Op-ed: Gottlieb says A.I. may take on doctors’ roles sooner rather than later
Dr. Scott Gottlieb is a CNBC contributor and is a member of the boards of Pfizer, genetic testing startup Tempus, health-care tech company Aetion Inc. and biotech company Illumina. He is also a partner at the venture capital firm New Enterprise Associates.
Researchers at Harvard presented a study demonstrating an achievement that would challenge any medical student. ChatGPT, a large language model, passed the U.S. Medical Licensing Exam, outperforming about 10 percent of medical students who fail the test annually.
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The inevitable question isn’t so much if but when these artificial intelligence devices can step into the shoes of doctors. For some tasks, this medical future is sooner than we think.
To grasp the potential of these tools to revolutionize the practice of medicine, it pays to start with a taxonomy of the different technologies and how they’re being used in medical care.
The AI tools being applied to health care can generally be divided into two main categories. The first is machine learning, which uses algorithms to enable computers to learn patterns from data and make predictions. These algorithms can be trained on a variety of data types, including images.
The second category encompasses natural language processing, which is designed to understand and generate human language. These tools enable a computer to transform human language and unstructured text into machine-readable, organized data. They learn from a multitude of human trial-and-error decisions and emulate a person’s responses.
A key difference between the two approaches resides in their functionality. While machine learning models can be trained to perform specific tasks, large language models can understand and generate text, making them especially useful for replicating interactions with providers.
In medicine, the use of these technologies is generally following one of four different paths. The first encompass large language models that are applied to administrative functions such as processing medical claims or creating and analyzing medical records. Amazon’s HealthScribe is a programmable interface that transcribes conversations between doctors and patients and can extract medical information, allowing providers to create structured records of encounters.
The second bucket involves the use of supervised machine learning to enhance the interpretation of clinical data. Specialties such as radiology, pathology and cardiology are already using AI for image analysis, to read MRIs, evaluate pathology slides or interpret electrocardiograms. In fact, up to 30% of radiology practices have already adopted AI tools. So have other specialties. Google Brain AI has developed software that analyzes images from the back of the eye to diagnose diabetic macular edema and diabetic retinopathy, two common causes of blindness.
Since these tools offer diagnoses and can directly affect patient care, the FDA often categorizes them as medical devices, subjecting them to regulation to verify their accuracy. However, the fact that these tools are trained on closed data sets, where the findings in data or imaging have been rigorously confirmed, gives the FDA increased confidence when assessing these devices’ integrity.
The third broad category comprises AI tools that rely on large language models that extract clinical information from patient-specific data, interpreting it to prompt providers with diagnoses or treatments to consider. Generally known as clinical decision support software, it evokes a picture of an brainy assistant designed to aid, not to supplant, a doctor’s judgment. IBM’s “Watson for Oncology” uses AI to help oncologists make more informed decisions about cancer treatments, while Google Health is developing DeepMind Health to create similar tools.
As long as the doctor remains involved and exercises independent judgment, the FDA doesn’t always regulate this kind of tool. The FDA focuses more on whether it’s meant to make a definitive clinical decision, as opposed to providing information to help doctors with their assessments.
The fourth and final grouping represents the holy grail for AI: large language models that operate fully automated, parsing the entirety of a patient’s medical record to diagnose conditions and prescribe treatments directly to the patient, without a physician in the loop.
Right now, there are only a few clinical language models, and even the largest ones possess a relatively small number of parameters. However, the strength of the models and the datasets available for their training might not be the most significant obstacles to these fully autonomous systems. The biggest hurdle may well be establishing a suitable regulatory path. Regulators are hesitant, fearing that the models are prone to errors and that the clinical data sets on which they’re trained contain wrong decisions, leading AI models to replicate these medical mistakes.
Overcoming the hurdles in bringing these fully autonomous systems to patient care holds significant promise, not only for improving outcomes but also for addressing financial challenges.
Health care is often cited as a field burdened by Baumol’s theory of cost disease, an economic theory, developed by economist William J. Baumol, that explains why costs in labor-intensive industries tend to rise more rapidly than in other sectors. In fields such as medicine, it’s less likely that technological inputs will provide major offsets to labor costs, as each patient encounter still requires the intervention of a provider. In sectors such as medicine, the labor itself is the product.
