VA takes a new approach to its electronic health record deployment, following a proposed $2 billion White House funding boost.
PHOTO CREDIT:Dr. Neil Evans, acting program executive director for VA EHRM-IO, testifying during the March 15, 2023 Senate Committee of Veterans Affairs Hearing.
The Department of Veterans Affairs targets a new approach to its electronic health record modernization deployment, moving away from individual site rollouts and instead “implementing waves of medical centers, multiple medical centers at one time, based on the relationships between those medical centers,” Dr. Neil Evans, acting executive program director of VA’s Electronic Health Record Modernization Integration Office, told GovCIO Media & Research in a recent interview.
Implementing the EHR in ‘Waves’
The rollout has been in a reset phase since April 2023, following reports that the system struggled with accuracy, enterprise standardization and reliability of data. Currently, the modern EHR is in place at six sites throughout the VA, with the most recent deployment occurring in March 2024 at the Lovell Federal Health Care Center in North Chicago.
The VA announced in Dec. 2024 that it would restart the rollout at four sites in Ann Arbor, Battle Creek, Detroit and Saginaw, with Michigan following in mid-2026. It also announced it will roll out the EHR at nine additional sites spread between Ohio, Indiana and Alaska.
VA plans to use the “wave” deployment approach Evans described when it resumes rollout in Detroit, Ann Arbor, Saginaw and Battle Creek, Michigan in 2026, since the four sites are integrated together and patients often receive specialty care at one facility or primary care at another.
“Going forward, implementing and choosing a schedule that really captures those natural pre-existing relationships, we believe, is an important part of the successful path forward, and that was also partly how we chose the sites that we chose,” Evans said.
VA’s EHR Program Sees Proposed Budget Boost
VA’s dormant but much-anticipated electronic health record modernization program could receive a jolt in funding from the Trump Administration in 2026. The White House’s proposed discretionary budget for FY 2026 calls for an increase of nearly $2.2 billion in funding for the EHR program, saying an accelerated rollout of the program is a “top priority effort.”
The proposed budget also plans to streamline much of the agency’s over 1000 IT systems, which it claims are “decades old” and “duplicative.” It pauses procurement of new systems and directs the U.S. Department of Government Efficiency Service to conduct a full review of the agency’s IT systems alongside the VA.
“There’s testing that we do, where we have to test every build to make sure it’s going to work properly when we go live with it. There’s infrastructure work that we need to do to make sure that our IT networks have been upgraded sufficiently to support the new technologies,” Evans said.
Learning from Federal Partners
As agencies like National Oceanic and Atmospheric Administration, Defense Department and Coast Guard work toward their electronic health record modernization goals, Evans said the VA is learning from their experience and from private sector partners as well.
“We’re not alone in going through an EHR transformation. The scale of what we’re doing in VA is significant, but the experience itself is not entirely unique. We are always open to learning, and have learned quite a bit from our federal partners, and actually from our non federal partners,” Evans said.
Evans emphasized that even after the EHR is rolled out across the country, work will need to be done to continually improve and refine the system to work for both patients and clinicians alike.
“We need to deploy the system, but we need to continue to optimize the system to meet the needs. Technology continues to mature. What we can accomplish using health information technologies is going to continue to improve as new capabilities, artificial intelligence and others, are introduced,” Evans said.
AI is a tool to get things done. To use it properly and generate value, organizations need the right capabilities — including a good understanding of data.
Artificial intelligence is getting all the buzz in the business world. But people often talk about “doing” AI without realizing that it’s just a tool for getting things done — a costly and complex tool.
“Like any tool, it creates no value unless it’s used properly,” said Barbara H. Wixom, a principal research scientist at the MIT Center for Information Systems Research. “AI is advanced data science, and you need to have the right capabilities in order to work with it and manage it properly.”
In a new research briefing, Wixom and CISR research fellow Cynthia M. Beathoutline three principles for implementing AI projects: Build the right capabilities, involve stakeholders from across the organization, and focus on realizing value.
In simple terms, data monetization is converting data into financial returns. Datasets could be sold to third parties, studied to improve processes, or used to create new business opportunities.
Seeing a return on investment from AI requires a “supercharged” data monetization strategy, Wixom said. There’s significant cost associated with the infrastructure, capabilities, and talent needed to get AI initiatives off the ground. And any enterprise that builds AI into a product — even if it’s something relatively simple, such as a customer service chatbot — must bear the associated legal and ethical responsibilities.
“So many missteps can occur,” Wixom said. “What we care about in the AI conversation is helping organizations embrace AI technology in a way that improves financial health.”
For example, many knowledge workers are using generative AI tools, such as ChatGPT, to write emails, create presentations, or pull key takeaways from meeting transcripts.
These conveniences shouldn’t be conflated with value, Wixom said. “If you invest millions of dollars in the capability to use AI in a sustaining way, is email productivity going to drive millions of dollars in value?” Wixom asked. “You need to know what your company needs.”
The CISR research briefing includes the example of CarMax, which used ChatGPT to aggregate data from customer reviews and other information sources to write summaries for 50,000 used cars listed on its website. A task that would have taken years to complete and required hundreds of content writers was accomplished in a matter of hours, the company’s chief information and technology officer said last year.
Below are more details on the researchers’ three principles aimed at guiding enterprise AI investments that generate value:
1. Invest in practices that build AI capabilities.
Successful AI use depends on advanced capabilities in data science, data management, data platforms, and acceptable data use.
Organizations may be tempted to forgo these investments if they purchase an off-the-shelf AI tool or have one custom-built for them. However, Wixom said it’s even more important for these organizations to build these capabilities to avoid running into trouble downstream.
“You have to understand the technology enough to trust it,” she said. “You don’t have to know the exact way neural networks work, but you do need to know how data scientists validate them — and you need to know what you don’t know.”
2. Involve all stakeholders in the AI journey.
Organizations [must] embrace AI technology in a way that improves financial health.
Barbara H. WixomPrincipal Research Scientist, CISRShare
Roles and titles differ among organizations, but the people who use AI tools, develop products, or offer solutions should be considered key stakeholders. Involving a variety of stakeholders in initiatives can help those without a background in data science better understand what AI can do, how much it costs, and how long it takes.
