Expertise and the PhD: Between depth and a flat place

1 INTRODUCTION

Expertise has come under increasing strain in recent years, undermining the authority of universities and public trust in research. It can be seen in the so-called edu-scepticism (Cowan, 2017) accompanying debates about graduates’ apparently diminishing employment prospects, particularly in the United Kingdom (UK), the United States, Canada and Australia, challenges to the role of Higher Education institutions as arbiters of knowledge and expertise, and post-truth rhetoric more broadly. Collectively, these developments suggest a reconfiguration and flattening of what constitutes expertise, how it may be acquired and a devaluing of specialisation.

The discrediting of universities and Higher Education more broadly has implications for the PhD, which can be seen as a synecdoche for the university as a whole. Indeed, scepticism about the role and value of a PhD in the labour market has been playing out for some time. Governments, policy agents and industry groups particularly in the developed world contend that the PhD is no longer fit for purpose and that a different kind of PhD is needed, one more attuned to the needs of end-users and capable of producing graduates who can move seamlessly from the university to industry where it is hoped they will drive knowledge-based innovation and economic growth (Cuthbert & Molla, 2015a; Group of Eight (G2017), 2017; Harman, 2002). At the same time, technology, labour market shifts, new disruptive business models, the promises and threats of artificial intelligence, and other factors are re-shaping what it means to be an expert and conceptions of expertise. While it is recognised that ‘democracy cannot function when every citizen is an expert’ (Nichols, 2017), or, to paraphrase Nietzsche, if we are all experts, none of us is (Kotzee & Smit, 2017, p. 646), discourse that flattens expertise or posits a version of expertise in which breadth and flexibility are foregrounded at the expense of depth, has implications for universities as knowledge-generating institutions and the credentials they bestow.

For a degree such as the PhD whose hallmark is depth the implications are potentially far-reaching. Depth is looking increasingly anachronistic given widespread calls from within universities and the governments who fund them to reform PhD programmes to better meet the needs of diverse end-users and a range of innovation-focused public policy objectives. As universities are required to demonstrate research impact, for example, PhD candidates are being called on to develop entrepreneurialism, commercialisation and other end-user-related competencies. Such calls are shining a spotlight on the skills profile of graduates. Just what capabilities should a PhD enable? More specifically, should disciplinary depth be emblematic of PhD-level expertise or should graduates’ skills sets look flatter, indicative of cross-disciplinary, transferable and generic skills?

This paper addresses these questions by undertaking a critical analysis of perceptions of PhD-level expertise and raising potential implications. Drawing on a range of sources, from the scholarly to the wider media, we draw together five exemplar models that are indicative of traditional and emerging conceptions of expertise, both in relation to the PhD and more broadly. These models demonstrate how the ratio between generalist, transferable skills and specialist knowledge in conceptions of expertise is transforming as the former is increasingly favoured over the latter.

In our discussion, we unpack these models and address the implications of a diminution of specialisation for the PhD, particularly with regards to the scope, aims and purpose. Questions we raise, for example, include just how well the capabilities generated through PhDs are currently understood, particularly given the diversity of models, both internationally and across disciplines. It is timely to reflect on these issues as the PhD is increasingly called upon to serve the multiple and potentially contradictory needs of an innovation and a knowledge economy on the one hand and traditional, disciplinary concerns on the other. Our analysis of PhD-level expertise has the potential to provide greater clarity for research educators and policymakers alike grappling with these complex issues.

Although the problem of expertise is arguably a key concept with respect to contemporary debates on the PhD, it has largely been overlooked as a focus of analysis in the literature. For example, while numerous studies have discussed the issue of generic skills and marketability/employability (Cryer, 1998; Gilbert, Balatti, Turner, & Whitehouse, 2017; Pole, 1997; Ylijoki & Henriksson, 2017), very few have examined the issue of expertise specifically in the context of the PhD (see Cuthbert & Molla, 2015a, 2015b). This is an oversight given effects of increased scepticism about expertise are arguably magnified when applied to the PhD. That is, expertise scepticism plays out with respect to the employability of PhD graduates as well as perceptions of the value of the knowledge generated through PhD research to society.

