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| | | News you ought to know about: - We’ve looked at woke from all sides now. Woke AI, that is. It’s become a widely discussed thing, thanks to President Donald Trump’s July 23 executive order “Preventing Woke AI in the Federal Government.” And you know what? All sides, pro-DEI movement, anti-DEI movement and DEI movement-agnostic—the acronym stands for diversity, equity and inclusion, which as a newish cause forms the core of what’s come to be called “woke” advocacy—make a defensible case. Here are thoughtful cogitations from writers holding to each of the three positions.
- DEI activism: “As AI reshapes the workplace, leaders must play a more strategic role when it comes to DEI, guiding how technology aligns with inclusion, ethics and human potential. The first step is reassessing the business model: Where can automation unlock value, and where could it risk undermining trust or equity? A clear understanding of this can lay the groundwork for a robust AI strategy. … In a world where AI is becoming part of everyday life, DEI can provide a competitive edge and drive sustainable growth. The future starts with strategy—at this point in time, with AI strategy. Leaders must act as agents of change, preserving human potential while guiding organizations through the integration of AI.”—Oksana Matviichuk in Forbes
- DEI reactionism: “Forecasters imagine a world in which virtually all human information is passed through AI algorithms, and end-users—billions of people around the world—will have their perceptions shaped by this information. The competition between models, and between nations, will become intense. … With the [anti-woke AI] executive order, Trump has staked clear ground: The U.S. government will support AI models that are factual, neutral and aligned with America’s national interests. No doubt there will be more battles to come, but Trump, Sacks and the White House’s entire AI team deserve enormous credit.”—Christopher Rufo in City Journal
- DEI agnosticism: “[W]hile we might wish AI models be ‘neutral and unbiased’—just as we might wish the same about TV news programs, magazine articles or social media moderation—the fact is that private companies, be they television networks or publishers or tech companies, have a right to make their products as biased as they want. It’s up to consumers to decide if they prefer neutral models or not. … Granted, the [July 23] executive order is not expected to try and mandate such a requirement across the board but to stipulate that this is mandatory for AI companies getting federal contracts. That seems fair enough in theory, but in practice, not likely.”—Elizabeth Nolan Brown in Reason
- AI can help save the lives of women and their newborns in poorer regions of the world. In fact, it represents a transformative solution to the problem of high maternal mortality rates in those areas, according to researchers at the University of Johannesburg in South Africa. Economist Nicholas Ngepah, PhD, and colleagues arrived at the conclusion, published July 28 in Globalization and Health, after analyzing longitudinal data from 70 countries. They found AI adoption significantly reduces maternal mortality, and the effect is especially pronounced in developing countries where “post-2000 advancements have led to notable declines.”
- AI’s best benefits, they reveal, are most evident in resource-strapped settings, where use of the technology tends to correlate with improved early diagnostics, personalized care and remote monitoring. By comparison, AI’s effects in developed countries are modest due to the slim margins for improvement in already-advanced health systems.
- “Policymakers should prioritize AI-driven healthcare, expand digital infrastructure and ensure equitable access to maximize its benefits,” Ngepah and co-authors write. “AI integration is crucial for addressing maternal health disparities and accelerating progress toward the World Health Organization’s Sustainable Development Goal 3.1,” which is to cut the global maternal mortality ratio to less than 70 per 100,000 live births.
- Pennsylvania is gearing up to regulate healthcare AI within its borders. Four Democrats and a Republican announced their intention July 28 to craft a bill covering three particular aims across the Keystone State. One is requiring transparency for patients and the public. Another is ensuring a human is stationed in the loop whenever AI is used for medical purposes. A third is mandating attestation by insurers or hospitals and clinicians to the Department of Insurance or Department of Health that “bias and discrimination already prohibited by law has been minimized in their use of AI” while showing “how they have made that determination to their respective regulators.” The bill’s primary sponsor is Democrat Rep. Arvind Venkat, MD, an emergency medicine specialist. Its Republican backer, Joe Hogan, stresses the importance of making sure AI is “not being over-relied upon in our healthcare system.” Announcement here, news release here.
- Florida is testifying to the power of healthcare AI for improving the patient experience along with care quality. Speaking at the July 23 gathering in Washington at which President Trump unveiled plans for the U.S. to “win the AI race,” a nurse leader from Tampa General Hospital said her institution is seeing “real, measurable improvements in fewer infections, better patient outcomes and more lives saved. With the help of AI, providers spend more time with patients and less time buried in paperwork.” There’s more on the presentation at Florida Politics.
