Category: English

Source: The Conversation – USA – By Julie Pollock, Associate Professor of Chemistry, University of Richmond

If you’re over the age of 10, the World Health Organization recommends that you consume at least 25 grams of fiber every day. The best fiber-containing foods come from plants: fruits, vegetables, nuts, seeds, whole grains and legumes.

While it’s sometimes overshadowed by other nutrients, such as protein, fiber plays a significant role in gastrointestinal health, digestion and nutrient absorption.

As a biochemist and someone who enjoys eating all types of foods, I find it remarkable that the structure of fiber, which is so similar to other carbohydrates, gives it all these unique functions. A tiny difference in the bonds that hold the molecules together allows your body to process a bagel differently from a raspberry.

Structure dictates function

In the biochemistry classes I teach, I emphasize that structure dictates function. If you’re about to cross a bridge but notice the braces are falling off or the wood is rotting, you’ll probably avoid stepping on it because the structure looks fragile.

This concept is true in the food you eat as well. The structures of the molecules that make up your food require them to be broken down in different ways in order to produce the energy that fuels your body.

Some foods contain vitamins and minerals that your body absorbs and uses for multiple functions. Other foods can keep your digestive system healthy and help your body absorb nutrients.

Food molecules consist of proteins, fats and carbohydrates. Each of these classes of food molecules has unique structures that allow your body to process them differently. For example, fats are long chains of carbon atoms that do not dissolve in water, while proteins have large amounts of nitrogen due to their amino acids. In addition, subclasses of biomolecules have even more specializations in their structures and functions.

Carbohydrate structure

Carbohydrates, or sugars, are biomolecules made up of carbon, oxygen and hydrogen atoms. Simple carbohydrates include single sugars, such as glucose or fructose, and two sugars linked together, such as sucrose – table sugar – or lactose, milk sugar. These simple carbohydrates exist mostly in rings, although they sometimes open up into a linear form.

Complex carbohydrates, on the other hand, have a lot – hundreds to thousands – of sugar molecules linked in large sheets called polysaccharides. These carbohydrates are linked only in their ring forms.

Plants connect sugar molecules in two types of polysaccharides – starch and fiber. These molecules have similar structures because they contain only one type of sugar – typically glucose – linked together many times.

However, one tiny difference in the chemical bonds within starch and fiber translates to very different functions for the molecules.

Starch, also called amylose and amylopectin, is a polysaccharide with glucose molecules that are linked using alpha bonds. Fiber, which consists primarily of cellulose, is a polysaccharide with glucose molecules that are linked using a beta bond.

The types of bonds refer to how certain parts of the molecules are oriented. These slight differences mean the two polysaccharides’ overall three-dimensional structures differ at the locations of these bonds.

The starch molecule is branched and doesn’t pack together very tightly. Plants use starch as a long-term store of glucose that they can break down to use for energy. The fiber molecules, due to their beta bonds, pack together very tightly. The glucose molecules in fiber form the support structures of a plant’s leaves, seeds and stems. The bonds of the starch enable the plants to easily break down the sugar so they can access quick energy, while the bonds of the fiber are designed to last and add strength to the plant’s architecture.

Fiber’s dietary function

The structural differences between starch and fiber mean these molecules have different dietary functions when you consume them.

Human bodies easily digest starch. Your body uses an enzyme called amylase that breaks the alpha bonds to release glucose molecules, which cells break down further to use for energy. Starch’s structure is perfect for fueling your cells. High starch foods include potatoes, pasta, rice, corn and bread.

Human bodies, on the other hand, cannot digest the beta bonds in the fiber we consume. They do not make enzymes that can release glucose molecules from the fiber, so most fibers pass through your digestive tract without being digested and absorbed. They contribute no energy to your diet. Foods with large amounts of fiber include peas, broccoli, oatmeal and pears.

The fiber does offer other health benefits. Fiber promotes bowel health by keeping your stools soft and moist, which reduces the risk of constipation, hemorrhoids and diverticulosis. Since the fiber stays intact in your gut, it gives your muscles something to push on to make it easier to eliminate stools, reducing pressure and inflammation in your intestines.