The CISR research briefing looked at the Australian Taxation Office, where business users provided regular feedback to data scientists about how AI models were performing. This helped all stakeholders understand how AI models made decisions, and it ensured that models had more positive benefits and fewer negative consequences. After implementing the models, which predicted tax-filing behaviors and offered nudges to citizens who needed to update work-related claims, the agency saw 113 million Australian dollars ($74 million) in changed claim amounts.
3. Focus on realizing value from AI.
In “Data is Everybody’s Business,” Wixom and her co-authors spell out five steps in the value creation cycle. Wixom explains them in the context of a common example in healthcare: predicting which patients in a hospital are at high risk of falling, and intervening to prevent it from happening.
Data. This comes from multiple sources, such as a medical history from electronic health records and current data from medical devices at the bedside.
Insight. This is where AI enters the picture to analyze data assets and predict who faces a high risk of a fall. Preventable falls are frequently linked to worse outcomes and higher costs of care.
Action. Here, insights inform changes to best practices. For example, a hospital may update its policies and send alerts to the nearest nurse when an at-risk patient starts to move in the bed — a sign that they may be trying to get up.
Value creation. In this scenario, the new policies result in fewer preventable falls, increased patient satisfaction, and shorter patient stays.
Value monetization. This occurs when the changes can be linked to tangible value creation. It may manifest as a reduced cost of care, which benefits hospitals compensated under performance-based contracts. It could also mean that fewer staff members are needed in a given unit.
A tough road from creation to monetization
Organizations need to plan out the five steps of value creation before any AI project commences, Wixom said. That will help executives see exactly what it will take to achieve returns on investment.
Monetization is the most difficult step. Many organizations get to value creation but are halted there. In a hospital, for example, additional revenue or reduced staffing costs may never materialize.
“You have to find a way to pay for this,” Wixom said. “Otherwise, you can’t sustain the investments, and then you have to pull the plug.”
Yet all isn’t lost if there are meaningful outcomes, such as a reduction in preventable falls, that don’t achieve monetization. In most cases, an organization now has the building blocks — data, insight, and action — to take on additional AI projects down the road. And it has experience successfully selling AI to stakeholders by focusing on what it can get done.
But without monetization, “AI will end up being a tool that sits on a shelf,” Wixom said. “You need to be talking about AI along with specific initiatives and the outcomes you want to achieve using it. And those outcomes need to be compelling for your organization.”
JPMorganChase just released an Open Letter to their third party suppliers, and sounded the AI security alarm!
The financial giant sees what others are missing:
Companies rushed to deploy AI without understanding the consequences. The mandate was clear: innovate or die. But JP Morgan’s latest security assessment reveals that:
78% of enterprise AI deployments lack proper security protocols
Most companies can’t explain how their AI makes decisions
Security vulnerabilities have increased 3x since mass AI adoption
The problem? Speed > security.
JP Morgan’s CTO Pat Opet put it bluntly: “We’re seeing organizations deploy systems they fundamentally don’t understand.” The financial sector is particularly vulnerable – with trillions at stake.
What JP Morgan recommends:
→ Implement AI governance frameworks before deployment → Conduct regular red team exercises against AI systems → Establish clear model documentation standards → Create dedicated AI security response teams
JP Morgan itself has invested $2B in AI security measures while slowing certain deployments.
The hard truth:
The AI security debt is growing faster than our ability to pay it down. Companies that prioritize security now will emerge as leaders. Those that don’t may not survive the coming AI security reckoning.
An open letter to third-party suppliers
By Patrick Opet, Chief Information Security Officer
The modern ‘software as a service’ (SaaS) delivery model is quietly enabling cyber attackers and – as its adoption grows – is creating a substantial vulnerability that is weakening the global economic system.
Software providers must prioritize security over rushing features. Comprehensive security should be built in or enabled by default.
We must modernize security architecture to optimize SaaS integration and minimize risk.
Security practitioners must work collaboratively to prevent the abuse of interconnected systems.
There is a growing risk in our software supply chain and we need your action
SaaS has become the default and is often the only format in which software is now delivered, leaving organizations with little choice but to rely heavily on a small set of leading service providers, embedding concentration risk into global critical infrastructure. While this model delivers efficiency and rapid innovation, it simultaneously magnifies the impact of any weakness, outage, or breach, creating single points of failure with potentially catastrophic systemwide consequences. Historically, software was distributed across diverse environments, each with unique security practices, inherently limiting the scale of any single breach. Today, an attack on one major SaaS or PaaS provider can immediately ripple through its customers. This fundamental shift demands our collective immediate attention.
At JPMorganChase, we’ve seen the warning signs firsthand. Over the past three years, our third-party providers experienced a number of incidents within their environments. These incidents across our supply chain required us to act swiftly and decisively, including isolating certain compromised providers, and dedicating substantial resources to threat mitigation.
Security must be prioritized
Risks extend beyond concentration alone. Fierce competition among software providers has driven prioritization of rapid feature development over robust security. This often results in rushed product releases without comprehensive security built in or enabled by default, creating repeated opportunities for attackers to exploit weaknesses. The pursuit of market share at the expense of security exposes entire customer ecosystems to significant risk and will result in an unsustainable situation for the economic system.
Security architecture must be modernized
Most critically, SaaS models are fundamentally reshaping how companies integrate services and data—a subtle yet profound shift eroding decades of carefully architected security boundaries. In the traditional model, security practices enforced strict segmentation between a firm’s trusted internal resources and untrusted external interactions using protocol termination, tiered access, and logical isolation. External interaction layers like APIs and websites were intentionally separated from a company’s core backend systems, applications, and data that powered them.
Modern integration patterns, however, dismantle these essential boundaries, relying heavily on modern identity protocols (e.g., OAuth) to create direct, often unchecked interactions between third-party services and firms’ sensitive internal resources. As a generic example, an AI-driven calendar optimization service integrating directly into corporate email systems through “read only roles” and “authentication tokens” can no doubt boost productivity when functioning correctly. Yet, if compromised, this direct integration grants attackers unprecedented access to confidential data and critical internal communications.
In practice, these integration models collapse authentication (verifying identity) and authorization (granting permissions) into overly simplified interactions, effectively creating single-factor explicit trust between systems on the internet and private internal resources. This architectural regression undermines fundamental security principles that have proven durability.
