AI Can’t Fix a Psychologically Unsafe Culture at Work

Posted on by Karina

You’ve probably seen the headlines. AI coaching tools promise to revolutionize leadership development. They offer 24/7 availability, instant feedback, and data-driven insights at a fraction of the cost of human coaches. Some platforms claim they can even detect emotional states through voice analysis or predict team dynamics through sentiment tracking.

Impressive? Absolutely.

A replacement for building genuine psychological safety? Not even close.

Here’s the uncomfortable truth: AI can analyze patterns, but it cannot create the conditions where people feel genuinely safe to be themselves. It can suggest responses to conflict, but it can’t model vulnerability. It can track engagement metrics, but it can’t build trust through shared human experience.

And if your team culture already lacks psychological safety, adding AI coaching tools might actually make things worse.

The Illusion of Connection

A hot take on AI coaching tools and the irreplaceable value of genuine psychological safety

Let me paint a picture. Sarah, a mid-level manager, receives a notification from her company’s new AI coaching platform. It’s detected that her team’s communication patterns suggest “potential disengagement.” The AI recommends she schedule one-on-ones and provides scripted questions to ask.

Sarah follows the script. Her team members give polite, surface-level answers. The AI marks the intervention as “complete.” The dashboard shows green checkmarks.

But nothing has actually changed.

Why? Because Sarah’s team doesn’t lack structured conversations. They lack the felt sense that it’s safe to tell Sarah what’s really going on. They need to know that admitting struggle won’t be held against them, that asking for help won’t signal incompetence, that disagreeing won’t damage their standing.

That kind of safety isn’t built through algorithms. It’s built through repeated human interactions where leaders demonstrate, through their own behavior, that vulnerability is not only accepted but valued.

What AI Misses: The Neuroscience of Safety

At ABL, our S.A.F.E.T.Y.™ framework is grounded in decades of neuroscience research. We know that psychological safety isn’t just a nice-to-have cultural feature. It’s a neurobiological necessity for high performance and innovation.

The framework identifies six core drivers that our brains need to function optimally:

  • Security: The need for certainty,
  • predictability, and consistency
  • Autonomy: The need for a sense of choice and control over our lives
  • Fairness: The need for equitable treatment and transparent processes
  • Esteem: The need to feel valued and respected
  • Trust: The need to belong to a trusted group and experience reliable relationships with those ‘like us
  • You: The unique factors that shape our individual experience

When these needs go unmet, our brains shift into threat mode. The amygdala takes over. Creativity shuts down. Collaboration becomes difficult. Performance suffers.

AI tools can measure some symptoms of these unmet needs such as declining engagement scores, increased turnover, reduced communication frequency– all lagging indicators of a problem when it’s too late. However, AI can’t address the root cause because it cannot provide the genuine human connection that the human brain fundamentally requires, nor can it predict, perceive, or contribute to a human’s response to their ‘human’ social experiences and interactions.

When you connect with a person, on a real level your brain might release oxytocin—the neurochemical associated with bonding and trust. Oxytocin is implicated in pair bonding, parental behavior, affiliation, and some forms of trust.

It’s quite different when an algorithm validates your feelings.

While an AI Chat Bot’s algorithmically delivered digital feedback or affirming responses can, indeed, engage reward-related brain regions, actual reciprocal human relationships are a particularly robust source of belonging and support that still cannot be matched by tech.

Where AI Falls Short on Each S.A.F.E.T.Y.™ Driver

Let’s break this down further.

Security Security requires more than risk assessments and compliance tracking. People feel secure when they experience predictable patterns, consistent processes, and clear information during uncertain times. When a team member asks about a change, they need detailed explanations, advance notice, and assurance that core systems will remain stable. AI can provide information, but it can’t create the felt sense of environmental stability and predictability that comes from a leader who maintains consistent routines, follows through on commitments, and minimizes disruptive surprises.

Autonomy isn’t just about being consulted—it’s about having genuine control and choice over your work and matters that impact you and your life. When a leader gives you decision-making authority over how you accomplish your goals, you feel your autonomy honored. AI might offer options, but it can’t grant the real authority and control that makes autonomy meaningful.

Fairness depends on transparency and the ability to explain the “why” behind decisions in ways that account for context and nuance. AI can apply rules consistently, but fairness often requires understanding the human story behind the situation. It requires judgment calls that balance competing values, something humans excel at and machines struggle with.

