Machine Learning Will Require A Shake-Up Of Higher Education And Tech Skills

Evolutions in machine learning will require a shake-up of higher education to ensure people have the right skills to get the most out of a world gradually succumbing to automation.

That’s according to a report by The Royal Society into the various impact machine learning will have on society and business; unsurprisingly, like many reports and hot takes from various bodies and industry, The Royal Society found that the rise of machine learning can bring a host of benefits.

But amid the potential to yield smart applications, better services, and extract value from big data being harvested by Internet of Things (IoT) networks, The Royal Society highlighted that smart machines and systems will need new skills to not only keep them up and running but also ensure that robots do not replace human workers completely.

Human and machine learning

“Machine learning will increasingly feature in both our work and personal lives. While not necessarily replacing jobs or functions outright, machine learning will force us to think about our occupations, and the skills necessary to function in a world where these systems are ubiquitous,” the report explained.

The Royal Society noted that the development of machine learning has created the need for three specific skills.

The first, is to train students and people to have a basic understanding of how data can be used with machine learning systems and the key concepts around the developing technology as well as some of the social and ethical impacts it could yield.

The second is to adjust university courses is disciplines such as healthcare, law and finance to reflect the impact machine learning can have and ensure that the technology is put to the benefit of organisations in these sectors, as well as creating a pool of informed practitioners of machine learning systems so that the benefits of smart software and machines can be better realised.

The third aspect is to support the development of advanced skills needed to fuel the development of machine learning and better facilitate its beneficial use.

“There is already high demand for people with advanced skills, and additional resources to increase this talent pool are critically needed,” the report said, drawing attention to the need to have skilled people to notice when a smart systems is inferring subjective bias or unfair conclusions to the data it is consuming.

A variety of other points, such as privacy, data governance and the worry over who is ultimately responsible for smart systems, were also deemed by The Royal Society as areas to consider.

But regardless of the potential major disruption the next-generation of machine learning systems could have on society and business, the developments of smart technology does not appear to be going away anytime soon, particularly when the tech industry has well-funded startups exploring how to create medical apps with artificial intelligence capabilities that aim to surpass the diagnostic skills of trained doctors.

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