This problem is getting worse not better
Further compounding the risks are specific vulnerabilities intrinsic to this new landscape: inadequately secured authentication tokens vulnerable to theft and reuse; software providers gaining privileged access to customer systems without explicit consent or transparency; and opaque fourth-party vendor dependencies silently expanding this same risk upstream. Critically, the explosive growth of new value-bearing services in data management, automation, artificial intelligence, and AI agents amplifies and rapidly distributes these risks, bringing them directly to the forefront of every organization.
This weakness is known to attackers who are now actively targeting trusted integration partners—Microsoft Threat Intelligence recently authored a blog post that Chinese state actors were shifting tactics to target “common IT solutions like remote management tools and cloud applications to gain initial access” to their downstream customers.
Call to action
We stand at a critical juncture. Providers must urgently reprioritize security, placing it equal to or above launching new products. ‘Secure and resilient by design’ must go beyond slogans—it requires continuous, demonstrable evidence that controls are working effectively, not simply relying on annual compliance checks. Customers should be afforded the benefit of secure by default configurations, transparency to risks, and management of the controls they need to operate safely within a SaaS delivery model. The ecosystem must address trustworthy integration. There are some solutions available today, like confidential computing, customer self-hosting, and bring your own cloud, which all give organizations stronger controls to protect their data while enabling them to benefit from SaaS solutions.
We must establish new security principles and implement robust controls that enable the swift adoption of cloud services while protecting customers from their providers’ vulnerabilities. Traditional measures like network segmentation, tiering, and protocol termination were durable in legacy principles but may no longer be viable today in a SaaS integration model. Instead, we need sophisticated authorization methods, advanced detection capabilities, and proactive measures to prevent the abuse of interconnected systems.
The most effective way to begin change is to reject these integration models without better solutions. I hope you’ll join me inrecognizing this challenge and responding decisively, collaboratively, and immediately.
Patrick Opet, Chief Information Security Officer, JPMorganChase
Pope Francis has made no secret of his intention to radically reform the administrative structures of the Catholic church, which he regards as insular, imperious, and bureaucratic. He understands that in a hyper-kinetic world, inward-looking and self-obsessed leaders are a liability.
Last year, just before Christmas, the Pope addressed the leaders of the Roman Curia — the Cardinals and other officials who are charged with running the church’s byzantine network of administrative bodies. The Pope’s message to his colleagues was blunt. Leaders are susceptible to an array of debilitating maladies, including arrogance, intolerance, myopia, and pettiness. When those diseases go untreated, the organization itself is enfeebled. To have a healthy church, we need healthy leaders.
Through the years, I’ve heard dozens of management experts enumerate the qualities of great leaders. Seldom, though, do they speak plainly about the “diseases” of leadership. The Pope is more forthright. He understands that as human beings we have certain proclivities — not all of them noble. Nevertheless, leaders should be held to a high standard, since their scope of influence makes their ailments particularly infectious.
The Catholic Church is a bureaucracy: a hierarchy populated by good-hearted, but less-than-perfect souls. In that sense, it’s not much different than your organization. That’s why the Pope’s counsel is relevant to leaders everywhere.
With that in mind, I spent a couple of hours translating the Pope’s address into something a little closer to corporate-speak. (I don’t know if there’s a prohibition on paraphrasing Papal pronouncements, but since I’m not Catholic, I’m willing to take the risk.)
Herewith, then, the Pope (more or less):
____________________
The leadership team is called constantly to improve and to grow in rapport and wisdom, in order to carry out fully its mission. And yet, like any body, like any human body, it is also exposed to diseases, malfunctioning, infirmity. Here I would like to mention some of these “[leadership] diseases.” They are diseases and temptations which can dangerously weaken the effectiveness of any organization.
The disease of thinking we are immortal, immune, or downright indispensable, [and therefore] neglecting the need for regular check-ups. A leadership team which is not self-critical, which does not keep up with things, which does not seek to be more fit, is a sick body. A simple visit to the cemetery might help us see the names of many people who thought they were immortal, immune, and indispensable! It is the disease of those who turn into lords and masters, who think of themselves as above others and not at their service. It is the pathology of power and comes from a superiority complex, from a narcissism which passionately gazes at its own image and does not see the face of others, especially the weakest and those most in need. The antidote to this plague is humility; to say heartily, “I am merely a servant. I have only done what was my duty.”
Another disease is excessive busyness. It is found in those who immerse themselves in work and inevitably neglect to “rest a while.” Neglecting needed rest leads to stress and agitation. A time of rest, for those who have completed their work, is necessary, obligatory and should be taken seriously: by spending time with one’s family and respecting holidays as moments for recharging.
Then there is the disease of mental and [emotional] “petrification.” It is found in leaders who have a heart of stone, the “stiff-necked;” in those who in the course of time lose their interior serenity, alertness and daring, and hide under a pile of papers, turning into paper pushers and not men and women of compassion. It is dangerous to lose the human sensitivity that enables us to weep with those who weep and to rejoice with those who rejoice! Because as time goes on, our hearts grow hard and become incapable of loving all those around us. Being a humane leader means having the sentiments of humility and unselfishness, of detachment and generosity.
The disease of excessive planning and of functionalism. When a leader plans everything down to the last detail and believes that with perfect planning things will fall into place, he or she becomes an accountant or an office manager. Things need to be prepared well, but without ever falling into the temptation of trying to eliminate spontaneity and serendipity, which is always more flexible than any human planning. We contract this disease because it is easy and comfortable to settle in our own sedentary and unchanging ways.
The disease of poor coordination. Once leaders lose a sense of community among themselves, the body loses its harmonious functioning and its equilibrium; it then becomes an orchestra that produces noise: its members do not work together and lose the spirit of camaraderie and teamwork. When the foot says to the arm: ‘I don’t need you,’ or the hand says to the head, ‘I’m in charge,’ they create discomfort and parochialism.
There is also a sort of “leadership Alzheimer’s disease.” It consists in losing the memory of those who nurtured, mentored and supported us in our own journeys. We see this in those who have lost the memory of their encounters with the great leaders who inspired them; in those who are completely caught up in the present moment, in their passions, whims and obsessions; in those who build walls and routines around themselves, and thus become more and more the slaves of idols carved by their own hands.
The disease of rivalry and vainglory. When appearances, our perks, and our titles become the primary object in life, we forget our fundamental duty as leaders—to “do nothing from selfishness or conceit but in humility count others better than ourselves.” [As leaders, we must] look not only to [our] own interests, but also to the interests of others.