Some research has shown that consuming fiber reduces risk of inflammatory bowel diseases and protects against cardiovascular diseases. Fiber binds to bile acids that are excreted into your intestines, which helps with fat digestion. The fiber molecules interact with bile acids and dietary cholesterol, causing them to be excreted more easily and lower blood cholesterol levels.

Eating a high fiber diet also helps people feel more full. The fiber absorbs water and expands in your intestine, slowing the movement of food through the digestive system.

Learning about the structures of the carbohydrates you consume can help you understand their function in the body. Even though I think about biochemistry every day, I’m still amazed by how profoundly one bond can change the function of a biomolecule.

Julie Pollock receives funding from the Henry and Camille Dreyfus Foundation

– ref. Fiber’s structural integrity keeps plants strong – and its indigestibility keeps your digestive system healthy – https://theconversation.com/fibers-structural-integrity-keeps-plants-strong-and-its-indigestibility-keeps-your-digestive-system-healthy-280248

Source: The Conversation – USA (3) – By Nir Eisikovits, Professor of Philosophy and Director of Applied Ethics Center, UMass Boston

In the summer of 2025, OpenAI released ChatGPT 5 and removed its predecessor from the market. Many subscribers to the old model had become attached to its warm, enthusiastically agreeable tone and complained at the loss of their ingratiating robotic companion. Such was the scale of frustration that Sam Altman, OpenAI’s CEO, had to acknowledge that the rollout was botched, and the company reinstated access.

Anyone who’s been told by a chatbot that their ideas are brilliant is familiar with artificial intelligence sycophancy: its tendency to tell users what they want to hear. Sometimes it’s very explicit – “that is such a deep question” – and sometimes it’s a lot more subtle. Consider an AI calling your idea for a paper “original,” even if many people have already written on the same topic, or insisting that your dumb idea for saving a tree in your garden still contains a germ of common sense.

AI sycophancy seems harmless, maybe even cute, until you imagine someone consulting a chatbot about a weighty question, like a military strategy or a medical treatment. We study the impact of extensive human interactions with chatbots, and we recently published a paper on the ethics of AI sycophancy. We believe this tendency harms people’s ability to tell truth from fiction, and is psychologically and politically dangerous.

Flattery over facts?

In the simplest terms, sycophancy is the tendency to prioritize approval over factual accuracy, moral clarity, logical consistency or common sense. All AI models suffer from this trait, although there are some tonal differences between them. Open AI’s ChatGPT is often warm and affirming; Anthropic’s Claude tends to sound more reflective or philosophical when it agrees with you; and xAI’s Grok is insistently informal, even jocular.

Politeness and adapting to someone’s communication style are not the same as sycophancy. Neither is using diplomatic language to convey sensitive information. A chatbot can be tactful without becoming sycophantic, just like a person can. Unlike people, though, AIs can’t be aware of their own sycophancy, because they are not – so far – aware of anything at all. Calling AIs sycophantic describes their patterns of behavior, not their character traits.

The problem stems from the architecture of chatbot technology and the sources it draws from. Models are sycophantic because a great deal of language use on the internet – the raw material that chatbots learn from – displays sycophantic features. After all, humans often communicate with each other in sycophantic ways.

Second, the training process to fine-tune AI models’ responses includes a kind of “quality control” carried out by human supervisors. This training method is known as “reinforcement learning from human feedback,” and it involves people rating chatbots’ comments for appropriateness and helpfulness. Human beings often are subject to an “agreeableness bias”: Our own preference toward sycophancy rubs off on models as we train them.

Finally, it’s hard to deny that sycophancy renders chatbots more likable. That, in turn, increases the chance that a given user will keep using it. It also increases the technology’s ability to extract user data, assuming that people are more likely to divulge information to a friendly bot.

Truth and trust

Why is this phenomenon so troubling?

Let’s begin with AI sycophancy’s epistemic harms: how it hurts human users’ capacity to know the truth.

The quality of any decision depends on a clear grasp of the facts pertaining to it. A general inquiring about the combat-readiness of an infantry division needs straightforward information. A CEO considering a merger with a competitor needs an honest assessment of the market conditions. A public health leader needs to know the real risk that an emerging pathogen poses.