- The most beloved name in U.S. healthcare is teaming with the world’s most valuable company to bring AI-based supercomputing into a hospital setting. The Mayo Clinic and Nvidia announced the move July 28. “While many institutions rely on cloud-based access to use AI, Mayo’s decision to build and run its own [computing] cluster on-site reflects both its ambition and its resources,” the Minnesota Star-Tribune reports. The newspaper quotes Mayo Chief Implementation Officer Micky Tripathi. The former federal chief AI officer notes that Mayo is one of very few healthcare organizations that have financial and human resources to run its own AI supercomputer “so that we can do everything we need to do.” The Star-Tribune notes this is the first time Nvidia’s chip technology will be used on so large a scale in healthcare. Get the rest.
- Which healthcare AI scribe is easy, secure, HIPAA-compliant—and totally free? Why, Doximity Scribe, of course. The social media platform for healthcare professionals announced the digital assistant’s release July 24. “Comparable scribe services can cost hundreds of dollars per user per month,” states Doximity Medical Director Alex Blau, MD. “We believe powerful tools like this should be accessible to all clinicians, not just those with the budgets.” All you need to do to get yours is be a physician or advanced practice provider with a Doximity account in good standing. Details here.
- Well played, China. Well played. While President Trump has been bellowing about the U.S. “winning” the global AI “race,” counterparts in the Middle Kingdom have been cooking up a counterview. Over the weekend, Premier Li Quang told attendees at the World AI Conference in Shanghai his country wants to generously share its AI learnings with other nations, particularly in underdeveloped regions, and helpfully coordinate global efforts at AI regulation. Reuters attended the gathering and reports: “Li did not name the United States but appeared to refer to Washington’s efforts to stymie China’s advances in AI, warning that the technology risked becoming the ‘exclusive game’ of a few countries and companies.”
- From AIin.Healthcare’s sibling news outlets:
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| | | Inside Fairview: A CMIO's Perspective on Driving AI Innovation in Healthcare
July 29, 1-2pm EDT - Virtual
How does a leading health system turn cutting-edge AI into everyday clinical impact?
Join Martin Raison, Co-Founder & CTO at Nabla, for a live, online conversation with Dr. Rebecca Markowitz, CMIO at M Health Fairview, as they explore what it takes to bring innovation to life across a complex care environment.
From ambient tech to predictive models and academic-community integration, discover how M Health Fairview has become a model for clinically grounded, enterprise-scale AI innovation.
Register now: https://info.dhinsights.org/spotlight-ai-innovation |
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| | | By viewing large-language AI models through the lens of harm-reduction thinking, healthcare adopters can cultivate a responsible, ethical and optimal integration of the technology. And they can do so while actively mitigating the inherent risks for all stakeholders involved. Two researchers in Sweden lay out the how’s and why’s in a paper published July 25 in the Journal of Medical Internet Research. “Harm reduction, traditionally applied in public health contexts such as substance use management, focuses on minimizing the negative consequences associated with certain behaviors rather than seeking solely to eliminate the behavior itself,” explain Birger Moëll, MSc, of KTH Royal Institute of Technology in Stockholm and Fredrik Sand Aronsson, MSc, of the Karolinska Institute. “Applied to the use of LLMs in medicine,” they add, “this means acknowledging their inevitable use by both patients and professionals and proactively developing strategies to make that use as safe, ethical and beneficial as possible.” Here are excerpts from the case they make. 1. A harm-reduction lens, adapted from public health practice, offers a pragmatic vision between prohibition and uncritical adoption. “For patients, the priority is to transform passive consumption of model output into a critically verified information-seeking process that preserves privacy and promotes timely care-seeking,” the authors write. “For clinicians, the core insight is that LLMs can safely augment but never replace clinical judgment when they are used within secure, governed environments that mandate human verification, bias checks and transparent disclosure.” More: ‘Implementing these measures demands institution-wide policies, continuous training and interdisciplinary oversight but can preserve patient safety, equity and trust while unlocking administrative efficiencies and decision-support benefits.’
2. By advocating for a human-in-the-loop baseline, we can guarantee safe deployments of AI systems in the medical domain.Once these systems are deployed and work well, evaluation can become more automated, Moëll and Aronsson point out. “This approach is also in line with how work might change through AI in other sectors,” they add. “Many occupations might have tasks involving the orchestration and evaluation of LLMs and LLM agents.” ‘As such, human-in-the-loop assurance seems like a sensible, safe way forward.’
3. Adopting a harm-reduction framework acknowledges the inevitability of LLM use by patients and clinicians.It also prioritizes strategies to mitigate harm rather than promoting “futile attempts at prohibition,” the researchers state before adding: ‘Ultimately, harm reduction is not a barrier to progress but a necessary, pragmatic pathway to ensure LLMs enhance, rather than undermine, the core values of equitable, evidence-based and patient-centered medicine.’
Read the whole thing. - In other research news:
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