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.
Jakub Porzycki | Nurphoto | Getty Images
Mark Zuckerberg’s announcement this week that Meta would pivot its moderation policies to allow more “free expression” was widely viewed as the company’s latest effort to appease President-elect Donald Trump.
More than any of its Silicon Valley peers, Meta has taken numerous public steps to make amends with Trump since his election victory in November.
That follows a highly contentious four years between the two during Trump’s first term in office, which ended with Facebook — similar to other social media companies — banning Trump from its platform.
As recently as March, Trump was using his preferred nickname of “Zuckerschmuck” when talking about Meta’s CEO and declaring that Facebook was an “enemy of the people.”
With Meta now positioning itself to be a key player in artificial intelligence, Zuckerberg recognizes the need for White House support as his company builds data centers and pursues policies that will allow it to fulfill its lofty ambitions, according to people familiar with the company’s plans who asked not to be named because they weren’t authorized to speak on the matter.
“Even though Facebook is as powerful as it is, it still had to bend the knee to Trump,” said Brian Boland, a former Facebook vice president, who left the company in 2020.
Meta declined to comment for this article.
In Tuesday’s announcement, Zuckerberg said Meta will end third-party fact-checking, remove restrictions on topics such as immigration and gender identity and bring political content back to users’ feeds. Zuckerberg pitched the sweeping policy changes as key to stabilizing Meta’s content-moderation apparatus, which he said had “reached a point where it’s just too many mistakes and too much censorship.”
The policy change was the latest strategic shift Meta has taken to buddy up with Trump and Republicans since Election Day.
A day earlier, Meta announced that UFC CEO Dana White, a longtime Trump friend, is joining the company’s board.
And last week, Meta announced that it was replacing Nick Clegg, its president of global affairs, with Joel Kaplan, who had been the company’s policy vice president. Clegg previously had a career in British politics with the Liberal Democrats party, including as a deputy prime minister, while Kaplan was a White House deputy chief of staff under former President George W. Bush.
Kaplan, who joined Meta in 2011 when it was still known as Facebook, has longstanding ties to the Republican Party and once worked as a law clerk for the late conservative Supreme Court Justice Antonin Scalia. In December, Kaplan posted photos on Facebook of himself with Vice President-elect JD Vance and Trump during their visit to the New York Stock Exchange.
Joel Kaplan, Facebook’s vice president of global policy, on April 17, 2018.
Niall Carson | PA Images | Getty Images
Many Meta employees criticized the policy change internally, with some saying the company is absolving itself of its responsibility to create a safe platform. Current and former employees also expressed concern that marginalized communities could face more online abuse due to the new policy, which is set to take effect over the coming weeks.
Despite the backlash from employees, people familiar with the company’s thinking said Meta is more willing to make these kinds of moves after laying off 21,000 employees, or nearly a quarter of its workforce, in 2022 and 2023.
Those cuts affected much of Meta’s civic integrity and trust and safety teams. The civic integrity group was the closest thing the company had to a white-collar union, with members willing to push back against certain policy decisions, former employees said. Since the job cuts, Zuckerberg faces less friction when making broad policy changes, the people said.
Zuckerberg’s overtures to Trump began in the months leading up to the election.
Following the first assassination attempt on Trump in July, Zuckerberg called the photo of Trump raising his fist with blood running down his face “one of the most badass things I’ve ever seen in my life.”
A month later, Zuckerberg penned a letter to the House Judiciary Committee alleging that the Biden administration had pressured Meta’s teams to censor certain Covid-19 content.
“I believe the government pressure was wrong, and I regret that we were not more outspoken about it,” he wrote.
After Trump’s presidential victory, Zuckerberg joined several other technology executives who visited the president-elect’s Mar-a-Lago resort in Florida. Meta also donated $1 million to Trump’s inaugural fund.
On Friday, Meta revealed to its workforce in a memo obtained by CNBC that it intends to shutter several internal programs related to diversity and inclusion in its hiring process, representing another Trump-friendly move.
The previous day, some details of the company’s new relaxed content-moderation guidelines were published by the news site The Intercept, showing the kind of offensive rhetoric that Meta’s new policy would now allow, including statements such as “Migrants are no better than vomit” and “I bet Jorge’s the one who stole my backpack after track practice today. Immigrants are all thieves.”
Recalibrating for Trump
Zuckerberg, who has been dragged to Washington eight times to testify before congressional committees during the last two administrations, wants to be perceived as someone who can work with Trump and the Republican Party, people familiar with the matter said.
Though Meta’s content-policy updates caught many of its employees and fact-checking partners by surprise, a small group of executives were formulating the plans in the aftermath of the U.S. election results. By New Year’s Day, leadership began planning the public announcements of its policy change, the people said.
Meta typically undergoes major “recalibrations” after prominent U.S. elections, said Katie Harbath, a former Facebook policy director and CEO of tech consulting firm Anchor Change. When the country undergoes a change in power, Meta adjusts its policies to best suit its business and reputational needs based on the political landscape, Harbath said.