2 PHD CRISIS DEBATE

Misgivings about specialisation have become a permanent fixture of debates about the PhD in the developed world. Issues to do with expertise are close to the heart of what might be called the PhD crisis debate that has been current for much of this century, notably in advanced economies such as the United States, the UK and Australia, over the suitability of PhD graduates for diverse workplaces and whether or not there are too many graduates being produced (Cuthbert & Molla, 2015a, 2015b; Cyranoski, Gilbert, Ledford, Nayar, & Yahia, 1988; Gould, 2015, December 3; Ražem (Ur.), 2015). We know that while many PhD graduates work in academia, the majority do not, although there are significant disciplinary variations (Vitae, 2016). While this is largely an employability debate, it reveals an underlying tension in contemporary Higher Education policy between an instrumental conception of the PhD in which it is seen narrowly in the service of knowledge societies and economic and social prosperity, and an older and potentially wider conception in which the value of the PhD is located in specialisation and the service of truth and knowledge (Clark, 2006; Cuthbert & Molla, 2015a; Golde, 2006). At the heart of the employability debate, then, is a question about the capabilities and adaptability of graduates. This question arises particularly from the criticism that the knowledge acquired through the PhD is overly narrow and unsuited to diverse career paths beyond academia (ACOLA, 2016; Higher Education Commission, 2006; Mowbray & Halse, 2010). Much of the debate, therefore, centres on the apparent benefits and deficits of specialisation versus generalist, transferable knowledge and skills. Is the PhD providing the right kind of expertise for diverse career paths, whether university-based, industry or both?

The traditional conceptualisation of the PhD sees it as representative of a high level of scholarship and engagement in original research that can lead to becoming an expert in a particular field of research (Cox, Adams, & Omer, 2015a, p. 4) or steward of the discipline (Golde & Walker, 2006). This conception persists even despite international differences between programmes—particularly between the United States and the UK models—and other variations, such as the professional doctorate and creative practice-based models. This focus on disciplinary specialisation, however, can come into tension with more recent calls for generalist, transferable capabilities suited to diverse careers, which may shift over the life of the graduate. This reflects a broader call for knowledge workers to be adaptable lifelong learners attaining evolving skill bundles to keep pace with new technologies and changes in employment opportunities.

The PhD reformists seek to overhaul what they see as a lumbering behemoth redolent of a bygone age with little relevance to today’s knowledge-based societies that demand adaptability and agility arguably better served by the lifelong accumulation of skill bundles on an as needed basis (Aoun, 2017; Carey, 2015; Susskind & Susskind, 2015). Work practices and industries are changing rapidly. Emerging and disruptive industries and businesses hungrily compete for a highly skilled and adaptive workforce. Digital industries, for example, are at the forefront of complex societal, cultural, technological and economic movements whose implications are yet to be fully understood. The PhD debate highlights the conundrum faced by many in Higher Education with regards to identifying, analysing and reconceptualising the knowledge and skills required for emerging labour practices. How to re-model the PhD expertise if the future of work is unpredictable?

Proponents of reforming the PhD can over-simplify the degree as a unitary and unchanging monolith, overlooking considerable disciplinary and international variations; and equally, sidelining innovations in the degree which have occurred over time. Examples abound and these include developments in Australia in the 1990s with respect to the professional doctorates, and more recent developments in the UK, which focus on advancing professional knowledge and practice (Academic Council CIT, 2012; Clarke & Lunt, 2017; Evans, Evans, & Marsh, 2008; Fell, Flint, & Haines, 2009; Lunt, McAlpine, & Mills, 2012). Other variants include the increased range of research outputs which may be subject to examination for the degree and which extend beyond the original thesis to include portfolios of work, artefacts accompanied by a critical dissertation and suites of publications. Arguably, the PhD in practice has proved more fluid and adaptable than straw-man-type arguments allow.

