The European Society of Radiology has published a white paper entitled “What the radiologist should know about artificial intelligence”.
This paper aims to provide a review of the basis for application of AI in radiology, to discuss the ethical and professional impact of AI technologies and to consider possible future developments.
Artificial Intelligence (AI) is one of the fastest growing areas of information technology with great relevance to radiology. PubMed returns 82,066 publications on Artificial Intelligence; 5,405 when combined with Radiology.
Radiologists, trainees and potential future radiologists need to understand the implications of AI for the specialty, what it means, how it can contribute to the radiological profession and how may change it in the future. The European Society of Radiology (ESR) is aware of the impact that IA is having on the field of radiology, from a technical-scientific, ethical-professional and economic point of view.
Much fear has been generated among radiologists by the statements in public media from researchers engaged in AI development, predicting the imminent extinction of radiology as a specialty. For example, Andrew Ng (Stanford) stated that “a highly-trained and specialized radiologist may now be in greater danger of being replaced by a machine than his own executive assistant“, while Geoffrey Hinton (Toronto) said “radiologists are like the coyote that is already over the edge of the cliff, but has not yet looked down and does not realize that there is no ground underneath him. You should stop training radiologists now. It is quite obvious that within 5 years, deep learning will go better than radiologists […..] We already have a lot of radiologists [….]” .
For this reason, the European Society of Radiology has decided to publish a white paper to deepen the applications of IA in radiology, examine the barriers that slow down its spread, the challenges that radiologists will face, the regulatory and technical aspects.
Even if you are not a radiologist, this paper should be read anyway, in order to understand what future is expected in the diagnostic imaging.