The Download: introducing the 10 Things That Matter in AI Right Now

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Introducing: 10 Things That Matter in AI Right Now

What actually matters in AI right now? It’s getting harder to tell amid the constant launches, hype, and warnings. To cut through the noise, MIT Technology Review’s reporters and editors have distilled years of analysis into a new essential guide: the 10 Things That Matter in AI Right Now.

The list builds on our annual 10 Breakthrough Technologies, but takes a wider view of the ideas, topics, and research shaping AI, spotlighting the trends and breakthroughs shaping the world.

We’ll be unpacking one item from the list each day here in The Download, explaining what it means and why it matters. Read the full rundown now—and stay tuned for the days ahead.

MIT Technology Review Narrated: desalination plants in the Middle East are increasingly vulnerable

As the conflict in Iran has escalated, a crucial resource is under fire: the desalinization technology that supplies water in the region.

President Donald Trump recently threatened to destroy “possibly all desalinization plants” in Iran if the Strait of Hormuz is not reopened. The impact on farming, industry, and—crucially—drinking in the Middle East could be severe. Find out why.

—Casey Crownhart

This is our latest story to be turned into an MIT Technology Review Narrated podcast, which we publish each week on Spotify and Apple Podcasts. Just navigate to MIT Technology Review Narrated on either platform, and follow us to get all our new content as it’s released.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 An unauthorized group has reportedly accessed Anthropic’s Mythos
Users in a private online forum may have gained access. (Bloomberg $)
+ Anthropic said the model was too dangerous for a full release. (Axios)
+ Mozilla used it to find 271 security vulnerabilities in Firefox. (Wired $)

2 Meta will track workers’ clicks and keystrokes for AI training
Tracking software is being installed on workers’ computers.(Reuters $)
+ Employees are up in arms about the program. (Business Insider)
+ LLMs could supercharge mass surveillance in the US. (MIT Technology Review)

3 ChatGPT allegedly advised the Florida State shooter
About when and where to strike, and which ammunition to use. (Washington Post $)
+ Florida’s attorney general is probing ChatGPT’s role in the shooting. (Ars Technica)
+ Does AI cause delusions or just amplify them? (MIT Technology Review)

4 SpaceX has secured the option to buy AI startup Cursor for $60 billion
Or pay $10 billion for the work they’re doing together. (The Verge)
+ SpaceX made the deal as it prepares to go public. (NYT $)
+ Musk’s endgame for the company may be a land grab in space. (The Atlantic $)

5 The Pentagon wants $54 billion for drones
That would rank among the top 10 military budgets for entire nations. (Ars Technica)
+ Shoplifters could soon be chased down by drones. (MIT Technology Review)

6 Apple’s new chief hardware officer signals a sprint to build in-house chips
Apple silicon lead Johny Srouji has been promoted to the role. (CNBC)

7 China’s government is tightening its grip on AI firms that try to leave
It’s doing all it can to stop firms like Manus sending talent and research overseas. (Washington Post $)

8 The FBI is probing the deaths of scientists tied to sensitive research
Including a nuclear physicist and MIT professor shot outside his home. (CNN)

9 The US is accelerating research into psychedelic medical treatment
Including the mysterious ibogaine. (Nature)
+ But psychedelics are (still) falling short in clinical trials. (MIT Technology Review)

10 The first retail boutique run by an AI agent has opened—and it’s chaos
The San Francisco shop is reassuringly mismanaged. (NYT $)

Quote of the day

“I was very impressed with myself to have the head of Apple calling to ‘kiss my ass’.” 

—Donald Trump pays a classy tribute to Tim Cook on Truth Social.

One More Thing

JOHN F. MALTA


This researcher wants to replace your brain, little by little

A US agency pursuing moonshot health breakthroughs has hired a researcher advocating an extremely radical plan for defeating death. His idea? Replace your body parts. All of them. Even your brain. 

Jean Hébert, a program manager at the US Advanced Research Projects Agency for Health (ARPA-H), believes we can beat aging by adding youthful tissue to people’s brains. Read the full story on his futuristic plan to extend human life. 


—Antonio Regalado

We can still have nice things

A place for comfort, fun and distraction to brighten up your day. (Got any ideas? Drop me a line.)