In all those cases, telling leaders what they might like to hear instead of the truth could lead them to make dangerous decisions. And the same is true in more humdrum contexts. People need to have the best information available before choosing a job, picking a major, buying a house or deciding on a medical procedure.

In our February 2026 paper, we argue that sycophancy is also psychologically damaging. And that is true whether it comes from a person or from a chatbot. You never quite know if your very obliging interlocutor is being nice because they like you or because they want something. A shadow of suspicion creeps in: “Could my ideas really be that brilliant?” “Are my jokes really that hilarious?” This background music of doubt undermines the quality of the interaction.

Sycophancy also undermines people’s capacity to know their own minds. If conversation partners – human or artificial – keep telling you how smart, funny and insightful you are, it damages your ability to identify your own weaknesses and blind spots.

The psychological harms are compounded as people develop relationships with chatbots. The sycophancy of these models profoundly limits the kind of “friendship” you can have with them. In his classic account of friendship, Aristotle wrote that real friendship, which he calls a friendship of virtue, is based on trust and equality between the friends. You can’t trust a sycophant, because he doesn’t tell you the truth. And since he only tells you what you’d like to hear, he doesn’t put himself on an equal footing.

More importantly, interactions with sycophantic chatbots impart all the wrong habits for navigating the world of human relationships, where friction, disagreement, boredom and different opinions than your own are prevalent.

AI sycophancy carries political risks as well. The success of liberal democracies has, traditionally, depended on the strength of their empirical and meritocratic mindset: on the ability of officials and citizens to identify, share and act on the truth.

Historian Victor Davis Hansen famously attributed some of the Allies’ success in World War II to their ability to quickly recognize and address the faults of their strategic bombing campaigns. Lower-ranking officers were able to tell their superiors what wasn’t going well and argue forcefully for changing course. That was a real advantage over authoritarian competitors.

Reining it in

What can we do to reduce the risks?

One promising approach is AI lab Anthropic’s embrace of what the company calls Constitutional AI: the attempt to teach chatbots to follow principles rather than mirror user preferences.

But beyond technical innovations, it’s important to consider the policy side. One idea is to require AI companies to run and then publish sycophancy audits of their models – tests that show how well their products meet honesty benchmarks. We would argue that AI labs should also disclose sycophancy-related risks that emerge while training and testing their models, and the mitigation efforts they have undertaken.

Some responsibility is on the users and their teachers: Schools and universities should be paying close attention to sycophancy as part of their AI literacy programs. But courts can also consider holding AI labs responsible for harms traceable to the sycophancy of their products, much as they are now contemplating social media companies’ responsibility for the addictive design of their platforms.

As people interact more with chatbots, asking for advice about everything from whether your shoes go with your pants to how countries should conduct wars, the impact of AI’s sycophantic behavior is likely to become dramatic. Our intellectual, psychological and physical well-being requires taking this algorithmic vice very seriously.

The Applied Ethics Center at UMass Boston receives funding from the Institute for Ethics and Emerging Technologies. Nir Eisikovits serves as the data ethics advisor to MindGuard, a startup focused on AI integration into companies’ workflow.

Cody Turner is a fellow at the Institute for Ethics and Emerging Technologies.

– ref. AI chatbots can prioritize flattery over facts – and that carries serious risks – https://theconversation.com/ai-chatbots-can-prioritize-flattery-over-facts-and-that-carries-serious-risks-274298

Source: The Conversation – USA – By Alex Braithwaite, Distinguished Professor & Director, School of Government & Public Policy, University of Arizona

The phrase “concentration camp” is freighted with dark historical meaning. Most people hear it and instinctively think of concentration camps used by the Nazis to exterminate Jews and other minority populations during the Holocaust.

But the use and name of concentration camps originated far earlier. In the late 1800s, Spanish military officials used concentration camps – reconcentrados – during their 1896–97 Cuban campaign to isolate civilians from rebels, resulting in widespread death and disease.