Esteem is built through recognition that feels personal and specific. Generic praise generated by an algorithm doesn’t land the same way as a leader who notices the particular way you solved a problem or the unique strength and value you brought to a project. Your brain knows the difference between authentic appreciation and automated praise and acknowledgment.

Trust develops through belonging to a group where we feel an ‘in-group’ connection —where we’re recognized as part of the tribe. AI can facilitate connections, but it can’t create the felt sense of tribal belonging that comes from being recognized as ‘one of us’ by other humans who share our identity, values, or experiences.

You—each person’s unique background, personality, culture, and triggers shape how they experience Security, Autonomy, Fairness, Esteem, and Trust. AI might personalize responses based on data, but it can’t truly understand the complex interplay of someone’s life story, cultural context, and personal history that determines what makes them feel psychologically safe.

The Real Risk of Human–Robot Interactions (HRI)

Human–human interactions (HHI) and human–robot interactions (HRI)

Here’s where things get concerning. Organizations struggling with psychological safety often look for quick fixes. AI coaching tools can seem like an efficient solution. They are scalable, measurable, and cost-effective. Yet deploying these tools in a psychologically unsafe culture can backfire in several ways, such as:

False sense of progress: Leadership sees adoption metrics and completion rates, assuming the problem is being addressed. Meanwhile, team members go through the motions without experiencing any real shift in how safe they feel.

Increased surveillance anxiety: AI tools that monitor communication patterns, sentiment, or productivity can heighten feelings of being watched and judged. For team members who already don’t feel safe, this amplifies their Security, Autonomy, Fairness, Esteem, and Trust concerns.

Depersonalization of support: When people reach out for help and receive algorithmic responses, it can reinforce the feeling that they’re just data points rather than valued individuals. This directly undermines their Esteem and  Trust.

Erosion of Trust: If AI tools make recommendations that leaders follow without genuine understanding or adaptation, it becomes obvious that the leader is outsourcing their judgment. This damages Trust in leadership.

Authenticity gap: Perhaps most damaging, AI tools can create a veneer of care without the substance. Team members can tell when responses are scripted or when check-ins are prompted by software rather than genuine interest or concern. This gap between appearance and reality corrodes the foundation of psychological safety.

What AI Can Do (And What Humans Must Do)

This isn’t an anti-technology argument. AI has legitimate value in leadership development and team management.

AI excels at:

  • Identifying patterns in large datasets that humans might miss
  • Providing just-in-time learning resources
  • Offering practice scenarios for skill development
  • Tracking progress on measurable behaviors
  • Reducing administrative burden so leaders have more time for people

These are useful capabilities. But they’re support tools, not replacements for human leadership.

Building psychological safety requires humans to:

  • Model vulnerability and authenticity
  • Respond to emotional nuance with empathy
  • Make judgment calls that balance competing values
  • Build trust through consistent, reliable presence
  • Create the felt sense of being seen and valued
  • Navigate complex interpersonal dynamics
  • Demonstrate that it’s safe to speak up, take risks and make mistakes

These capabilities emerge from our shared humanity. They require emotional intelligence, social awareness, and the willingness to be present with discomfort. Qualities that remain distinctly human.

A Better Approach: Human-Centered, Tech-Supported

The most effective path forward combines human wisdom with technological support.

Start with the human foundation. Before they can create safety for others, leaders need to understand their own S.A.F.E.T.Y.™ drivers, what their brain needs, how it is triggered, and how their S.A.F.E.T.Y.™ sensitivities may impact themselves and those they lead. This self-awareness comes through reflection, feedback from other humans, and the sometimes uncomfortable work of examining our own biases and blind spots.

Once leaders have built this foundation, they can use AI tools strategically:

  • To surface data that prompts important conversations
  • To provide reminders and structure for consistent practices
  • To offer learning resources that deepen understanding
  • To track whether behavioral changes are occurring over time

But the actual work of building psychological safety: the conversations, the vulnerability, the connection, the trust-building, remains human work.

The Path Forward for Leaders Like You

If you’re a team leader reading this, you might feel the pressure to adopt the latest tools while also sensing that something essential is missing from your team culture. You’re not wrong.

