Why are there seven days in a week? – Henry E., age 8, Somerville, Massachusetts
Waiting for the weekend can often seem unbearable, a whole six days between Saturdays. Having seven days in a week has been the case for a very long time, and so people don’t often stop to ask why.
Most of our time reckoning is due to the movements of the planets, Moon and stars. Our day is equal to one full rotation of the Earth around its axis. Our year is a revolution of the Earth around the Sun, which takes 365 and ¼ days, which is why we add an extra day in February every four years, for a leap year.
But the week and the month are a bit trickier. The phases of the Moon do not exactly coincide with the solar calendar. The Moon cycle is 27 days and seven hours long, and there are 13 phases of the Moon in each solar year.
Some of the earliest civilizations observed the cosmos and recorded the movements of planets, the Sun and Moon. The Babylonians, who lived in modern-day Iraq, were astute observers and interpreters of the heavens, and it is largely thanks to them that our weeks are seven days long.
The reason they adopted the number seven was that they observed seven celestial bodies – the Sun, the Moon, Mercury, Venus, Mars, Jupiter and Saturn. So, that number held particular significance to them.
Other civilizations chose other numbers – like the Egyptians, whose week was 10 days long; or the Romans, whose week lasted eight.
The Babylonians divided their lunar months into seven-day weeks, with the final day of the week holding particular religious significance. The 28-day month, or a complete cycle of the Moon, is a bit too large a period of time to manage effectively, and so the Babylonians divided their months into four equal parts of seven.
The number seven is not especially well-suited to coincide with the solar year, or even the months, so it did create a few inconsistencies.
However, the Babylonians were such a dominant culture in the Near East, especially in the sixth and seventh centuries B.C., that this, and many of their other notions of time – such as a 60-minute hour – persisted.
The seven-day week spread throughout the Near East. It was adopted by the Jews, who had been captives of the Babylonians at the height of that civilization’s power. Other cultures in the surrounding areas got on board with the seven-day week, including the Persian empire and the Greeks.
Centuries later, when Alexander the Great began to spread Greek culture throughout the Near East as far as India, the concept of the seven-day week spread as well. Scholars think that perhaps India later introduced the seven-day week to China.
Finally, once the Romans began to conquer the territory influenced by Alexander the Great, they too eventually shifted to the seven-day week. It was Emperor Constantine who decreed that the seven-day week was the official Roman week and made Sunday a public holiday in A.D. 321.
The weekend was not adopted until modern times in the 20th century. Although there have been some recent attempts to change the seven-day week, it has been around for so long that it seems like it is here to stay.
So there we are, the ancient history of the week. Including the fact that the weekend was not adopted until the 20th century. In the 1940’s to be precise.
You open a free app to do one simple thing. Before you even start, a full-screen message asks whether you want to try the paid version. The “Start free trial” button is large, bright and hard to miss. The option to keep using the free version is smaller, buried at the bottom. The same prompt appears again tomorrow. And the day after that.
A lot of people look at screens like that and think, “Surely this has to be illegal.” We even have a name for them, “dark patterns.” They feel pushy. They waste time. They seem designed to wear you down. But in most cases, they are perfectly lawful.
“Dark pattern” is not a legal term with a clear boundary. It is a broad label for digital designs that nudge, pressure, confuse or trap users. As a legal scholar who studies consumer protection and digital design, I think the most important thing for readers to understand is that the label “dark pattern” covers a broad spectrum.
Some of that spectrum is just annoying. Some of it is aggressive salesmanship. And some of it crosses the line into deception or coercion. Federal and state consumer protection laws are mostly aimed at that last category. They do not ban every design choice people dislike, only those that trick or coerce.
Annoying isn’t illegal
The ‘X’ in the upper right corner of this ad, for users to click to dismiss the ad, appears after the ad has been displayed for a moment. The ad also has an ‘X’ in the upper left corner, which is part of the image in the ad. Some users might click the ‘X’ on the left to dismiss the ad but instead be sent to the ad’s website. Possibly annoying but not illegal. Screen capture by Gregory Dickinson
That reality may sound unsatisfying, but it is not unusual. Offline life is full of things that are irritating but not unlawful. Think of the cashier who asks whether you want to sign up for the store credit card, then points out the discount you are turning down, then asks again. Most people know exactly what is happening. They roll their eyes, say no and try to shop somewhere else next time.
