IORMA in a Royal Society study on the future of machine learning

In January 2016 I reported to IORMA businesses on the excitement of contributing to the Royal Society’s study of the future of machine learning (ML) in building UK competitiveness – and the impact that it will have on people as consumers and citizens.
See IORMA in a Royal Society study on the future of machine learning: here

On 12 April 2016, the Royal Society then held a large public meeting for people to give their views and expectations of living in a world that is increasingly driven by intelligent systems.

Barbara Walker
Director of Innovation and Government Relations


Machine learning produces intelligent systems that detect and produce vast amounts of information, and can run,entire processes - learning and adapting as they go.  ML isn't the same thing as robotics - it can run robotic devices, but it can also be applied to big data to find trends and relationships that elude human analysis, and show what more needs to be known, letting the intelligent system seek that new data for itself.  A leading use in business is to predict customer behaviour, and co-relate it with people's attitudes and behaviour in other fields such as travel and learning.

Chaired by Marcus du Sautoy, the panel’s star – in my view – was Chris Bishop, Laboratory Director at Microsoft Research Cambridge.  He clarified that machine learning is not just about robotics; a topic that gets some vivid coverage in films and the media, with newspapers competing to attack or defend the Terminator portrayal of human demise.  In fact, the impact of intelligent systems – even without the sinister actions of clunking humanoids – demands our attention.  For most of us it’s fine that machine learning enables systems to analyse big data, to find relationships, to predict consumer behaviour and preferences.  But when the system learns from its own experience, and perhaps from its friends in the networks it belongs to, and starts forming strategic decisions – is that going too far for comfort?

An aspect of machine learning of particular importance to IORMA is the impact that it will have on jobs, and on how organisations are run in future.  Views vary widely; mostly as regards the level of jobs that are under threat – semi or unskilled, skilled, middle or senior management – company Boards? See the IORMA Knowledge Hub forecasts in this respect.  And as customers do we really want that degree of intervention in our decision making?  As usual, where there’s innovation and controversy, there’s Google.  See:  Google calendar update uses artificial intelligence to make its users into better .

Presumably, as better people, we will be fitting in some time for the luxury of driving our cars – while we still have the chance.  See Google cars – and Toyota and Tesla.

These trends are of huge importance to business that live and thrive on consumer commerce, as the people who went along to the Royal Society discussion and demonstration are our customers, employees and shareholders. 
So machine learning, as well as autonomous vehicles, including drones, are a rich vein for the IORMA iLab, the IORMA Knowledge Hub and IORMA Events into the future.


Translate »