Ready to learn Artificial Intelligence? Browse courses like Uncertain Knowledge and Reasoning in Artificial Intelligence developed by industry thought leaders and Experfy in Harvard Innovation Lab.
I’m in medical school and I want to become a radiologist—but is it a ‘safe bet,’ or will AI take my job?”
Amidst the hustle-and-bustle of radiology and health tech conventions where my company meets with radiologists, medical center representatives, and fellow health tech professionals, I’m increasingly confronted with anxious questions like this. But while the tone and tenor of many discussions surrounding radiology and tech easily lends itself to such questions, the reality is that radiology remains a solid career path, and my answer is that AI will only serve to dramatically improve radiologists’ workplace conditions. While AI may take over certain tasks currently performed by radiologists, jobs in the field will remain abundant—and growing reliance on AI technology will only augment the other tasks that occupy a radiologist’s day.
Here are four reasons today’s budding radiologists need not fear AI displacement.
The power of communication
A crucial aspect of any radiologist’s job is communicating with other medical professionals. Radiologists glean and offer insight in their conversations with other specialists, and these complex conversations are as central to the profession as other tasks, like image analysis.
Machines are incapable of conducting these types of conversations with humans, giving radiology professionals a powerful and irreplaceable role. Moreover, doctor-patient communication is both smart medicine and in high demand amongst patients; this level of human connection cannot be readily supplanted.
AI means radiologists can focus on what’s most important
Equipped with AI to perform tasks such as image scanning, anomaly detection, and the like — radiologists will have more time to focus on the most critical elements of their jobs: giving more direct attention to each review, focusing in on the anomalies spotted in each scan, and providing a personal touch by interfacing with patients and other medical specialists.
Too many variables
Even as AI technology becomes increasingly sophisticated, there are too many complex issues in radiology for AI to address comprehensively — meaning that AI will therefore not be able to dictate a sufficiently holistic response when issues arise.
Humans harbor contextual and critical thinking faculties that are essential when making decisions based on complex information. What’s more, while machines can be trained with sufficient data to detect outliers, humans do not need to be constantly programmed with more data to do so.
Productivity drives demand
When AI is integrated into existing workflows, a stronger network of technology will facilitate more natural processes to facilitate a workflow capable of handling more cases – demanded in today’s medical environments.
AI’s normalization of radiologists’ workflow will foster both better organization and better healthcare for patients — reducing errors, enhancing communication, and enabling radiologists to devote more time to complex tasks. As the process is regulated, the work that radiologists are currently performing will be replaced with more and more productive work. This process enables a virtuous cycle: with greater productivity will come higher demand, better capabilities and better service.
From CT and MR scans to the emergence of tele-radiology, the radiology profession has already shown a remarkable ability to integrate new technologies and processes into its workflow. Rising healthcare demands will create the need for new efficiencies, which will enable radiology professionals to better perform their jobs and manage workflows.
AI will significantly transform radiology, allowing radiologists to analyze more scans in less time, prioritize scans, and maintain a high level of accuracy. While such benefits are considerable, the fact that AI will take over certain tasks does not mean it will be displacing radiologists’ jobs. AI cannot replace the invaluable communication human radiologists provide, and in the case of particularly complex scans, the technology is not advanced enough to replace human analysts with their experience and insights. In the final analysis, AI will provide radiologists the space to focus more of their time and energy on the aspects of radiology that have inspired people to join the profession in the first place—diagnostics, patient care, and medical collaboration.
Given mounting workloads and the severe shortage of radiologists in the face of rising demand, AI augmentation will be a tremendous boon to the profession—not an existential threat.
