What does it mean to be a scholar in an age of AI?

The academic profession, including in business schools, is like an exclusive members club. Faculty members seek tenure, promotions and greater prestige among peers based on a well-understood set of elite rules. A scholar whose article is published in the most prestigious journal, with the highest standards for acceptance and rejection, will achieve rewards in a way publication in a less-lauded journal may not. 

But this long-established code of the academic professor is based on a pivotal understanding: scarcity. The underlying premise is that there is a very limited number of truly exceptional journal articles competing for the career-advancing spots in the very best journals.  

AI can speed up article creation and more

So what happens when generative artificial intelligence (AI) upends this understanding by allowing the creation – all within ethical academic bounds and peer-acknowledged excellence – of far more than a limited number of exceptional articles, perhaps even a virtually limitless supply of them? 

That’s the focus of an editorial, ‘From scarcity to abundance’, in the Academy of Management Journal (AMJ) – one of the most elite journals in the field of business management, co-authored by Matthew Grimes, Professor of Entrepreneurship and Sustainable Futures at Cambridge Judge Business School. 

Elite academic articles often take many years to reach publication stage, but the authors say “generative AI tools now increasingly offer capabilities aimed to increase those efficiencies and the pace at which those efficiencies are realised by scholars” – a very polite way of saying that AI may seriously disrupt the entire supply chain for academic articles, which currently assumes a molasses-like speed. 

Then there’s another key question: can AI surface interesting research questions as well as the minds of human scholars? “The extent to which generative AI will augment or replace academics in the creative tasks associated with scholarship is a matter of debate (indeed, the authors of this editorial have internally expressed such debate), yet the potential should be taken seriously,” the editorial says. 

What does it now mean to be a scholar or academic journal? 

“We pose 2 questions, given the potential promise of generative AI to increase both the quantity and quality of scholarship,” says the editorial:

1. What does it mean to be a scholar when the know-what’and know-how barriers to becoming one are minimised (anyone who wants to can participate in scholarship)?
2. What does it mean to be a journal that publishes scholarship when the field is flooded with manuscripts that meet the highest possible human-mediated standards for:
   • practical importance
   • theoretical intrigue
   • methodological rigor?

The editorial makes clear that the journal’s editors don’t have all the answers at this still-young point in the evolution of generative AI, but makes equally clear that these difficult questions need urgently to be asked. 

Asking awkward questions and prompting deep thinking of academics 

“The future of academic publishing in the age of AI poses very awkward questions for academics to be asking about ourselves, our colleagues and our profession,” says editorial co-author Professor Grimes. “We are all academics trained and working in an era where the scarcity of truly first-class research was the guiding principle, but we are looking at a rapidly advancing new era of generative AI in which the scarcity of knowledge production can no longer be assumed. 

“The editorial doesn’t attempt to curb the use of generative AI in producing scholarship: there are clearly some hazards such as well-documented ‘AI hallucinations’ (relevant but false information) and ‘deep research fakes’ (data manipulation to deceive the academic community), but there is also truly great research potential in AI in areas ranging from the creation of academic articles, to bridging the gap between academic theory and practice, to the ability to improve the peer-review system of evaluating the merits of academic literature. 

“Our purpose in writing this editorial is to prompt some deep thinking and soul searching amongst ourselves and our peers about what we want our profession to look like given the rapid advances in AI,” says Matthew. 

The authors say they don’t seek to codify the academic profession’s response to AI, but rather to examine different uncertainties that will affect scholarship. “We are merely at the beginning of a conversation we expect to be having for many years to come,” they say. 

AI in academic journals: good faith should not be assumed 

The editorial also looks at how journals currently deal with generative AI, noting that the Academy of Management will soon publish guidelines on AI use for its suite of journals and conference submissions. 

“At the moment, however, many existing journal policies surrounding generative AI appear to be operating on the assumption that authors, reviewers, and editors will act in good faith,” the authors say. Given the risks such as “hallucinations” coupled with rapid advances in AI, “we believe such an assumption is inadequate” and that governance rules are needed such as specialised review protocols for papers that employ generative AI. 

The editorial then returns to what generative AI means for the academic profession. 

Generative AI challenges the distinctive value of management scholarship 

“Our investigation of the implications of generative AI for management scholarship and for our profession is not meant as a call to arms to defend the profession and its current boundaries,” the editorial concludes. 

“Instead, in the short-term, we view this as a call to prepare ourselves, as well as our current and future PhD students, with the appropriate knowledge not only to use but, more critically, to evaluate algorithmic knowledge production.” 

“In the long term, we view this editorial as a call to rethink the distinctive value of our profession in a world of abundant management scholarship. In other words, we suspect that a plausible generative AI-led shift from scarce academic knowledge production to abundant academic knowledge production will inevitably increase the urgency around answering a fundamental question: To what problems in society is management scholarship the (unique) solution?”