3 THE RECONFIGURATION AND FLATTENING OF EXPERTISE

Commentators on business, innovation and entrepreneurship claim the era of the specialist expert is in decline and is being replaced by the ascendency of the so-called expert generalist (Mansharamani, 2012; Simmons, 2015; Simmons & Chew, 2016). The era of specialist expertise was dominated by professions such as science, medicine and law with expertise conceptualised along disciplinary lines which corresponded to the organisation of learning and professional credentialing in universities. By distinction, the emerging expert generalists are said to acquire expertise through diverse industries and disciplines and apply this knowledge in innovative and entrepreneurial ways.

Aligned with this line of thinking, we are seeing universities in advanced economies foreground transferable, generalist skills rather than specialisation as the attributes required by graduates to equip them for the world of 21st-century work. A focus on industry partnerships, potential for commercialisation and entrepreneurial outcomes reflects a shift that is driven by employability concerns and a broader push for so-called rapid learning (ACOLA, 2016; Australian Government, 2011; Borrell-Damian et al., 2010; Finkel, 2016; Glover, 2006; Research Council UK (RCUK), 2017; Universities Australia, 2016, 2017).

We see this reflected in the workplace with the decline of linear, singular or predictable career pathways. Business models and employability in the 21st century are marked by ‘the emergence of massively disrupted economies’ (Oliver, 2015, p. 56) which in turn require graduates (at all levels) to be adaptable, lifelong learners. The value of Higher Education as a preparation for professional work is also being questioned. For example, an internal study by Ernst & Young found only minimal evidence that academic qualifications had an impact on job performance (Krook, 2017; Lam, 2015). Similarly, the US tech sector and companies such as Google and Apple are said to privilege the work ethic and talent of potential employees for a broad range of jobs over formal qualifications (Jackson, 2017). Added to these shifts, traditional business models and modes of employment are being challenged by the emergence of companies such as Uber and Airbnb with core structures that are ‘small and agile with a large network’ (O’Reilly, 2015).

Aoun (2017, president of Northeastern University, in his book on robot proofing Higher Education, argued for a lifelong learning model with flexible learning options that include ‘internships, co-ops, work-study jobs, global experiences, and original research opportunities’, rather than a monolithic degree. An increasing number of course options for students are not connected to a university or technical institution at all, and which in turn require less financial investment relative to return (such as Lynda.com, 2017). Massive open online courses (MOOCs) (Carey, 2015) represent a new method of online education delivery. Universities, non-governmental organisations (NGOs) and commercial providers and apps such as Duolingo offer an educational alternative that is affordable and flexible.

Collectively, these developments mark a reconfiguration and flattening of what is perceived to constitute expertise and how it may be acquired, a devaluing of specialisation and a belief that economic prosperity is tied to diversified learning and developing innovative business ventures. In addition, this new discourse gains moral and political traction in its claims for the democratisation of access to expertise, as distinct from the putative elitism of expertise contingent on Higher Education. For example, Noveck (2016) argued that when ordinary citizens are denied access to knowledge and inclusion in decision-making, ‘expertise is not compatible with the idea of equality’. The result, as Turner, 2001 put it, is that: ‘we are faced with the dilemma of capitulation to the “rule of experts” or democratic rule which is “populist”’ (p. 124). An older view, that ‘great discoveries come from years of deep specialised research’ (Monkman & Seagull, 2017), appears to have lost both favour and moral ground.

