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Is AI's Role in Healthcare Innovative or an Overstep?

As AI diagnoses become more common, questions about trust, efficacy, and the future role of healthcare professionals come to the forefront.

If you’re new here, this is the latest edition of the Build Mode newsletter, where we gather the collective wisdom of the people building with AI, designing the future of work, and leading the most important companies of the next decade. Subscribe here to get the top insights in your inbox every week.

THE BIG IDEA

Is AI's role in healthcare innovative or an overstep?

The conversation around LinkedIn—and virtually every healthcare panel we attended at SXSW—was dominated by one topic: Will AI replace medical professionals?

A feature on the Today show told a story about a boy named Alex, whose medical condition left 17 doctors stumped. So, his mom turned to ChatGPT in desperation, fed it all the data from Alex’s numerous MRIs, and it came back with a diagnosis that no one else had considered: tethered cord syndrome — which, upon confirmation by a new doctor, led to successful surgery and significant improvement in Alex's condition.

Stories like this expose two emerging trends:

  1. Patients want more autonomy in their health — we’re seeing them turn to AI to understand their health issues. Maybe ChatGPT is this generation’s WebMD?
  2. There’s a growing trust in AI, where quick, AI-driven insights are valued alongside traditional medical advice.

It's no longer a question of whether GenAI has a role in healthcare but how we can harness it responsibly to enhance patient care. But generative AI entering our healthcare processes is a double-edged sword.

One example is Google's AMIE, an AI system optimized for medical diagnostic reasoning and patient conversations. It’s a powerful tool and it reflects a move towards improving AI's clinical consultation capabilities. But shiny new healthtech solutions often end up in the tarpit — that’s when a startup idea that seems like a great opportunity but has actually been tried many times before ends up not working out. Promising yet impractical solutions can actually slow progress down.

This is where the human element becomes crucial. At a SXSW discussion titled "Will AI replace health workers? No, but it will turn them into tech workers," J&J's Jim Swanson highlighted AI's role as an enhancer rather than a replacer in healthcare. He explained how integrating digital skills in healthcare training doesn't just prepare professionals for an AI-driven future, but also allows them to focus on what they do best — caring for patients. We’ve seen similar results — like when A.Team partnered with a Fortune 100 company to build a GenAI tool that reduced nurse burnout by 40%.

Swanson spoke about the growing importance of tech literacy across all roles at Johnson & Johnson, including AI and ML. This focus on digital skills in training new hires has been so effective that it has led J&J to value soft skills more highly in their recruitment process.

The integration of AI tools offers a promising avenue to address systemic issues within healthcare, improving the system without sidelining practitioners. This approach also serves as a helpful compass to avoid the healthtech tarpit. As healthcare leaders and professionals navigate this evolving landscape, focusing on the human element offers a way to sidestep the pitfalls of overhyped technological solutions.

The consensus? AI is not going to replace health workers (at least anytime soon) — but it will certainly redefine their roles.

As patients increasingly seek AI-driven insights into their health issues, the medical community faces a dual challenge: embracing the potential of AI while addressing the concerns it raises. By placing a premium on the human aspects of healthcare delivery, we not only avoid the traps of the healthtech tarpit but also ensure that AI genuinely augments the patient and provider experience.

While we appreciate our doctors having the latest AI tools for clinical decision-making — the idea of receiving a diagnosis from C3PO isn’t on anyone’s wishlist.

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CHART OF THE WEEK

The six stages of healthtech grief

The 6 Stages of Health Tech Grief

When an enterprising person looks out at the American healthcare system it’s immediately obvious: There are so many ways we could improve this thing.

Right away there’s a sense of optimism. There’s so much potential for disruption. Think of how many times in your life you had to write your information onto a clipboard in a waiting room!

Armed with these good intentions and an addressable market close to a trillion, many a healthtech founder has set out to change things. Then: Reality strikes back. Turns out it’s a uniquely challenging industry. Ambition gets scaled down. Disillusionment sets it. Call it the healthtech grief cycle.

Out-of-Pocket is a deeply informed and charmingly written healthcare newsletter from Nikhil Krishnan, and in the latest issue, he breaks that cycle down into six stages. You can read the full 58-page treatise here. It’s a super useful guide that outlines the path taken by 90% of entrepreneurs so that you can avoid the common traps and prepare for the inevitable speed bumps.

WATERCOOLER

The Rise of Shrimp Jesus

The Rise of Shrimp Jesus

When was the last time you went on Facebook?

If the answer is 2014, we have an update for you: The platform is crawling with AI-generated images created by scammers and spammers.

99.9% of it is garbage. Shrimp Jesus, however, is admittedly pretty cool-looking.

With widespread access to image-generating AI tools, scammers have taken over Facebook groups and pages, flooded them with insane posts, and then sent bots to comment “Amen” to boost their algorithmic popularity and go viral. It’s a genius strategy.

A recent study from the Stanford Internet Observatory found that the scammers seem to be “motivated by profit or clout, not ideology.” In other words—no one is yet worshipping Shrimp Jesus. The researchers say this underlines the need for AI transparency and provenance standards.

Meta is pouring money into AI so fast it’s hard to comprehend. They want to accumulate more than 340,000 H100 GPUs from NVIDIA. Zuckerberg is personally emailing AI experts at Google to try and poach them in a bid to race against OpenAI.

Our take: Facebook was already a cesspool of garbage content—maybe Zuck should use some of those GPUs to take Shrimp Jesus mainstream.

DEEP DIVE

The Top 10 Use Cases for Generative AI in Healthcare

If any industry could use generative AI advances to simplify and expedite processes, it’s healthcare. Doctors, nurses, and support staff take marathon shifts to provide around-the-clock services, often without the necessary resources or human capital to function efficiently.

Luckily, we’re already seeing substantial progress.

Major health providers, tech companies, and well-funded startups have released a proliferation of internal and patient-facing AI applications that make the jobs of health practitioners, researchers, insurance providers, and back-office support that much easier. From analyzing images to fast-tracking diagnoses to identifying new drugs and treatment options to a slew of automated administrative capabilities—GenAI is transforming the healthcare industry.

  1. Clinical note-taking

Organizing vast quantities of patient notes and histories is a time-intensive, manual process—and one ripe for AI automation. Abridge bills itself as “the most trusted AI-powered clinical conversation platform, purpose-built for healthcare.” The company’s Enterprise tech generates clinical notes in real-time during patient visits, structured in the industry’s preferred formats (History of Present Illness, Assessment & Plan, Physical Exam, and more).

  1. Scheduling appointments

Scheduling a doctor’s appointment is often a hassle, and in 2024 there’s no need to play phone tag with an overworked receptionist. Enter AgentifAI, the AI scheduling platform tailored to healthcare.

  1. Drug discovery and research

Identifying new drugs can take years using conventional methods, but AI advances can greatly expedite the process. AlphaFold is an AI system developed by Google DeepMind that generates 3D protein structures from amino acid sequences—researchers have already used the tech to identify hundreds of thousands of potential new psychedelics.

Read the Full Article

EVENTS

Gen AI Salon: The Future of Health

This month, we're zeroing in on the transformative potential of AI within healthcare at the Gen AI Salon: The Future of Health.

Join us on Wednesday April 24th to uncover insights from Carenostics Co-Founder, Kanishka Rao on AI's potential to bridge chronic disease gaps, strategies from Mount Sinai’s Rachel Tornheim on AI-powered clinical workflows, and robust discussions on AI in clinical decision-making with leaders like Jessica Beegle, former Chief Innovation Officer at LifePoint Health.

Register here

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