Your team doesn’t need more technology. They need more of you. The real, imperfect, trying-your-best you.

They need you to:

  • Ask how they’re really doing and wait for the honest answer
  • Admit when you don’t know something
  • Respond to mistakes with curiosity instead of judgment
  • Notice what’s unique and valuable about each person’s contributions
  • Follow through on commitments, especially small ones
  • Show up consistently, even when it’s uncomfortable

This is harder than implementing an AI tool. It requires ongoing effort, self-reflection, and the courage to be genuinely present with your team.

But this is also where the real transformation happens. When you create genuine psychological safety, you unlock your team’s full potential. People bring their best thinking, take smart risks, collaborate across differences, and stay engaged even when work gets challenging.

No algorithm can create that. Only humans can.

The Bottom Line

AI coaching tools have their place in the modern workplace. They can support learning, provide structure, and offer useful data. But they cannot, and should not, replace the human work of building psychological safety.

Your team’s brains are wired to seek connection with other humans. They need to feel seen, valued, and safe in ways that only genuine human interaction can provide. The S.A.F.E.T.Y.™ drivers aren’t just abstract concepts; they’re neurobiological requirements for optimal functioning.

Before you invest in the next AI solution, ask yourself: Have we built the human foundation? Do our leaders understand their own psychological safety needs? Can they recognize and respond to these needs in others? Are we creating the conditions where people feel genuinely safe to be themselves?

If the answer is no, no amount of artificial intelligence will fix that. But if you’re willing to do the human work. The messy, uncomfortable, deeply rewarding work of building real psychological safety. You’ll create something no algorithm can replicate: a team where people thrive.

Ready to Build Real Psychological Safety?

At ABL, we help leaders develop the self-awareness and skills needed to create genuinely psychologically safe teams. Our approach is grounded in neuroscience and focused on the human capabilities that make great leadership possible.

Explore our resources:

Because building psychological safety isn’t about finding the right tool. It’s about becoming the right kind of leader.

 

Citations

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Carter CS. Oxytocin and love: Myths, metaphors and mysteries. Compr Psychoneuroendocrinol. 2021 Dec 27;9:100107. doi: 10.1016/j.cpnec.2021.100107. PMID: 35755926; PMCID: PMC9216351.

Delgado MR, Fareri DS, Chang LJ. Characterizing the mechanisms of social connection. Neuron. 2023 Dec 20;111(24):3911-3925. doi: 10.1016/j.neuron.2023.09.012. Epub 2023 Oct 6. PMID: 37804834; PMCID: PMC10842352.

De Castro Martins C, Chaminade T, Cavazza M. Causal Analysis of Activity in Social Brain Areas During Human-Agent Conversation. Front Neuroergon. 2022 May 17;3:843005. doi: 10.3389/fnrgo.2022.843005. PMID: 38235459; PMCID: PMC10790851.

Fang CM, Liu AR, Danry V, Lee E, Chan SWT, Pataranutaporn P, Maes P, Phang J, Lampe M, Ahmad L, Agarwal S. How AI and human behaviors shape psychosocial effects of chatbot use: a longitudinal randomized controlled study. arXiv [Preprint]. 2025 Mar 21. Available from: https://arxiv.org/abs/2503.17473

Spatola, N., Chaminade, T. Precuneus brain response changes differently during human–robot and human–human dyadic social interaction. Sci Rep 12, 14794 (2022). https://doi.org/10.1038/s41598-022-14207-9

AI and the Brain: Answering the Questions Everyone’s Asking

Posted on by Mikayla Hull

The uptake of AI has moved from a novelty to daily habit for hundreds of millions of people in the space of a few years. That speed has left the science trailing the adoption, but a wave of studies published over the past year are starting to give real answers to the questions people are actually asking. While the evidence in the neuroscience field is still in its infancy, there are some interesting themes emerging.  Below are some common questions I’ve encountered over the past year by concerned AI users from a variety of backgrounds and industries, with some associated early evidence.

Is AI making us worse thinkers?