4 WHAT IS EXPERTISE?

What did expertise look like before the current disruption? Historically, expertise has been equated with extensive knowledge, high skill levels (technical, manual and intellectual), together with extensive accumulated experience in a specific field and a superior ability to rapidly solve complex and/or novel problems (Anders Ericsson, Prietula, & Cokely, 2007; Collins & Evans, 2002; Garrett, Caldwell, Harris, & Gonzalez, 2009; Grundmann, 2017; Noveck, 2016; Skovholt & Jennings, 2001; Turner, 2001). In the 1980s, Hubert Dreyfus and Stuart Dreyfus posited a developmental model of expertise from novice to expert which has become something of a benchmark (see Addis & Winch, 2017; Brey, 2001; Dreyfus & Dreyfus, 1986; Skovholt & Jennings, 2001; Turner, 2001; Winch, 2017). The Dreyfuses’ subsequent research (Dreyfus & Dreyfus, 1988) investigated computer versus human expertise, finding computers unable to replicate the tacit, intuitive knowledge and experience of human experts (more recently, see Aoun, 2017). Part of the process of building these systems involved interviewing experts ‘seeking to make explicit their often unverbalized and intuitive knowledge’ (Brey, 2001, p. 12). As Mukherjee (2017) explained, expert performance does not lie in knowing what or knowing how, its ‘most powerful element […]’ lay in ‘a third realm of knowledge: knowing why’. As Anders Ericsson et al. (2007 explained, ‘there are no shortcuts to gaining true expertise’ and knowledge management systems rarely, if ever, deal with what psychologists call knowledge’. Moreover, the 10,000-hour rule, first proposed by psychologist Anders Ericsson, who has extensively researched expertise since the 1970s, suggests that intense practice for 10 years or 10,000 hours is required to become a true expert (Gladwell, 2008). In addition, expertise is closely associated with deliberate practice and the key to success in a specific field. ‘Genuine experts not only practice deliberately but also think deliberately’ (Anders Ericsson et al., 2007), a skill which also takes time to develop to a high level.

In discussions about expertise in non-academic fora, the focus is on types of expertise that will lead to business success. The expert generalist tends to be the hero in these models rather than the specialist. Orit Gadeish, the woman commonly attributed with creating this term, believes ‘she is an expert at being a generalist’ (Johansson, 2006, p. 76). Gadeish argued that an expert generalist is ‘adept at generating innovative strategies and insights for any industry’ (p. 77). Expert generalists are often identified as successful business people, such as Warren Buffett and Elon Musk (who commenced but did not complete a PhD), for their capacity to cope with disruptive challenges that may prove difficult for a specialist. This is often attributed to adaptability, or the ability and curiosity to master and acquire expertise in different disciplines, industries, countries and on a range of topics. According to Simmons (2015), ‘the 10,000-hour rule works well in areas with defined rules that don’t change such as sports, music, and games’. However, it is argued the essential attributes for business are adaptability, the capacity for rapid change and network building with diverse people.

5 MODELS OF EXPERTISE AND THE PHD

We now turn to look at what these changing conceptions of expertise mean for the PhD. We address this question below by constructing and graphically representing five exemplar models of expertise. These are derived from a range of sources—the scholarly to the wider media. Metaphorically, models of expertise are dominated by shapes and letters: the I single field specialists; the T generalist with specialist knowledge in one field; the M has deep knowledge in more fields than a T and is more cross-functional; the Pi-shaped has two areas of expertise with generalist knowledge; the comb-shape signifies multiple fields of expertise together with generalist knowledge; the E-shape represents a combination of experience, expertise, exploration; and the key embodies expertise in multiple fields of varying levels with broad generalist skills (see Akay, 2015; Bridgstock, 2015).

Arguably, criticisms of the PhD locate graduates at the single domain specialist end of the spectrum with limited generalist knowledge and deep disciplinary knowledge, the I-shaped single field specialist (Figure 1). However, calls for increased transferability of knowledge and employability skills seek to shift the skills of PhD graduates toward greater generalist knowledge (Figure 2).

The figure of the expert generalist/polymath has been associated with a number of 21st-century entrepreneurs such as Elon Musk, as well as the original Renaissance Man, Leonardo da Vinci. Arguably, they are rare and it takes decades to acquire the requisite skill base, often as a result of working in different fields. Rather than the antithesis of the hyper-specialised expert they are credited with the ability to master a number of disciplines. The expert generalist is rich with general knowledge together with an innovation and learning advantage as a result of investigating multiple fields that can be applied in flexible combinations of which the specialist expert may not be capable.

But just how realistic is it to imagine PhD graduates as potential polymaths? An alternative model is offered by Australia’s Chief Scientist, Alan Finkel (2016). He argued that the ideal PhD graduate would possess a Pi-shaped profile, that is, they would be someone who combines two specialist areas of expertise together with generalist knowledge (Figure 3). These people are adaptive, agile and for Finkel, could ‘apply this capacity [deep discipline knowledge], beyond their primary field’. More modest than the polymath, the Pi-shaped expert would know a lot about one or two things. Neither jack of all trades nor narrow specialists; they are what might be called adaptive specialists. But just how realistic is this model and how—if at all—would PhD programmes need to change to assure graduates with this profile?

