What is a profession? The classical understanding is that professions are self-organised and self-regulating groups of experts who control the application of specialised knowledge in relation to particular areas of social life. This is reflected in the dictionary definition as an occupation “that involves prolonged training and a formal qualification”; these are the means through which a profession regulates its practice and draws a boundary between those within the profession and those outside of it. We can obviously think of academics as a professional group in this sense, given the significance of credentials to academic work, the lengthy training required to enter it and the ongoing role which professional associations play in shaping the norms of academic life. There are immense variations in what this looks like in practice, within and between systems, but the starting point for this post is that academics constitute a professional group in the classical sense.
In his seminal work on the sociology of professions, Andrew Abbott offers a looser definition in which “professions are exclusive occupational groups applying somewhat abstract knowledge to particular cases” (pg 8). This captures the variation within higher education more effectively than the classical understanding, pointing to the core of professional status which might otherwise be complicated by the breakdown of the Humboldtian ideal in which research and teaching are tightly connected, as well as the limits on collegial self-organisation ensuing from the marketisation of the academy. These conditions mean there are turf wars over who is an academic and who is not, whether from academic elitism (e.g. hostility towards professors of practice without PhDs) or from academic managers (e.g. the requirement for a PhD within institutions where these have not been traditionally expected). But what defines academics as a profession is the application of abstract knowledge to particular cases (i.e. teaching, research, impact) coupled with a boundary between who does this as an academic and who does it in some different capacity.
Abbott stresses how professional groups exercise their influence at the intersection between theoretical knowledge and practical intervention; they control the abstractions which shape how knowledge translates into practical techniques, including the definition of the ‘problems’ to which those techniques applied and the form taken by the techniques themselves:
For me this characteristic of abstraction is the one that best identifies the professions. For abstraction is the quality that sets interprofessional competition apart from competition among occupations in general. Any occupation can obtain licensure (e.g., beauticians) or develop an ethics code (e.g., real estate). But only a knowledge system governed by abstractions can redefine its problems and tasks, defend them from interlopers, and seize new problems—as medicine has recently seized alcoholism, mental illness, hyperactivity in children, obesity, and numerous other things.
The System of Professions, pg 8
What defines the profession is a theoretical body of knowledge which sits in a dynamic relationship with practice. In contrast to the orthodox approach to professions which exclusively focused on their social organisation, Abbott draws attention to the nature of professional work and its relationship to that organisational context. As he puts it, “the central phenomenon of professional life is thus the link between a profession and its work, a link I shall call jurisdiction” (pg 20). This is the field upon which competition between professions plays out, in competing claims to jurisdiction constituted through struggles over how problems and interventions are defined. This account emphasises how the content of professions is what professionals actually do:
Sociological work on professions, including much of the power literature of the last decade, pays little attention to the actual work that is done and the expertise used to do it. Freidson’s work is a striking exception. Historical study, by contrast, has emphasized the actual work performed. In professions as diverse as librarianship, engineering, psychiatry, and the clergy, historians have shown the intimate relation of professional structure and culture to work itself. The sociological theorists have not learned from this that work must be the focus of a concept of professional development
The System of Professions, pg 18
This is where the impact of technology can be profoundly significant, as an exogenous shock with the capacity to force change in professions. In some cases this can mean the death of professions, if a change in the technological foundation of their work doesn’t provoke a successful reconfiguration of their jurisdiction. From pg 28:
We are so fascinated with the success of American medicine, in particular, that we forget the specialized, knowledge-based occupations that have disappeared. Some have gone because the organization or technology that created them has disappeared. The railroad professions and protoprofessions—dispatchers, agents, surgeons—are one such example. Had they developed knowledge that abstracted beyond the world of the railroad, they might have survived its fall. But dispatching did not become what we now think of as operations research, even though its central task was essentially under the jurisdiction now held by that.