Not exactly, but it does seem to be changing when and how hard we think. The clearest evidence comes from MIT Media Lab’s “Your Brain on ChatGPT” study, which had 54 participants write essays while wearing EEG headsets, either using ChatGPT, using a search engine, or working entirely unaided. The unaided group showed the strongest, most widespread neural connectivity during the task; the search-engine group was intermediate; the ChatGPT group showed the weakest overall neural coupling.  That doesn’t mean people using AI produced worse essays.  In fact, human and AI judges often scored the AI-assisted essays competitively. What changed was how much cognitive work went into producing them, and how well people retained what they’d made. In the first session, 83% of ChatGPT users couldn’t correctly quote a sentence from an essay they’d written minutes earlier, compared to about 11% in the other two groups.

If I stop using the AI, does my brain “snap back”?

Not immediately, according to the same study. A subset of participants was reassigned to the opposite condition in a fourth session — people who’d used ChatGPT for three sessions had to write unaided, and vice versa. The group moving from ChatGPT to unaided writing still showed weaker neural connectivity and reduced engagement, even with the tool taken away. The carryover suggests the effect isn’t purely situational — something about sustained AI reliance seems to persist for at least a little while after the tool is gone. The reverse was more encouraging: participants moving from unaided writing to ChatGPT showed a network-wide spike in connectivity and higher recall, suggesting the deficit isn’t necessarily permanent, just slow to reverse.

Do we actually trust AI too much as a society?

Most likely. A Wharton team ran three preregistered experiments with 1,372 participants, giving them reasoning problems where an AI assistant was sometimes deliberately programmed to produce wrong answers. When the AI was wrong, about 80% of participants followed it anyway, performing worse than if they’d had no AI assistance at all. Trust in the AI was the strongest predictor: people who trusted the tool more had roughly 3.5 times greater odds of following its faulty answers. Only around 20% of participants actively caught and overruled the AI’s mistakes. The researchers call this pattern “cognitive surrender”, which refers to a conscious decision to trust AI, but a quiet failure to scrutinize what it produces. A related survey of knowledge workers by Microsoft and Carnegie Mellon researchers found the same effect in real workplace use: higher confidence in generative AI tracked with less critical thinking, and a shift from active problem-solving toward passive review of AI output.

Does using AI to check facts make me better at spotting misinformation on my own?

Apparently not much. A follow-up MIT Media Lab study found that conversations with AI reduced people’s belief in misinformation in the short term but built no lasting ability to detect it independently. The researchers compare this to how GPS may have eroded our capacity to navigate without it….the tool solves the immediate problem without transferring the underlying skill.  So it may be that our brains are being wired to decrease the ability to objectively scrutinize the information around us.

Is AI making everyone think and write more alike?

There’s early evidence of this too. In the MIT essay study, ChatGPT-assisted essays converged on more similar language and content than essays from the unaided or search-engine groups.  In other words, participants using AI tended to reach for the same phrasing and the same named entities. A separate, broader paper in Trends in Cognitive Sciences looked at this at scale across large language model usage and found a similar homogenizing effect on human expression and thought. If AI systems are trained on similar data and tend toward similar “safe” outputs, it stands to reason that heavy reliance on them could narrow the range of how people express ideas, though this is an early and still-developing area of research.

Is this just a problem for students, or does it impact experts too?

Both, but in different ways. Most of the research above involves people still building skills, like students, general knowledge workers, developers. A separate study of computer program developers learning a new coding library with and without AI assistance and found that AI sped up task completion but measurably slowed how well developers actually learned the material. So, what we are seeing is an impact on the rate of skill formation.  The shortcut works, but the underlying competence doesn’t develop the same way.

A different and arguably more unsettling finding comes from a year-long study of practicing oncologists. AI assistance improved their diagnostic accuracy but appeared to affect their subjective confidence in their own clinical judgment. This isn’t a failure to learn, but something closer to “intuition rust” in people who already have the expertise. It suggests AI reliance can erode confidence, even in situations where it clearly makes people more accurate.

Does this mean I should stop using AI tools?

The research doesn’t point that way. One of the more useful findings comes from Michael Gerlich, a researcher whose earlier work is often cited as evidence that AI erodes critical thinking. In a follow-up study, he had 150 participants write essays under three conditions: no AI, unguided ChatGPT use, and ChatGPT use with structured prompting. His conclusion was that the offloading effect depends heavily on how people engage with AI, not simply whether they use it.  What it suggests is that deliberate, scaffolded use can support critical thinking rather than erode it. In simple terms, that means putting structure, guidance and human oversight around AI so that it improves people’s work without replacing their judgment. That distinction, passive offloading versus active, structured engagement is probably the single most actionable takeaway across this entire body of research.