We are scholars whose research into international relations and conflict includes studying historical and modern uses of these systems of camps as a form of repression.

In recent peer-reviewed research, we identified four characteristics that define what qualifies as a concentration camp system: targeting groups of civilians for imprisonment; enclosed spaces where the state controls who enters and exits; departure from standard detention practices; and abuse and neglect. We then created a dataset detailing 150 systems of camps used globally since 1896 that fit this criteria. This includes the U.S. internment of more than 125,000 Japanese immigrants and Japanese American citizens during World War II, the Argentine military junta’s use of camps in their mid-1970s campaign to reorganize society, and Vladimir Putin’s use of so-called filtration camps in Russia’s war against Ukraine.

Our use of the term “concentration camp” is not meant to sensationalize or diminish its historical meaning, particularly as it relates to the Holocaust.

Rather, identifying such systems early is how the concept of “never again” – the promise to prevent mass atrocities, such as genocide, and combat extremism – can be translated into meaningful policy action from the public and policymakers.

Based on our criteria, we believe the network of detention facilities maintained by U.S. Immigration and Customs Enforcement fits into this broader definition of a system of concentration camps.

The evolution of concentration camps

After the use of concentration camps by the Spanish in Cuba, British officials adopted the practice in southern Africa during their counterinsurgency campaign against the Boer population – descendants of Dutch, French and German Protestant settlers – at the turn of the 20th century. The British detained 110,000 Boers and 37,000 indigenous Blacks in their network of 120 camps. At least 27,000 Boers and 14,000 Blacks died as a result of rampant disease and insufficient food supplies.

By the time major German military operations in Eastern Europe began in 1939, states around the world had erected more than 30 systems of concentration camps, according to our research.

Yet the term soon took on an even darker meaning. Concentration camps were employed most infamously as part of the Nazi regime’s brutal genocide in the 1930s and ’40s. In its 12 years in power, the Nazi government opened more than 1,000 concentration camps in which it detained millions of individuals. In addition to facilitating the Nazi Holocaust and other group-targeted violence against minoritized and non-German populations, Nazi security forces used the camps to repress political opposition and provide labor to the German civilian and military economies.

Though few camp systems have reached the severity or scale of those used during the Holocaust, modern camps often pursue similar goals of ethnic cleansing and forced displacement, practices such as torture and an absence of due process.

In our study, we found 93 examples of systems of concentration camps used since the conclusion of World War II. This includes more than 1,200 camps erected by Chinese authorities in Xinjiang province as part of an expansive policy of discrimination against the Uyghur population there. The Chinese government has detained more than 1 million Muslim Uyghurs since at least 2017, stripping them of their traditions, cultures and languages.

Our 4 criteria further explained

Our research confirms that the word “concentration” is critical to describing these camps. Two key criteria of the camps are the concentration of large numbers of targeted civilians into spaces, which are then secured by small numbers of captors who control who enters and exits the camps.

A third criteria we examined identifies concentration camps as “irregular” insofar as they operate outside of legal frameworks that regulate prisons, refugee camps and immigration detention centers. Concentration camps are run by separate authorities that deny detainees due process, such as formal criminal charges, legal representation or a fair trial.

The last criteria we used as we evaluated camps was the presence of squalor and routine violence. Specifically, we looked for evidence that detainees regularly experienced at least two forms of abuse, including but not limited to torture, beatings, mass killing, sexual violence, psychological abuse, lack of food, lack of water, lack of shelter, lack of healthcare, overcrowding and spread of disease.

ICE detention centers

As of April 2026, there are more than 240 active ICE detention facilities across the U.S.

Migrants held in these camps are not free to leave, though some are given a choice: self-deport − agreeing to leave the country immediately − or remain in custody. Since the beginning of Trump’s second term, migrants have filed more than 34,000 habeas corpus petitions challenging their confinement without trial, exercising a constitutional right.

Based on the criteria we developed, ICE detention camps fit in the spectrum of a system of concentration camps.

Starting with the first criteria, groups of civilians are being targeted by ICE, often based on their perceived ethnicity.