On completion of a PhD a graduate has acquired three to four years of specialised knowledge and expertise in a discipline on top of at least three to four years of generalist education which precedes this and, in many cases, prior experience in the labour market. The idea that expertise can be fast-tracked and then applied to other, often multiple disciplines or industries is open to question. There is no doubt that to have the ability to cross disciplinary or industry boundaries is desirable, however, it takes time and how far an individual can transfer from the original field of research may have limits.

The key-shaped model may address such issues (Figure 4). In this model, individuals have varying degrees of disciplinary expertise over several domains that lead to translatable knowledge and the ability to collaborate with specialists from dissimilar disciplines and industries. Ruth Bridgstock (2015), for example, argued that ‘as the number of teeth increase they support and widen the horizontal stroke/spine of the key’ resulting in greater levels of innovation, creativity and problem-solving skills.

This brings us to the last model of expertise we are considering here: the multipotentialites (Wapnick, 2017) and scanners (Sher, 2006) (Figure 5). This model promotes an eclectic mix of skills and experience that is apparently transferable across disciplines together with a high level of adaptability. Wapnick (2015) suggested in a TED Talk that there is still a need for specialists but the best teams will have both a multipotentialite and a specialist. Multipotentialites have many interests, passions and creative pursuits and Wapnick’s (2017) advice via her website Puttylike is that ‘you should stop striving for “Mastery” rather just learn until you satisfy your curiosity or [have] accomplished something cool’. Rather than a diluted version of an expert generalist or polymath (often associated terms in Wapnick’s articles), this model would add colour to the alphabet soup of expertise, reflecting the eclectic accumulation of assorted crayons through a diverse palette of pursuits.

6 IMPLICATIONS FOR THE PHD

As we have shown, promotion of generic, transferable knowledge over specialisation features in all the exemplar models of expertise discussed here bar the first. Our concern, in short, is that the expert generalist and associated models come at the price of deep, specialised knowledge. This raises numerous issues of the PhD. For example, to what extent is the pursuit of specialist knowledge compatible with development of diverse skill bundles, comprising: broad/deep; technical/non-technical; and single/multidisciplinary skill sets? As Cuthbert and Molla (2015a) has argued previously, where deficiencies are asserted in the work skills of PhD graduates, the common solution is to add more explicit skills training to address this deficiency. We see this in the Australian Government (2011) report on research workforce productivity which calls for highly specialised skills associated with a specific field of research coupled with ‘generic, high-level cognitive and technical capabilities which are broadly transferable across different domains’ (p. 1). The result is a growing wish list of additional skills added to an arguably over-burdened doctoral curriculum in the emerging pro-skills PhD (Barnacle & Dall’Alba, 2015; Cuthbert & Molla, 2015a). An alternative to adding more and more to the PhD is to re-examine and better articulate what kinds of capabilities are actually generated by the PhD in its current range of forms. This could offer a fruitful way forward, particularly given the diversity of PhD models and that the range of outcomes are currently poorly understood.

A further issue we want to raise with respect to these exemplar models of expertise is to do with scope. There’s a tendency to focus knowledge and skills—the what and how of expertise. This has two limitations we wish to highlight.

Firstly, there is a risk that such conceptions of expertise promote an ad hoc, non-integrated approach to learning and curricula which is at odds with deep, transformational learning. For example, recent studies suggest ad hoc writing skills courses can be of limited benefit to PhD candidates (Mowbray & Halse, 2010; Winch, 2017). Winch argued that development of expertise requires perceptual ability at all stages of professional education. Further, the ability to judge and act appropriately in professional contexts, such as to perceive the essentials in complex situations, requires a multidimensional and integrated educational approach encompassing aims, curriculum, pedagogy, resources and assessment (Barnacle & Dall’Alba, 2015; Winch, 2017). It is questionable that an ad hoc/add-on skills-based approach will be appropriate for this purpose.

