The University Of 2030

Future Perfect: What Will Universities Look Like in 2030?

From robots to the most popular course, academics share their predictions

Times Higher Education | December 24, 2015

Recently the media had fun comparing the vision of life in 2015 depicted in the 1989 film Back to the Future Part II with the reality – with the internet being the glaring omission. But what if we were to try to predict the academy’s future? Could we do a more accurate job? After all, isn’t that one of the tasks of university leaders, given that the future is coming even to those who don’t have a time machine in their sports cars?
We asked several distinguished academics to tell us how they imagine higher education will look in 2030. 

In 15 years, we will have no one to teach. The professional jobs for which we prepare students will be done by intelligent machines.

Source: https://www.timeshighereducation.com/features/what-will-universities-look-like-in-2030-future-perfect

Source: https://www.algomau.ca/media/style_assets/images/news/research_matters_400.jpg

<more at https://www.timeshighereducation.com/features/what-will-universities-look-like-in-2030-future-perfect; related links: https://www.insidehighered.com/blogs/globalhighered/universities-2030-learning-past-anticipate-future (Universities 2030: Learning from the Past to Anticipate the Future. April 28, 2014) and http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf (The Future of Employment: How Susceptible Are Jobs to Computerisation? Carl Benedikt Frey and Michael A. Osborne. September 17, 2013. [Abstract: We examine how susceptible jobs are to computerisation. To assess this, we begin by implementing a novel methodology to estimate the probability of computerisation for 702 detailed occupations, using a Gaussian process classifier. Based on these estimates, we examine expected impacts of future computerisation on US labour market outcomes, with the primary objective of analysing the number of jobs at risk and the relationship between an occupation’s probability of computerisation, wages and educational attainment. According to our estimates, about 47 percent of total US employment is at risk. We further provide evidence that wages and educational attainment exhibit a strong negative relationship with an occupation’s probability of computerisation.])>