The same is true online. A repeated pop-up can be obnoxious. A guilt-inducing button can be tacky. But consumers recognize ordinary annoyance for what it is. In many cases, the market answer is simple: Close the app, ignore the pitch or take your business elsewhere.
Similarly, law does not ban persuasive sales pitches just because they are effective. A car salesperson who keeps steering you toward the upgraded model is trying to influence your choice. So is the airline clerk who offers travel insurance. So is the restaurant server who asks whether you want dessert. Salesmanship is nothing new. Digital design often borrows from familiar techniques.
That helps explain why lawmakers cannot simply outlaw “manipulation.” And so many interfaces are built to persuade, openly and lawfully.
What crosses the line
What the federal FTC Act and analogous state consumer-deception statutes usually care about is not whether a design is annoying. They focus on whether the design is likely to mislead a reasonable consumer. That is the core idea in modern consumer protection law.
So a design is likelier to be unlawful when it hides key facts, makes an optional choice look mandatory or tricks people about the effect of the button they are pressing. A fake countdown timer, a disguised ad, a misleading one-click purchase button or a cancellation path that looks finished when it is not are all different from ordinary hard selling. Those designs do not just pressure users; they can deceive them.
That is also why the app maker’s intent is not always the key question. In many consumer protection cases, a company does not get a free pass just because no one said, “Let’s trick people.” The legal question is often about effect: What would a reasonable user likely understand from this screen?
Research on dark patterns reinforces that concern. Even relatively mild designs can push people into choices they would not otherwise make. And regulators have increasingly focused on subscription flows, hidden fees and cancellation obstacles for exactly that reason.
The instructions for this web form and the pop-up box that appears when users click ‘Continue’ indicate that the form has required fields. The form uses the word ‘mandatory,’ which could lead some users to believe that the form itself is required in order to continue when it is instead optional. Possibly annoying but not illegal. Screen capture by Gregory Dickinson
Why it feels like dark patterns are everywhere
One reason people might think there are no laws against dark patterns is that they see them so often. But that frequency reflects that the term covers a wide range of conduct, from lawful nagging to outright deception.
It also reflects enforcement limits. Regulators cannot chase every irritating screen on every app and website. They have to prioritize the worst cases. That leaves a lot of borderline conduct in the wild, which makes the whole problem feel bigger and murkier to ordinary users.
So when people ask why there is not a law against dark patterns, the best answer is that there already is, but the law does not prohibit every annoying or high-pressure design. It targets lies, misleading cues and coercive obstacles.
That line can be fuzzy. But the fuzziness is not a mistake. It is what you get when the law tries to separate persuasion from deception in a world full of both.
George Bernard Shaw once remarked that America and Britain are “two countries separated by the same language.”
A long time ago that became a quotable quote. Shaw was born in Dublin in 1856 and died in England in 1950. He was 94.
Although I have visited the USA many times before, I came to live here in Merlin, Oregon, with Jeannie, my gorgeous wife, in 2012. And we love living here.
However, I still think like an Englishman and spell my words in English English.
Read the following. I am sure you will enjoy it.
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Despite all the likes, literallys and dropped g’s, English isn’t decaying before our eyes
While these common gripes point to eccentric speech patterns, they don’t point to grammatical annihilation. English has weathered far worse.
Let’s start with something we can all agree on: Old English, spoken from approximately A.D. 450 to 1100, is pretty unintelligible to us today. Anyone who’s had the pleasure of reading “Beowulf” in high school knows how different English back then used to sound. Word endings did a lot more grammatical work, and verbs followed more complicated patterns. Remnants of those rules fuel lingering debates today, such as when to use “whom” over “who,” and whether the past tense of “sneak” is “snuck” or “sneaked.”
The language went on to experience centuries of tumult: Viking invasions, which introduced Old Norse influence; Anglo-Norman French rule, which shifted the language of the elite to French; and 18th-Century grammarians, who dictated norms with their elocution and grammar guides.