The disease of existential schizophrenia. This is the disease of those who live a double life, the fruit of that hypocrisy typical of the mediocre and of a progressive emotional emptiness which no [accomplishment or] title can fill. It is a disease which often strikes those who are no longer directly in touch with customers and “ordinary” employees, and restrict themselves to bureaucratic matters, thus losing contact with reality, with concrete people.
The disease of gossiping, grumbling, and back-biting.This is a grave illness which begins simply, perhaps even in small talk, and takes over a person, making him become a “sower of weeds” and in many cases, a cold-blooded killer of the good name of colleagues. It is the disease of cowardly persons who lack the courage to speak out directly, but instead speak behind other people’s backs. Let us be on our guard against the terrorism of gossip!
The disease of idolizing superiors. This is the disease of those who court their superiors in the hope of gaining their favor. They are victims of careerism and opportunism; they honor persons [rather than the larger mission of the organization]. They think only of what they can get and not of what they should give; small-minded persons, unhappy and inspired only by their own lethal selfishness. Superiors themselves can be affected by this disease, when they try to obtain the submission, loyalty and psychological dependency of their subordinates, but the end result is unhealthy complicity.
The disease of indifference to others. This is where each leader thinks only of himself or herself, and loses the sincerity and warmth of [genuine] human relationships. This can happen in many ways: When the most knowledgeable person does not put that knowledge at the service of less knowledgeable colleagues, when you learn something and then keep it to yourself rather than sharing it in a helpful way with others; when out of jealousy or deceit you take joy in seeing others fall instead of helping them up and encouraging them.
The disease of a downcast face. You see this disease in those glum and dour persons who think that to be serious you have to put on a face of melancholy and severity, and treat others—especially those we consider our inferiors—with rigor, brusqueness and arrogance. In fact, a show of severity and sterile pessimism are frequently symptoms of fear and insecurity. A leader must make an effort to be courteous, serene, enthusiastic and joyful, a person who transmits joy everywhere he goes. A happy heart radiates an infectious joy: it is immediately evident! So a leader should never lose that joyful, humorous and even self-deprecating spirit which makes people amiable even in difficult situations. How beneficial is a good dose of humor! …
The disease of hoarding. This occurs when a leader tries to fill an existential void in his or her heart by accumulating material goods, not out of need but only in order to feel secure. The fact is that we are not able to bring material goods with us when we leave this life, since “the winding sheet does not have pockets” and all our treasures will never be able to fill that void; instead, they will only make it deeper and more demanding. Accumulating goods only burdens and inexorably slows down the journey!
The disease of closed circles, where belonging to a clique becomes more powerful than our shared identity. This disease too always begins with good intentions, but with the passing of time it enslaves its members and becomes a cancer which threatens the harmony of the organization and causes immense evil, especially to those we treat as outsiders. “Friendly fire” from our fellow soldiers, is the most insidious danger. It is the evil which strikes from within. As it says in the bible, “Every kingdom divided against itself is laid waste.”
Lastly: the disease of extravagance and self-exhibition. This happens when a leader turns his or her service into power, and uses that power for material gain, or to acquire even greater power. This is the disease of persons who insatiably try to accumulate power and to this end are ready to slander, defame and discredit others; who put themselves on display to show that they are more capable than others. This disease does great harm because it leads people to justify the use of any means whatsoever to attain their goal, often in the name of justice and transparency! Here I remember a leader who used to call journalists to tell and invent private and confidential matters involving his colleagues. The only thing he was concerned about was being able to see himself on the front page, since this made him feel powerful and glamorous, while causing great harm to others and to the organization.
Friends, these diseases are a danger for every leader and every organization, and they can strike at the individual and the community levels.
____________________
So, are you a healthy leader? Use the Pope’s inventory of leadership maladies to find out. Ask yourself, on a scale of 1 to 5, to what extent do I . . .
Feel superior to those who work for me?
Demonstrate an imbalance between work and other areas of life?
Substitute formality for true human intimacy?
Rely too much on plans and not enough on intuition and improvisation?
Spend too little time breaking silos and building bridges?
Fail to regularly acknowledge the debt I owe to my mentors and to others?
Take too much satisfaction in my perks and privileges?
Isolate myself from customers and first-level employees?
Denigrate the motives and accomplishments of others?
Exhibit or encourage undue deference and servility?
Put my own success ahead of the success of others?
Fail to cultivate a fun and joy-filled work environment?
Exhibit selfishness when it comes to sharing rewards and praise?
Encourage parochialism rather than community?
Behave in ways that seem egocentric to those around me?
As in all health matters, it’s good to get a second or third opinion. Ask your colleagues to score you on the same fifteen items. Don’t be surprised if they say, “Gee boss, you’re not looking too good today.” Like a battery of medical tests, these questions can help you zero in on opportunities to prevent disease and improve your health. A Papal leadership assessment may seem like a bit of a stretch. But remember: the responsibilities you hold as a leader, and the influence you have over others’ lives, can be profound. Why not turn to the Pope — a spiritual leader of leaders — for wisdom and advice?
Fears about potential future existential risk are blinding us to the fact AI systems are already hurting people here and now.
October 30, 2023
This is an excerpt from Unmasking AI: My Mission to Protect What Is Human in a World of Machines by Joy Buolamwini, published on October 31 by Random House. It has been lightly edited.
The term “x-risk” is used as a shorthand for the hypothetical existential risk posed by AI. While my research supports the idea that AI systems should not be integrated into weapons systems because of the lethal dangers, this isn’t because I believe AI systems by themselves pose an existential risk as superintelligent agents.
AI systems falsely classifying individuals as criminal suspects, robots being used for policing, and self-driving cars with faulty pedestrian tracking systems can already put your life in danger. Sadly, we do not need AI systems to have superintelligence for them to have fatal outcomes for individual lives. Existing AI systems that cause demonstrated harms are more dangerous than hypothetical “sentient” AI systems because they are real.
The pioneering AI researcher and activist shares her personal journey in a new book, and explains her concerns about today’s AI systems.
One problem with minimizing existing AI harms by saying hypothetical existential harms are more important is that it shifts the flow of valuable resources and legislative attention. Companies that claim to fear existential risk from AI could show a genuine commitment to safeguarding humanity by not releasing the AI tools they claim could end humanity.
