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A small town in Finland is experimenting with a new type of infrastructure: the world’s largest sand battery. The batterya 42-foot-tall, nearly 50-foot-wide silo filled with 2,000 tons of crushed stonesits on the edge of a parking lot. When there’s extra renewable electricity on the grid and power is cheap, the system uses electricity to heat up the crushed stone. That heat is stored in the battery until nearby buildings need to use it. [Photo: Polar Night Energy] The basic approach is simple. “We just heat air and [circulate it] through sand,” says Liisa Naskali, COO of Polar Night Energy, the Finnish startup that designed the technology. Sand, or other material crushed into sand-size particles, has the ability to store heat for weeks. Unlike some other batteries, the system doesn’t rely on chemicals, doesn’t degrade, and won’t catch on fire. The town, called Pornainen, relies on a district heating network to heat a group of buildings, from city offices and the local school to some businesses and apartment complexes. Until recently, the network burned oil or wood chips to run. But the municipality is aiming to become carbon neutral, and realized that it needed to make a change. [Photo: Polar Night Energy] Now if someone in a nearby apartment turns on hot water for a shower, the heat comes from the sand battery. Like other district heating systems, the heat from the battery travels to other buildings via pipes filled with hot water; each building has its own equipment to distribute the heat to radiators, floor heaters, or other HVAC systems. [Photo: Polar Night Energy] The battery started running this summer, and was officially inaugurated this week, meaning the district heating system no longer uses oil at all. Over the summer, it relied entirely on the sand battery. As the weather gets colder, the system will use both the battery and wood chips, but the use of wood chips can drop by around 60%. (Burning wood chips is technically carbon neutral since trees take in carbon as they grow, but since trees are slow to grow and burning is fast, it’s not a good short-term climate solutionand it also produces a lot of other pollution.) [Photo: Polar Night Energy] Though the startup calls the technology a “sand” battery, it can use other materials. For the new installation in Pornainen, the company turned to soapstone scraps from a nearby fireplace manufacturer. That helped reduce waste and avoided the environmental challenges of sourcing sand, which is typically excavated from rivers, lakes, or shorelines. [Photo: Polar Night Energy] Inside the silo, the company uses a heat exchanger and a closed-loop system to circulate heat. Software runs heaters when electricity prices are low. Throughout the summer, Naskali says, the utility paid around 10% of the average price of electricity by charging only at optimal times. That helps make the technology cost-competitive, though the initial installation cost is high, she says. The startup is now in talks with other utilities. Factories can also use the technology to replace fossil fuels for high-heat processes. Other startups, including Rondo Energy and Antora Energy, are also pioneering new approaches to thermal energy storage. For Polar Night Energy, the project in Pornainen is a critical proof point. “This is really important for us, Naskali says, because now we can show thatthis really works.
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E-Commerce
Its been 70 years since Douglas McGregor sketched a management theory at MIT Sloan that leaders still ignoreand their teams pay the price. Known as Theory X and Theory Y, McGregors framework built on Abraham Maslows work on employee self-actualization, and it quickly became one of the foundational texts of modern management thinking. In McGregors theory, leaders fall into two camps. Theory X managers assume that employees are inherently lazy, need constant supervision, and would rather coast along than contribute. Theory Y managers, by contrast, see employees as self-motivated, responsible, and capable of growth if given the right environment. The kicker is that both kinds of managers usually get exactly the employees they expect, no matter who they originally hired. What McGregor was tapping into was the fact that certain beliefs have an uncanny way of turning into real, measurable effects on human behavior. Whether its placebo studies in medicine or examining how teachers’ expectations impact classroom performance, the science is unambiguous about how simple expectations can have far-reaching effects. The psychology behind high expectations Psychologists were among the first to observe and take note of the feedback loops expectations set off. Take the now-famous study by Robert Rosenthal and Lenore Jacobson in 1968. Elementary school teachers were told that a group of randomly selected students had been identified as “late bloomers” who were about to show remarkable academic growth. The result surprised even the researchers themselves. Those students did indeed outperform their peers, in part because the teachers, subconsciously or not, started treating them differently by offering more encouragement, more patience, and more challenging material. The students responded in kind, rising to the challenge now that someone in authority believed them capable of meeting it. The only thing that had changed was the expectations. The expectation