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I run a workplace management platform. Here's how AI is reshaping both the culture and physical form of offices. - Yahoo

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This week, a power line failure occurred just outside Washington, DC, which typically allows the electrical grid to recover within seconds. However, this incident took over 10 minutes to stabilize due to a simultaneous shutdown of more than 3 gigawatts worth of power from data centers.

Data collected by Ting Labs, a startup utilizing an IoT sensor network, highlighted that the voltage across the PJM grid surged from Northern Virginia to Chicago as a result of this event. While the incident did not lead to a blackout, it did cause noticeable flickering of lights throughout the area, illustrating the significant impact large data centers can have on the grid — a trend that experts anticipate will occur more frequently.

Northern Virginia, part of the PJM territory, boasts the highest concentration of data centers globally. Ricardo de Azevedo, CTO of ON.Energy, described the situation as indicative of broader issues, pointing to similar events becoming increasingly common.

This recent occurrence resembled a similar incident from two years prior, also affecting the PJM grid, raising concerns about the potential for more severe disruptions if data centers do not adopt strategies to handle such power outages effectively. The PJM Interconnection is the largest grid operator in the United States, managing the electrical supply for 67 million customers across states from New Jersey to Illinois.

During this week's event, data centers quickly transitioned to backup power systems, leading to a rapid drop in demand of around 3.1 gigawatts within 30 seconds, according to PJM data. Although the grid initially showed signs of recovery, further load reductions caused it to take an additional 11 minutes to stabilize. The data centers that disconnected accounted for roughly 3% of PJM’s total demand at that time, as reported by Reuters.

While 3% may seem minor, the grid must maintain a delicate balance between supply and demand. An imbalance can lead to voltage fluctuations. While minor deviations can be tolerated, substantial changes can activate grid failsafes, resulting in disconnections.

As disturbances from the failed power line reached Northern Virginia data centers, they swiftly shifted to backup power, exacerbating the initial load drop and contributing to voltage instability that made lights flicker. Ali Zain Banatwala, a senior market models specialist at the Independent Electricity System Operator, mentioned that the affected data centers acted almost instantaneously, disconnecting in unison to the voltage dip.

To mitigate similar issues in the future, Banatwala emphasized the need for a more structured protocol that allows neighboring data centers to disconnect or reconnect in a staggered manner. This change could enable grid operators to devise more effective contingency plans.

Alternatively, there’s potential for reengineering data centers to better withstand such disruptions. ON.Energy has been innovating a new uninterruptible power supply designed for entire data center campuses. Their system integrates batteries and advanced power conversion technology, allowing the grid to perceive a stable load without fluctuations from the various components operating within the data center. This setup enables operators to adjust computing tasks efficiently while minimizing the impact on the grid.

Importantly, this system allows data centers to manage power variations: excess energy can be stored in batteries during peak demand, while surplus can be dispatched immediately if grid supply dips, preventing issues like those experienced during the recent outage.

ON.Energy is currently in the process of installing 3 gigawatts of its systems across four different data center locations, as per de Azevedo’s statement.

Grid operators are becoming increasingly aware of the challenges posed by large power loads such as data centers. For instance, ERCOT is now mandating that these facilities be capable of "riding through" power disruptions.

However, urgency remains. The recent mass disconnection event was double the scale of a previous incident in 2024, where 60 data centers together disconnected, pulling 1.5 gigawatts from the grid. At that time, data centers represented about 6% of PJM's total load, a figure projected to rise to 24% by 2040. Without timely solutions, the implications for grid stability could worsen significantly.

A downed power line highlighted an escalating issue with AI data centers. Here’s the solution.

Dark, stormy night outside a glass-walled AI data center. A wooden utility pole has snapped, live wires sparking orange-red on wet pavement. Inside the building, rows of server racks flicker between dim red warning lights and blackout. A lone technician in a high-visibility vest kneels under the beam of a handheld lantern, inspecting an emergency generator. Tense, dramatic shadows and warm spark glows highlight the vulnerability—and hint at the fixes needed.

One fallen power line exposed a growing AI data center problem. Here’s how to fix it. - TechCrunch

- A downed power line caused 3 gigawatts of data centers to disconnect from the grid.  
- The PJM grid experienced voltage spikes, causing flickering lights without leading to a blackout.  
- Experts warn that data centers need improvements to handle power supply disruptions effectively.  

A power line went down outside of Washington, DC, this week. Normally, the grid would only need a few seconds to recover from such an event. But this one took more than 10 minutes because more than 3 gigawatts of data centers stopped drawing power nearly simultaneously.

The event caused voltage across the PJM grid to spike from Northern Virginia to Chicago, according to data collected by Ting Labs, a startup that runs an IoT sensor network out of people’s electrical sockets.

The event didn’t cause a blackout, but it did cause lights across the region to flicker. The incident demonstrated the effect that data centers can have on the grid — an outcome that experts believe will become more frequent.

Northern Virginia, which is in PJM’s territory, is home to the highest concentration of data centers in the world.

“It’s the canary in the coal mine,” Ricardo de Azevedo, CTO at ON.Energy, told TechCrunch. These sorts of events involving large loads like data centers are “happening more and more,” he added.

The event echoes one that happened two years ago, also on PJM’s grid, and it could foreshadow larger events if data centers aren’t built to more elegantly handle disruptions to power supplies. The PJM Interconnection manages grids from New Jersey to Illinois and serves 67 million customers, making it the largest grid operator in the United States.

When the power line went down this week, it triggered data centers to switch to backup power, and about 3.1 gigawatts of load vanished in about 30 seconds, according to PJM data. The grid appeared to recover somewhat, but a short time later additional loads dropped off. At its peak, PJM’s grid had an extra 3.49 gigawatts of electricity on it. It took another 11 minutes before it stabilized. The disconnected data centers represented around 3% of total demand on PJM at the time, according to Reuters.

A few percent may not sound like much, but the electrical grid needs to operate in a state of near-perfect balance, with supply and demand closely matched. If they don’t, voltages can sag or spike. The grid and devices connected to it can tolerate small fluctuations, but if those fluctuations grow too large, they’ll trigger failsafes within the grid or within individual facilities, causing them to disconnect.

When data centers in Northern Virginia sensed the fluctuation caused by the failed power line, they switched to backup power, which removed their load from the grid. As more data centers made the switch, they removed greater amounts of load from the grid. What started as a relatively small drop in supply became an even larger drop in demand, sending supply surging and causing light bulbs to flicker.

Most data centers make decisions in a split second, and those that disconnected this week appear to be no different. When the voltage dip reached them, they all decided to disconnect within a few seconds of each other, Ali Zain Banatwala, senior market models specialist at the Independent Electricity System Operator, told TechCrunch.

“We need to figure a way for these loads that are located next to each other to sequentially either disconnect or reconnect,” he said. A more orderly process would allow grid operators to develop more robust procedures in advance.

Alternatively, data centers could be built to absorb disruptions and not turn their backs to them. One startup, ON.Energy, has been working on a product to help data centers — and the grid — ride through events like the one that occurred this week.

The company has developed an uninterruptible power supply for an entire data center campus, covering not just servers but also chillers and other equipment. The company essentially hides the data center behind a bank of batteries connected to sophisticated power conversion equipment. All the grid “sees” is one consistent, well-behaved load rather than the peaks and valleys from each individual part of the data center. ON.Energy’s system allows data centers to ramp computing workloads up and down, including AI training, without bothering the grid.

Perhaps more important, it also means that data centers can absorb power fluctuations from the grid. Rather than disconnecting from the grid, ON.Energy’s system can use any extra power to charge its batteries, and if the flow dips, the system can dispatch power to servers. Plus, it can follow the grid’s lead within milliseconds, preventing sags or surges like the ones that caused this week’s problem for PJM.

ON.Energy is currently installing a total of 3 gigawatts worth of its systems at four different data center campuses, de Azevedo said.

Grid managers have also woken up to the problem.

ERCOT, for example, is going to require large loads like data centers to “ride through” disruptions, de Azevedo said.