In that time, English has lost almost all of the more complex linguistic trappings it was born with to become the language we know and – at least, sometimes – love today. And as I explain in my new book, “Why We Talk Funny: The Real Story Behind Our Accents,” it was all thanks to the way that language naturally evolves to meet the social needs of its speakers.
From dropping the ‘l’ to dropping the ‘g’
The things we tend to label as “bad” or sloppy English – for instance, the “g” that gets lost from our -ing endings or the deletion of a “t” when we say a word like “innernet” – actually reflect speech habits that are centuries old.
Take, for example, “often.” Originally spoken with the “t,” that pronunciation gradually became less favored around the 15th century, alongside that “l” in “talk” and the “k” in know. Meanwhile, the “s” now stuck on the back of verbs like “does” and “makes” began as a dialectal variant that only became popular in 16th-century London. It gradually replaced “th” whenever third persons were involved, as in “The lady doth protest too much.”
While dropping the “l” in talk may have been initially frowned upon, today it would be strange if you pronounced the letter. And the shift makes sense: It smoothed out some linguistic awkwardness for the sake of efficiency.
If people learned to look at language more like linguists, they might come around to seeing that there is more than one perspective on what good speech consists of.
And yes, that absolutely is a sentence ending with a preposition – something many modern grammar guides discourage, even though the idea only took hold after 18th-century grammarian Robert Lowth intimated it was a less elegant choice based on the model of Latin.
Though Lowth voiced no hard and fast rule against it, many a grammar maven later misconstrued his advice as an admonition. Just like that, a mere suggestion became grammatical law.
The rise of the grammar sticklers
Many of today’s ideas about what constitutes correct English are based on a singular – often mistaken – 19th-century view of the forces that govern our language.
Emulation of upper-crust speech norms became popular among the nouveau riche. With literacy also on the rise, grammarians and elocutionists raced to dictate the terms of “proper” English on and off the page, which led to the rise of usage guides and dictionaries that were eager to sell a certain brand of speech.
Another example of grammarian angst reconfiguring the view of an otherwise perfectly fine form is the droppin’ of the “g.” It became so tied to slovenly speech that it was branded with an apostrophe in the 19th century to make sure no one missed its lackadaisical and nonstandard nature.
Up until the 19th century, however, no one seemed to care whether one pronounced it as “-in” or “-ing.”
In fact, evidence suggests that -ing wasn’t even heard as the correct form. Many elocution guides from the 18th century provide rhyming word pairs like “herring/heron,” “coughing/coffin” and “jerking/jerkin,” which suggest that “-in” may have been the preferred pronunciation of words ending with “-ing.” Even writer and satirist Jonathan Swift – a frequent lobbyist for “proper” English – rhymes “brewing” with “ruin” in his 1731 poem “Verses on the Death of Dr. Swift, D.S.P.D..”
Embrace the change
Language has always shifted and evolved. People often bristle at changes from what they’ve known to what is new. And maybe that’s because this process often begins with speakers that society usually looks less favorably on: the young, the female, the poor, the nonwhite.
But it’s important to remember that being disliked and bad are not the same thing – that today’s speech pariahs are driven by the same linguistic and social needs as the Londoners who started going with “does” instead of “doth” or dropped the “t” in often.
So if you think the speech that comes from your lips is the “correct” version, think again. Thou, like every other English speaker, art literally the product of centuries of linguistic reinvention.
Winter is more than just a season in the western U.S. – it is a savings account to get farms and homes through the long, dry summer ahead. As the snowpack that accumulates in the mountains through winter slowly melts in late spring and summer, it feeds into rivers and reservoirs that keep communities and ecosystems functioning.
The April 1 snowpack measurement has long been the single most important number in western water management, considered a strong proxy for how much water the mountains are holding in reserve.
Across the western United States, temperatures from November through February were among the warmest on record, with many areas 5 to 10 degrees Fahrenheit (2.8 to 5.5 degrees Celsius) above the 20th-century average. March continued to break heat records. At lower elevations, the higher temperatures meant a significant part of the winter’s precipitation fell as rain rather than snow. In some places, snowfall accumulated but melted quickly during warm periods.