+ A Lego set was sent to the edge of space—and survived.
+ Go behind the scenes with Werner Herzog as he guides a new generation of filmmakers.
+ This video about enshittification perfectly captures the frustration of the degrading internet.
+ NASA’s latest deep-space capture offers a rare view of planetary systems in their absolute infancy.

STAT+: Publicly, Kennedy embraces a more moderate MAHA

WASHINGTON — Health secretary Robert F. Kennedy Jr. once said there are no vaccines that are safe and effective. On Wednesday, he seemed to have changed his tune.

Across two Senate hearings, Kennedy noted that as health secretary, he funded the development of new vaccines, green-lit new shots for patients, asserted flu vaccines are preventive care, and even urged “every child to get the MMR,” a shot he previously suggested wasn’t safe. Last week, he acknowledged the shot could have saved the life of a child who died of measles.

Kennedy’s agenda continues to make waves across American health care, as his department pursues a broad crackdown on alleged fraud and seeks to upend Americans’ relationship with ultra-processed foods, all after major cuts across health agencies and a reworking of vaccine policy. But the about-face expands to a number of core MAHA issues — chemicals in food and the government’s relationship with industry among them.

It comes as some leaders of the insurgent movement have grown skeptical of the administration they rallied to support, forcing the Trump administration to thread the needle between courting the MAHA base’s ongoing support and dropping MAHA priorities seen as impractical or politically unwise. 

Continue to STAT+ to read the full story…

STAT+: Federal test of AI prior authorization is delaying care for seniors, report says

Washington state hospitals say their Medicare patients are waiting two to four times longer in some cases for procedures that are now subject to prior authorization under a new Medicare program. 

The report from Sen. Maria Cantwell (D-Wash.) is among the first to document alleged patient harm stemming from the Centers for Medicare and Medicaid Services’ new Wasteful and Inappropriate Service Reduction, or WISeR, Model. Cantwell is one of several Democratic members of Congress who have been urging CMS to scrap the program, which launched Jan. 1. 

Cantwell aired her concerns about WISeR to Health and Human Services Secretary Robert F. Kennedy Jr. at a Senate Committee on Finance hearing Wednesday. She said CMS is using artificial intelligence as a “denial device” and that patients are waiting weeks to get sign off for services that previously didn’t require approval. 

Continue to STAT+ to read the full story…

Former tobacco executive joins CDC senior leadership, raising concerns over industry influence

A former tobacco industry executive has been appointed to senior leadership at the Centers for Disease Control and Prevention, alarming public health advocates and critics of industry influence on government.

Stephen Sayle, named in March as the CDC’s deputy director for legislative affairs, previously worked at Fontem Ventures, a subsidiary of the British multinational tobacco corporation Imperial Brands. Between 2017 and 2018, he was U.S. vice president of corporate affairs at Fontem, which is focused on non-combustible tobacco products like the e-cigarette brand blu and the oral nicotine pouch brand Zone. 

Read the rest…

Global Mapping of Telemedicine Regulation and Ethical Safeguards: Mixed Methods Exploratory Document Analysis