The clock is ticking, though. The mass disconnection this week was twice as large as a similar event in 2024, when 60 data centers simultaneously disconnected, pulling 1.5 gigawatts of load from the grid. Back then, data centers accounted for about 6% of PJM’s load, according to Synapse Energy Economics. By 2040, they are expected to make up 24%. If the problem isn’t addressed soon, things could get a lot worse.

One fallen power line exposed a growing AI data center problem. Here’s how to fix it.

Last March, Anthropic, an innovative AI firm known for its chatbot Claude, released a study examining the implications of artificial intelligence on the labor market. This analysis was intended to address concerns that advanced AI could dramatically alter human life and diminish the need for human workers.

In May of the previous year, Anthropic's co-founder Dario Amodei expressed the belief that AI might eliminate 50% of entry-level positions within five years. By January, he indicated that AI could serve as a “general labor substitute for humans,” and in June, he highlighted the potential dangers of an economy trapped in a cycle of rapid growth and increasing inequality.

Despite these dire predictions, Anthropic's report indicates that the impact of AI has not met these expectations. The findings reveal that since late 2022, there has been no significant rise in unemployment among workers who are most vulnerable to AI automation. The current implementation of AI technology is still only a small fraction of what is theoretically possible. For example, Claude currently handles merely 33% of all tasks in the computer and math domain, even though it could potentially manage nearly 100%.

While there is a surge in investment in data centers, productivity gains have not matched the high hopes set by early tech predictions. In fact, labor productivity growth has been slower in the AI era’s initial three years compared to the tech boom of the 1990s.

OpenAI’s Sam Altman, one of the leading figures in AI, has recently voiced skepticism regarding fears of mass job loss. He remarked in May that the anticipated “jobs apocalypse” may not materialize as some industry advocates claim. MIT economist David Autor echoed this sentiment, noting that many have observed slower changes in the job market than anticipated.

This shift in perspective has sparked discussions around a more nuanced understanding of how automation interacts with human employment. Analysts are now questioning whether AI will truly bring about the profound changes it promised. Since peaking in early June, the tech-heavy Nasdaq index, largely driven by AI stocks, has seen an approximately 8% decline.

Critics of the idea that AI can seamlessly transform industries point to the "O-ring" theory, derived from the Challenger space shuttle disaster caused by a faulty O-ring. The argument suggests that until AI can perform every task flawlessly, the value of remaining tasks will increase. This could either elevate the worth of higher-skilled workers or create new opportunities for lower-skilled labor as AI takes on more complex duties.

A recent study highlighted that while AI substitutes tasks at a significant rate, the overall employment impacts have been modest. Reduced demand in affected roles can be balanced by increased labor demand driven by productivity gains in companies that adopt AI.

However, the landscape could shift, as Jed Kolko emphasizes that research into AI’s effects on the labor market is still in its early stages. Amodei's predictive window remains open for nearly four more years, suggesting that significant changes could take time. The Federal Reserve notes a rapid rise in AI adoption among businesses.

Autor also points out that AI is continuing to improve, with progress showing no signs of stagnation. The potential for a dystopian or utopian AI future remains alive, particularly for those in control of the technology. Daron Acemoglu, a Nobel laureate economist, observed that insiders remain optimistic, with many still anticipating the arrival of artificial general intelligence soon. Elon Musk continues to promote the vision of a world where AI and robots enable universal income, allowing work to become optional.

Historically, economists have noted the discrepancy between technological advancements and productivity statistics. Robert Solow remarked, "You can see the computer age everywhere but in the productivity statistics." However, it eventually took time for these technologies to be integrated in ways that reflected their impact on productivity.

Yet, challenges loom on the horizon for AI. It may not eliminate all human labor, nor live up to its promises of vast economic benefits at an acceptable cost. Public sentiment has turned against the construction of AI data centers, with 70% of Americans opposing them, partially due to concerns over rising energy costs and fears of societal upheaval.

Numerous issues remain unresolved; despite significant progress in AI, questions persist about its ability to meet the diverse needs of a modern economy. Autor highlights that not all problems can be solved computationally, as AI excels at replicating language but struggles to apply it accurately to reality. Its limitations continue to result in significant errors.

Additionally, the economic feasibility of AI remains in question. Even if AI could one day address all societal challenges, the financial implications of widespread AI deployment appear daunting, with discussions around investing 20% to 40% of GDP in AI data centers becoming increasingly common. The International Energy Agency forecasts that the energy demands from data centers will more than double to around 945 terawatt-hours by 2030, surpassing the entire energy consumption of Japan.

The financial outlook for AI is tenuous, as rapid model obsolescence means that investment may not yield returns. Acemoglu warns that companies creating AI systems could face severe financial losses, amounting to hundreds of billions annually.

Altman's newfound caution could be seen as a strategic maneuver, suggesting that equating the AI revolution with mass unemployment may be politically unwise. However, broader skepticism about AI’s capabilities is more than just a marketing angle. The ambitious promises surrounding AI’s transformative powers face significant challenges as the possibility emerges that it may not deliver what society is willing to pay for.

The impending AI job crisis is unlikely to occur in the near future.

A bright, sunlit open-plan office where diverse professionals sit at sleek desks collaborating with a friendly humanoid robot that’s handing a document to a smiling engineer. Potted plants and floor-to-ceiling windows fill the space with warm natural light, conveying harmony between human workers and AI rather than replacement.

The AI jobs apocalypse probably isn’t coming anytime soon - The Guardian

- Anthropic's report indicates no significant unemployment increase from AI exposure since 2022.  
- Productivity gains from AI have been slower than expected, resembling the IT boom's early years.  
- Public opinion on AI has soured, with 70% opposing local AI datacenter construction.  

In March, Anthropic, the cutting-edge artificial intelligence business that gave us the chatbot Claude, published an analysis on the impact of AI on employment, to help us assess the claim that intelligent robots were about to redefine human existence, ending demand for human labor.

Last year in May, Anthropic’s co-founder, Dario Amodei, claimed AI could wipe out half of all entry-level jobs in one to five years. Last January, he told us AI would probably become a “general labor substitute for humans”. In June he said we risk “a world where the economic trade-off dial is stuck on the hypergrowth, hyper-inequality setting”.

And yet, Anthropic’s report suggests that, so far, AI’s impact has fallen short of expectations: “We find no systematic increase in unemployment for highly exposed workers since late 2022,” the report stated. Deployment of the technology “remains a fraction of what’s feasible”. Claude covers just 33% of all tasks in the computer and math category whereas theoretically it could take over nearly 100% of them.

Spending on datacenters is going through the roof, for sure, but productivity has not been experiencing the galloping gains that the technorati’s epochal prognostications lead one to expect. Labor productivity was, in fact, slower in the first three years of our AI era than during the information technology boom that began in the mid 1990s.

Even OpenAI’s Sam Altman, AI’s most public face, says he now doubts its job-killing potential. “I don’t think we’re going to have the kind ​of jobs apocalypse that some of the companies in our space advocate or talk about,” he said in May. As Massachusetts Institute of Technology economist David Autor noted: “A lot of people have noticed that the world is not changing as fast as they predicted.”

This has opened the public conversation to a less cataclysmic narrative of the evolution of the technology. The emerging new story not only puts more emphasis on the complexity of the relationship between automation and human work across history. It is also raising doubts about the very feasibility of the threatened AI transformation of the universe. The tech-heavy Nasdaq index, which had been propelled almost exclusively by the rise of AI-related stocks, has fallen about 8% since its peak in early June.

One strand of critique of the “AI-will-do-everything” story might be called the O-ring argument. It comes from the mid-flight explosion of the space shuttle Challenger 73 seconds into its flight on 28 January 1986. A lengthy investigation concluded that the demise of the multibillion dollar spaceship was caused by a rubber O-ring that didn’t work at low temperatures.

That cheap O-ring proved critical. The analogy suggests that as long as AI cannot perform every task perfectly, it will increase the value of the remaining tasks. Depending on which the AI takes over, it could increase the value of high skill workers who are relieved by AI of the low-end part of their job, or increase the opportunity of lower skilled workers by taking over the more expert tasks.

