Postdigital Science and Education

, Volume 1, Issue 1, pp 236–239 | Cite as

Review of Joseph E. Aoun (2017). Robot Proof: Higher Education in the Age of Artificial Intelligence

Cambridge, Massachusetts: The MIT Press. 187 Pp. ISBN 9780262037280
  • Brian SudlowEmail author

Debates and discussions are growing about how universities handle the shift towards a world dominated by artificial intelligence. One recent article in The Conversation underscored the importance of this shift for the practices of learning and teaching (Alam and Kendall 2018). Other observers of this process are more concerned, however, not about how universities deploy artificial intelligence for their own core activities, but rather about how they prepare students for a world of work saturated in artificial intelligence and shaped by the social, professional and economic dynamics that it can produce. Andrew Wachtel, President of the American University of Central Asia, recently stipulated that he would not be accepting a university presidency offered to him in Kazakhstan unless the university in question was prepared to take on board his strategy to meet this very issue (Wachtel 2018). One key problem here of course is that nobody is quite sure what a world increasingly run by artificial intelligence will actually look like, or indeed how fast that world could evolve into something else entirely different.

This is why predictions about what that this future world will look like are an integral part of the analysis in Joseph E. Aoun’s recent book Robot-Proof: Higher Education in the Age of Artificial Intelligence. Aoun is president of Northeastern University in Boston, an institution that describes itself as a “global, experiential research university built on a tradition of engagement with the world” (Northeastern University 2018). In terms of its vocation, Northeastern is committed to translational research and to being a university of the professions. Ineluctably, therefore, the evolving world of work represents a shifting target that Northeastern must watch closely in order to achieve its mission. Moreover, in the development of its 2025 Strategy (Northeastern University 2016) – the burdens of which Robot-Proof sets out for us – certain forecasts about the world of work have been placed front and centre.

Thus, Aoun argues, universities have a duty to students to prepare them for a world of work in which the “pressures of automatisation and globalization and the increasing complexities of available work” (17) are upsetting many erstwhile balances. There are shades here of Klaus Schwab’s forecasts in The Fourth Industrial Revolution (2017). Right across the developed and indeed the developing world, the value of routine labour is increasingly depressed because machines are consuming the tasks once performed by human beings. If part of the problem is increasing job scarcity, another part is related to the evolution of employment, a factor recognised by Susskind and Susskind in their The Future of the Professions: How Technology Will Transform the Work of Human Experts (2015). Still, Aoun finds no place for any neo-Malthusian gloom in which humans will only be able to fight for scraps of employment behind the henceforth dominant machines. Rather, the robot-proofing challenge for Aoun will be twofold: how do humans learn to work alongside the machines, and how do they provide labour or skills that AI cannot as yet – there is always an unstated ‘as yet’ in the calculation – provide?

In the robot-proof agenda, two human qualities offer themselves as strategic anchors in this regard: sociability and creativity. First, while computers could soon rival us for cognition, precision and power, we continue to excel them not only by internalising social codes but also in our ability to flit between such social codes. Moreover, our sociability is not merely genetic or physical but expresses itself in vastly complex, symbolic systems that are open to the inflexions of individual or group psychology, as well as other synchronic or diachronic factors. The sociability dimension imbricates with the other skill advantage that humans have over technology: the capacity for creativity. Aoun explains:

Other animals apply intelligence to solving problems: crows fashion tools to pluck bugs out of wood and sea otters yield rocks to crack clamshells. But only human beings are able to create imaginary stories, invent works of art and even construct carefully reasoned theories explaining perceived reality. Only human beings can look at the moon and see a goddess, or step on it and say we are taking a leap for all mankind (21).

Sociability and creativity, therefore, offer an initial anthropological response to the technological challenges outlined above. So far, so good.
One of the problems with forecasts about the future world of work, however, is that they can sometimes be based solely on analyses of technological advances disconnected from the networks of human interaction. Sociability and creativity might put one ahead of the machines in some respects but they are not the be all and end all of the matter. As Aoun notes paradoxically, technical proficiency appears lower on employers’ agendas than things such as initiative, work ethic and, notably, leadership. In fact, the last of these is frequently cited as the most desirable of employment skills. At the same time, the world of technology also demands ‘softer’ skills related to highly organised working systems. Cross-functionality and the ability to operate in and across large and diverse systems are competencies now highly prized by employers. According to the data Aoun has seen, employers increasingly want to see recruits with deep listening skills, the ability to rapidly summarise and share their knowledge, alongside the capacity to conceptualise, synthesise and communicate effectively. Aoun reaches his conclusion thus:

These are complex questions requiring intellectual discipline and nuanced thought – and the professional workplace of tomorrow is only getting more complex. Soon enough professionals will function in tandem with intelligent machines. Whatever the industry – finance, law, manufacturing, media or any other – it will require cognitive capacities that equip it for tasks we might not even be able to imagine yet. These capacities are mindsets rather than bodies of knowledge – mental architecture rather than mental furniture. Going forward, people will still need to know specific bodies of knowledge to be effective in the workplace, but that alone will not be enough when intelligent machines are doing much of the heavy lifting of information. To succeed, tomorrow’s employees will have to demonstrate a higher order of thought […] Because critical thinking and systems thinking are crucial for the human employees of the future, it is imperative we instil them through the education of the present. Universities will have to develop methods to nurture these cognitive capacities in students (41–43)