The total area of the western U.S. with snow cover was exceptionally low compared with the rest of the 21st century. National Snow and Ice Data Center
As a result, even regions that received near- or above-normal precipitation for the season failed to build substantial snowpack. In the northern Rockies and the mountains of the Pacific Northwest, any above-average snow accumulation was largely confined to the highest elevations, while middle and lower elevations had relatively little snowpack.
This situation is a hallmark of warming winters. As global temperatures rise, the freezing line where precipitation changes from rain to snow moves up the mountains, shrinking the area capable of sustaining a seasonal snowpack.
At the vast majority of the U.S. Natural Resources Conservation Service’s snow measurement stations across the West, the snowpack’s snow-water equivalent on March 30, 2026, was less than 50% of the 1991-2020 median. Natural Resources Conservation Service
The exceptionally warm winter of 2025–26 across much of the western U.S. delivered a powerful preview of what the regional water cycle in a warmer climate may increasingly look like: less snow and a fundamental reshaping of the hydrograph – the chart of how much water flows through streams across the year.
A flattening hydrologic pulse
The consequences of this shift for water supplies are already visible in streamflows.
In multiple river basins in the West, streamflows were above average in winter and early spring, and some locations were approaching record-high levels. Historically, that water would have remained frozen in the snowpack until late spring. Instead, precipitation arriving as rain – along with intermittent midwinter melting events – increased the runoff.
Scientists who study natural water flows, as I do, pay attention to the hydrographs of streamflows in river basins to see when the water flow in mountain streams is strongest and how long that flow is likely to continue into summer.
This hydrograph showing two years of water flows in the St. Mary River near Babb, Mont., reflects the difference between a typical late-spring peak, as 2025 saw, and several midwinter peaks from warm temperatures and rain, as 2026 is seeing. U.S. Geological Survey
In recent years, rising temperatures have led to a redistribution of streamflows throughout the winter and early spring in ways that are fundamentally reshaping the hydrographs of snowmelt-dominated rivers. Rather than a single dominant peak during late spring or early summer, smaller peaks emerge in winter and early spring. At the same time, the traditional snowmelt pulse, relied on to fill reservoirs in late spring, weakens.
In effect, the hydrograph is flattening. The winter of 2025–26 illustrates this phenomenon: Higher early-season streamflows suggest the West will see less runoff later in the year when communities, farms and wildlife need it.
The Colorado River: A system on the edge
Nowhere does the convergence of record warmth, depleted snowpack and altered hydrology carry higher stakes than in the Colorado River Basin. More than 40 million people in seven states plus Mexico and 5.5 million acres of farmland depend on the river’s water, but the river’s flow is no longer meeting demand.
The April-through-July 2026 runoff into Lake Powell – the reservoir behind Glen Canyon Dam and the primary index of the Upper Colorado River Basin’s annual water budget – is currently forecast to rank among the lowest in recent decades. It has been tracking close to the grim years of 2002 and 2021, considered benchmarks of western drought.
Unless spring brings substantial late-season snowfall to the high mountains, 2026 could join those years as a marker of how thin the margin between water supply and demand has become in a river system already under sustained stress from two decades of drought and water overuse.
The low reservoir levels in the basin in 2026 and the low snowpack are adding fears of water shortages just as the seven states that rely on the Colorado River are struggling to reach a new water use agreement.
The changing rhythm of water in the West
The winter of 2025–26 highlights two emerging realities.
First, temperature is increasingly dominating precipitation in determining western water supplies. Even above-normal precipitation cannot compensate for persistent warmth when it falls as rain rather than snow and accelerates snowmelt in the mountains.
Second, the nature of the West’s streamflows is shifting in ways that complicate water management.
Rain-on-snow events can produce flooding in winter, as the Seattle area saw in late December 2025. A low snowpack also means less runoff in summer, which can exacerbate water shortages and raise the wildfire risk as landscapes dry out. Even if a year has normal precipitation, if it falls as rain or there is earlier snowmelt, then evaporation through summer, in a warmer climate, will leave less water in the system.
Snowpack declines, earlier runoff, elevated winter flows and flattened hydrographs are all consistent with long-standing projections for the western United States as global temperatures rise.
What makes the winter of 2025-26 notable is how clearly these signals appeared, even in a year without widespread precipitation deficits.