As one recent study noted: “despite strong substitution at the task level, overall employment effects are modest, as reduced demand in exposed occupations is offset by productivity-driven increases in labor demand at AI-adopting firms.”

Things could change. As Jed Kolko points out, research on the labor market impact of artificial intelligence is still in its infancy. There are almost four years to go in Amodei’s one-to-five year window. And maybe devastation hits in year six. According to the Federal Reserve, adoption of AI is expanding fast across businesses.

Moreover, Autor argues, AI is getting better. And its progress shows no sign that it will soon hit a ceiling. “Skepticism about the stochastic parrot is behind us,” he told me. The dystopian AI future – utopian, if you get to own and run the AI – is still on the cards.

“Insiders are as gung ho as ever,” noted Daron Acemoglu, the Nobel prize-winning economist. “They still believe artificial general intelligence is around the corner.” Indeed, Elon Musk has not budged from the dream that “AI+Robots will be able to do everything, resulting in universal high income. Work will be optional.”

One may recall the quip by Nobel prize-winning economist Robert Solow in the early years of the computer revolution: “You can see the computer age everywhere but in the productivity statistics.” It took another 10 years or so, as businesses reorganized around the new technology. But computers did eventually show up in the stats.

Clouds are nonetheless gathering on the AI horizon. It’s not just that AI may not end all human work. AI may not deliver on its promise of vast economic opportunity at a price that humanity is willing to pay.

The politics have decidedly soured on the project. Seven in 10 Americans oppose building AI datacenters in their area. While this has to do with their insatiable demand for energy, which drives up local electricity costs, AI’s unpopularity is no doubt related to the proposition that it will destroy society as we know it.

There are other bumps in the road. Despite its vast progress, big doubts remain on whether AI can do everything a modern economy needs. “Not everything is a computational problem,” notes Autor. AI is good at replicating language, but it cannot connect language to the reality around it. Despite its progress, it still makes plenty of critical mistakes.

And then there are the impossible economics. Even if AI could eventually solve all our problems, the solution looks expensive. How much of GDP are we willing to invest in AI datacenters, 20%? 30%? 40%? According to some estimates, that is where we are headed. The International Energy Agency estimates that power demand from datacenters will more than double by 2030 to about 945 terawatt-hours, more than the energy consumption of Japan.

The economics look more fragile considering how fast the investment in AI depreciates, as new models overtake those developed just a few months ago. Companies developing AI models “are never going to make money”, Acemoglu said. “They are losing hundreds of billions of dollars every year.”

One may discount Altman’s new modesty as a PR feint. Somebody may have told him that equating the AI revolution with mass joblessness was not smart politics. But misgivings about AI’s vaunted capabilities are more than a marketing twist. The grand, epochal promise may be in trouble. Maybe artificial intelligence can’t deliver at a price society is willing to pay.

The AI jobs apocalypse probably isn’t coming anytime soon

Colleges and universities nationwide are rapidly adjusting to the swift integration of artificial intelligence (AI) into educational environments. Among them, Cornerstone University is taking a proactive stance, aiming to develop graduates who are "irreplaceable." Instead of restricting AI from classrooms, the institution believes in guiding students to utilize the technology responsibly.

"We aspire to take the lead," stated Gerson Moreno-Riaño, the president of Cornerstone University, in an interview with Fox News Digital. "Our goal is to be at the forefront among educational institutions. To achieve this, we need insights from market experts who can provide direction and strategic guidance."

Located in Grand Rapids, Michigan, Cornerstone recently formed the President's Artificial Intelligence Advisory Board. This group comprises specialists from various disciplines, including philosophy, engineering, enterprise AI, theology, and education. Their role is to offer advice on the university's AI curriculum, ethical considerations, and long-term strategies.

Moreno-Riaño emphasized that the board aims to ensure that Cornerstone's educational offerings evolve in sync with the fast-changing AI landscape, while also helping faculty adapt effectively and maintaining alignment with the university's Christian principles.

Universities across the nation are adopting a variety of strategies concerning AI, yet many lack comprehensive policies, often leaving it to faculty discretion when addressing AI in their classrooms. For instance, Harvard University does not enforce a universal policy on AI. Instead, it mandates that instructors communicate their individual policies to students, offering a few templates for guidance but allowing for personal customization. Some instructors have prohibited the use of generative AI tools, such as ChatGPT, while others encourage students to explore these technologies.

Similarly, Vanderbilt University advises faculty to develop their own policies on generative AI that align with the institution's Honor Code; however, there is no overarching policy in place. Faculty are ultimately responsible for conveying expectations clearly to students.

Moreno-Riaño noted that this fragmented approach is something Cornerstone seeks to avoid. 

"I've spoken with numerous college presidents and experts, and it seems many universities are uncertain about how to handle artificial intelligence," he explained. "This lack of a cohesive strategy results in challenges for both students and faculty, leading to a deficiency in direction."

He advocated for an educational model that goes beyond merely informing students, aiming instead to cultivate wisdom and discernment. The emphasis should be on preparing students to engage with technology in meaningful ways.

Moreno-Riaño also commented on how many educational institutions focus excessively on the risks of AI, particularly the potential for academic dishonesty, rather than emphasizing teaching responsible use of the technology. He posited that the tendency to ban AI due to cheating concerns reflects a misunderstanding of how it can be harnessed positively.

"Our mission in education is to equip faculty and students to engage with AI wisely, maximizing the potential benefits and reducing educational costs," he said.

As AI capabilities grow, discussions surrounding its implications for higher education have expanded to consider which degrees and career paths will remain relevant in an AI-influenced job market. However, Moreno-Riaño argued that the conversation should shift toward producing graduates who are "irreplaceable" professionals, instead of just focusing on direct career adaptations to AI.

"I don’t believe there are entirely safe career paths anymore; every field will be radically altered by AI," he stated. "We should prioritize cultivating graduates whose unique human qualities cannot be duplicated."

For Moreno-Riaño, this doesn't entail simply teaching coding skills or focusing solely on AI-centered career tracks. Rather, it requires nurturing the aspects of humanity that machines cannot replicate.

"While we recognize that careers will transform significantly, the capability for wisdom and discernment is irreplaceable," he said. He further elaborated that true wisdom cannot be gained merely by recalling answers; it emerges from tackling challenges and learning from mistakes. 

"The challenge with AI is that, while it may provide accurate answers, it takes away the essential struggle necessary for growth," he asserted.

Ultimately, he believes the process of navigating difficulties and honing judgment is vital in cultivating "irreplaceable" graduates. Universities should leverage AI to enrich student learning experiences, fostering wisdom as critical to maintaining the value of a higher education in the AI era. 

"Faculty must serve as sources of wisdom for our students," he noted.

Moreno-Riaño emphasized that Cornerstone's distinctive approach lies in its commitment to integrating the latest technology while remaining faithful to its Christian values.

"I believe Christianity has significant insights to offer here; understanding what it means to be human, as we are made in God’s image, is crucial," he shared. He pointed to the founding principles of America as reflecting this core tenet, which he believes remains foundational for Christian higher education.

Ultimately, he contended that instead of resisting AI, educational institutions must embrace it as a tool that enhances human potential rather than diminishes it.

"It's here to stay," he concluded. "Our challenge now is to learn to use it effectively, ensuring it serves our best interests rather than the other way around."

Christian university seeks to create 'irreplaceable' graduates in the era of AI transforming higher education.

A golden-hour university courtyard framed by Gothic stone buildings topped with a subtle cross; a poised adult graduate in cap and gown clutching a Bible stands center, bathed in warm natural light as ghostly robotic silhouettes behind her dissolve into drifting digital code, lush green lawns and sunlit stained-glass windows lending a hopeful, story-driven scene.

Christian university aims to produce 'irreplaceable' graduates as AI reshapes higher education - Fox News

- Cornerstone University aims to embrace AI technology while maintaining Christian values in education.  
- The President’s Artificial Intelligence Advisory Board will guide curriculum development and ethical considerations.  
- Emphasizing human discernment, the university seeks to produce irreplaceable graduates amid AI changes.  