Background: Telemedicine has become central to digital health strategies, yet the regulatory environment that shapes ethical safeguards and equitable access remains uneven and incompletely assessed across countries. Legal and normative instruments matter because they define requirements for privacy, consent, accountability, professional readiness, and barrier reduction. Objective: This study aimed to map the current global landscape of normative instruments related to telemedicine and identify which ethical and social safeguards are explicitly addressed, with particular attention to equity. Methods: We conducted a document analysis guided by the READ (ready the materials, extract data, analyze data, and distill findings) framework. From February 2024 to February 2026, we conducted a structured web-based search across all World Health Organization (WHO) member states with no language restrictions, using official government sources, statutory professional regulators, and institutional publication channels. Retrieval combined internal site searches, direct navigation, external search engine queries, and targeted snowball sampling to identify currently in-force instruments. Two researchers independently extracted and coded data using a predefined codebook. We operationalized 10 binary items covering regulatory presence and scope (questions 1 and 2), safeguards for data protection (question 3), consent and disclosure (questions 4 and 5), prior in-person prerequisites (question 6), monitoring (question 7), training requirements (question 8), and equity (questions 9 and 10). We summarized frequencies overall and stratified by WHO region and World Bank income group and conducted a qualitative thematic analysis of included normative instruments. Results: Of the 194 WHO member states, 81 (41.8%) had at least one current normative instrument related to telemedicine in force. Among these, 72.8% (59/81) defined telemedicine or telehealth. Data protection provisions were most common (73/81, 90.1%), followed by mandatory informed consent (n=71, 87.7%) and monitoring mechanisms (n=65, 80.2%). Fewer countries required disclosure of telemedicine limitations (n=36, 44.4%) or mandated telemedicine-specific training (n=26, 32.1%). Prior in-person consultation requirements were uncommon (n=8, 9.9%). Equity-related safeguards were uneven: 51.9% (n=42) referenced justice, equity, or nondiscrimination, whereas 30.9% (n=25) included concrete barrier reduction provisions (eg, digital inclusion or accommodations for people with disabilities and minors). Conclusions: Telemedicine regulation is becoming more common, but both coverage and safeguarding content remain uneven. While privacy, consent, and monitoring are frequently addressed where regulation exists, disclosure, physician competency, and operational equity measures are less consistently specified. Strengthening telemedicine governance will require translating ethical commitments into enforceable standards that address digital determinants of access and protect groups at risk of exclusion.
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Exploring User Experiences of an Augmented Reality Smartphone App Prescribing Exercise for Children and Young People With Cancer: Results From a Qualitative Study

Background: Mobile health (mHealth), and specifically smartphone apps, have grown exponentially in both functionality and accessibility and are becoming an important component of health care. Research exploring the use of mHealth for managing or treating chronic diseases, such as cancer, has shown promising effects. Yet, comparatively little work has examined how such technologies can enhance exercise interventions for young people with cancer. To optimize the effectiveness of mHealth in these contexts, it is essential to build a stronger evidence base on user experience. Objective: This study aimed to investigate how healthy children and young people engaged with an augmented reality (AR) app developed specifically for children and young people undergoing cancer treatment, and to identify design features that may support engagement and behavior change in the intended clinical population. Methods: School and university students, aged 8‐21 years, were eligible to participate in the study. Practical workshops allowed participants to engage with the AR exercise app before taking part in focus groups to explore user experiences. Data were analyzed using qualitative content analysis, which also involved a critical friend approach using 2 researchers (HM and KS). Suggested improvements were mapped against the motivational affordances’ taxonomy. Results: A total of 39 participants aged 8‐21 years took part in the focus group study. Participants found the demonstrations and varied exercises useful but expressed some concerns regarding data safety and functionality of the novel AR avatar. It was proposed that additional educational components, challenges, and rewards, as well as a customizable avatar, social support features, and audio instructions for a more inclusive design would be desirable and could enhance user experience. When mapped against the motivational affordances taxonomy, the suggested improvements aligned primarily with mechanisms of user education, challenges, feedback, cooperation, and comparison. Conclusions: This study provides an understanding of how apps that prescribe exercise can be optimized to enhance motivation and user experience. By assessing feedback and suggestions for improvements, the findings highlight key design features that may support engagement. While this initial work focused on healthy, age-matched participants, further evidence specifically in children and young people with a childhood cancer diagnosis is needed. International Registered Report Identifier (IRRID): RR2-10.1177/14604582241288784
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Enhancing the Predictive Value of Formative Evaluation in Extended Reality Adoption: Addressing the Experience Gap

Formative evaluation is widely used in implementation science to anticipate barriers and facilitators prior to the deployment of health technologies, typically relying on stakeholders’ reported beliefs collected before real-world exposure. This approach has proven informative for many digital health tools; however, its application to immersive and embodied technologies such as extended reality (XR) warrants closer scrutiny. Most XR interventions in health care are delivered through head-mounted displays, which depend on spatial perception and sensorimotor engagement. Several implementation-relevant properties, including comfort, perceived intrusiveness, safety, and workflow disruption, often become apparent only through direct interaction. At the same time, large segments of the health care workforce remain XR-naive, such that preuse judgments are frequently shaped by anticipation rather than experience. Drawing on concepts from implementation science, grounded cognition, and human-computer interaction, this Viewpoint examines a plausible interpretive problem in XR adoption and argues that perception-based formative evaluation, when applied through frameworks developed for screen-based technologies, may misclassify barriers and facilitators. Rather than questioning formative evaluation as a methodological approach, we identify a boundary condition for its interpretability in experience-dependent technologies and propose a pragmatic refinement: incorporating brief experiential familiarization before eliciting stakeholder perceptions to strengthen early-stage assessment and improve alignment with real-world implementation decisions.
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Knowledge, Attitudes, and Training Needs for AI in Primary Care: National Survey Study of Clinicians in the Veterans Health Administration