This shift highlights the need for adaptive reservoir operations – the ability to adjust water storage and release decisions in real time to capture earlier runoff and preserve water for longer dry seasons, while still maintaining space in reservoirs for flood control during wetter winters. For communities across the West, it also reinforces the growing reality that the familiar seasonal rhythm of mountain water is changing.
A pet‑friendly homeless shelter pilot reduced the rate of homelessness among the people it helped in California.
This was an article published on the 16th March by The Conversation. It shows how the homeless shelters benefit from being pet-friendly. It’s sort of obvious but then again not common-sense.
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A pet‑friendly homeless shelter pilot reduced the rate of homelessness among the people it helped in California
A homeless woman in Los Angeles holds her dog after a free veterinary visit in 2024. Mario Tama/Getty Images
California’s Department of Housing and Community Development established this pilot program in 2019. Its goals were straightforward: to make homeless shelters more accommodating to people with pets – mostly dogs – so that people living on the streets don’t have to choose between staying in shelters or abandoning their pets.
The program disbursed US$15.75 million between 2020 and 2024 to 37 organizations across the state. The funding allowed shelters to build kennels or other pet-friendly spaces, provide pet food and supplies, and offer basic veterinary care. It also covered the costs of staffing and maintaining insurance required to operate pet-friendly shelters.
We found that the program helped 4,407 people experiencing homelessness keep their pets while getting support. Many were able to enter shelters, and their animals received needed veterinary care. A total of 886 people ultimately moved into permanent housing with their pets – a higher success rate than the statewide average for homeless people in California.
Theoretically, this funding should have reduced the number of pet owners living on the streets. Yet since 2019, the year the program began, the number of homeless people in Los Angeles with dogs and other pets has increased.
Since 2017, I’ve led the USC research team that produces the annual homeless count estimates for Los Angeles. The U.S. Department of Housing and Urban Development requires this exercise for any city seeking federal funding for homelessness services.
Before the pandemic, we generally found that roughly 1 in 8 people did. We also found that nearly half of homeless pet owners had been turned away from a homeless shelter because it couldn’t accommodate their animal.
Despite programs like California’s Pet Assistance and Support program, my research team has found that the share of people living on the streets of Los Angeles who say they have a pet increased to roughly 1 in 5 by 2025.
Share of homeless people in LA with pets is rising
The percentage of homeless people in Los Angeles with pets rose from 12% in 2017 to 20% in 2024 and 2025, according to an annual census.
Bar chart showing that the percentage of homeless people in Los Angeles with pets has grown since 2017.
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Need for more pet-friendly programs
We still don’t know why the share of homeless people with pets has gotten so much larger.
The Weingart Tower, where some of Los Angeles’ formerly homeless people reside and receive social services, has a small dog park. Grace Hie Yoon/Anadolu via Getty Images
The number of homeless people in Los Angeles has fallen by more than 4% since 2023 to just over 72,000 people in 2025. But based on my research findings, I would expect the number of people living on the city’s streets – with and without pets – to rise over time unless more affordable housing becomes available.
And growth in the homeless population may be hard to avoid without more efforts like California’s Pet Assistance and Support Program – on a larger scale than the pilot we studied.
This past Christmas, I helped my parents choose a water filter. The latest “smart” models all came with a smartphone app that promised to monitor filter life, track water quality and automatically request service. Yet my father, age 75, and mother, 67, were quick to reject them in favor of a nondigital model.
“Every time it updates or I forget how to use it, we’ll have to call you,” my dad said.
As an only child living 8,000 miles (12,875 kilometers) away, I didn’t need convincing. My parents are aging in place and don’t need traditional caregiving – they cook, drive and manage their home just fine. Instead, I provide what I call technology caregiving: helping them with their digital activities of daily living, from online banking to booking theater tickets.
But as the tech industry shifts toward artificial intelligence agents and generative user interfaces – promising to make devices smarter than ever – I am bracing for this invisible workload to become heavier, not lighter. In addition to being a technology caregiver, I’m a computer scientist who studies human-computer interaction.
Technology caregiving
Technology caregiving is the act of helping someone use digital tools. While this isn’t entirely new – people have long helped grandparents program VCRs and connect parents’ desktop computers to the internet – the stakes have changed.