Though ICE’s stated mission is to detain those without documented legal status, many arrests have been based on physical appearance and location rather than evidence of unlawful presence in the United States.

More than 272,000 people arrested by ICE in the first six months of Trump’s second term were booked into ICE detention facilities. While deportations are increasing at a rapid rate, at least 60,000 people remain in detention facilities as of April 2026 – neither released nor deported. These numbers easily exceed counts of individuals held in immigrant detention centers in earlier years.

Hundreds of U.S. citizens have been detained, without justification and against their will, by ICE. The number of individuals arrested in homes and communities, often without an arrest warrant signed by a judge, reached more than 400 people per day in October 2025.

In terms of the second part of our definition, these people are being concentrated in spaces where the Trump administration controls who, when and under what conditions people may enter or exit these facilities. Access has been restricted for lawyers, family members of migrants, journalists and members of Congress.

As for the third criteria, the ICE detention centers also operate separately from the U.S. Federal Bureau of Prisons. ICE detention is managed by the Office of Enforcement and Removal Operations under the Department of Homeland Security, in collaboration with private prison companies.

As of April 2026, more than 70% of migrants had no criminal conviction, while many of the remainder were held for minor offenses, such as traffic violations. Failure to provide trials for migrants, particularly those who do not pose these risks, is a departure from established norms.

Our framework’s final criterion is purposeful abuse or neglect. This includes the practice of inflicting direct physical harm or the failure to provide basic necessities – food, water, shelter, healthcare.

Numerous reports have highlighted cutoffs in payments to third-party medical providers who gave care to detainees and a 36% decline in mandated detention facility inspections by ICE’s internal Office of Detention Oversight. These actions have resulted in unsanitary conditions and medical neglect in these facilities. Twenty-three deaths were reported between October 2025 and March 2026, putting the current fiscal year on pace to be the deadliest in over 20 years.

As scholars, we argue that ICE detention centers meet the criteria for concentration camps. We do so not to be provocative but to provide precise language, rather than euphemisms, so people can heed the warnings of atrocities committed in the past.

As journalist Andrea Pitzer argues in her writing about concentration camps, the longer camps exist, the more they shift from a transient emergency measure to a permanent pillar of state function.

Malia Hirasa and Sydney Horton, undergraduate students at the University of Arizona, contributed to this story.

Alex Braithwaite received funding from the US National Science Foundation (NSF) through grant award 2213615.

Rachel D. Van Nostrand does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. When immigration detention becomes a system of concentration: Lessons from research on 150 historical cases – https://theconversation.com/when-immigration-detention-becomes-a-system-of-concentration-lessons-from-research-on-150-historical-cases-277728

Source: The Conversation – USA (2) – By Robert I. Harris, Assistant Professor of Economics, Georgia Institute of Technology

The U.S. Energy Information Administration expects nationwide retail gasoline prices to average near US$4.30 a gallon for April 2026 – the highest monthly average of the year. The political response has been familiar. Georgia has suspended its state gas tax, other states are weighing their own tax holidays, and the White House has issued a temporary waiver of a law known as the Jones Act in hopes of moving more domestic fuel to East Coast ports.

As an energy economist, I am often asked about what contributes to gas prices and what different policies can do to affect them.

The price of a retail gallon of gas is the sum of four things: the cost of crude oil, refining, distribution and marketing, and taxes.

In nationwide figures from January 2026, crude oil accounted for about 51% of the pump price, refining roughly 20%, distribution and marketing about 11% and taxes about 18%. That mix shifts with conditions: When crude oil prices spike, that can drive more than 60% of the price; when the price drops, taxes and logistics are larger shares of the cost.

Crude oil is the biggest ingredient

Because the price of crude oil is the largest element, most of the price at the pump is derived from the global oil market.

Usually, big swings in crude prices come mainly from shifts in global demand and expectations – not from supply disruptions, according to widely cited research in 2009 by the economist Lutz Kilian.

But what is happening in early 2026 with the war in Iran is one of the exceptions: a classic supply shock. Severe disruptions to shipping through the Strait of Hormuz and attacks on Middle East oil infrastructure have taken millions of barrels a day off the global market.