“In 2028, they’ll recalibrate again,” she said.
After the 2016 election and Trump’s first victory, for example, Zuckerberg toured the U.S. to meet people in states he hadn’t previously visited. He published a 6,000-word manifesto emphasizing the need for Facebook to build more community.
The social media company faced harsh criticism about fake news and Russian election interference on its platforms after the 2016 election.
Following the 2020 election, during the heart of the pandemic, Meta took a harder stand on Covid-19 content, with a policy executive saying in 2021 that the “amount of COVID-19 vaccine misinformation that violates our policies is too much by our standards.” Those efforts may have appeased the Biden administration, but it drew the ire of Republicans.
Meta is once again reacting to the moment, Harbath said.
“There wasn’t a business risk here in Silicon Valley to be more right-leaning,” Harbath said.
While Trump has offered few specific policy proposals for his second administration, Meta has plenty at stake.
The White House could create more relaxed AI regulations compared with those in the European Union, where Meta says harsh restrictions have resulted in the company not releasing some of its more advanced AI technologies. Meta, like other tech giants, also needs more massive data centers and cutting-edge computer chips to help train and run their advanced AI models.
“There’s a business benefit to having Republicans win, because they are traditionally less regulatory,” Harbath said.
Meta’s CEO Mark Zuckerberg reacts as he testifies during the Senate Judiciary Committee hearing on online child sexual exploitation at the U.S. Capitol in Washington, U.S., January 31, 2024.
Evelyn Hockstein | Reuters
Meta isn’t alone in trying to cozy up to Trump. But the extreme measures the company is taking reflects a particular level of animus expressed by Trump over the years.
Trump has accused Meta of censorship and has expressed resentment over the company’s two-year suspension of his Facebook and Instagram accounts following the Jan. 6 attack on the Capitol.
In July 2024, Trump posted on Truth Social that he intended to “pursue Election Fraudsters at levels never seen before, and they will be sent to prison for long periods of time,” adding “ZUCKERBUCKS, be careful!” Trump reiterated that statement in his book, “Save America,” writing that Zuckerberg plotted against him during the 2020 election and that the Meta CEO would “spend the rest of his life in prison” if it happened again.
Meta spends $14 million annually on providing personal security for Zuckerberg and his family, according to the company’s 2024 proxy statement. As part of that security, the company analyzes any threats or perceived threats against its CEO, according to a person familiar with the matter. Those threats are cataloged, analyzed and dissected by Meta’s multitude of security teams.
After Trump’s comments, Meta’s security teams analyzed how Trump could weaponize the Justice Department and the country’s intelligence agencies against Zuckerberg and what it would cost the company to defend its CEO against a sitting president, said the person, who asked not to be named because of confidentiality.
Meta’s efforts to appease the incoming president bring their own risks.
After Zuckerberg announced the new speech policy Tuesday, Boland, the former executive, was among a number of users who took to Meta’s Threads service to tell their followers that they were quitting Facebook.
“Last post before deleting,” Boland wrote in his post.
Before the post could be seen by any of his Threads followers, Meta’s content moderation system had taken it down, citing cybersecurity reasons.
Boland told CNBC in an interview that he couldn’t help but chuckle at the situation.
“It’s deeply ironic,” Boland said.
— CNBC’s Salvador Rodriguez contributed to this report.
WATCH: Meta is returning to free speech tradition, says Facebook’s former chief privacy officer Chris Kelly
Jaap Arriens | Nurphoto | Getty Images
Apple is losing market share in China due to declining iPhone shipments, supply chain analyst Ming-Chi Kuo wrote in a report on Friday. The stock slid 2.4%.
“Apple has adopted a cautious stance when discussing 2025 iPhone production plans with key suppliers,” Kuo, an analyst at TF Securities, wrote in the post. He added that despite the expected launch of the new iPhone SE 4, shipments are expected to decline 6% year over year for the first half of 2025.
Kuo expects Apple’s market share to continue to slide, as two of the coming iPhones are so thin that they likely will only support eSIM, which the Chinese market currently does not promote.
“These two models could face shipping momentum challenges unless their design is modified,” he wrote.
Kuo wrote that in December, overall smartphone shipments in China were flat from a year earlier, but iPhone shipments dropped 10% to 12%.
There is also “no evidence” that Apple Intelligence, the company’s on-device artificial intelligence offering, is driving hardware upgrades or services revenue, according to Kuo. He wrote that the feature “has not boosted iPhone replacement demand,” according to a supply chain survey he conducted, and added that in his view, the feature’s appeal “has significantly declined compared to cloud-based AI services, which have advanced rapidly in subsequent months.”
Apple’s estimated iPhone shipments total about 220 million units for 2024 and between about 220 million and 225 million for this year, Kuo wrote. That is “below the market consensus of 240 million or more,” he wrote.
Apple did not immediately respond to CNBC’s request for comment.
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