Today, digitization is ubiquitous. Helping with these tools is no longer just occasional unpaid tech support – it is a form of continuous caregiving essential for maintaining independence. For example, even the simple act of clipping coupons has gone digital – marginalizing older adults who are unable to navigate store apps to access these discounts.
People often view older adults as resistant to technology, but recent years – particularly since the COVID-19 pandemic – have shattered that myth. While gaps in internet access and device ownership remain, they are no longer major barriers to technology access.
Today’s seniors are not tech-averse, but constant updates and interface changes make using technology more difficult for them. Jose Luis Raota/Moment via Getty Images
The emerging crisis is not about access, but effective use. Many older adults are now online and willing to use these tools, but they require frequent help from family, friends or communities.
The innovation tax
The problem isn’t just that devices and apps are getting complex; it’s that they are constantly changing. Frequent software updates and shifting interfaces can be frustrating for all users, but they turn familiar tools into foreign concepts for older adults.
This unpredictability is about to accelerate. Take generative user interfaces, which designers can use to dynamically generate an interface in minutes. Pair them with AI agents, and the system can assume the designer’s role, taking independent actions based on how it perceives a user’s intent or need.
If the “Pay Bill” button is in a different place every third time you open a particular app because an AI decided to optimize the interface, you might feel perpetually incompetent if you can’t quickly locate it. While the industry calls this personalization, for an older adult it is a moving target.
This relentless pace of change – even when intended to be helpful – is directly at odds with age-related cognitive changes. And this dynamic is continuing with the new generation of seniors. They may be more eager to adopt new tools than the last, but wanting to use technology is not the same as being able to use it when the rules are constantly changing.
To navigate a brand new or shifting interface, your brain relies on fluid intelligence: the ability to reason, solve novel problems and ignore distractions on the fly. Unlike the knowledge that people accumulate over time, fluid intelligence naturally declines with age.
When an app updates or an AI optimizes a layout, it forces the user to discard their hard-won mental models and start over. For an older adult, this isn’t just a minor inconvenience; it is a taxing job for their working memory.
As an older adult participant in a study my colleagues and I conducted put it:
“I had a computer on my desk in 1980, OK, when nobody else did. So this is not a foreign language, but the changes that are made with little to no explanation and then things that you knew how to do have either changed or disappeared completely, that is the stuff that absolutely drives me, and I will tell you, every other older adult in America nuts.”
Help the helper
I believe that the way forward is to stop treating tech support as an afterthought and start designing for the technology caregiver. Digital literacy training for seniors and encouraging designing technologies for all users are important but not enough; it’s important to build tools that share the burden.
We have never thought of this before but the question is a valid one.
The article, which was presented by The Conversation, raised the question. As you will see the article starts with the sentence “Americans love dogs.” To my mind, it is many more people than Americans who love dogs. Let’s read the article.
It all seems part of what Mark Cushing, a lawyer and lobbyist for veterinary issues, calls “the pet revolution”: the more and more privileged place that pets occupy in American society. In his 2020 book “Pet Nation,” he argues that the internet has caused people to become more lonely, and this has made them focus more intensely on their pets – filling in for human relationships.
I would argue that something different is happening, however, particularly since the COVID-19 lockdown: Loving dogs has become an expression not of loneliness but of how unhappy many Americans are with society and other people.
And I am no different. I live with three dogs, and my love for them has driven me to research the culture of dog ownership in an effort to understand myself and other humans better. By nature, dogs are masters of social life who can communicate beyond the boundaries of their species. But I believe many Americans are expecting their pets to address problems that they cannot fix.
Rescuing shelter animals grew in popularity, and on social media people celebrated being at home with their pets. Dog content on Instagram and Pinterest now commonly includes hashtags like #DogsAreBetterThanPeople and #IPreferDogsToPeople.
One 2025 study found that dog owners tend to rate their pets more highly than their human loved ones in several areas, such as companionship and support. They also experienced fewer negative interactions with their dogs than with the closest people in their lives, including children, romantic partners and relatives.
Today, millennials make up the largest percentage of pet owners. Some cultural commentators argue dogs are especially important for this generation because other traditional markers of stability and adulthood – a mortgage, a child – feel out of reach or simply undesirable. According to the Harris Poll, a marketing research firm, 43% of Americans would prefer a pet to a child.