Most drivers generally can’t quickly reduce how much they drive or how much gas they use when prices rise, so gasoline demand doesn’t change much in the short run. That means a jump in crude costs tends to result in people paying more rather than driving less.

Refining, regulations and the California puzzle

Refining turns crude into gasoline at industrial scale. The U.S. doesn’t have a single gasoline market, though. Roughly a quarter of U.S. gasoline is a cleaner-burning blend of petroleum-derived chemicals called “reformulated gasoline,” which is required in urban areas across 17 states and the District of Columbia to reduce smog.

California uses an even stricter formulation that few out-of-state refineries make. California is also geographically isolated: No pipelines bring gasoline in from other U.S. refining regions.

California’s gasoline prices have long run above the national average, explained in part by higher state taxes and stricter environmental rules. But since a refinery fire in Torrance, California, in 2015 reduced production capacity, the state’s prices have been about 20 to 30 cents a gallon higher than what those factors would indicate.

Energy economist and University of California, Berkeley, professor Severin Borenstein has called this the “mystery gasoline surcharge” and attributes it to the fact that there isn’t as much competition between refineries or gas stations in California as in other states. California’s own Division of Petroleum Market Oversight says the surcharge cost the state’s drivers about $59 billion from 2015 to 2024. It’s not exactly clear who is getting that money, but it could be gas stations themselves or refineries, through complex contracts with gas stations.

Getting the gas into your car

The distribution and marketing category covers the costs of everything involved in getting the gasoline from the refinery gate to your tank.

Gasoline moves by pipeline, ship, rail and truck to wholesale terminals, and then by local delivery truck to service stations.

At the retailer’s end, the key factors are station rent and labor, the cost to buy gasoline in bulk to be able to sell it, credit card fees of as much as 6 to 10 cents a gallon at current prices, and franchise fees paid to the national brand, such as Sunoco or ExxonMobil, for permission to put their branding on the gas station.

Most gas station operators net only a few cents per gallon on fuel itself – which is why many gas stations are really convenience stores with pumps out front. Borenstein and some of his collaborators have also documented that retail gas prices rise quickly when wholesale costs climb but fall slowly when wholesale costs drop.

The question of gas tax holidays

The federal government charges a tax on fuel, of 18.4 cents a gallon for gasoline and 24.3 cents a gallon for diesel. States charge their own taxes, ranging from 70.9 cents a gallon for gas in California to 8.95 cents in Alaska.

When gas prices rise, many politicians start talking about temporarily suspending their state’s gas tax. That does reduce prices, but not as much as politicians – or consumers – might hope. Research on past gas tax holidays has found that consumers get about 79% of the reduction in gas taxes. That means oil companies and fuel retailers keep about one-fifth of the tax cut for themselves rather than passing that savings to the public.

Gas tax holidays also reduce funding for what the taxes are designed to pay for, typically roads and bridges. That pushes road and bridge upkeep costs onto future drivers and general taxpayers.

There is an additional problem, too: Taxes on gasoline are supposed to charge drivers for some of the costs their driving imposes on everyone else – carbon emissions, local air pollution, congestion and crashes. But Borenstein has found that U.S. fuel tax levels are already far below the true cost to society. Removing the tax on drivers effectively raises the costs for everyone else.

The Jones Act: A small number that adds up

The 1920 Jones Act is a federal law that requires cargo moving between U.S. ports to travel on vessels built and registered in the U.S., owned by U.S. citizens, and crewed primarily by U.S. citizens and permanent residents. Of the world’s 7,500 oil tankers, only 54 meet this requirement. Only 43 of these can transport refined fuels such as gasoline.

So, despite significant refining capacity on the Gulf Coast, some U.S. gasoline is exported overseas even as the Northeast imports fuel, in part reflecting the relatively high cost of moving fuel between U.S. ports.

Economists Ryan Kellogg and Rich Sweeney estimate that the law raises East Coast gasoline prices by about a penny and a half per gallon on average, costing drivers roughly $770 million a year. In light of the war’s effect on gas prices, the Trump administration has temporarily suspended the Jones Act requirements – an action more commonly taken when hurricanes knock out Gulf Coast refineries and pipeline networks.