How solid is all of this, really?

Considering how new all of this is, the data are reasonably solid in direction, but still early in certainty. The flagship MIT study is a preprint, not yet peer-reviewed, with a sample of 54 people (only 18 completed the crossover phase), testing one model (GPT-4o) on one task (short essay writing). The Wharton and Microsoft/CMU studies have larger samples and add real-world workplace data, but every study in this space shares the same limitation of being short-term. Sessions span weeks or months, not years.  That’s the biggest open question left in the field:  what happens over years of sustained AI use, rather than months, and how that plays out differently for adults with established cognitive habits versus younger users whose skills are still forming. Almost nothing exists yet on that timeline, and it’s the gap every author in this space points to next.

Across writing, reasoning, factchecking, coding, and medicine, a consistent pattern is emerging: AI tools that solve a problem for you tend to reduce the depth of engagement, memory formation, or confidence that comes from solving it yourself.  However, the size and duration of that effect look different depending on how deliberately the tool is used. None of the current research supports avoiding AI but rather suggests that you are likely doing your brain a disservice by putting total reliance and unconditional trust in its output.

 

References:

Gerlich, M. (2025). AI Tools in Society: Impacts on Cognitive Offloading and the Future of Critical Thinking. Societies, 15(1), 6. https://www.mdpi.com/2075-4698/15/1/6

Gerlich, M. (2025). From Offloading to Engagement: An Experimental Study on Structured Prompting and Critical Reasoning with Generative AI. Data, 10(11), 172. https://doi.org/10.3390/data10110172

Kosmyna, N., Hauptmann, E., Yuan, Y. T., Situ, J., Liao, X. H., Beresnitzky, A. V., Braunstein, I., & Maes, P. (2025). Your Brain on ChatGPT: Accumulation of Cognitive Debt when Using an AI Assistant for Essay Writing Task. arXiv preprint arXiv:2506.08872. https://arxiv.org/abs/2506.08872

Lee, H. P., Sarkar, A., Tankelevitch, L., Drosos, I., Rintel, S., Banks, R., & Wilson, N. (2025). The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems (CHI ’25), Article 1121. https://doi.org/10.1145/3706598.3713778

Rani, A., Danry, V., Liang, P. P., Lippman, A., & Maes, P. (2026). Dialogues with AI Reduce Beliefs in Misinformation but Build No Lasting Discernment Skills. In Proceedings of the 2026 CHI Conference on Human Factors in Computing Systems (CHI ’26), Article 792. https://doi.org/10.1145/3772318.3790656

Shaw, S. D., & Nave, G. (2026). Thinking—Fast, Slow, and Artificial: How AI is Reshaping Human Reasoning and the Rise of Cognitive Surrender. Wharton School Research Paper / SSRN working paper. https://papers.ssrn.com/sol3/papers.cfm?abstract_id=6097646 (preprint: https://doi.org/10.31234/osf.io/yk25n_v1)

Shen, J. H., & Tamkin, A. (2026). How AI Impacts Skill Formation. arXiv preprint arXiv:2601.20245. https://arxiv.org/abs/2601.20245

Sourati, Z., Ziabari, A. S., & Dehghani, M. (2026). The Homogenizing Effect of Large Language Models on Human Expression and Thought. Trends in Cognitive Sciences. https://www.cell.com/trends/cognitive-sciences/abstract/S1364-6613(26)00003-3 (preprint: https://arxiv.org/abs/2508.01491)

Loneliness Is More Than a Feeling – It’s a Hidden Threat to Workplace Performance

Posted on by Mikayla Hull

For years, loneliness was viewed primarily as a social problem. If someone felt disconnected, the solution seemed obvious: encourage them to spend more time with other people. New research published in Nature Communications fundamentally changes that perspective.

Using one of the most rigorous scientific approaches ever applied to the question, researchers from the University of Bristol and collaborators demonstrated that loneliness is not simply a consequence of poor mental health—it is an independent driver of declining psychological wellbeing, reduced life satisfaction, and deteriorating overall health.

For organizational leaders, HR professionals, and anyone concerned with workplace culture, this finding carries profound implications.