effect Journalist David Robson chronicles just how far this phenomenon goes in The Expectation Effect (which should be required reading for leadership). From placebo heart surgeries that deliver real relief to workouts that burn more fat just because people believe theyre working harder, Robson lays out the scientific evidence showing how our expectations construct reality around us. The psychology behind the effect is simple: Your brain doesnt sit around waiting for input like a neutral recordkeeper. It ceaselessly guesses and simulates what might happen so that you can be prepared for whatever comes across your desk. At each moment, the brain is busy constructing an internal map of whats likely to happen, and then it updates that map based on whatever comes next. Its no surprise to find that our expectations prime the brains sensory and emotional circuits almost as if something is already happening. If you are expecting pain, the amygdala lights up before you even stub your toe. If you expect failure, your cortisol rises, attention narrows, and your working memory takes a hit before youve even started the task. Expect a sense of existential dread and meaninglessness at work? Here you go, says the brain, lowering your dopamine levels until motivation plummets because your brains prediction model no longer sees a reason to invest cognitive effort. Thats why a sugar pill can relieve chronic pain, why sham surgeries produce real outcomes, and why a warm-up jog feels harder if you think it’s the workout. The experience conforms to the prediction, and belief becomes biology. When leaders talk about setting the tone or creating a culture of excellence, theyre not that far from hitting upon something truly powerful. If we accept that expectations change biology, cognition, and motivation, then leveling them appropriately becomes one of leaderships central tasks. Careful what you expect, because you might get it If you walk into a boardroom assuming your team lacks ambition, youll subconsciously act like it by designing processes that assume failure. Your team, in turn, will rise, or in this case, sink, to the level you’ve set. Welcome to management by cynicism. Nelson Repenning, an MIT Sloan professor and coauthor of the new book Theres Got to Be a Better Way, has spent his career helping leaders break out of this cycle. He advises people to expect more, and better, from others as a starting point. When people fail, we treat it like a character flaw. But in most organizations, failure is a design problem, he says. The question every leader should ask isnt Why did they screw up? Its What about our system made it easy to screw up? Repenning and longtime collaborator Don Kieffer argue that modern management has become too disconnected from the work itself. Youd be amazed how many executives cant describe how the work actually gets done, Kieffer says. Its like trying to fix a car without opening the hood. These leaders cant set a good expectation because theyre so far removed from reality to begin with. Without that intimacy, leaders default to assumptions, not expectations. Before long, youre managing caricatures of your team instead of the real people doing the work. Great leaders dont set expectations and step back Anyone can ask for a 17% increase in revenue and expect it to happen, Repenning says. But thats not a healthy way to set goals, let alone a culture of expectations. Leaders need to know what they are asking for, and they need to understand how powerful the expectations they set are. This is where too many leaders trip over their own lofty visions. They expect more but enable less. Perhaps some even care less. Repenning calls this the paradox of servile leadership: Great leaders dont set expectations and step back. They ask, What do you need from me to get there? Then they go and move those boulders. The accompanying leadership model isnt that much more complicated. Set the target, communicate belief, and then roll up your sleeves to start fixing whats brokenwhether its systems, workflows, org charts, tools, or, yes, your assumptions. McGregor and Maslow would be nodding along if they were still with us. Decades before we started talking about psychological safety and employee empowerment, they argued that the job of management was to unlock people’s natural drive. Give them autonomy and show them how their work connects to a bigger picture. Eliminate the management by the stopwatch and start practicing management by the soul. Expectation is freedisappointment is expensive If you expect your team to take shortcuts, youll create a culture of cutting corners. If you expect your team to challenge ideas, theyll innovate. If you expect mediocrity, youll be surrounded by it. And the inverse holds, too. When a leader believes in their people, when they really believe in their capacity to achieve, something remarkable happens: People stretch to meet the expectations and trust begins to compound. Done right, simply expecting greatness might do more than any retreat r bonus ever could, Repenning says. But expecting isnt enough. You still have to earn it. Thats the fine print of McGregors theory, and the trap too many leaders fall into. They want the results of Theory Y, but still manage like they believe in Theory X. The message that sends is I dont really think youve got it in you. But prove me wrong. Thats not leadership. Thats abdication. And now you know how to do better.