Secondly, the focus on what and how overlooks the why, or the issue of the motivations that drive or inform experts in professional practice. A focus on knowledge and skills overlooks the question of what should orient or direct the professional practice of graduate researchers. Echoing other scholars of expertise (Dreyfus & Dreyfus, 1988; Mukherjee, 2017), Grundmann (2017, in his work examining the problem of expertise in knowledge societies, argued that expertise is misunderstood if we equate it simply with knowledge and skills, as some kind of possession. He argued expertise is relational in that it mediates between knowledge production and application, as: ‘… essentially something delivered at the request of someone else who wants it’ (Grundmann, 2017, p. 26). Expertise lies, therefore, in deployment—in what we do with what we know. For Grundmann: ‘experts mediate between the production of knowledge and its application; they define and interpret situations; and they set priorities for action’ (p. 27). The significance of this, what Grundmann calls, ‘hybrid activity’ is that it requires combining ‘elements of scientific reasoning with social and political expertise’ (p. 37). In other words, it is not just what you know but what you do with it and why.

Superficially at least, the notion of a ‘ rounded person’ and an appreciation of ‘that which should direct the use’ of one’s knowledge may call for more than specialist knowledge. The notion of generic or transferable skills, however, fails to do justice to such ethical and other qualities. Indeed, it’s difficult to imagine how the quality of the rounded person could be accumulated through atomistic skill bundles and the like. This issue also challenges the binary logic of breadth versus depth in this context. Ironically, perhaps there’s breadth in depth after all, for example, in the form of the depth of knowledge that enables an appreciation of the limitations of knowledge and the complexity of ethical practice.

Such findings point positively to the adaptability of PhD graduates and a capacity to reconcile the traditional aims of the PhD with contemporary demands of a knowledge-based society. There are nonetheless unresolved questions about just how much we should be asking from PhDs and the implications of shrinking or flattening conceptions of expertise for a degree whose hallmark is—or at least has been—depth.

7 CONCLUSION

We set out in this paper to render visible the complex, contested field in which the PhD is located with respect to debates about expertise, Higher Education and work. The demise or otherwise of the traditional university has been the subject of debate for many years (Barnett, 2015, 2017; Christensen, Eyring, & Grout, 2011; Readings, 1997). The widespread scepticism about expertise, however, presents new challenges in a technologically disrupted and changing world. Implications for the role and value of the PhD are considerable. Given the dual outcomes of the PhD—new knowledge and a professional researcher—the ill winds of expertise scepticism have the potential to be particularly pernicious.

We do not have scope in this paper for a detailed response to the question of how to develop PhD graduates for expert professional practice and there are, of course, challenges in developing such a response, particularly given the PhD varies globally and across programmes and disciplines. There are implications, for example, concerning the design of PhD programmes, the composition of supervisory teams, what is considered an allowable assessable output and what counts as a contribution to knowledge. Many universities are already diversifying their PhD delivery to address such issues; for example, see the University of British Columbia’s (2018) graduate pathways to success model. Such programmes illustrate the scope of what can be done within the so-called traditional PhD, not just the professional doctorate. It is also clear, however, that further research is needed to understand more fully the nature of PhD graduates’ engagement beyond the academy with industry, governments, NGOs and in enterprises they have formed. This is needed to get a better measure of the adaptiveness of doctoral-level expertise and to test assumptions about the need to broaden PhD programmes to include increased generic and transferable skills training at the expense of specialist expertise.

Aoun’s (2017) critique of the model of educational provision which saw ‘universities adopt a Field of Dreams sort of approach … build it and they will come’ together with monolithic degrees sounds antiquated in a disruptive and constantly changing world. It must also be acknowledged, however, that this new disruptive world has been developed by individuals who gained many of their skills—if not finally taking out their degrees—in universities. It is just possible that both universities, the education they provide up to and including the PhD are more adaptive than their critics allow. In particular, it is possible that PhD graduates’ in-depth knowledge and specialised expertise is just what is needed to resolve complex and pressing global social and economic problems.