To compensate for these challenges, medicine has incorporated more non-physician providers to lower costs. However, this strategy reduces but doesn’t eliminate the central economic dilemma. When the technology becomes the doctor, however, it can be a cure for Baumol’s cost disease.
As the quality and scope of clinical data available for training these large language models continue to grow, so will their capabilities. Even if the current stage of development isn’t quite ready to completely remove doctors from the decision-making loop, these tools will increasingly enhance the productivity of providers and, in many cases, begin to substitute for them.
An Optimus bot from Tesla on display during the 2024 World AI Conference & High-Level Meeting on Global AI Governance at the Shanghai World Expo Exhibition and Convention Center on July 7, 2024.
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Tesla CEO Elon Musk says China’s new trade restrictions on rare earth magnets have affected the production of the company’s Optimus humanoid robots, which rely on the exports.
Speaking on a Tesla earnings call on Tuesday, Musk said that the company was working through the issue with Beijing and hoped to get approval to access the critical resources.
China, earlier this month, imposed new export controls on seven rare earth elements and magnets used in everything from defense to energy to automotive technologies. The move was in retaliation for U.S. President Donald Trump’s escalating tariffs.
According to Musk, Beijing has asked Tesla to guarantee that the rare earth magnets under expert control will not be used for military purposes.
“China wants some assurances that these aren’t used for military purposes, which obviously they’re not. They’re just going into a humanoid robot,” he said.
The new restrictions, which have raised the risk of global shortages, require exporters of medium and heavy rare earths in question to receive licenses from China’s Ministry of Commerce.
China dominates the market for many of these rare earths, with the U.S. unprepared to fill a potential shortfall, according to the Center for Strategic & International Studies.
Meanwhile, the Trump administration has into potential new tariffs on all U.S. imports of critical minerals in response to China’s export controls.
Future growth at risk?
During the earnings call on Tuesday, Musk emphasized the importance of humanoid robots to the company’s future plans.
“The future of the company is fundamentally based upon large scale autonomous cars and large scale, large volume and vast numbers of autonomous humanoid robots,” he said.
Previously, Musk had announced plans for Optimus to produce about 5,000 units this year as the technology grows as part of Tesla’s future business plans. Moreover, he said that Tesla would deploy the robots in its EV factories.
It’s unclear to what extent export controls might alter these plans. However, Musk reassured investors on Tuesday that the company still plans to produce thousands of robots this year, with thousands also expected to be deployed at Tesla factories.
The emerging technology could help Tesla drive some investor optimism as its EV business struggles, with its stock down about 37% year-to-date.
Steve Westly, founder and managing partner of The Westly Group and former Tesla Board member, told CNBC’s ‘Closing Bell Overtime‘ on Tuesday that the company needs to find a new growth engine soon.
The company is expected to face stiff competition from other humanoid robot players in China, such as Unitree Robotics and AgiBot, both of which reportedly plan to enter mass production this year. The export controls could give the Chinese players another advantage over their U.S. competitors, according to some analysts.
While Musk is upbeat about Tesla’s prospects in the space, going so far as to claim that it is ahead of the competition, he is concerned that the leaderboard will be filled with Chinese companies.
Elon Musk meets with Indian Prime Minister Narendra Modi at Blair House in Washington DC, USA on February 13, 2025.
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Tesla is cautiously navigating an entry into India, CFO Vaibhav Taneja said on Tuesday in the U.S., as the electric vehicle maker faces falling sales and tariff threats.
Speaking on an earnings call, Taneja confirmed reports that the company is working on an expansion into India, adding that it would be a great market to enter, thanks to its “big middle class.”
Nevertheless, India is also “a very hard market,” with EV imports into the country subject to a 70% tariff and about 30% luxury tax, he said, noting that this could make India-sold Tesla’s twice as expensive, he said.
“That’s why we’ve been very careful trying to figure out when is the right time… these kinds of things create a little bit of tension, which we are trying to work out,” he added.