The Hidden Difference Between Being Alone and Feeling Alone

One of the study’s most important contributions is distinguishing two concepts that are often mistakenly treated as the same. Social isolation refers to the number of relationships a person has. Loneliness reflects the quality of those relationships.

Someone may spend every day in meetings, collaborate with dozens of colleagues, attend conferences, and maintain a full calendar, yet still experience profound loneliness if they don’t feel genuinely understood, supported, or psychologically safe.

Conversely, someone with a relatively small social network can feel deeply connected and thrive. The research found that subjective loneliness (not simply being socially isolated) was the stronger predictor of poor mental health.

For professionals at every level, this distinction matters enormously. Many people have extensive professional networks but very few authentic relationships.

The Science Behind the Finding

Historically, researchers struggled with a fundamental question: Does loneliness make people unhealthy, or do unhealthy people simply become lonely? To answer this, the investigators combined three independent scientific approaches:

  • Large population studies
  • Comparisons between siblings (controlling for shared childhood experiences)
  • Mendelian randomization, a genetics-based method that helps establish causal relationships rather than simple correlations

All three methods pointed to the same conclusion: Loneliness itself contributes directly to poorer mental health and lower wellbeing. That consistency provides unusually strong evidence that loneliness is not merely associated with declining health, but helps drive it.

The Modern Workplace Paradox

Modern organizations are increasingly connected technologically while becoming more emotionally disconnected. Remote work, hybrid teams, and digital communication dominate. Ironically, many employees have never been more connected—or more lonely.

The result is often:

  • Chronic stress
  • Reduced resilience
  • Emotional exhaustion
  • Eventually, burnout

This new research suggests that those consequences may be driven not simply by workload but by the absence of meaningful human connection.

Why the Brain Responds So Strongly

Humans evolved as profoundly social organisms. Our brains continuously evaluate whether we belong. When we experience genuine connection, neural systems involved in reward, safety, and emotional regulation become more active.

When loneliness persists, the brain shifts into a more vigilant, defensive state. People become more likely to:

  • Interpret situations negatively
  • Perceive greater social threat
  • Ruminate
  • Experience anxiety
  • Become emotionally exhausted

Over time these patterns reduce wellbeing and increase vulnerability to depression. The new study reinforces that this is not simply a psychological experience—it produces measurable consequences for overall health.

Connection as a Performance Factor

Organizations often invest heavily in professional development by teaching communication skills, strategic thinking, technical competencies, and decision-making. While all of these matter, the fact remains that one of the strongest predictors of sustained workplace performance may be something far more basic: The ability to build authentic human connection.

Trust, psychological safety, belonging, and empathy are not “soft skills.” They represent biological conditions that allow the brain to perform at its highest level.

Teams that feel connected:

  • Think more creatively
  • Recover from setbacks more quickly
  • Collaborate more effectively
  • Demonstrate greater resilience under pressure

Questions Worth Asking

Whether you’re reflecting on your own experience or considering your team’s wellbeing, these questions matter:

  • Who truly knows you at work?
  • Where can you be completely authentic?
  • Which relationships consistently restore your energy?
  • When was the last time you felt deeply understood by a colleague?
  • Are you surrounded by people—or genuinely connected to them?

These reflections may ultimately influence wellbeing and performance just as much as discussions about productivity or career strategy.

A New Organizational Priority

Perhaps the most important conclusion from this work is that loneliness should no longer be viewed as a private emotional struggle. It is a measurable health risk. The researchers found consistent evidence that loneliness contributes to poorer mental health, reduced life satisfaction, and worse overall health. While they did not find definitive proof linking loneliness to individual diseases such as heart disease or diabetes, they observed an increased likelihood of poorer self-rated health and living with multiple chronic conditions simultaneously.

For organizations, this means employee wellbeing initiatives should evolve beyond perks and engagement surveys. Creating cultures where people genuinely feel seen, valued, and connected may be one of the most powerful investments a company can make—not only for wellbeing, but for innovation, resilience, and long-term performance.

The evidence is clear: Connection isn’t a luxury. It’s a necessity.

Reference:

Hilliard DD, Wootton RE, Sallis HM, et al. Investigating relationships between loneliness, social isolation and health. Nature Communications. 2026;17. DOI: 10.1038/s41467-026-74758-7

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