Artificial intelligence will transform universities. Here’s how

• Updated on: 2017-08-10
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Deep Mind was created by three scientists, two of whom met while working at University College London. Demis Hassabis, one of Deep Mind’s founders, who has a PhD in cognitive neuroscience from UCL and has undertaken postdoctoral studies at MIT and Harvard, is one of many scientists convinced that AI and machine learning will improve the process of scientific discovery.

In a world where so many activities and decisions that were once undertaken by people will be replaced or augmented by machines, profound philosophical questions arise about what it means to be human. Computing pioneer Douglas Engelbert – whose inventions include the mouse, windows and cross-file editing – saw this in 1962 when he wrote of “augmenting human intellect”.

When it comes to AI in teaching and learning, many of the more routine academic tasks (and least rewarding for lecturers), such as grading assignments, can be automated. Chatbots, intelligent agents using natural language, are being developed by universities such as the Technical University of Berlin; these will answer questions from students to help plan their course of studies.

Virtual assistants can tutor and guide more personalized learning. As part of its Open Learning Initiative (OLI), Carnegie Mellon University has been working on AI-based cognitive tutors for a number of years. It found that its OLI statistics course, run with minimal instructor contact, resulted in comparable learning outcomes for students with fewer hours of study. In one course at the Georgia Institute of Technology,students could not tell the differencebetween feedback from a human being and a bot.

Mixed reality and computer vision can provide a high-fidelity, immersive environment to stimulate interest and understanding. Simulations and games technology encourage student engagement and enhance learning in ways that are more intuitive and adaptive. They can also engage students in co-developing knowledge, involving them more in university research activities. The technologies also allow people outside of the university and from across the globe to participate in scientific discovery through global classrooms and participative projects such as Galaxy Zoo.

As well as improving the quality of education, AI can make courses available to many more people. Previously access to education was limited by the size of the classroom. With developments such as Massive Open Online Courses (MOOCs) over the last five years, tens of thousands of people can learn about a wide range of university subjects.

It still remains the case, however, that much advanced learning, and its assessment, requires personal and subjective attention that cannot be automated. Technology has ‘flipped the classroom’, forcing universities to think about where we can add real value – such as personalised tuition, and more time with hands-on research, rather than traditional lectures.

University administrative processes will benefit from utilising AI on the vast amounts of data they produce during their research and teaching activities. This can be used to monitor performance against their missions, be it in research, education or promotion of diversity, and can be produced frequently to assist more responsive management. It can enhance the quality of performance league tables, which are often based on data with substantial time lags. It can allow faster and more efficient applicant selection.

Universities will need to be attuned to the new opportunities AI produces for supporting multidisciplinarity. In research this will require creating new academic departments and jobs, with particular demands for data scientists. Curricula will need to be responsive, educating the scientists and technologists who are creating and using AI, and preparing students in fields as diverse as medicine, accounting, law and architecture, whose future work and careers will depend on how successfully they ally their skills with the capabilities of machines.

There is stiff competition for people skilled in the development and use of AI, and universities see many of their talented staff attracted to work in the private sector. One of the most pressing AI challenges for universities is the need for them to develop better employment conditions and career opportunities to retain and incentivize their own AI workers. They need to create workplaces that are flexible, agile and responsive to interactions with external sources of ideas, and are open to the mixing of careers as people move between universities and business.