India has signaled interest in Tesla setting up a base in the country, though the country’s protectionist policies present some obstacles for the EV maker.
Taneja’s statements come just days after Tesla CEO Elon Musk spoke with India’s Prime Minister Narendra Modi on topics including collaboration on technology and innovation.
Modi also met with Musk during his visit to Washington, D.C., in February, fueling speculation about Tesla’s plans for India. That same month, sources told CNBC-TV18 that the company was considering importing EVs from its Berlin plant into the country as early as April.
On India’s part, the government has proposed a new policy that could see EV tariffs fall from about 70% to 15% for firms that plan to localize some manufacturing in the country.
Still, experts have told CNBC that Tesla would face price pressures under the scheme, with the company likely to push for further policy reforms.
However, American President Donald Trump’s new tariffs placed on U.S. trading partners, including India, could cast a cloud over potential negotiations between Tesla and New Delhi.
Washington has imposed additional tariffs of 10% on India, but these could rise by 26% if a 90-day pause on Trump’s “reciprocal tariffs” ends without a U.S.-India trade deal.
Vice President JD Vance met with Modi in India on Monday, hailing “significant” progress made in trade talks between the two countries.
Tesla reported disappointing first-quarter results Tuesday, including a 20% year-over-year drop in automotive revenue and a 71% slump in net income.
U.S. President Donald Trump talks to the media, next to Tesla CEO Elon Musk with his son X Æ A-12, at the White House in Washington, D.C., U.S., March 11, 2025.
Kevin Lamarque | Reuters
Elon Musk said on Tuesday that he doesn’t like high or unpredictable tariffs, but any decision on what happens with them “is entirely up to the president of the United States.”
Speaking on his company’s first-quarter earnings call, with tariff-related uncertainty swirling across the economy, Musk said Tesla is in a relatively good position, compared to other U.S. automakers, because it has “localized supply chains” in North America, Europe and China.
Musk said Tesla is the “least-affected car company with respect to tariffs at least in most respects.”
Tesla reported troubling quarterly earnings and sales on Tuesday, including a 20% year-over-year drop in automotive revenue and a 71% plunge in net income. The company also said that it wasn’t providing any guidance for 2025 at least until its second-quarter update.
While Musk is one of President Donald Trump’s closest advisers, tariffs are the one issue where he’s partially broken with the administration. He recently called Peter Navarro, Trump’s top trade adviser, a “moron” and “dumber than a sack of bricks.”
On Tuesday’s call, however, Musk said, “If some country is doing something predatory with tariffs,” or “if a government is providing extreme financial support for a particular industry, then you have to do something to counteract that.”
Tesla’s stock price has been hammered since the president floated his plan for widespread tariffs earlier this month, and that was after the shares plunged 36% in the first quarter, their worst performance for any period since 2022.
Because Tesla manufactures cars that it sells in the U.S. domestically, the company isn’t subject to Trump’s 25% tariff on imported cars. But Tesla counts on materials and supplies from China, Mexico, Canada and elsewhere for manufacturing equipment, automotive glass, printed circuit boards, battery cells and other products.
Musk said he offers his advice to the president on tariffs.
“He will listen to my advice. But then it’s up to him, of course, to make his decision,” Musk said. “I’ve been on the record many times saying that I believe lower tariffs are generally a good idea.”
He added that he’s an advocate for “predictable tariff structures,” as well as “free trade and lower tariffs.”
Musk said Tesla’s energy business faces an “outsized” impact from tariffs because it sources lithium iron phosphate battery cells, used in his company’s cars, from China.
“We’re in the process of commissioning equipment for the local manufacturing of LFP battery cells in the U.S.,” he said. But he said the company can “only serve a fraction of our total installed capacity” with its local equipment.
“We’ve also been working on securing additional supply chain from non-china based suppliers, but it will take time,” he said.
Musk called Tesla the most “vertically integrated car company” but said that there are still plenty of parts and materials that come from other countries. Even though it’s built a lithium refinery in Texas, “we’re not growing rubber trees and mining iron yet,” he said.
WATCH: Tariffs on batteries out of China can end up being really costly
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