A recent study published in The British Medical Journal tested whether artificial intelligence (AI) could pass the examination for the Fellowship …

A recent study published in The British Medical Journal tested whether artificial intelligence (AI) could pass the examination for the Fellowship of the Royal College of Radiologists (FRCR). Radiologists in the United Kingdom (UK) must pass the FRCR examination before completing their training. Assuming that AI can pass the same test, it could replace radiologists. The final FRCR exam has three components, and candidates require a passing mark in each component to pass the exam overall. In the rapid reporting component, candidates must analyze and interpret 30 radiographs in 35 minutes and correctly report at least 90% of these to pass this part of the exam. This session gauges candidates for accuracy and speed.

The idea behind centaur chess was simple: while the best AI could now defeat the best human at chess, an AI and human working together (a "centaur") would be the most powerful player of all, because man and machine would bring complementary skills to bear. And because humans and AIs are strong on different dimensions, together, as a centaur, they can beat out solo humans and computers alike." AI is now so far superior to humanity in this domain that a human player would simply have nothing to add. For instance, once an AI system can provably drive a truck better and safer in all conditions than a human can--the technology is not there today, but it is getting closer--it simply will not make sense for humans to continue driving trucks. A common refrain in the field of radiology these days goes like this: "AI will not replace radiologists, but radiologists who use AI will replace radiologists who do not." This is a quintessential articulation of the myth of augmentation. So to start, AI will indeed be used to augment human radiologists: to provide a second opinion, for instance, or to sift through troves of images to prioritize those that merit human review. Once it is established beyond dispute that neural networks are superior to human radiologists at classifying medical images--across patient populations, care settings, disease states--will it really make sense to continue employing human radiologists? From security guards to accountants, from taxi drivers to lawyers, from cashiers to stock brokers, from court reporters to pathologists, human workers across the economy will find their skills out of demand and their roles obsolete as increasingly sophisticated AI systems come to perform these activities better, cheaper and faster than humans can. Chief among these are roles that involve empathy, camaraderie, social interaction, the "human touch." Human babysitters, nurses, therapists, schoolteachers, and social workers, for instance, will continue to find work for many years to come. The idea behind centaur chess was simple: while the best AI could now defeat the best human at chess, an AI and human working together (a "centaur") would be the most powerful player of all, because man and machine would bring complementary skills to bear. And because humans and AIs are strong on different dimensions, together, as a centaur, they can beat out solo humans and computers alike."

Dating back to the Industrial Revolution, people have speculated that machines would render human ... [ ] work obsolete. Unlike in earlier eras, artificial intelligence will prove this prophecy true. "When looms weave by themselves, man's slavery will end." Stanford is hosting an event next month named "Intelligence Augmentation: AI Empowering People to Solve Global Challenges." This title is telling and typical.

Now that this attention-grabbing headline has drawn you in, let me clarify. Data scientists should not partake in illegal drugs. Data scientists should participate in pharmacological research, as artificial intelligence and machine learning can add value, even when the data scientist does not have a background or training in physics, biology, chemistry, or medicine. The CAIA Association and FDP Institute had a recent conversation with Woody Sherman, the CSO of Silicon Therapeutics. While many of us can be left behind in a discussion of computational drug discovery, it seems that almost everyone today is a budding epidemiologist trying to better understand the prevention and spread of COVID-19, so let's continue.

This is part of a series of stories examining how artificial intelligence is disrupting industries. Can artificial intelligence (AI) make health care smarter? The technology sector is investing heavily in new applications for AI in medicine, in the hope that algorithms can bring new capabilities to medical diagnoses and patient care. One of the areas where artificial intelligence is emerging as a valuable tool is radiology, which offers an early study in the benefits of AI in medicine, and its potential impact on the healthcare workforce. Anytime a patient breaks a bone, sprains an ankle or hits their head, the radiology industry goes to work, using x-rays, CT scanners, MRI machines and other tools and techniques to take a closer look inside the human body without the need for surgery.

It's ridiculous to think that in the coming two decades, artificial intelligence will replace radiologists, says AI expert Eliot Siegel, M.D. Even if AI got good at reading medical images, "radiologists do much more than that," he says. In the accompanying video interview, Siegel, a radiology professor at the University of Maryland School of Medicine and chief of Imaging Services at the VA Maryland Health Care System, will highlight these and other reasons why it's ridiculous to think computers will replace radiologists. He'll discuss them during a SIIM debate on the subject June 2 that will include Bradley J. Erickson, M.D., associate research chair in the radiology department at Mayo Clinic in Rochester. AI might not replace radiologists, but it could radically change the practice of radiology in just a few years, he says.

In this special guest feature, Elad Walach, CEO of Aidoc, offers four important reasons today's budding radiologists need not fear AI displacement. Elad is the Founder and CEO of Aidoc, a smart radiology company that uses deep learning to streamline the workflow of radiologists. After earning his Master of Science in Computer Science from Tel Aviv University, he served as a Researcher and Team Leader in the Israeli Air Force, focusing on computer-vision and machine learning. His success in operational solutions and leadership has been pivotal in establishing Aidoc. He is a seasoned public speaker, appearing at various institutions including the Hebrew University of Jerusalem, Israel Society for Biological Psychiatry and Shaare Zedek Medical Center.

Recent advances in artificial intelligence have led to speculation that AI might one day replace human radiologists. Researchers have developed deep learning neural networks that can identify pathologies in radiological images such as bone fractures and potentially cancerous lesions, in some cases more reliably than an average radiologist. For the most part, though, the best systems are currently on par with human performance and are used only in research settings. That said, deep learning is rapidly advancing, and it's a much better technology than previous approaches to medical image analysis. This probably does portend a future in which AI plays an important role in radiology.