Artificial Intelligence is a technology whose time has come

Artificial Intelligence is a technology whose time has come


The pace of change in disruptive technologies is accelerating. According to Moore’s Law, computing doubles every 18 to 24 months in terms of both performance and affordability. This principle also applies to other technologies, such as robotics, artificial intelligence (AI), nanotechnologies, biotechnologies and additive manufacturing.

AI is rapidly affecting all elements of contemporary societies and economies including higher education institutions (HEI's). The very concept of ‘deep learning,’ central to progress in AI, clearly impinges on the purpose of HEI's and may create new competition for them. If done right, AI can augment and empower what these institutions already do; but continuing their missions of research, teaching and external engagement will require fundamental reassessment and transformation. Have HEI's found their disruptive advantage?

Technology has ‘flipped the classroom’ forcing HEI's to think about where to add real value – such as personalised tuition, more time with hands-on research, rather than traditional lectures.

AI is impacting the very way we communicate, socialise and learn, according to Dr Cobus Oosthuizen, Dean of the Milpark Business School. “Digital classrooms are on the rise, transforming the learning experience. Experimentation with immersive learning experiences with the use of virtual and augmented reality are also increasing.” Dr Oosthuizen says these technologies make the learning experience more engaging and transformative and can contribute to faster learning, improved retention and decision-making.

“It is expected that as these technologies will continue to advance and have abilities we currently can’t fathom. I don’t think, however, that lecturing will be completely abolished soon, at least not over the next ten years […,] but beyond that, it is difficult to make a prediction,” he explained. “As far as possible and plausible of complete abolishment of lecturing is concerned, I would suggest a 15-year timeline. In terms of probable, 20 years seems likely, but is this what we want to happen? Personally, I would rather opt for human lecturing augmented by AI, whether via face-to-face or online engagement […,] in other words, a coalescence of man and machine.”

It still remains the case, however, that much-advanced learning, and its assessment requires personal and subjective attention that cannot be automated.  University administrative processes will benefit from utilising AI on the vast amounts of data they produce during their research and teaching activities. Dr Oosthuizen says great strides are being made with the development and deployment of AI in university administrative processes, with examples such as grading and tutoring.

He says that while AI can be instrumental in the tracking of individual student performance, identify the gaps and indicate when interventions are needed to prevent dropouts, “lecturers may not be aware of gaps in their lectures and study materials that adversely impact student performance. There are AI systems that already assist with bridging this gap. In addition, AI is also applied in application and admission procedures, as well as identifying at-risk students. This is enabled, through the AI’s ability, to very quickly and accurately run through mountains of data and calculate all input combinations of variables.”

As far as providing insights on student career progression, “my sense is that the complexity of ‘humanness’ still poses numerous challenges to AI. When considering individuals’ personality, skills, competencies, preferences, psychophysiological makeup and the like, the variables appear innumerable. I think that we’re unlikely to see AI being fully applied for this purpose. For the foreseeable future, AI’s role in this regard would be at most to augment human decision-making. However, within a decade the tide could turn, with AI’s advancements and its abilities evolving through deep learning.”

HEI's are the drivers of disruptive technological change, like machine learning, AI and automation. It is the duty of these institutions to reflect on their broader social role, and create opportunities that will make society resilient to this disruption. 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 HEI's and business. One of the most pressing AI challenges for HEI's is the need for them to develop better employment conditions and career opportunities to retain and incentivise their own AI workers.

31 Oct 2017