How professions respond to technological change needs to be a matter of the substance of their work, because their claims to jurisdiction are grounded in the routine tasks through which their work is conducted. As Abbott puts it, “Each profession is bound to a set of tasks by ties of jurisdiction, the strengths and weaknesses of these ties being established in the processes of actual professional work” (pg 33). Work is where abstract claims of jurisdiction are operationalised or fail to be operationalised over time; the latter will lead to deterioration and diminishment over time. If there are other ways to perform tasks without professional expertise, or the tasks themselves become redundant, the legitimacy of the professions can rapidly evaporate. What are they for?
Technology operates by changing the nature of tasks, creating new ones and providing alternative ways of doing the same thing. Consider the claim the MOOC would render the university redundant by providing globally scalable ways of teaching more effectively at lower cost. Or the resurgence with generative AI of the claim that robotic tutors could replace university teachers. Or the infamous claim that ‘big data’ rendered theory redundant. All of these techno-utopian claims represented profound threats to the academic profession but fizzled out because the underlying technology has thus far prove disappointing (MOOCs and robotic tutors) or academic expertise reconsolidated itself to claim jurisdiction over the emerging arena (the transition from ‘big data’ to computational social science and social data science). If we assume that generative AI will not fall into the former category, it means the latter response is crucial in so far as that the academic profession will need to reconstitute itself in ways which demonstrate a ‘value added’ under rapidly changing socio-technical circumstances.
The problem is that what Abbott describes as the “objective foundation for professional tasks” (pg 39) has been shifting for some time, which Steve Fuller imprecisely (but basically correctly) characterises as the challenge the internet poses to academic monopoly over the knowledge system. The knowledge system can now in a real sense talk to anyone who wants to interact with it. The political economy of platform capitalism, the unreliability of LLMs and the disastrous second order effects likely to emerge from this are all crucial to making sense of this fact, but I want to insist it is nonetheless now a social fact. This has fascinating implications for the academic profession which I increasingly feel I will be exploring for years.
The motivation underlying my upcoming Generative AI for Academics is that the professional cultures which emerge around these technological shifts will be crucial for how the academic profession changes or dies in the coming years. Not least of all in terms of the possible reconstitution of our jurisdictional claims, which is a creative struggle in abstraction which can itself be enriched through generative AI. The prioritisation of digital literacy which preceded generative AI can be helpfully framed in these terms i.e. we no longer monopolise (digitalised) knowledge but rather constructive engagement with it. There is a possibility for professional expansion of the form Abbott identifies in historical case studies in which domains are expanded, in this case supported by the cognitive-multiplier effects of generative AI. From pg 25:
In consequence, its chief jurisdictional monopoly, conveyancing, had by this century been delegated to a subordinate professional group, the managing clerks, who did the work under the very loose supervision of solicitors. This internal subordination of routine work is a characteristic strategy of professions claiming more jurisdiction than they can effectively serve, American medicine being the best example.
But the trajectory of social media within higher education makes me extremely pessimistic this will happen. This was a tiny ripple in the pond in comparison; a certain range of tasks which constitute our role was shifted by the emergence of social platforms and the productive responses in the early years were not sustained over time. I increasingly suspect that generative AI will be a disaster for the knowledge system and wider society, but one which academics have the capability of mitigating if we can establish a reflexive culture which enables us to deploy it effectively in responding to the wider socio-technical transformation it is bringing about.
TL;DR. Here’s Claude AI’s summary 😬 This post analyzes how generative AI threatens academic jurisdiction over knowledge production. Andrew Abbott’s theory defines professions by their control over abstract knowledge applied to practical problems. New technologies can disrupt professions by changing those problems and knowledge domains. Generative AI allows novel knowledge production outside academic control. Past innovations like MOOCs did not fundamentally threaten academics’ jurisdiction over teaching and research. But generative AI represents a more foundational challenge to academics’ monopoly over knowledge. Already social media has eroded academic jurisdiction without an effective professional response. Rapidly developing generative AI will further disrupt knowledge circulation. Academics must quickly build digital literacy and reflexive professional cultures to retain influence over the emerging socio-technical landscape. If academics fail to assert jurisdiction over generative AI’s impacts, their profession faces decline. By creatively expanding jurisdiction, academics can constructively integrate generative AI’s opportunities while constraining its risks. But time is running out for this proactive professional self-reinvention.
Mark Carrigan 