<strong>Background:</strong> Clinicians are the interface between artificial intelligence (AI) applications and patient care. To maximize benefits and minimize risks of AI, clinicians must be “AI-ready”—that is, willing and able to understand, evaluate, and appropriately use AI tools in practice. Prior literature suggests that clinicians lack fundamental competencies in the use of AI. These gaps could be especially problematic in primary care, given its broad reach into patient care. We surveyed primary care providers (PCPs) in the United States’ largest integrated health care system, relatively early in its widespread implementation of clinical AI for frontline use, in order to identify readiness gaps that may warrant particular attention as part of a comprehensive AI implementation strategy. <strong>Objective:</strong> The aim of this study was to characterize PCPs’ use, knowledge, attitudes, and training priorities related to AI in order to inform health system AI implementation efforts. <strong>Methods:</strong> We conducted a national cross-sectional survey of United States Veterans Health Administration (VA) PCPs in October 2025, assessing AI use, self-reported knowledge, attitudes, and training experience. Descriptive analyses summarized responses with exploratory bivariate comparisons across clinician subgroups. Conventional content analysis with inductive coding was used to characterize open-ended responses providing a definition of AI. <strong>Results:</strong> Among 170 respondents (170/989, 17.2% response rate), 66.5% (113/170) reported current AI use, most commonly generative AI and decision support tools. Overall attitudes toward AI were positive, with 70.6% (120/170) mostly enthusiastic or more enthusiastic than apprehensive. Confidence in understanding sources of AI bias (62/170, 36.5%) and ethical issues (81/170, 47.6%) was limited. When asked to define AI, very few respondents provided an accurate technical definition. Key concerns about use of AI included accountability, accuracy, and transparency. Though 88.2% (150/170) identified AI training as a priority, only 26.5% (45/170) had any training. Training experiences ranged widely in source, focus, and structure. <strong>Conclusions:</strong> PCPs are eager to harness AI’s practical advantages but lack foundational competencies to do so in ways that maximize benefit and minimize risk. Our findings highlight a need for targeted education that prioritizes critical appraisal, workflow integration, and risk mitigation, supported by governance that addresses clinicians’ concerns and validated measures to evaluate progress toward an AI-ready workforce. These steps can empower PCPs to leverage AI safely and effectively and strengthen the quality and safety of primary care delivery at scale.

Counterclockwise Virtual Reality–Based Embodiment of a Younger Self and Revisit of a Past Iconic Event in Older Adults: Between-Groups Study of Cognitive and Physical Performance