I am not opposed to preventing the creation of fatal AI systems. Governments concerned with lethal use of AI can adopt the protections long championed by the Campaign to Stop Killer Robots to ban lethal autonomous systems and digital dehumanization. The campaign addresses potentially fatal uses of AI without making the hyperbolic jump that we are on a path to creating sentient systems that will destroy all humankind.
Though it is tempting to view physical violence as the ultimate harm, doing so makes it easy to forget pernicious ways our societies perpetuate structural violence. The Norwegian sociologist Johan Galtung coined this term to describe how institutions and social structures prevent people from meeting their fundamental needs and thus cause harm. Denial of access to health care, housing, and employment through the use of AI perpetuates individual harms and generational scars. AI systems can kill us slowly.
Given what my “Gender Shades” research revealed about algorithmic bias from some of the leading tech companies in the world, my concern is about the immediate problems and emerging vulnerabilities with AI and whether we could address them in ways that would also help create a future where the burdens of AI did not fall disproportionately on the marginalized and vulnerable. AI systems with subpar intelligence that lead to false arrests or wrong diagnoses need to be addressed now.
When I think of x-risk, I think of the people being harmed now and those who are at risk of harm from AI systems. I think about the risk and reality of being “excoded.” You can be excoded when a hospital uses AI for triage and leaves you without care, or uses a clinical algorithm that precludes you from receiving a life-saving organ transplant. You can be excoded when you are denied a loan based on algorithmic decision-making. You can be excoded when your résumé is automatically screened out and you are denied the opportunity to compete for the remaining jobs that are not replaced by AI systems. You can be excoded when a tenant-screening algorithm denies you access to housing. All of these examples are real. No one is immune from being excoded, and those already marginalized are at greater risk.
This is why my research cannot be confined just to industry insiders, AI researchers, or even well-meaning influencers. Yes, academic conferences are important venues. For many academics, presenting published papers is the capstone of a specific research exploration. For me, presenting “Gender Shades” at New York University was a launching pad. I felt motivated to put my research into action—beyond talking shop with AI practitioners, beyond the academic presentations, beyond private dinners. Reaching academics and industry insiders is simply not enough. We need to make sure everyday people at risk of experiencing AI harms are part of the fight for algorithmic justice.
Check out the Five Takeaways from #HIMSS25 to watch #FEHRM Director William Tinston share the latest about the #FederalEHR and what’s ahead in the evolving #healthcare landscape. https://lnkd.in/em_PSw6y.
AI technologies have had an undeniable impact on the information landscape.
If deployed responsibly, AI can facilitate access to accurate, reliable information, foster free expression, and contribute to healthy and vibrant information ecosystems.
One of the focus areas of the meeting was AI’s impact on information integrity.
Two key risks were highlighted:
1. The role of AI in curating and creating information, and people’s growing reliance on this technology to shape their understanding of the world.
At present, tech companies continue to integrate AI into our everyday applications at breakneck speed but genAI tools cannot uniformly be relied on as sources of accurate information.
Ongoing studies and testing show that they frequently do not distinguish between rigorous science on the one hand and dirty data or outright nonsense on the other.
And yet, people are increasingly accessing this convenient and flawed data without being equipped to assess its veracity or reliability. This can contribute to a deeply concerning trend: thelack of trust in any information source and in the information ecosystem more broadly.
People just don’t know what is real and what to believe.
At pivotal societal moments and especially in fragile settings, this can feed into instability and unrest, sometimes with disastrous consequences.
We are, in effect, guinea pigs in an information experiment in which the resilience of our societies is being put to the test.
2. The misuse of AI in facilitating the creation and dissemination of false and hateful information at scale.
This can affect the peace and security of communities and countries.
GenAI tools have made it immeasurably easier for a broad range of actors to spread false claims for financial or strategic gain.
It now costs next to nothing to quickly and easily create a flood of convincing lies and hate, with minor human intervention.
To target specific groups and individuals, actors draw on our personal data that has been sold as part of the advertising supply chain.
Tactics like this can trigger diplomatic crises, incite unrest, and undermine understanding of realities on the ground.
AI-generated deep fake images, audio and video have been weaponized in conflicts from Ukraine, to Gaza, to Sudan.
We’re also now seeing AI used openly and explicitly to generate content designed to undermine social cohesion.
Content that demonises or dehumanises women, refugees, migrants, and minorities.
Content that is anti-Semitic, Islamophobic, racist and xenophobic.
The UN has experienced grave impacts on our missions and priorities.
Peace and humanitarian operations are targeted with false and hateful narratives, negatively affecting the safety and security of UN personnel and making the tasks of implementing their mandates harder.
In turn, this is impacting communities small and large, jeopardizing their stability.
What are some of the concrete steps needed to address these areas of risk?
The UN system has been ramping up efforts.
This includes the 3R approach:
research, risk assessment and response.
Through research we can better understand information risks in complex, multiplatform, multilingual environments.
Our work includes outreach with affected communities to hear and understand their perceptions and concerns.
UN entities then assess the risk posed to UN mandate delivery and thematic priorities.
We use this insight to design appropriate mitigation and response measures.
Most immediately, this means quick and proactive communication to address information voids.
This can be done through our own channels and also via coalitions with community leaders, influencers and civil society groups.
Of course, these efforts require resources, including for skills training and technology.
The Principles provide a framework for action to strengthen the information ecosystem — and are a resource to UN member countries in meeting the commitments agreed in the Global Digital Compact.
The Principles contain recommendations for a wide range of stakeholders around five pillars: societal trust and resilience; healthy incentives; public empowerment; independent, free and pluralistic media; and transparency and research.
The United Nations Global Principles for Information Integrity
Three key recommendation areas are highlighted below.
1. Countries play a central role in shaping information spaces, beginning with obligations to respect, protect and promote human rights, in particular the right to freedom of expression.
This means that regulatory measures to address information integrity comply with applicable international law and are carried out with the full participation of civil society.
Freedom of expression requires not only that people are able to express their views, but that they are able to seek and receive ideas and information of all kinds.
It is exponentially harder to do this when you’re in a polarized, opaque information environment crowded with lies and hate.
In such a landscape, guardrails allow for more free speech, not less, and protect people who feel unsafe in online spaces, giving voice to those otherwise silenced.
Guardrails can help enable inclusive access to information.
And they can support and encourage innovation and help foster public trust in fast-emerging AI technologies.