Colleges and universities across the country are scrambling to respond to the rapid adoption of artificial intelligence. One Christian university is looking to embrace the technology and graduate students who are "irreplaceable." Cornerstone University wants to show other higher education institutions that the goal shouldn't be keeping AI out of the classroom, but rather help students learn to use it wisely.

"We want to lead," Cornerstone University President Gerson Moreno-Riaño told Fox News Digital. "We want to be ahead of other institutions, but we need the insight of experts in the marketplace right now that can give us guidance, direction and insight to do this and to do it well."

Cornerstone University, located in Grand Rapids, Michigan, recently announced the President’s Artificial Intelligence Advisory Board. The board is made up of experts in several fields, including philosophy, engineering, enterprise AI, theology and higher education. The members are tasked with advising Cornerstone on AI curriculum, ethics and long-term strategy.

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Moreno-Riaño said the board was formed to ensure that Cornerstone's curriculum keeps pace with the rapidly evolving AI landscape, help faculty adapt to the technology and ensure the university's approach remains grounded in its Christian values.

Top universities across the country are taking different approaches to AI as the technology becomes more widely available. However, many do not have school-wide policies and instead ask faculty to use their discretion in their classrooms.

Harvard University does not have a university-wide policy regarding AI, but instead requires instructors to inform students of their policies. The university has three examples of policies that faculty can use, but it also allows them to make their own guidance. One policy prohibits the use of generative AI, such as ChatGPT, in all stages of work, while another encourages students to "explore" the limits of the tech.

AI CHATBOTS TAKE HEAT OVER LEFT-WING BIAS: ‘NO LONGER BE CONSIDERED NEUTRAL’

Vanderbilt University also encourages faculty to establish their own generative AI use policies for their courses, as long as they align with the school's Honor Code. While the university does not have a blanket policy on generative AI, it holds faculty members responsible for clearly articulating their expectations to their students.

Moreno-Riaño said that kind of fragmented approach is exactly what Cornerstone is hoping to avoid.

"I've spoken to many college presidents and experts and have a sense that many universities right now don't know what to do with artificial intelligence," he said. "They lack a coherent strategy and focus, and what happens is that both the students suffer, and the faculty and the staff suffer. There's no guidance and direction."

"So, we want to ensure that we prepare and develop our faculty well, our staff well too, to how do we engage this in a way that continues to form our students, not just inform them. And prepare them with wisdom, not just information," he added.

The Cornerstone president also said that higher education institutions are too often focused on the potential risks of students using AI to cheat, rather than trying to teach them how to use it responsibly. Moreno-Riaño suggested that many higher education professionals who ban AI because of potential cheating are not approaching the technology in the right way. He acknowledged the negatives of AI, but said that those who are only focused on the bad, have failed to see how it can be used for good.

"Our job in academia is to prepare our faculty and ultimately our students to be able to use it with discernment and for institutions to use it to extend the reach of what they're accomplishing and quite frankly, lower the costs of what it takes to deliver an education," he said.

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As AI becomes more capable and accessible, the conversation surrounding its relationship with higher education has expanded beyond the classroom. Students and parents are increasingly questioning which degrees and career paths will be valuable as AI reshapes the modern workforce. However, Moreno-Riaño believes they're asking the wrong question, saying that AI will change nearly every profession.

"I don't think there's a safe career or a safe diploma, a safe major. I think every field will be significantly transformed by this. But I think the question we should be asking is that we should think about producing graduates that can't be replaced," Moreno-Riaño told Fox News Digital.

For the Cornerstone president, it comes down to producing graduates who are "irreplaceable" in their fields. He argued that this does not necessarily mean teaching them to code or to focus on career paths that are AI-driven or resistant; rather, it requires universities to nourish the aspects of their students' humanity that cannot be replicated.

"I think careers are going to be transformed and changed. There's no doubt about it," he said. "But it's a human capability for wisdom and discernment that can't be replaced."

Moreno-Riaño said that students do not become wiser just by memorizing the correct answer to a question, arguing that the process played an important role in their development. He recalled a high school math teacher who insisted that students show every part of their work rather than simply writing the answer.

"The dilemma with AI is it gives you the right answer, but robs you from the struggle," he said.

Moreno-Riaño argued that the struggle to solve problems, work through mistakes and develop judgment, is ultimately what produces "irreplaceable" graduates. He added that universities should use AI to enhance students' learning experiences with the aim of helping them develop wisdom, something he thinks will be key as people question the value of a college degree in the AI age.

"Faculty need to be sources of wisdom for our students," he said.

What makes Cornerstone's approach unique, according to Moreno-Riaño, is the university's efforts to adapt to cutting-edge technology while also staying true to its Christian values.

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"I think Christianity has so much to offer here to say, we understand what the person is, we're image bearers of God, this means something," he told Fox News Digital. He added that America's founders understood this principle, which he says still sits "at the core of Christianity and of Christian higher ed."

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Ultimately, Moreno-Riaño believes universities should not resist AI and instead must find ways to ensure that AI remains a tool that serves people rather than replacing them.

"It's here to stay," he said. "Now we have to learn how to use it and ensure that it serves our good purposes, not that we serve its purposes."

Christian university aims to produce 'irreplaceable' graduates as AI reshapes higher education

At a recent gathering, a prominent figure encouraged attendees to seize the financial opportunities tied to data-center development, stressing that if they don't pursue these prospects, someone else will. He urged local leaders to promote data centers within their communities, insisting that embracing the trend is essential.

During an event at the Environmental Protection Agency, he highlighted pledges from data center developers and utility companies to keep electricity rates stable, addressing widespread concerns that the boom in data center construction could lead to soaring energy costs for Americans. This commitment serves as a strategic move for companies like OpenAI and Oracle, offering them political cover as they navigate the complex economic implications of upgrading the aging U.S. power grid over time.

Despite recognizing potential risks, he appears unwilling to change course, particularly as the AI sector looms as a political blind spot for him. The rapid advancements in this field may challenge his ability to gauge shifting political sentiments, potentially jeopardizing his party's prospects in upcoming elections.

A coalition of religious leaders, labor organizations, and local activists is expressing anxiety over AI and the economic changes it signifies, presenting a significant political challenge for anyone aligned against those concerns. As the leading voice in this arena, he finds himself most vulnerable to backlash.

In terms of wealth creation, Americans are quick to rally around opportunities for financial gain, reminiscent of the fervor surrounding cryptocurrencies and prediction markets. However, when it comes to artificial intelligence, everyday people are not convinced that Big Tech offers them a winning lottery ticket. While he boasts about the soaring stock market, many Americans remain skeptical, focusing instead on job displacement and growing wealth inequality.

Take, for instance, the high-profile IPO of SpaceX, which initially appeared to promise great returns. For those regular investors who entered at the right moment, the stock has since plummeted by 30%.

Adding to the challenges posed by AI is a formidable political coalition that resonates with the electorate he seeks to appeal to. He may disregard the warnings from Pope Leo XIV, who recently emphasized the need for safeguards around AI to preserve human dignity. However, he cannot dismiss similar concerns coming from influential evangelical leaders within the U.S. 

Walter Kim, head of the National Association of Evangelicals, echoed the Pope's sentiments, stating that while AI can be beneficial, it also poses significant risks. He highlighted the potential for AI in key sectors to undermine human involvement in critical decision-making processes. Kim described AI's impact as a modern-day Tower of Babel, where reliance on technology could sever our connections with God and with each other.

Although Kim’s organization does not endorse political candidates or threaten campaigns against Trump, his statements signal a shift in attitudes among a demographic that has traditionally supported him.

Other groups interested in backing Trump and his Republican colleagues are more straightforward in expressing their expectations. Following a mixed record with union support, it is becoming increasingly clear that the GOP must address AI apprehensions to secure labor backing. Liz Shuler, president of the AFL-CIO, made this point at a recent union convention, emphasizing the necessity for candidates to prioritize workers over algorithms. 