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E-Commerce
How will AI affect American workers? There are two major narratives floating around. The techno-optimist view is that AI will free humans from boring tasks and create new jobs, while the techno-pessimist view is that AI will lead to widespread unemployment. As a sociologist who studies job insecurity, Im among the pessimists. And thats not just because of AI itself. Its about something deeperwhat scholars call American exceptionalism. While people commonly use this phrase to refer to anything that makes the U.S. unique, I use it narrowly to refer to the countrys approach to work and social welfare, which is quite different from the systems in other rich countries. I suspect AI will turbocharge American exceptionalism in ways that make workers more afraid of losing their jobs. When fused with organizations adoption of new types of AI, workers fears may soon become reality, if they havent already. An “exceptional” system for American workers Lets start with what makes the U.S. different, especially from other rich countries. The U.S. has relatively low levels of unionization, an at-will employment system, a modest welfare state, and a two-party system that lacks a social democratic tradition. Many wealthy countries boast higher unionization rates, stricter protections against being fired, andparticularly in Europemore robust welfare states. In other words, even before AI came into the picture, American workers were facing a system stacked against them. This tendency grew more pronounced starting in the late 1970s, with Democrats and Republicans alike pursuing reforms such as stripping regulations and rolling back the welfare state. Between 1983 and 2022, unionization rates fell by more than 50%; they remain low today. In the 1990s, President Bill Clinton pledged to end welfare as we know it and followed with a law slashing support programs. Meanwhile, U.S. workers inflation-adjusted wages have stagnated, and income inequality has risen since the 1970s. The current Trump administration has taken these exceptional traits even further. From firing the head of the National Labor Relations Board to his executive order undermining federal employee unions, Trump has usurped the power of regulatory agencies and workers themselves. And more cuts to the welfare state are coming now that Trumps domestic policy bill has been signed into law, including reductions in food aid and health insurance. One telling example is the Trump administrations mass firing of federal workers. While they are making their way through the courts, these efforts are notable for targeting government positions that have long been thought to be the most secure jobs. As a sociologist, I think its fair to say that the U.S. is even more exceptional than it was just a year ago. This trend lays the foundation for U.S. workers to fear losing their jobs, for employers to cut workers loose, and for people to struggle making ends meet. American exceptionalism, meet AI To understand whats happening, it helps to look at the different kinds of artificial intelligence, which generally refers to machines such as computers that can perform tasks comparably to humans. One type is predictive AI, which is what powers your streaming and social media recommendations. The second type is generative AI, which is used to create seemingly novel content. ChatGPT and other large language models fall in this category. The third type, agentic AI, cannot only predict and plan outcomes but also can act autonomously to achieve those outcomes. Self-driving cars are perhaps the most well-known example. Companies are increasingly using generative AI to boost productivity. According to Stanford Universitys 2025 AI index report, generative AI has already surpassed human performance on a range of tasks, including visual reasoning and answering competition-level math and PhD-level science questions. The U.S. Bureau of Labor Statistics has warned that generative AI will affect jobs across a range of industries. I think agentic AI will have dramatic implications for the workforce. Companies are already beginning to use it for customer service in industries from finance to travel. As if on cue, OpenAI recently released ChatGPT Agent, which it says can handle complex tasks from start to finish. When you combine technological advancementssuch as the current transition to generative AI and the likely broader agentic AI transitionwith turbocharged American exceptionalism, you get a formula for job insecurity and displacement. How AI might affect the future of job security Interestingly, despite having fewer protections from firing and a more threadbare unemployment system, American workes are no more afraid of losing their jobs than workers in other rich countries, research shows. These perceptions are generally constant over time, but they spike as a result of certain economic reforms and during recessions. Among the findings in my own research on free-market-driven economic reforms in Europe, people were most worried about losing their jobs in countries that had ratcheted up such policies within the past five years. That trend has important implications for the United States. Recent polling shows that about a third of U.S. workers believe AI will hurt their jobs or job opportunities. Business leaders say they expect job losses in the service industries, supply chain management, and human resources over the next three years. Theres no shortage of predictions about AI-driven job gains and losses, but solid data is hard to come byand dont even bother asking most companies about AI-related layoffs. On one hand, business leaders surveyed by McKinsey in 2024 reported high demand for new jobs such as AI compliance specialist and AI ethics specialist, which are the kinds of new roles that techno-optimists say will be created by AI. On the other hand, its no small irony that AI was reportedly used to facilitate the mass firing of federal workers and may soon replace some Department of Education workers jobs. Americas fusion of limited labor protections and aggressive AI adoption could create the perfect storm for widespread job insecurity. While unions have organized for AI-related job protections, and states are attempting to regulate AI, the U.S.s path realistically depends less on workers and local politicians actions than on what companies do. And I think companies increasing integration of AI will likely hurt American workers more than it helps. If nothing changes, job insecurity may become the new normal. Jeffrey C. Dixon is a professor of sociology at College of the Holy Cross. This article is republished from The Conversation under a Creative Commons license. Read the original article.
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