There is growing awareness among the communities the UN serves that the sooner guardrails are established, the less the risk for us all.
2. Information integrity is not possible without a free, independent and pluralistic media.
Professional journalism requires considerable investment. Yet the advertising-driven business model which long supported independent media has drastically eroded.
AI has prompted new concerns. Quality journalism is being scraped and summarized or used to train AI without permission or compensation.
GenAI search summaries replacing standard search results can reduce web traffic to news sites, further affecting revenue streams.
Many news outlets, particularly at the local level, just can’t compete. For them it is not just a matter of relevance. It is a matter of survival.
The result is news deserts. The vacuum is filled by AI-generated articles or downgraded versions of journalistic content, or malicious content imitating news.
This can be particularly destabilising in conflict and crisis zones.
Responses must therefore urgently support sustainable business models for public interest media.
They must also ensure better protection for media workers, along with researchers, academics and civil society, who are under attack around the world.
3. There is an urgent global need for public empowerment in the information ecosystem, including through measures to boost resilience.
Media and digital literacy skills can allow people to navigate information spaces safely and effectively.
Countries can prioritize the literacy needs of groups in vulnerable and marginalized situations — who are often those most adversely affected by information risks.
They can also undertake literacy efforts around specific problems related to AI, keeping up with new and emerging technologies
Public awareness must improve around online rights, how AI works, and how personal data is used.
The urgency of the challenge requires multi stakeholder coalitions with collaborations between countries to support capacity building and increase global resilience.
This is the only viable path to an information ecosystem in which AI innovation is harnessed for information integrity, human rights and international peace and security.
The text above is adapted from a briefing to the Security Council by Charlotte Scaddan, Senior Adviser on Information Integrity, UN Global Communications
The Indian Health Service (IHS) is a federally mandated health system providing care to approximately 2.6 million American Indian and Alaska Native people across 574 federally recognized Tribes. Many IHS facilities are in rural or remote areas, often providing the only available healthcare. Unlike other American health systems, IHS is not a benefit or entitlement – it is the product of treaties between the United States and sovereign Tribal Nations.
In FY2023, IHS spent approximately $4,078 per person on care, compared to a national average expenditure of $14,570 per person. Despite challenges, including aging facilities and staffing shortages, IHS delivers remarkable care. Staffed by dedicated Native and allied physicians, nurses, public health workers, and technicians, these facilities are models of resilience. They frequently incorporate traditional healers and language keepers into care delivery, finding innovative ways to meet complex health needs.
Federal decisions, like those discussed by Health Secretary Robert F. Kennedy Jr. during his “Make America Healthy Again” tour, directly impact the resources and policies that shape the IHS and its ability to serve Tribal communities effectively. Additional resources at IHS, combined with the cultivation and empowerment of Indigenous healthcare professionals and Tribal leadership, could be transformative. We hope that the pleas from our tribal members resonated with Secretary Kennedy and leads to meaningful support for IHS.
Secretary Kennedy The New York Times CDC Indian Country Today Indian Health Service Johns Hopkins Bloomberg School of Public Health National Indian Health Board National Native News Native News Online Urban Indigenous Collective Urban Indian Health Institute Johns Hopkins Department of International Health
When two black holes spiral inward and collide, they shake the very fabric of space, producing ripples in space-time that can travel for hundreds of millions of light-years. Since 2015, scientists have been observing these so-called gravitational waves to help them study fundamental questions about the cosmos, including the origin of heavy elements such as gold and the rate at which the universe is expanding.
But detecting gravitational waves isn’t easy. By the time they reach Earth and the twin detectors of the Laser Interferometer Gravitational-Wave Observatory (LIGO), in Louisiana and Washington state, the ripples have dissipated into near silence. LIGO’s detectors must sense motions on the scale of one ten-thousandth the width of a proton to stand a chance.
LIGO has confirmed 90 gravitational wave detections so far, but physicists want to detect more, which will require making the experiment even more sensitive. And that is a challenge.
“The struggle of these detectors is that every time you try to improve them, you actually can make things worse, because they are so sensitive,” says Lisa Barsotti, a physicist at the Massachusetts Institute of Technology.
Nevertheless, Barsotti and her colleagues recently pushed past this challenge, creating a device that will allow LIGO’s detectors to detect far more black hole mergers and neutron star collisions. The device belongs to a growing class of instruments that use quantum squeezing—a practical way for researchers dealing with systems that operate by the fuzzy rules of quantum mechanics to manipulate those phenomena to their advantage.
Physicists describe objects in the quantum realm in terms of probabilities—for example, an electron is not located here or there but has some likelihood of being in each place, locking into one only when its properties are measured. Quantum squeezing can manipulate the probabilities, and researchers are increasingly using it to exert more control over the act of measurement, dramatically improving the precision of quantum sensors like the LIGO experiment.
“In precision sensing applications where you want to detect super-small signals, quantum squeezing can be a pretty big win,” says Mark Kasevich, a physicist at Stanford University who applies quantum squeezing to make more precise magnetometers, gyroscopes, and clocks with potential applications for navigation. Creators of commercial and military technology have begun dabbling in the technique as well: the Canadian startup Xanadu uses it in its quantum computers, and last fall, DARPA announced Inspired, a program for developing quantum squeezing technology on a chip. Let’s take a look at two applications where quantum squeezing is already being used to push the limits of quantum systems.
Taking control of uncertainty
The key concept behind quantum squeezing is the phenomenon known as Heisenberg’s uncertainty principle. In a quantum-mechanical system, this principle puts a fundamental limit on how precisely you can measure an object’s properties. No matter how good your measurement devices are, they will suffer a fundamental level of imprecision that is part of nature itself. In practice, that means there’s a trade-off. If you want to track a particle’s speed precisely, for example, then you must sacrifice precision in knowing its location, and vice versa. “Physics imposes limits on experiments, and especially on precision measurement,” says John Robinson, a physicist at the quantum computing startup QuEra.
By “squeezing” uncertainty into properties they aren’t measuring, however, physicists can gain precision in the property they want to measure. Theorists proposed using squeezing in measurement as early as the 1980s. Since then, experimental physicists have been developing the ideas; over the last decade and a half, the results have matured from sprawling tabletop prototypes to practical devices. Now the big question is what applications will benefit. “We’re just understanding what the technology might be,” says Kasevich. “Then hopefully our imagination will grow to help us find what it’s really going to be good for.”
