3% of GDP, compared to a current level of 1.7%. Despite the recent unveiling of an industrial stategy for the UK which has the tech and digital sectors at its heart, the employers’ organisations believes the country risks being left behind in cutting-edge areas like robotics and space tourism. While these are usually identified by the shiny gleam of the devices they inhabit, they are both powered by data and analytics.

At the same time, the Campaign to Protect Rural England published a study into 86 road schemes which showed them to have largely failed to boost local economies or relieve congestion. With the budget for roadbuilding set to triple to £3 billion annually by the end of the decade, it is a good time to be asking whether this is money well spent.

Step back from whatever vested interests informed these campaigns - or feel challenged by them - and you can not help but see a powerful alternative. The future does not lie in building more roads, but in making more efficient use of the existing ones and building smart traffic management systems that interact with the new generation of connected cars. Similarly, getting off the planet may appeal to scientists, but it is finding new drivers of productivity that will really help to drive up GDP, with the AI supporting robotics right at its heart.

For this next generation of investment into data infrastructure to be realisable, however, there needs to be a concerted effort to agree on what it should be built around. In particular, the dread concept of industry standards has to be addressed - and this is undoubtedly where Government intervention and support has a role to play.

Consider those smart roads. Better traffic flows can result from vehicles operating in automated convoys for longer journeys as well as from smart traffic controls that read and respond to the level of vehicles around. Highways infrastructure will need to be able to talk to cars and lorries, which will need in turm to communicate with other vehicles around them. Only standardised data models and interoperability will allow this to happen - if the marketplace is left to its own devices, the risk is of no compatibility between different marques or the road management systems. 

So now is the time to be pulling together academic research and commercial interests to ensure this data-driven, analytically smart future can actually be delivered. Among the challenges faced by the UK are that US-oriented models will become the de facto norm. Suppose they turn out to be unable to operate vehicles that drive on the left? (In case you think that’s ridiculous, NASA managed to lose a Mars probe because one of its engineering teams was working in metric and the other in imperial. By the time you find that out, it’s too late…)

Adopting a completely fesh approach to infrastructure spending would be a smart move and this is one of those political moments where it is just possible to tear up the ideas of the past and adopt new ones for the future. Right now, investing in data and analytics is cheap, compared to building roads or space stations. So why not make a start?

Please note that blogs are the sole view of the author and that they are not neccesarily the view of IQ ddg Ltd and should not be interpreted as advice. Please read our full disclaimer

Director of research and editor-in-chief, DataIQ
An expert commentator on all things data, David has been editor of DataIQ since its inception in 2011.

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