Amid those pressures, many people turn to the comfort of a pet – but the expectations for what dogs can bring to our lives are becoming increasingly unreasonable.
For some people, dogs are a way to feel loved, to relieve pressures to have kids, to fight the drudgery of their job, to reduce the stress of the rat race and to connect with the outdoors. Some expect pet ownership to improve their physical and mental health.
But expecting that dogs will fill the social and emotional gaps in our lives is actually an obstacle to dogs’ flourishing, and human flourishing as well.
In philosophical terms, we could call this an extractive relationship: Humans are using dogs for their emotional labor, extracting things from them that they cannot get elsewhere or simply no longer wish to. Just like natural resource extraction, extractive relationships eventually become unsustainable.
The late cultural theorist Lauren Berlant argued that the present stage of capitalism creates a dynamic called “slow death,” a cycle in which “life building and the attrition of life are indistinguishable.” Keeping up is so exhausting that, in order to maintain that life, we need to do things that result in our slow degradation: Work becomes drudgery under unsustainable workloads, and the experience of dating suffers under the unhealthy pressure to have a partner.
Similarly, today’s dog culture is leading to unhealthy and unsustainable dynamics. Veterinarians are concerned that the rise of the “fur baby” lifestyle, in which people treat pets like human children, can harm animals, as owners seek unnecessary veterinary care, tests and medications. Pets staying at home alone while owners work suffer from boredom, which can cause chronic psychological distress and health problems. And as the number of pets goes up, many people wind up giving up their animal, overcrowding shelters.
So what should be done? Some philosophers and activists advocate for pet abolition, arguing that treating any animals as property is ethically indefensible.
Perhaps we can reconfigure aspects of home, family and society to be better for dogs and humans alike – more accessible health care and higher-quality food, for example. A world more focused on human thriving would be more focused on pets’ thriving, too. But that would make for a very different America than this one.
I do not recognise the unhealthy culture as mentioned four paragraphs above. But Jeannie and me do understand and believe the alternative: “Some scientists argue that dogs made us human, not the other way around.”
I’ve said it many times before but perhaps some of our newer readers haven’t heard the fact that when I met Jean in 2007 she was looking after twenty-three dogs, and numerous cats, and it was pure magic. In 2008 I went to Mexico, where Jean lived, with Pharaoh. Then in 2010 we came north to Arizona to be married. We had sixteen dogs and seven cats with us.
It might come as a surprise to learn that the brain responds to training in much the same way as our muscles, even though most of us never think about it that way. Clear thinking, focus, creativity and good judgment are built through challenge, when the brain is asked to stretch beyond routine rather than run on autopilot. That slight mental discomfort is often the sign that the brain is actually being trained, a lot like that good workout burn in your muscles.
Think about walking the same loop through a local park every day. At first, your senses are alert. You notice the hills, the trees, the changing light. But after a few loops, your brain checks out. You start planning dinner, replaying emails or running through your to-do list. The walk still feels good, but your brain is no longer being challenged.
Routine feels comfortable, but comfort and familiarity alone do not build new brain connections.
For decades, scientists believed that the brain’s ability to grow and reorganize, called neuroplasticity, was largely limited to childhood. Once the brain matured, its wiring was thought to be largely fixed.
But that idea has been overturned. Decades of research show that adult brains can form new connections and reorganize existing networks, under the right conditions, throughout life.
The takeaway is simple: Repetition keeps the brain running, but novelty pushes the brain to adapt, forcing it to pay attention, learn and problem-solve in new ways. Neuroplasticity thrives when the brain is nudged just beyond its comfort zone.
Tasks that stretch your brain just beyond its comfort zone, such as knitting and crocheting, can improve cognitive abilities over your lifespan – and doing them in a group setting brings an additional bonus for overall health. Dougal Waters/DigitalVision via Getty Images
The reality of neural fatigue
Just like muscles, the brain has limits. It does not get stronger from endless strain. Real growth comes from the right balance of challenge and recovery.
When the brain is pushed for too long without a break – whether that means long work hours, staying locked onto the same task or making nonstop decisions under pressure – performance starts to slip. Focus fades. Mistakes increase. To keep you going, the brain shifts how different regions work together, asking some areas to carry more of the load. But that extra effort can still make the whole network run less smoothly.