What then is the solution for a university intent on preparing its students for this future world of work, a world shaped not only by shifting technologies but by the shifting demands of employers and the seemingly smaller margins that separate economic success from economic disaster? Northeastern’s solution, as described by Aoun in Robot-Proof, is the development of what he calls Humanics. This is a new model that serves to develop essential future skills and instil in students a body of knowledge concerning the highly technological world around them. Humanics is structured along two axes. Along the first of these are the so-called New Literacies: the technological literacy of coding and basic engineering principles, the data literacy required by the demands of understanding, interpreting and utilising big data, taking into account the presuppositions of its collection and the questions that initially framed it; and the human literacy required by the demands of social milieu, leadership, teamwork, emotional and social maturity and dexterity.

The second axis of Humanics encompasses a set of cognitive capacities that Aoun also argues are essential for the future world of work. The first of these is critical thinking – the importance of which has long been established – with its openness to convergent or divergent logics and its balancing of varied data and contingencies. The second essential capacity is systems thinking which enables individuals to cross systematic disciplinary boundaries and provide solutions that draw on multiple fields of insight; Aoun cites the example of Dutch architect Koen Olthuis who brought his architectural systems thinking to the problem of rising sea levels and dreamt up the floating building (65). The third of Aoun’s critical cognitive capacities is entrepreneurship through which employees will bring added value to their companies by innovative thinking and development. Companies have to reinvent themselves in evolving markets.

The last of these cognitive capacities is cultural agility, a skill demanded by the conditions of globalisation. It requires empathy, discretion, human nuance and the ability to go deep in another culture. It is the kind of expertise advocated by the now famous series of HSBC adverts. No computer can tell us how to connect with a foreigner or to understand how what is desirable can change in different cultural contexts. Contexts are so multifarious and subject to rapid evolution that human mastery of them is only partially assured in any case. Developing cultural agility or intercultural competence should be at the heart of any future skills agenda.

One last condition shapes the Northeastern agenda for Humanics: their already well-established system of work placements (called ‘co-ops)’ that provides learning for life. As positive as this last condition sounds, its unspoken realism is clear enough. The world of technology and the world of work are in constant and indeed rapid evolution. Those who do not learn for life could be overtaken not by their own natural entropy but by the transformation of the milieu around them. Aoun’s world of work is a field of social acceleration.

The strength of Aoun’s agenda for robot-proofing students and indeed for transforming university curricula lies in trying to match the contents of programmes of study to the demands that students will meet on graduation. Employability itself is a moving target. There is a fairly close correspondence between the skills that Humanics incorporates and the skillsets that, according to the World Economic Forum (2016), will be required in the short-to-medium term. In this respect, Aoun’s model and the strategy adopted by Northeastern seems to offer a richer fayre than that advocated by the analyses of McAfee and Brynjolfsson (2014) with respect to the second machine age.

Nevertheless, it is a model that appears to have a rose-tinted view of digital technologies and their impact on human beings. Gazzaley and Rosen (2017) have argued that we need to take more seriously the challenge of this high-tech world to our ancient brains. Moreover, as Cal Newport (2016) has shown, those who have prospered most in the nascent world of artificial intelligence frequently develop the ability to step out of it for prolonged periods within any working period. Alongside the cognitive skills that Aoun’s model identifies, other skills could be needed to prosper in the future world of artificial intelligence, not least those that promote creative and critical thinking through the careful curation of the conditions for prolonged attention, or its restoration. Such an agenda is not likely to be wildly popular with many digital natives and certainly not with the manufacturers and purveyors of the latest indispensable electronic devices. Nevertheless, the skills that it proposes seem to be a sine qua non condition of intellectual agility – of perennial robot-proofing – in a world of digital dynamics.


  1. Alam, N., & Kendall, G. (2018). Five ways artificial intelligence will shape the future of universities. The Conversation, 18 April. Accessed 8 May 2018.
  2. Gazzaley, A. & Rosen, L. (2017). The distracted mind: ancient brains in a hi-tech world. Cambridge: MIT Press.Google Scholar
  3. McAfee, A., & Brynjolfsson, E. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. London: W. W. Norton and Company.Google Scholar
  4. Newport, C. (2016). Deep work: Rules for focused success in a distracted world. London: Piatkus.Google Scholar
  5. Northeastern University (2016). Academic Plan: Northeastern 2025. Accessed 8 May 2018.
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  7. Schwab, K. (2017). The fourth industrial revolution. London: Portfolio Penguin.Google Scholar
  8. Susskind, R., & Susskind, D. (2015). The future of the professions: How technology will transform the work of human experts. Oxford: Oxford University Press.Google Scholar
  9. Wachtel, A. (2018). Universities in the age of AI. Project Syndicate, 2 February. Accessed 8 May 2018.
  10. World Economic Forum (2016). Human capital outlook: Association of Southeast Asian Nations (ASEAN). Kuala Lumpur, Malaysia: World Economic Forum. Accessed 8 May 2018.

Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  1. 1.Aston UniversityBirminghamUK

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