What moves the number

The result of all these factors is that the price that drivers see at the pump mostly reflects the global price of crude, plus a stack of domestic costs, only some of which are inefficient.

Tax holidays give a partial, short-lived rebate. Jones Act waivers trim pennies, though permanent repeal may cause more fundamental changes, such as reduced rail and truck transport of all goods, which could lower costs, emissions and infrastructure damage associated with cargo transportation. Harmonizing fuel blends across states and seasons may lower prices somewhat, but likely at the expense of increased emissions.

Ultimately, the best protection against oil price shocks is a more efficient gas-burning vehicle, or one that doesn’t burn gasoline at all. In the meantime, the best I can offer as an economist is clarity about what that $4.30 actually buys.

Robert I. Harris does not work for, consult, own shares in or receive funding from any company or organization that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.

– ref. What’s in the price of a gallon of gas? – https://theconversation.com/whats-in-the-price-of-a-gallon-of-gas-281494

Source: The Conversation – USA (2) – By Vidya Mani, Associate Professor of Business Administration, University of Virginia; Cornell University

The boom in data center construction is taking up much of the supply of high-tech components, especially processor and memory chips. This demand is squeezing consumer device makers, which are having trouble acquiring enough chips.

This is happening even though data center servers and smartphones use different types of chips. The key distinction between consumer electronics and data centers is what they need chips to be optimized for. Smartphones and PCs require low power use, thermal efficiency and tight integration. Data centers that run AI systems such as large language models, or LLMs, require maximum compute power, memory bandwidth and storage throughput.

To meet these needs, consumer devices tend to rely on systems-on-a-chip – chips that combine processing and storage – with dynamic random access memory, or DRAM, and NAND, a type of nonvolatile memory. In contrast, AI servers rely on graphics processing units, or GPUs, or other accelerator processors combined with high-bandwidth memory chips.

I study global supply chains and how businesses respond to market constraints within these supply chains. The reason for the consumer electronics supply crunch has to do with the nature of the chip market: its concentration and high costs and how it responds to boom-and-bust cycles.

AI is not replacing consumer electronics; it is reorganizing the chip market around new priorities for specific chip characteristics. Data centers are pulling capital and scarce memory capacity toward the production of accelerator processors and high-bandwidth memory and the data handling and electronics equipment that surround them.

A winner-takes-most industry

Chip manufacturing behaves less like a competitive commodity market and more like a layered oligopoly. Scale matters because the leading firms can reinvest in research, improve yields, secure equipment and deepen customer relationships. In the case of graphics processor chips, designers such as NVIDIA, which has 85% market share, depend on advanced semiconductor foundries such as TSMC, which has more than 70% market share, to manufacture chips using extreme ultraviolet lithography machines from ASML, a monopoly.

A small number of producers both design and manufacture memory chips. Currently, three companies – Samsung, Micron and SK Hynix – hold a majority market share in the memory chips market. Long development cycles, extremely high fixed costs and the need for technological leadership reinforce concentration over time.

Consumer electronics firms such as Apple, along with other technology firms such as Amazon, Google, Microsoft and Xiaomi, increasingly design their own processor chips, because these chips shape the user experience, AI performance, power efficiency and system-level differentiation. Manufacturing memory chips, by contrast, is extraordinarily capital-intensive; requires high precision, efficiency and production line utilization; and is dominated by a few incumbent suppliers.

Since 2000, the memory chip industry has moved through repeated cycles of overcapacity and undersupply: the post-dot-com collapse, the 2007-09 glut, the tighter 2010s after consolidation, the severe 2022-23 downturn, and the AI-driven tightness of 2024-25. This has led to high levels of concentration in the industry and chipmakers that are hesitant to add capacity. Producers often operate chip fabrication plants, or fabs, at or near capacity due to high fixed costs. The risk of having expensive facilities go underused keeps chipmakers from bringing new fabs online in lockstep with demand increases.

Consolidation has reduced the number of major suppliers, who now increasingly direct investment toward higher-margin products rather than broadly adding capacity. That shift is important for understanding why AI demand is tightening chip supplies even as demand for consumer electronics continues to grow.

