Artificial Intelligence (AI) is presented in the media as likely to have huge impacts on knowledge work for better or worse. We should ask ourselves whether and how this change is going to happen.

AI is a broad umbrella term that refers to the ability of computers to process large amounts of data, learn, perform knowledge tasks, and make decisions without human intervention. AI enables computers to perform typically human tasks and potentially permeate all facets of our lives. Examples from various domains are conceivable, such as self-driving taxis, robots that carry out surgery, packages delivered by drones to our backyards, automated court decisions,  computers that trade securities, or carry out bombings in times of war.

This development of AI, which has been called the fourth industrial revolution, has sparked a debate about the influence of AI on knowledge work. Knowledge workers’ primary activities are collecting, processing, and providing information. Examples are consultants, lawyers, scientists, physicians, and engineers.

Some authors argue that AI will change knowledge work radically and that computers will replace many knowledge workers. This technologically deterministic view assumes that technology is an essential causal factor for social change. There are two variants of this view. According to the utopian variant, replacing knowledge workers with AI leads to major benefits, such as happier people, efficiency gains, more leisure time, and a better functioning society. According to the dystopian variant of technological determinism, AI leads to significant problems, such as massive job losses, poverty, inequality, and a dehumanized society.

Others oppose this deterministic view on AI, arguing that humans have the power to shape, adapt, use or reject this technology in a way that suits them. This adaptation occurs in specific social, cultural, economic, and political circumstances, making technology use varied, hard to predict, and context-dependent. This view on the effects of technology on work is called Social Shaping of Technology (SST).

Radiology appears to be a prime discipline affected by AI within the healthcare domain. AI applications have emerged to interpret brain scans, mammograms, CT, and MRI scans faster and better than radiologists. For example, AI systems can better detect breast cancer than human radiologists. This raises the question of how AI will change the work of radiologists now and in the future.

Geoffry Hinton, a well-known computer scientist, expressed a technologically determinist view by claiming that AI will replace the radiology profession and that we should stop training radiologists. Andrew Ng, professor and expert in AI at Stanford, stated that highly-skilled and specialized radiologists are more likely to be replaced by AI than by radiologists in training.

Drawing on an SST perspective, others like Tomer Nawrocki argue that these radical predictions about radiologists are exaggerated and based on commercial hype. AI can change certain aspects of radiologists’ work and replace some tasks, but it will not make the radiological profession obsolete. Significant social, political, ethical, legal, and economic barriers to the use of AI in radiology will prevent radiologists from becoming unemployed. Radiologists are powerful professionals and their profession is multifaceted and involves more than just interpreting images. As a result, AI will enable radiologists to reinvent their work by gradually embedding AI's capabilities.

In the spirit of the Social Shaping of Technology, our research focuses on how new technologies, such as AI, can change people's work and how knowledge workers are not passive bystanders but have the power to shape the technology in expected and unexpected ways.  Feel free to contact me if you have questions about the inter-relationship between technology, people, and organizations.

 Author: Albert Boonstra - albert.boonstra@rug.nl