LIGO is blazing a trail to answer that question, by enhancing the detectors’ ability to measure extremely tiny distances. The observatory registers gravitational waves with L-shaped machines capable of sensing tiny motions along their four-kilometer-long arms. At each machine, researchers split a laser beam in two, sending a beam down each arm to reflect off a set of mirrors. In the absence of a gravitational wave, the crests and troughs of the constituent light waves should completely cancel each other out when the beams are recombined. But when a gravitational wave passes through, it will alternately stretch and compress the arms so that the split light waves are slightly out of phase.
The resulting signals are subtle, though—so subtle that they risk being drowned out by the quantum vacuum, the irremovable background noise of the universe, caused by particles flitting in and out of existence. The quantum vacuum introduces a background flicker of light that enters LIGO’s arms, and this light pushes the mirrors, shifting them on the same scale as the gravitational waves LIGO aims to detect.
Barsotti’s team can’t get rid of this background flicker, but quantum squeezing allows them to exert limited control over it. To do so, the team installed a 300-meter-long cavity in each of LIGO’s two L-shaped detectors. Using lasers, they can create an engineered quantum vacuum, in which they can manipulate conditions to increase their level of control over either how bright the flicker can be or how randomly it occurs in time. Detecting higher-frequency gravitational waves is harder when the rhythm of the flickering is more random, while lower-frequency gravitational waves get drowned out when the background light is brighter. In their engineered vacuum, noisy particles still show up in their measurements, but in ways that don’t do as much to disturb the detection of gravitational waves.“ You can [modify] the vacuum by manipulating it in a way that is useful to you,” she explains.
The innovation was decades in the making: through the 2010s, LIGO incorporated incrementally more sophisticated forms of quantum squeezing based on theoretical ideas developed in the 1980s. With these latest squeezing innovations, installed last year, the collaboration expects to detect gravitational waves up to 65% more frequently than before.
Quantum squeezing has also improved precision in timekeeping. Working at the University of Colorado Boulder with physicist Jun Ye, a pioneer in atomic clock technology, Robinson and his team made a clock that will lose or gain at most a second in 14 billion years. These super-precise clocks tick slightly differently in different gravitational fields, which could make them useful for sensing how Earth’s mass redistributes itself as a result of seismic or volcanic activity. They could also potentially be used to detect certain proposed forms of dark matter, the hypothesized substance that physicists think permeates the universe, pulling on objects with its gravity.
The clock Robinson’s team developed, a type called an optical atomic clock, uses 10,000 strontium atoms. Like all atoms, strontium emits light at specific signature frequencies as electrons around the atom’s nucleus jump between different energy levels. A fixed number of crests and troughs in one of these light waves corresponds to a second in their clock. “You’re saying the atom is perfect,” says Robinson. “The atom is my reference.” The “ticking” of this light is far steadier than the vibrating quartz crystal in a wristwatch, for example, which expands and contracts at different temperatures to tick at different rates.
In practice, the tick in the Robinson team’s clock comes not from the light the electrons emit but from how the whole system evolves over time. The researchers first put each strontium atom in a “superposition” of two states: one in which the atom’s electrons are all at their lowest energy levels and another in which one of the electrons is in an excited state. This means each atom has some probability of being in either state but is not definitively in either one—similar to how a coin flipping in the air has some probability of being either heads or tails, but is neither.
Then they measure how many atoms are in each state. The act of measurement puts the atoms definitively in one state or the other, equivalent to letting the flipping coin land on a surface. Before they measure the atoms, even if they intend to wind up with a 50-50 mixture, they cannot precisely dictate how many atoms will end up in each state. That’s because in addition to the system’s change over time, there is also inherent uncertainty in the state of the individual atoms. Robinson’s team uses quantum squeezing to more reliably determine their final states by reducing these intrinsic fluctuations. Specifically, they manipulate the uncertainties in the direction of each atom’s spin, a property of many quantum particles that has no classical counterpart. Squeezing improved the clock’s precision by a factor of 1.5.
To be sure, gravitational waves and ultra-precise clocks are niche academic applications. But there is interest in adapting the approach to other, potentially more mainstream uses, including quantum computers, navigation, and microscopy.
The increased use of quantum squeezing is part of a wider technological trend toward higher precision—one that encompasses cramming more transistors on chips, studying the universe’s most elusive particles, and clocking the fleeting time it takes for an electron to leave a molecule. Squeezing benefits only measurements so subtle that the randomness of quantum mechanics contributes significant noise. But it turns out that physicists have more control than they think. They may not be able to remove the randomness, but they can engineer where it shows up.
Only a year ago, Pat Gelsinger intended for Intel to compete with Nvidia, but the new CEO, Lip-Bu Tan, is burying that ambition. He does not aim at the Client Computing Group when discussing funding new engineering ideas and innovations. The Day 1 principle is a start-up philosophy; the new AI strategy after Gaudi has been virtually written off.
And it makes sense. While Intel was playing CEO roulette, Nvidia increased its R&D budget dramatically, and the AI giant did not need to fund other hobby projects like Intel. To catch Nvidia, Intel needed a big bet, which Gaudi never was, and now it is too late.
In 2024, Intel was spending 45% of its operating budget on Intel Foundry, and what was left of the R&D budget was prioritised for the Client Computing Group.
This is insufficient to compete with Nvidia, so the Intel Periscope has turned towards the two smaller vessels involved in XPU designs.
If the New Intel and the 2025 Vision are important to you, read more here: https://lnkd.in/drXUPZXJ
Intel’s new CEO, Lip-Bu Tan, brought many new words that can give us insight into Intel’s strategy. While words don’t easily move supertankers like Intel, words are important, and all strategy and transformation begin with words.
Under Pat Gelsinger, there were several strategic pivots. While he was the master of creative external CapEx deals to fund Intel Foundry, the strategy was retrenched to a focus on the x86 franchise and the Client Computing group under Michelle Johnston Holthaus as she protected her CCG tribe.
The appointment of Lip-Bu Tan does not continue the current Intel Strategy, and it is vital to understand what the new CEO brings to the party. You can think what you want about Intel, but it still powers most of the world’s computing even though it is struggling to do so profitably. Intel is still a key factor in the development of the semiconductor industry.