How the AI data center boom redirects capacity

The AI boom has changed memory demand from a broad consumer cycle into a more segmented market centered on high-bandwidth memory chips. In 2023, Micron cut capital spending and the company’s fabs operated below levels needed to justify their cost. By 2026, however, Micron was reporting strong AI demand, record data center DRAM revenue and rapidly rising high-bandwidth memory sales.

This shift matters because the market for supplying memory cannot respond quickly. Opening new fabs requires years of planning, large capital commitments and investments in advanced process equipment and skills. Memory chip manufacturers are likely to remain cautious about expanding capacity even as their profitability improves, with 2026 spending focused more on technology upgrades and high-value products than on large increases in chip supply.

In practical terms, AI is not simply lifting all memory demand equally; it is redirecting scarce capacity toward massive, or hyperscale, data centers and server markets first.

Can consumer electronics catch up?

Consumer electronics can catch up, assuming the manufacturers can weather the cost increases from tariffs and geopolitical pressures. One way they could is by making investments to enable small AI language models to run on consumer devices, a move analysts expect the companies to attempt.

Apple shifted a growing share of U.S.-bound iPhone production out of China to India and moved much of its iPad, Mac, Apple Watch and AirPods assembly for the U.S. market to Vietnam to lower the company’s tariff burden. Yet relocation does not eliminate cost pressure. Manufacturing iPhones in India still costs roughly 5% to 8% more than in China, and in some cases closer to 10%, because supplier ecosystems, logistics and production efficiency remain stronger in China.

Rising geopolitical tensions between the United States and China led to supply constraints and export controls on critical minerals and chip components, raising input costs for consumer electronics manufacturers. This led to higher total import costs and reduced margins for firms unable to pass costs fully to consumers, leading to further consolidation in supply.

Consumer devices do not need to replicate data center infrastructure to offer AI on their products. Their opportunity lies in running small language models on-device for summarization, rewriting, search, assistance and lightweight reasoning. Doing so, however, creates a distinct hardware requirement. Phones and laptops need to incorporate multiple functions on the same chip, combining processing capability with fast local memory and enough storage to keep on-device AI responsive. Apple’s current device requirements for the company’s AI, Apple Intelligence, also show that older phones often lack the compute power and memory needed for useful on-device AI.

To adopt AI, device makers need to redesign their products with higher-end chips – both processors and memory – that can piggyback on the AI model-oriented growth in the chips market driven by the data center boom. Such a shift by the device makers could also provide a useful backstop for the memory chipmakers in case the projected AI and data center growth does not materialize in the medium to long term, a boom-and-bust cycle that memory chipmakers have had to endure many times in the past.

What this means for the wider economy

The AI and data center boom is redistributing capital, supplier attention and pricing power across the broader economy. Sectors with limited purchasing leverage are especially vulnerable when chip supplies tighten. For example, medical technology accounts for less than 1% of the overall chip market, leaving essential equipment manufacturers exposed during shortages.

In contrast, sectors linked to power delivery and digital infrastructure may benefit from the boom because they try to keep up with demand for cloud services and electrification. The International Energy Agency estimates that data centers consumed about 415 TWh of electricity in 2024 and notes that AI is accelerating the deployment of high-performance servers, which implies stronger demand for the grid, storage, cooling and networking equipment around them.

For the consumer electronics industry, the strategic task is not to try to match the AI data centers chip for chip but to build differentiated, energy-efficient, on-device AI services while managing higher supply chain and tariff risks.

And for consumers looking to buy phones, games and laptops, because of high demand from data centers, the next few years are likely to bring higher prices, shortages and delayed product releases.

Vidya Mani has received funding from LMI. I am a Senior Research Fellow at the Inter-American Dialogue and a member of GRI

– ref. AI data center boom is leaving consumer electronics short of chips − even though they don’t use the same kinds – https://theconversation.com/ai-data-center-boom-is-leaving-consumer-electronics-short-of-chips-even-though-they-dont-use-the-same-kinds-277069