AI's impact on professions

Recent additions include research on the impact of AI and digital technologies on PROFESSIONS.

The go-to reference is Richard Susskind and Daniel Susskind’s The Future of the Professions (Oxford University Press, 2015).

The two authors warn professions that the power of AI will challenge the “grand bargain” they’ve operating under for 200 years or more,—that is, the right to exclusive practice of particular services on the basis of possessing complex knowledge and skills. The exponential increase in the capabilities of digital technologies, they think, will inevitably have a negative impact on profession’s employment prospects:

“over time–by which we mean decades, rather than overnight–there will be technological unemployment in the professions. In other words, there will not be sufficient growth in the types of professional task in which people, not machines, have the advantage to keep most professionals in full employment” (291)

Aside from the employment issue, technology will change the very core of professional work. As it makes it possible to standardise and systematise substantial amounts of complex information, the knowledge that was once the preserve of the professionals and the reason for their privileges will be made available to non-professionals. This will have positive consequences for the broader population.

Before this broad study of professions, Richard Susskind explored the impact of digital technologies on the practice of the law, in The End of Lawyers? (Oxford University Press , 2008) and Tomorrow’s Lawyers (OUP, 2013).

Other legal experts are not as worried about the impact of technology on their profession. Philip Segal in “Legal Jobs in the Age of Artificial Intelligence” (Savannah Law Review 5, 2018) writes that

“When telephones were new, many respectable lawyers would not have one on their desks. Senior lawyers greeted word processors and computers the same way in the 1970s. Those efficiencies were unstoppable, and in their presence more law jobs were produced than ever before. What we call artificial intelligence is no different. Messengers and typists lots their jobs when legal and non-legal firms adopted word processing, voicemail and other new technology. They were replaced with more people who could add more value. Artificial intelligence will do the same thing: out will go the lawyers who do repetitive, uncreative work. Lawyers who survive will need particular skills to manage the machines that will make law more productive and therefore more affordable. The productivity will make room for lawyers in brand new fields—some foreseeable and some not.”

Milan Markovic, in “Rise of the Robot Lawyers” (Arizona Law Review 61, 2019) has a similar assessment:

“This article challenges the notion that lawyers will be displaced by artificial intelligence on both empirical and normative grounds. Most legal tasks are inherently abstract and cannot be performed by even advanced artificial intelligence relying on deep-learning techniques. In addition, lawyer employment and wages have grown steadily over the last twenty years, evincing that the legal profession has benefited from new technologies, as it has throughout its history. Lastly, were large-scale automation of legal work possible, core societal values would counsel against it. These values are not merely aspirational but are reflected in the multifaceted role of lawyers and in the way that the legal system is structured.”

Experts in other professions also remain optimistic about the employment impact of technology in their own field.

In psychiatry for instance, Brunn, et al. write that:

“Given their specific skillset— including, notably, complex social skills—it seems likely that psychiatrists may actually be relatively well sheltered from job displacement. Indeed, psychiatry requires greater integration of cultural and psychosocial factors than other, more patternbased disciplines. Hence, in a perspective where competencies that are complementary to machine prediction will become more valuable in the future while competencies that are substitutes for machine prediction will become less valuable, psychiatrists could capitalize on the potential benefits of AI in psychiatric practice” (Academic Psychiatry 44(4), p.462)

This is confirmed by Doraiswamy, Blease and Bodner, who report that in a major survey of their profession:

“Only 3.8 % of respondents felt it was likely that future technology would make their jobs obsolete and only 17 % felt that future AI/ML was likely to replace a human clinician for providing empathetic care” (Artificial Intelligence in Medicine 102, 2020).

One area that is widely predicted to be severely impacted, and is already undergoing major changes, is finance.

In a 2018 report for the Boston Consulting Group, which sought to predict job losses in the industry by 2027, He, Guo, Zhou and Guo concluded that

“about 23% of China’s financial sector jobs will be disrupted by AI by 2027. The job cuts in the banking, insurance and capital markets will be 22%, 25% and 16%. The working hours of the remaining 77% will be reduced by about 27% due to AI, equivalent to an increase in efficiency of 38%.”

As in the case of law, however,

“AI will also create employment demand in the financial industry. It will also retain employees who are more creative, better communicators and able to solve complex problems”.

AI and machines are also anticipated to have major disruptive impacts in the health professions, in medical research, for physicians in the core areas of diagnosis, treatment and prognosis, and in nursing.

In these fields as well, however, expert opinions are divided. In a “Head to Head” debate published in 2018 in The BMJ (363), Jörg Goldhahn rebutted point by point the arguments for the irreplaceability of human practitioners, notably on account of their capacity for caring and compassion. He concluded that

Doctors as we now know them will become obsolete eventually.

In reply, Vanessa Rampton made the case that it was not just the capacity for genuine compassion that would make doctors irreplaceable, but also the fact that illnesses cannot be reduced to measurable symptoms. The lateral and holistic thinking of human specialists would still be required to take into account all non-quantifiable factors:

Although they will augment the capacities of physicians, machines will never replace them entirely. In particular, physicians will remain better at dealing with the patient as a whole person, which involves knowledge of social relationships and normativity. As the Harvard professor Francis Peabody observed in 1927, the task of the doctor is to transform “that case of mitral stenosis in the second bed on the left” into the complex problem of “Henry Jones, lying awake nights while he worries about his wife and children.” Humans can complete this transformation because they can relate to the patient as a fellow person and can gain holistic knowledge of the patient’s illness as related to his or her life. Such knowledge involves ideals such as trust, respect, courage, and responsibility that are not easily accessible to machines.

A comparable case is made by Joseph Pepito and Rozzano Locsin about nursing:

“To be relevant in the future technological world, by growing as caring professionals, nurses can leave the more basic tasks to machines such as taking the vital signs, performing nursing procedures, and medication dispensing, while the human nurses attend to more complex issues. This would not only unload the nurses of their routine tasks to a machine, it would also give them enough freedom to plan with the aid of artificial intelligence in the care of patients as they participate in their care. Because machines are unable to understand the unpredictable aspects and contexts of nursing situations, human nurses will be able to provide better care to patients because of their ability to engage in participative encounters involving, among other things the unpredictable human emotions and use of critical thinking skills in making clinical decisions. Person-centered care would be implemented at a participative level. Focus would be on the person being nursed rather than on fixing the person or the completion of a person's missing parts.” (“Can Nurses remain relevant in a technologically advanced Future?” International Journal of Nursing Sciences 6(1):110)

The repository also includes entries on AI in Science and AI in Teaching.

This is obviously an area of huge interest with growing numbers of publications from multiple specialist fields. Contributions from site visitors would be particularly welcome to enrich the repository and keep it up-to-date.

Image

“The Doctor dismissing Death” (1785) (after Thomas Rowlandson). Etching: Peter Simon (1764–1813), Aquatint: Francis Jukes (1747–1812). Metropolitan Museum of Art.