In his first keynote, Lip-Bu Tan directly discussed not being happy with where Intel is. While this is not the same as signalling a strategic change, his statements about ruthlessly focusing on the truth are. This is an acceptance of the Intel culture of “glossing over” rather than facing the brutal truths.
The most radical idea that Lip-Bu Tan introduced was that Intel needs to adopt a day 1 mentality. While it sounds like more words, the implications of a “Day 1 mentality” can mean dramatic change for the Intel organisation and culture, as Intel is currently the poster child of a “Day 2” company.
Amazon’s “Day One”: A Philosophy of Perpetual Innovation
At the heart of Amazon’s relentless drive lies its “Day One” philosophy, which emphasises maintaining a startup-like mentality, even within a massive corporation. Introduced by Jeff Bezos in his 1997 shareholder letter, “Day One” is about constant curiosity, nimbleness, and a willingness to experiment. It’s the antithesis of “Day Two,” where complacency sets in, and companies become slow, bureaucratic, and less customer-focused.
Bezos understood that customer obsession is the key to maintaining “Day One” vitality. As customers always seek better, faster, and more innovative solutions, companies must continuously adapt and evolve to meet their needs. As tech reporter Alex Kantrowitz explains in his book “Always Day One,” this philosophy encourages building for the future, not resting on past achievements. It means treating even a sprawling enterprise like a small, agile startup, fostering a culture of innovation and a relentless focus on the customer. In essence, “Day One” is about embracing change, challenging the status quo, and always acting with the urgency and passion of a company just starting.
Lip-Bu keeps flirting with “Day 1” as he calls for customer focus.
“My number one priority was spending time with customers, and they gave me honest feedback. We have a lot of work ahead of us.”
While talking to customers and getting feedback is essential, it is not the same as becoming customer-centric. A company like Apple is customer-centric and has delivered the most successful consumer product ever, even though nobody ever asked for an iPhone.
Talking to customers isn’t enough; you’ll need to understand their future situation and latent needs. This is not Intel’s traditional starting point, as the company has its cultural roots deep in products and technology, and Lip-Bu Tan wants to challenge that.
When discussing his background, Lip-Bu Tan highlights times when he successfully changed the culture of the companies he was involved with. This signals that cultural change is high on the agenda, and he believes he is the right person to drive it.
This also reveals that Lip-Bu Tan believes that corporate culture can be designed within a reasonable timeframe, which sounds more straightforward than it is.
Anybody who has worked in a company with several acquisitions knows that the acquired culture does not die. It lives on in the acquired people and influences the existing culture.
One of the key features of a large corporation is what I call management-dampening. All top management decisions must pass through the hierarchical layers in a sense-making process. The simple CEO decisions have complex impacts on the organisation, and each level needs to adapt to them in a way that makes sense for that layer and their internal and external customers.
The company’s suspension system ensures that radical changes don’t break the system and prevent change from happening.
I have seen several examples of how the management-dampening system has saved (prevented) senior management’s panic-flip-flopping decisions. Unfortunately, it also dampens necessary changes and complicates cultural change.
An overview of the “Day One” philosophy can be seen below, along with the key message.
As Lip-Bu Tan talks about the truth, it is necessary to highlight Intel’s current approach to these principles. While you might disagree with my assessment, it is hard to characterise Intel as anywhere near a “Day One” company.
Lip-Bu Tan recognises this as he states that he is unhappy with things and wants to correct past mistakes. He wants to create the “New Intel”, an engineering-first company, suggesting that Intel is currently a “something else-first” company.
The truth
The foundation of everything I do starts with a data-driven assessment of the current situation. While I know it is easier to sell happy data, it is a principle of mine to stay clear of liking and disliking data.
There can be many truths, and data does respond to torture. Still, it is always in the company’s best interest to begin the strategic formulation based on an honest assessment of the situation.
Happy data rarely creates happy endings.
Intel is undoubtedly in a difficult spot, and Lip-Bu Tan’s ambitions are at odds with reality. Scarcity creates tension between different objectives but is innovation’s greatest friend.
As I pointed out in The Corporate Sandwich Model, Intel externally has a problem with the truth. It is all rah-rah and up and to the right. This might be different internally, but I doubt it.
It’s time to explore the tension between reality and the Intel 2025 Vision.
The x86 Franchise
The most apparent change in strategy from Gelsinger to Holthaus was the introduction of the “x86 franchise”. That the Queen of the Client Computing Group praised the holiest of relics in CCG was unsurprising and looked like the usual internal divisional power game. Lip-Bu Tan adds colour to the x86 concept and positions it more as an asset in the Foundry strategy as part of the differentiation strategy: IP and localisation. The x86 is also positioned in the future AI strategy built on the smoulders of Gaudi that Holthaus effectively killed by calling it “difficult” to use
The Innovation perspective.
Intel is trying to reduce operating costs to achieve positive cash flow. However, it is becoming evident that Intel’s current AI data centre product strategy is non-existent.
In the 2024 Intel Vision keynote, Pat Gelsigner called Gaudi the only alternative to Nvidia H100 in data centre learning applications. As Michelle Johnston Holthaus took the co-CEO chair, she demonstrated the rift between the client group and the other divisions and called Gaudi challenging. This was a virtual death sentence, and Lip-Bu Tan is not reviving the architecture.
He clearly stated that Intel is unhappy with its current position and needs to develop a new approach. Intel needs higher performance, lower power and lower cost. In one year, The focus shifted from competing with Nvidia to competing with Broadcom and Marvell in XPU accelerators in inference rather than Nvidia in Learning and inference.
This also correlates with his statements about becoming an outside-in company that starts with the customer’s problem rather than the hardware in the old inside-out approach.
Nvidia’s AI strategy builds on a well-executed product strategy, while Broadcom and Marvell are working on customer problems. Customers are telling Li-Bu Tan that they would love an Intel AI Platform (cheaper, faster, lower power—surprise!), and he has started deep-dive dives into reimagining the products.
This is the key area to win as AI accelerates tech adoption and is the only driver behind the upturn. Other focus areas, such as photonics, quantum, and robotics, are on the agenda, but the data centre AI needs to be revived.
The competitive situation in AI is hopeless for Intel.
Excluding Nvidia revenue makes it even more embarrassing for Intel. For now, it is evident that Intel is not aiming at Nvidia and learning but at the competitors in sight that are focusing on the accelerator designs.
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