Shuler’s stance isn't anti-AI; she simply seeks to ensure that emerging technologies benefit more than just tech firms and investors. This sentiment is echoed by Sean O’Brien, leader of the International Brotherhood of Teamsters, who previously noted that unions have historically been sidelined in discussions about AI.

Palantir's CEO, Alex Karp, who shares a background in union culture, warned that the primary threat to AI progress could stem from political unrest, which seems increasingly likely given the growing unease regarding data centers.

Interestingly, it is New York state that has initiated a ban on new data center construction under Governor Kathy Hochul. Yet, the concerns surrounding data centers transcend political affiliations. A recent poll indicated that a majority of conservative Republicans (53%) oppose local data center projects, alongside 58% of all registered voters and 74% of liberal Democrats.

This convergence of religious conservatives, labor unions, and local activists calling for a measured approach to AI presents a unified front that politicians would do well to heed. Those who choose to overlook these rising sentiments may find themselves facing consequences as the elections draw near. With just 101 days until Election Day, the urgency for action is palpable.

Analysis: A robust new alliance of AI critics is forming without Trump's awareness.

A dimly lit stage seen from behind a lone figure in a dark suit with unmistakable swept-back hair—Trump’s silhouette—facing an empty podium. Behind him in his “blind spot,” a resolute group of AI skeptics stands shoulder to shoulder, their signs bearing a crossed-out microchip symbol. Above them, a single, gently illuminated American flag drapes against the shadowed backdrop, casting muted highlights across the scene and suggesting a growing movement emerging just out of view.

Analysis: A powerful new coalition of AI skeptics is coalescing right in Trump's blind spot - CNBC

- Trump encourages local officials to embrace data-center development despite concerns over rising energy costs.  
- An emerging coalition fears AI's societal impacts, posing risks for Trump's political support.  
- Union leaders advocate prioritizing workers' needs over AI advancements in political agendas.  

Someone is going to get rich on data-center development, and it might as well be you, he told the audience. "If you don't take all that money, somebody else is going to take it. You might as well do it yourself."

But Trump couldn't help but align himself with the companies, even at an event at the Environmental Protection Agency on the pledge that was designed to show he's looking out for the little guy. He exhorted the assembled governors and other local officials to sell their constituents on data centers. "You can't fight it. You have to go with it," he said.

On Thursday, he touted commitments by data center developers and utilities not to raise electricity prices, nodding to fears across the country that a surge in data center construction will spike Americans' energy bills. The pledge is a no-brainer for the likes of OpenAI and Oracle , giving them political cover as the complex economics of making changes to aging U.S. grids plays out over years and decades.

Trump seems aware of the danger, yet can't help himself from hurtling toward it.

AI is positioned right in his blind political spot . The industry and its rapidly developing technology threaten to overwhelm Trump's often-uncanny ability to sense changes in the political winds and could damage his party's fortunes in the midterm election and the longer-term legacy he values.

The emerging coalition of religious leaders , labor unions and local activists that worries about artificial intelligence and the broader economic upheaval it portends poses a political problem for anyone who gets on the wrong side of that issue . And President Donald Trump is the person most at risk.

Here's the thing about getting rich. If Americans sniff a chance it could happen to them, they don't need to be told twice to get behind it. That's why crypto and prediction markets are ideas that can't be killed, no matter how unlikely it is that you, personally, will really get rich off them.

When it comes to artificial intelligence, however, rank and file Americans just aren't buying the idea that Big Tech is handing them a golden lottery ticket. Trump can tout the stock market boom all he likes — the Nasdaq composite has had 20 record closes this year — but too few Americans have enough of a stake in the market for rising share prices of a select few tech companies and the indexes that contain them to overcome their worries about job instability and the continuing concentration of wealth.

To wit, Elon Musk's SpaceX looked like a great opportunity for those who were able to invest early. For those Regular Joes fortunate enough to have a few bucks in a brokerage account during its IPO last month, shares are down 30%.

And now add to the class-and-wealth problems of AI a heavyweight political coalition that has sway with the voters Trump would most like to persuade.

The president may be willing to write off Pope Leo XIV, who issued an influential encyclical in May warning that AI needed guardrails to protect our humanity. But Trump can't so easily swipe away the same language when it comes from the heart of the evangelical movement here in the U.S.

Walter Kim, president of the National Association of Evangelicals, praised the pope's warnings on AI. "There are positive benefits, but there are also extraordinary harms," Kim said on CNBC's "Squawk Box" on Wednesday.

Kim worried that the prominence of AI in healthcare, education and warfare risks taking human beings out of the loop on our most important decisions.

"It is, as the Pope described in his recent encyclical, the construction of a Tower of Babel, the trust in a technology that reflects human hubris, that not only disconnects us from God but disconnects us from each other," Kim said.

Kim's evangelical group doesn't endorse candidates and isn't threatening any kind of overt political campaign against Trump. But Kim's message is a warning sign that the ground is shifting, even among a voting bloc that has backed Trump since early in his first presidential run.

Other groups whose favor Trump and fellow GOP politicians might want to win are being even more blunt. Republicans made a play for union support under Trump to mixed success. Increasingly, if they want to win union backing, that will require taking AI concerns more seriously.

Liz Shuler, president of the AFL-CIO, the largest U.S. labor federation, laid that out at the union's convention last month.

"For all of those candidates who are already out there starting to run for president in 2028, if you want to hold the highest office in the land, hear these words: Working people should come before algorithms," she said.

Shuler doesn't claim to be anti-AI, but she wants to see the new technology help more than the tech firms and their investors. So does Sean O'Brien, head of the International Brotherhood of Teamsters, who spoke at the Republican National Convention in 2024. "We've never had a seat at the table," he said in a recent event with Palantir CEO Alex Karp organized by the center-right group American Compass.

Karp, who grew up in a union household, chimed in, "I think the biggest challenge to AI in this country is political unrest."

The potential for that unrest is clear in the nationwide rumbling against data centers.

It may be liberal New York state that has moved first to impose a moratorium on building data centers under Gov. Kathy Hochul. But so far, the issue isn't polarized along familiar lines. A majority — 53% — of conservative Republicans opposes building data centers locally, according to a June poll by the Yale Program on Climate Communication.

A majority of registered voters, or 58%, shared that opposition to local data center construction, as did 74% of liberal Democrats, in the poll.

The religious right, labor unions, and the broad coalition of local activists are all coming together to say, "slow down" on AI. The politicians who listen will find a powerful groundswell of support behind them.

Those who don't? Well, Election Day in November is just 101 days away.

Analysis: A powerful new coalition of AI skeptics is coalescing right in Trump's blind spot

During a recent Google AI event in San Francisco, Jeff Dean, the head of Google's artificial intelligence division, shed light on a technical process known as distillation—previously a niche discussion in tech circles. In a podcast, Dean explained how Google's pursuit of performance improvements led to the discovery of this technique, which enables the creation of smaller, more efficient AI models derived from larger, sophisticated models. He noted that distillation is essential for enhancing these compact models while relying on a high-performance “frontier model.” What was once an obscure topic in the tech community has now ignited widespread debate, especially in the wake of Chinese lab Moonshot AI launching its Kimi K3 model, which has rapidly demonstrated competitive capabilities compared to leading AI offerings from American companies like Anthropic and OpenAI. Unlike their U.S. counterparts, which provide access only to proprietary AI models, Moonshot and similar labs in China have taken a different approach by offering open-weight models for users to download and modify freely.

This shift has raised eyebrows among U.S. officials, who suspect that Moonshot AI's rapid ascent can be traced back to distillation practices viewed as akin to intellectual property theft. White House advisor Michael Kratsios suggested on social media that Moonshot AI may have utilized Anthropic’s frontier Fable model to create K3, hinting at a sophisticated internal setup enabling large-scale distillation that complicates efforts to monitor these activities.