Background: The original counterclockwise study carried out in the late 1970s provided an extreme example of “reminiscence therapy,” reporting improvements in older adults’ cognitive and physical functioning after they had lived for 5 days in a house set up as if decades earlier (the 1950s). We tested a virtual reality (VR) analog of this approach, enhanced by embodying participants in a virtual body that looked like themselves at the corresponding younger age. Objective: This study aimed to examine whether brief VR exposures combining (1) embodiment in a virtual body as one’s younger self and (2) immersion in an iconic past event improve age-related subjective and performance outcomes compared with a current-self VR control condition. Methods: We carried out a between-groups study with 23 healthy older adults (aged 65‐85 years; mean age 71.2, SD 4.03 years). Participants were randomly allocated to either a Young Self condition (n=11; mean 72.3, SD 4.17), where they were embodied in a virtual body that looked like themselves from the 1960s, or in a Current Self control condition (n=12; mean 70.1, SD 3.75), where participants were embodied in their current body. There were 5 sessions. In Session 1, participants completed a baseline assessment. There were then 2 VR exposures, approximately 1 week apart (Sessions 2‐3), and follow-ups at 1 week (Session 4) and approximately 2 weeks (Session 5) after the final VR exposure. Outcomes included subjective age, awareness of age-related change, World Health Organization–Five Well-Being Index, Trail Making Test performance, and physical functioning (eg, grip strength). Results: A hierarchical Bayesian analysis revealed that 1 week after the final VR exposure, those in the Young Self condition demonstrated lower subjective age than those in the Current Self condition (prob=.95). They had higher awareness of positive age-related change (prob=.89) and a higher score on the World Health Organization–Five Well-Being Index (prob=.84). Moreover, with respect to performance variables, they took less time to trace a trail (prob≥.99), made fewer mistakes in doing so (prob=.89), had greater right-hand (prob=.85) and left-hand (prob≥.99) grip strength. However, 2 weeks after their final VR exposure, these differences diminished apart from positive awareness of age-related change (prob=.82), trail-making mistakes (prob=.83), and left-hand grip strength (prob≥.99). Here, “prob” refers to posterior probability. Conclusions: The results demonstrate that even 2 short VR exposures, where people were embodied in their younger body and immersed in an iconic event from more than 50 years earlier, resulted in improvement in some age-related responses. This is encouraging for further research with more extensive VR experiences over a longer time period.
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Effectiveness of a Fully Automated Mobile Therapeutic Versus a General Chatbot in Reducing Depression and Anxiety and Improving Well-Being: Feasibility Randomized Controlled Trial

Background: Given the increasing prevalence of depression and anxiety disorders and enduring barriers to care, there is a critical need for alternative treatment options. Generative artificial intelligence (AI) chatbots show promise for increasing access to mental health care, though more direct research is needed to establish their efficacy. Objective: This pilot study aimed to test the efficacy of a generative mental health chatbot rooted in solution-focused therapy compared to the general-purpose ChatGPT and an assessment-only control (AOC) group on depression, anxiety, and well-being. Methods: A total of 185 English-speaking adults were recruited online and randomly assigned to one of three groups: AI therapy, ChatGPT, or AOC. Of these, 147 eligible participants filled out a pretreatment assessment. Over a 3-week period, the AI therapy group (n=44) was instructed to complete 3 structured, fully automated app-based sessions per week (9 total), while the ChatGPT group (n=60) was instructed to engage in 9 unstructured conversations with ChatGPT (GPT-4o–based models). The control group (n=43) received no intervention. In the AI therapy group, 39% (n=17) completed all sessions, as did 62% (n=38) of those in the ChatGPT group. Primary outcome measures, self-assessed online at baseline and postintervention, included the Patient Health Questionnaire-9 (PHQ-9), Overall Depression Severity and Impairment Scale (ODSIS) (depression), 7-item Generalized Anxiety Disorder Scale (anxiety), and World Health Organization Well-Being Index (5-item version) (well-being). Linear mixed effects models were used for data analysis. Results: Compared to AOC, both the AI therapy group (=−0.47; =.01) and the ChatGPT group (=−0.44; =.02) demonstrated significant reductions in depression scores measured by PHQ-9. The AI therapy group showed nonsignificant reductions in anxiety (=−0.37; =.11) and ODSIS depression scores (=−0.25; =.22) and an increase in well-being (=0.12; =.53) compared to AOC. Similarly, a nonsignificant reduction in anxiety (=−0.27; =.22) and ODSIS depression scores (=−0.12; =.53) and an increase in well-being (=0.20; =.29) were observed in the ChatGPT group compared to AOC. The AI therapy group did not significantly outperform the ChatGPT group on any outcomes (PHQ-9: =−0.19; =0.03; =.87; 7-item Generalized Anxiety Disorder Scale: =−0.57; =−0.11; =.62; ODSIS: =−0.59; =−0.13; =.50; and WHO: =−0.38; =−0.07; =.69). Conclusions: Both the structured generative AI chatbot and ChatGPT showed a significant reduction in depression scores compared to the control group. No significant effects were observed across other outcomes, although descriptive trends indicated improvements in anxiety. While the AI therapy group showed descriptively better outcomes for depression and anxiety, differences between groups were not significant. A larger sample and longer intervention may be needed for the emerging trends to yield clinically meaningful effect sizes. Trial Registration: OSF Registries osf.io/r76ef;
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