Distillation involves using the outputs of advanced AI models to inform the training of new models and is increasingly seen as controversial. Experts liken it to a student reaping the benefits of another’s hard work without putting in the required effort. In a collective stance, major tech players, including Nvidia, Microsoft, and Meta, rallied together to urge lawmakers against imposing restrictive regulations on open-weight AI models, asserting that such actions could hinder innovation and drive business overseas. They emphasized the importance of allowing distillation as a legitimate method for enhancing AI technology development.

The U.S. government faces a challenging dilemma regarding Chinese technology, especially as incidents involving IP theft and national security concerns arise. Colin Shea-Blymyer, a research fellow at Georgetown, pointed out that the government is assessing the competitive edge gained by Chinese companies leveraging American AI outputs. Meanwhile, Aaron Levie, CEO of Box, expressed the need for U.S. firms to access cutting-edge technology regardless of its origin, suggesting that innovation, whether sourced from the U.S. or China, ultimately drives progress in AI.

Despite the focus on the Chinese AI landscape, many U.S. companies, including Nvidia with its Llama Nemotron model, have also employed distillation techniques in their development processes. Shashi Bellamkonda, research director at Info-Tech Research Group, commended distillation as a valuable strategy for creating cost-effective models based on larger counterparts.

However, Anthropic holds reservations regarding distillation due to its specific concerns about its proprietary technology. The company alleges that entities like China's DeepSeek and Moonshot have been extensively using resources from its Claude model for competitive gains. Anthropic emphasizes that halting misuse of its models is crucial for national security, advocating for cohesive action among industry stakeholders and policymakers.

In response to the growing threat of unauthorized distillation, companies like OpenAI and Anthropic have revised their terms of service to prohibit such use, raising potential issues of intellectual property violation. Despite ongoing litigation over content used to train their own models, industry participants argue that as demand for AI solutions continues to surge, adopting innovative strategies to enhance efficiency is paramount. Some, like Hamal from SecurityPal, are open to utilizing models such as Kimi K3 if proper safeguards are in place, highlighting the intricacies of balancing cost, security, and competitive advantage in the evolving AI landscape.

From Silicon Valley to Washington, the tech industry is now fixated on a single AI concept: Distillation.

A bright, sunlit modern lab: on the left a sleek, glass-clad Silicon Valley server rack glowing with neural-network circuits; on the right a minimalist Washington, D.C. Capitol dome model with a small U.S. flag pinned behind it; between them a giant crystal “knowledge” droplet slowly falling from the complex network into a compact, chip-shaped vial below, symbolizing AI distillation.

From Silicon Valley to DC, the tech world is suddenly obsessed with one concept in AI: Distillation - CNBC

- Jeff Dean highlighted AI distillation's potential to enhance smaller models without large frameworks.  
- Chinese lab Moonshot AI's Kimi K3 sparked fears of IP theft and competition.  
- Major tech companies urge policymakers to avoid stifling innovation amid distillation concerns.  

Jeff Dean, head of artificial intelligence at Google LLC, speaks during a Google AI event in San Francisco, California, U.S., on Tuesday, Jan. 28, 2020. David Paul Morris | Bloomberg | Getty Images

Earlier this year, Google AI lead Jeff Dean, on a podcast, discussed a concept that, at the time, was hardly spoken about outside of wonky tech circles: distillation. In talking about the development of Google's AI models, Dean said that he and colleagues discovered artificial intelligence distillation techniques because Google was looking to improve performance on its systems without relying on one large image recognition model. "Through distillation, which is a key technique for making the smaller models more capable, you have to have the frontier model in order to then distill it into your smaller model," Dean said in February. Five months later, distillation has suddenly become a hot-button topic from Silicon Valley to Washington, D.C., as techies and lawmakers debate whether the practice is turning into a national security threat and enabling China to catch the U.S. in the high-stakes AI race. Concern bubbled up late last week after Chinese lab Moonshot AI released Kimi K3, and users quickly found it to be competitive with the best commercially available AI from Anthropic and OpenAI. Unlike the leading U.S. AI companies, which sell access to proprietary models, Moonshot and other Chinese labs are offering so-called open-weight models that allow users to download the technology, tweak it and run it wherever they want. Some government officials attribute Moonshot's ability to catch up so quickly to distillation, describing it as theft of American intellectual property, specifically by incorporating Anthropic's frontier Fable model. "We have information that Moonshot AI distilled Anthropic's Fable for the development of its K3 model," White House advisor Michael Kratsios posted on X on Wednesday. "To do this they developed a sophisticated internal platform to conduct large scale distillation against U.S. models, allowing them to quickly switch between multiple methods of access to avoid detection."

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At a high level, distillation refers to the use of answers from a chatbot or work product from an advanced AI model to train another model. The practice is controversial because, depending on how it's used, it can allow a model developer to create a competitive offering by simply using the output from companies that have invested many millions or billions of dollars developing the most sophisticated training technology. "It's almost like someone went to the lectures, read the textbook, and did all the hard work of doing the homework," said Pukar Hamal, founder of AI security firm SecurityPal. "Then some other student is like, 'Hey, I didn't do that. Can I just copy your work?'" Whether it was Kratsios' post or something else, the biggest tech heavyweights on the planet came together on Friday in what might be unprecedented fashion to make their position clear. After a series of social media posts throughout the week, tech giants Nvidia, Microsoft, Meta, Palantir joined with more than 20 other companies to release a letter urging policymakers to avoid "premature restrictions" on open-weight AI models that would "stifle competition or drive innovation overseas." "Distillation, or the practice of using one model's outputs to help train or improve another, is a widely used technique for model improvement, evolution, and validation," they wrote.

Complicating the China problem

The emergence of distillation presents a conundrum to U.S. policy makers, who have long been concerned about Chinese technology in terms of both IP theft and national security issues. Colin Shea-Blymyer, a research fellow at Georgetown's Center for Security and Emerging Technology, said the U.S. government is trying to figure out its position. The government could argue that Chinese and Russian companies "have used the outputs of hardworking American models to make themselves more performant, and so they have an unfair advantage there," Shea-Blymyer said. Box CEO Aaron Levie was one of the signatories of Friday's letter. Levie said in an interview that to stay competitive, U.S. companies need to be able to access the best technology, no matter where it's developed. "Generally the arc is going to be that the more innovation that there is, whether that's from the U.S. or China or otherwise, you should expect more AI progress, and generally it'll bend toward being even lower cost and more efficient over time," Levie said. Although much of the current discourse centers on Chinese open-weight AI models like Kimi K3, many companies have incorporated the distillation technique when creating their own models, said Shashi Bellamkonda, research director at Info-Tech Research Group. Nvidia, for instance, used distillation as part of the training process for its Llama Nemotron series of models, as detailed in an accompanying research paper. "It is a legitimate and a very valuable technique to train a smaller, cheaper model on outputs of a larger model, and is practiced all the time," Bellamkonda said.

Dario Amodei, co-founder and chief executive officer of Anthropic, during an interview on "The Circuit with Emily Chang" at Anthropic's headquarters in San Francisco, California, US, on Thursday, April 30, 2026. Jason Henry | Bloomberg | Getty Images

However, Anthropic has a different view, because the company sees how its models are being used and has a burgeoning business to protect. In February, the company said its Claude capabilities were being distilled on an "industrial scale" by China's DeepSeek, Moonshot, and MiniMax, which used about 24,000 fake accounts, generating 16 million exchanges. Anthropic, which is valued at close to $1 trillion and has aspirations of going public in the near future, said stopping illicit distillation was a matter of national security. "Anthropic and other US companies build systems that prevent state and non-state actors from using AI to, for example, develop bioweapons or carry out malicious cyber activities," the company said in its February post. And stopping it requires "rapid, coordinated action among industry players, policymakers, and the global AI community." OpenAI and Anthropic are banning distilling in their terms of service. Bellamkonda said they're essentially suggesting that using their larger models without authorization represents potential IP theft. But with AI costs skyrocketing, companies will do whatever it takes to drive efficiency. Hamal said he would have no problem using Chinese open-weight models like Kimi K3 at SecurityPal, which automates security assessments using AI. He says it could save them a lot of money. "We would make sure that there's no nefarious backdoors in the code," Hamal said. "But hosting it on our own infrastructure after we've done an assessment, why not?" One big problem for Anthropic and OpenAI as they try to make their case about IP theft is that both companies have relied on other sources of content to build their models, and have been sued for doing so. Max Pritt, an attorney for Boies Schiller Flexner who represents book authors in copyright litigation against AI firms, said the government is in the same boat. "The administration, at least publicly, has focused its efforts on the protection of technology companies' intellectual property, while remaining silent in large part about creators and individuals' intellectual property that was used without authorization," Pritt said. WATCH: China's AI firms are finding ways to monetize even as their models remain open

From Silicon Valley to DC, the tech world is suddenly obsessed with one concept in AI: Distillation

In Jacinto City, what initially started as a simple real estate advertisement quickly escalated into a heated community issue, prompting local leaders to take action and engage with concerned residents. A report from Chron in May unveiled that a brokerage firm was promoting an old glass bottle manufacturing site as a site for a potential AI data center. If developed, this could have resulted in one of the largest data centers in the Houston area.

Just weeks later, community worries transitioned from online chatter to an official resolution by city officials on July 2, opposing any data center developments within city limits until they could gather further information and policy guidance.

The city council firmly stated, “WHEREAS, the City Council finds that it is in the best interest of the citizens of Jacinto City to formally express opposition to the construction and development of data centers within the City limits until additional information and policy direction can be obtained and evaluated.”

As Texas becomes a hotspot for AI data center development, attracting significant investments and expansive proposals, local skepticism has risen alongside the industry’s rapid growth.

City Manager Lon Squyres recounted that following the news release, the city received over 150 calls and emails from both Jacinto City and surrounding Houston residents, all expressing opposition to the data center idea. “There has not been one person that's called that's been pro data center," he shared. This backlash culminated in a packed City Council meeting, with residents expressing their concerns. While Squyres humorously noted some came "with figurative pitchforks," they left feeling reassured after city officials clarified they were not in pursuit of a data center developer.

These reactions surprised city leaders who were just as taken aback by the marketing push as the community. The former glass bottle factory located at 4202 Fidelity St. had been a key employer in Jacinto City since the 1960s, with Budweiser being its last major client. The plant's closure in July 2024 ended decades of employment for local families.

The property has remained empty since, but the soaring demand for AI data centers and its heavy industrial zoning made the site appealing for potential investors. A brochure by Marcus and Millichap described the property as a prime development opportunity for data center advancements.

While Squyres acknowledged that the broker had done extensive research, it's important to note that no formal offers for data center use have been presented to Jacinto City officials thus far. However, the property owner did reach out for information regarding zoning regulations.

Because the site is privately owned, it holds the right to sell, and the zoning could accommodate a data center. Squyres explained that a blanket ban on data centers may lead to potential legal challenges for the city. Instead, local officials aim to create regulations to address any possible negative impacts from industrial developments, including future data centers.

In the wake of this issue, city leaders felt compelled to educate themselves about data centers more than they had anticipated. Squyres and the assistant city manager visited various data centers across Texas, monitoring noise levels and engaging with nearby residents to understand their experiences. An unplanned visit to Red Oak, home to a Google data center, revealed that the facility was quieter and less intrusive than some had imagined. Yet, these findings further emphasized the need for caution in considering such large-scale projects for Jacinto City.

The city aims to ensure that any new data center not only occupies the space but also contributes positively to the community. Tools for regulation may include constraints on lighting, power consumption, and water usage. Furthermore, they will require participation in safety and accountability organizations, as well as public forums for community interaction.

Squyres confirmed that no tax incentives would be offered to data centers, making it clear that this avenue is off the table for them. 

Currently, city officials are in talks with a different company regarding the former glass factory, and while details remain under wraps, Squyres assured the community that it is not a data center.

Amidst the ongoing discussions, Squyres reiterated the city's commitment to transparency concerning major development projects. "We owe the public an explanation of whatever goes in there, who they are, what they do, and what impact it's going to have on the city," he stated, emphasizing the importance of open dialogue with residents regarding future developments.

One AI data center plan galvanized the residents of Jacinto City.

A moody twilight scene on a suburban street: a diverse group of adult residents gathered under a single streetlamp, holding handmade protest signs (“No Data Center,” “Protect Our Air”) and a rolled-up blueprint of a looming data center behind a chain-link fence. In the background, the dark silhouette of the proposed facility’s server racks glows faintly. Warm, natural light from the lamp cuts through the deepening sky, highlighting determined faces and creating a tense, story-driven atmosphere.

How one AI data center listing sent Jacinto City into action - Chron

- Jacinto City officials passed a resolution opposing data center development within city limits.  
- Residents expressed strong concerns over a potential AI data center at a former factory.  
- City leaders are exploring alternatives for the site, ensuring transparency with residents.  

Jacinto City water tower. Photo courtesy Jacinto City. Jacinto City/Jacinto City

What began as an industrial real estate listing quickly sent Jacinto City leaders into overdrive, with phones ringing off the hook and City Council chambers filling with concerned residents.

Chron’s reporting in May revealed that a brokerage firm was advertising an old glass bottle factory as a potential data center location. If the sale had happened, it could have been one of the largest data centers in the surrounding Houston area.

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In a matter of weeks, concern over a potential AI data center went from online discussions threads to an official city resolution expressing opposition to data center development on July 2.

“WHEREAS, the City Council finds that it is in the best interest of the citizens of Jacinto City to formally express opposition to the construction and development of data centers within the City limits until additional information and policy direction can be obtained and evaluated.”

A resolution expressing formal opposition to data center development until further study in Jacinto City was passed by city officials on July 2, 2026. screenshot/Jacinto City

Texas has become an epicenter for AI data center development, drawing billions of dollars in investment and proposals for sprawling campuses across the state. But as the industry's footprint grows, so has public skepticism.

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Striking a nerve

Once the news broke, backlash was immediate, City Manager Lon Squyres admits.

He told Chron that City Hall fielded more than 150 calls and emails—not only from Jacinto City residents, but also from people across the Houston area.

"There has not been one person that's called that's been pro data center," Squyres said. The concern culminated at a July City Council meeting, where an unusually large crowd packed Council chambers.

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Some residents arrived "with figurative pitchforks”, Squyres joked, but left relieved after city officials explained they were not actively recruiting a data center developer.

“These people are passion ate about this and quick to think automatically that somehow the city's hiding something, or that there's something already done,” said Squyres.

But according to Squyres, city officials were just as surprised by the marketing advertisement as residents were.

The Factory that caught the AI boom

The glass bottle plant located on 4202 Fidelity St. had been one of Jacinto City’s largest employers since opening in the 1960s, with Budweiser serving as the latest major customer. Squyres said the plant employed three to four generations of residents before it closed up for good in July 2024.

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The former Ardagh Glass bottle plant at 4202 Fidelity St. in Jacinto City was featured in a commercial real estate marketing brochure as a potential site for an AI data center. N/A/Marcus & Millichap

Since then, the property has sat vacant. However as demand for AI data centers surged, the 30-acre site's heavy industrial zoning and existing infrastructure made the property prime to market as a potential data center site.

“4202 Fidelity Street in Houston, Texas is a premier development opportunity with existing high-voltage infrastructure and scale for data center hyperscale and AI advancement,” states the brochure, produced by commercial real-estate firm Marcus and Millichap.

While Squyres noted that the research was “pretty extensive” on the broker’s part, no company has ever approached Jacinto City with an offer or proposal to use the property for a data center.

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However, Squyres did field a call from the property owner in May inquiring about the site's zoning regulations.

Since it is privately owned, it would be the owner’s legal right to sell to a buyer of their choosing. And based on zoning alone, it could go to a data center.

For this reason, an outright ban on all data centers could open the city up to lawsuits later down the line, Squyres explained. However, the city is looking to establish ordinances to mitigate potential negative neighborhood impacts—not just for a data center, but for any industrial facility that chooses to land in Jacinto City.

In fact, when the data center controversy arose, city leaders were spurred to learn more about data centers than they ever expected. Squyres and the assistant city manager visited data centers around Texas. They walked facilities with a decibel meter, spoke with nearby residents and even made an unplanned stop in Red Oak, home to one of Google's data centers.

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Activists marched for San Marcos City Park to City Hall to protest proposed data centers in the area. (Sara Diggins/The Austin American-Statesman via Getty Images) Austin American-Statesman/Hearst/The Austin American-Statesman vi

Squyres was surprised to find, speaking with neighbors in Red Oak, that the facility in their neighborhood was far quieter and less disruptive than residents feared. However, the experience still reinforced that Jacinto City should proceed cautiously before allowing a project of that scale.

“We’d want them to be good neighbors and contribute something back to the community, other than just occupy space,” said Squyres.

Tools at the city's disposal include regulating lighting, power draw and water use. In addition, they would require any company to participate in regional safety and accountability groups, emergency‑planning and incident‑reporting systems, as well as a public forum where residents can question the company.

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The city also maintains it would not offer any tax incentives to a data center, “that is completely off the table for us,” Squyres said.

The future of 4202 Fidelity

For now, city officials say residents can put their data center fears to rest.

Squyres said the city is in discussions with a different company for the former glass bottle plant. While he can not disclose many details about the prospective buyer, he can say with confidence that it is not a data center.

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More importantly, Squyres said, the controversy reinforced the city's long standing commitment to being transparent with residents about significant development projects.

"We owe the public an explanation of whatever goes in there, who they are, what they do and what impact it's going to have on the city," Squyres said. "That needs to be done in a public forum."

Whatever eventually replaces the old bottle plant, Squyres said residents won't have to learn about it through an online real estate listing.

How one AI data center proposal mobilized Jacinto City residents

UNITED STATES SSPL via Getty Images

AI accelerates many things. One of those things, you might assume, is business strategy. Or, at a more established level, corporate governance.

To put it another way, the business strategy of larger businesses, i.e. corporations, will probably be heavily influenced by AI. And what will the technology drive these corporate behemoths to do?

We know, intuitively, that AI, all things being equal, tends to reinforce existing trends. So if the goal is to make money for shareholders, AI is likely to take that objective and run with it, supercharging those returns to share or dividend holders.

I was reading this illuminating piece from the Harvard Law School Forum on Corporate Governance by Pierluigi Matera, and I wanted to break down some bits of this, to consider what our economies are likely to do in response to more powerful AI.

Sharing and Showing Values

Matera begins with this (please forgive the lengthy block quote):

“Artificial intelligence (AI) is rapidly transforming corporate governance. While much attention has focused on AI’s impact on operations, compliance, and risk management, its influence on shareholder activism deserves equal scrutiny—particularly as younger, technologically fluent investors bring their generational values to bear on corporate decision-making. This evolution signals the potential emergence of identity-driven activism: a form of shareholder engagement that reflects priorities beyond short-term returns, such as climate action, diversity, and long-term social accountability—or any other cause, whatever it may be, to the extent that it creates common ground. Millennials and Gen Z investors, armed with AI-enabled tools, are increasingly capable of identifying causes they care about, crafting targeted proposals, and coordinating collective action with remarkable precision and speed.”

All of that sounds promising, in the sense that younger small investors may have more progressive ideals. But then Matera writes:

“Empirical data from the 2022–2024 proxy seasons suggest that AI’s democratizing potential remains structurally constrained, with its primary benefits accruing to large and well-resourced actors.”

Saying that AI’s democratizing and shareholder activism remain “structurally constrained” sounds, well, less hopeful, on the whole.

Matera then goes into four “signals” supporting the idea of constrained change, first, suggesting that some of the more idealistic shareholder proposals “have increased in volume, yet now face mounting resistance,” that millennials are participating less than was expected, and that activists are winning fewer board seats.

Here’s the last of the four related assertions verbatim:

“Fourth, although AI is increasingly embedded in activist strategies—including predictive analytics, sentiment analysis, and voting simulations—these technologies remain largely concentrated in the hands of institutional investors and well-capitalized funds. Millennial-led or grassroots initiatives have yet to gain meaningful access to, or benefit significantly from, these technological advancements.”

That’s pretty clear: the big fish keep winning.

Economy and Cyberwarfare

Let me show you this segment of the essay line by line. First, Matera contends:

“At the same time, corporations are deploying AI to strengthen their defenses against activist interventions.”

Part of the idea is the use of AI for forecasting:

“Companies are turning to predictive modeling and sentiment tracking to uncover vulnerabilities, anticipate potential challenges, and reinforce the position of incumbent boards.”

To what end?

“From AI-generated earnings scripts to sophisticated risk assessment systems, these innovations are being harnessed to consolidate managerial control—making it more difficult for dissidents to succeed.”

And this observation:

“In many cases, the same algorithmic tools that empower activists are being repurposed to neutralize them.”

Matera concludes:

“This dual use of AI highlights a core paradox: the same technology that promises to decentralize influence may also entrench existing power structures.”

That sounds daunting to someone who thinks that AI can change the world for the better.

The Future is Unwritten

There’s a significant ambiguity in the end of Matera’s piece, here, which the writer titles the past is prologue :

“The transformative potential of AI may indeed represent a new chapter in corporate governance—one built upon the foundations of what has come before, yet oriented toward a future rich with possibility. While the data remain inconclusive, the fulfillment of this promise may ultimately depend on whether directors anticipate rather than resist generational change. With foresight and responsibility, this next chapter could well be one of innovation, inclusivity, and enduring progress.”

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So, things could go either way.

Thoughts from an Experienced Business Leader

I also wanted to include this: recently, I sat down with Mark Lynch, former top brass member at eBay and Microsoft, among others, to talk about how all of this works in the age of AI.

Lynch started with an anecdote that he says shaped his thinking in high school.

“When I was a freshman in high school, my brother, who was a junior, came home one day from his economics class and said, ‘Mark, I just learned that the purpose of the economy is to make profits for shareholders.’ I thought, ‘Oh, really? I thought the purpose was to make the stuff we need. I thought it was to give us jobs. I thought, you know, that's what it's all about. He said, no, no, that's what I learned. He's the authority figure. He's my big brother, and the teacher was even more of an authority figure. And sure enough, all through the 70s and 80s, this message was broadcast: the purpose of the economy is to make profits for shareholders.”

The subtext of Lynch’s story is that this is not a good top-level objective. But I digress.

The Neoliberal Age – and What Comes Next

Speaking further on the economy, Lynch defined neoliberalism for us.

“Neoliberalism is the name that we give to the era that really started in the 70s and 80s,” he said. “It was based on the economics of that time, the 50s and the 60s. It sort of created an era that we all know. We think of it as economics. Before that, there was Keynesianism that went on for decades.”

Then he spoke to the future.

“There will be things that come next,” Lynch continued, “and one of the questions is: Are we at a moment of change? I think there's enough going on that makes me feel like we are in that sort of moment. A lot of people, maybe the majority of Americans, don’t feel that the economy is working for them. We have degraded our natural environment. We have we have AI looming above us. It's going to cause massive change one way or the other. So this is the moment of change.”

He returned to something he presented early in the discussion: the need to make AI work in ways that are beneficial to humans.

“Every change brings opportunity,” he said. “I'm not a tech optimist. I spent my career in technology. I think technology can solve human problems, and I think the purpose of the economy is to solve human problems that then enable us to flourish. That's what we want our economy to do for us, and it doesn't, always.”

He ended with this:

“I think the right way to measure things is: does this innovation solve something that helps us make life better for ourselves?”

I agree.

Stay tuned.

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About SK Group

SK Group, South Korea’s second-largest conglomerate, is a global technology and industrial leader that delivers innovations, products, and services across the Artificial Intelligence, semiconductors, energy, and life sciences ecosystems. Headquartered in Seoul, SK has a diverse portfolio of businesses and investments with over 175 affiliate companies and over 100,000 employees worldwide. http://eng.sk.com

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