Neural fatigue is more than feeling tired. Brain imaging studies show that during prolonged mental work, the networks responsible for attention and decision-making begin to slow down, while regions that promote rest and reward-seeking take over. This shift helps explain why mental exhaustion often comes with stronger cravings for quick rewards, like sugary snacks, comfort foods or mindless scrolling. The result is familiar: slower thinking, more mistakes, irritability and mental fog.
This is where the muscle analogy becomes especially useful. You wouldn’t do squats for six hours straight, because your leg muscles would eventually give out. As they work, they build up byproducts that make each contraction a little less effective until you finally have to stop. Your brain behaves in a similar way.
Likewise, in the brain, when the same cognitive circuits are overused, chemical signals build up, communication slows and learning stalls.
Overdoing any task, whether it be weight training or sitting at the computer for too long, can overtax the muscles as well as the brain. Halfpoint Images/Moment via Getty Images
Sleep is the brain’s night shift. While you rest, the brain takes out the trash through a special cleanup system called the glymphatic system that clears away waste and harmful proteins. Sleep also restores glycogen, a critical fuel source for brain cells.
During REM sleep, the stage of sleep linked to dreaming, the brain replays patterns from the day to consolidate memories. This process is critical not only for cognitive skills like learning an instrument but also for physical skills like mastering a move in sports.
The most important lesson from this science is simple. Your brain is not passively wearing down with age. It is constantly remodeling itself in response to how you use it. Every new challenge and skill you try, every real break, every good night of sleep sends a signal that growth is still expected.
You do not need expensive brain training programs or radical lifestyle changes. Small, consistent habits matter more. Try something unfamiliar. Vary your routines. Take breaks before exhaustion sets in. Move your body. Treat sleep as nonnegotiable.
So the next time you lace up your shoes for a familiar walk, consider taking a different path. The scenery may change only slightly, but your brain will notice. That small detour is often all it takes to turn routine into training.
The brain stays adaptable throughout life. Cognitive resilience is not fixed at birth or locked in early adulthood. It is something you can shape.
If you want a sharper, more creative, more resilient brain, you do not need to wait for a breakthrough drug or a perfect moment. You can start now, with choices that tell your brain that growth is still the plan.
That last section of the article is most powerful. I’m speaking of the section that is headed Train, recover, repeat.
The human brain notices when even small changes to our normal routine occur. Also that exercise strengthens the brain plus our brains stay adaptable throughout our lives. Amazing!
The science of looking at other worlds is amazing.
With so much going wrong, primarily politically, in the world, I just love turning to news about distant places; and by distant I mean hugely so. That is why I am republishing this item from The Conversation about other stars.
ooOOoo
NASA’s Pandora telescope will study stars in detail to learn about the exoplanets orbiting them
Exoplanets are worlds that orbit other stars. They are very difficult to observe because – seen from Earth – they appear as extremely faint dots right next to their host stars, which are millions to billions of times brighter and drown out the light reflected by the planets. The Pandora telescope will join and complement NASA’s James Webb Space Telescope in studying these faraway planets and the stars they orbit.
I am an astronomy professor at the University of Arizona who specializes in studies of planets around other stars and astrobiology. I am a co-investigator of Pandora and leading its exoplanet science working group. We built Pandora to shatter a barrier – to understand and remove a source of noise in the data – that limits our ability to study small exoplanets in detail and search for life on them.
Observing exoplanets
Astronomers have a trick to study exoplanet atmospheres. By observing the planets as they orbit in front of their host stars, we can study starlight that filters through their atmospheres.
These planetary transit observations are similar to holding a glass of red wine up to a candle: The light filtering through will show fine details that reveal the quality of the wine. By analyzing starlight filtered through the planets’ atmospheres, astronomers can find evidence for water vapor, hydrogen, clouds and even search for evidence of life. Researchers improved transit observations in 2002, opening an exciting window to new worlds.
When a planet passes in front of its star, astronomers can measure the dip in brightness, and see how the light filtering through the planet’s atmosphere changes.
For a while, it seemed to work perfectly. But, starting from 2007, astronomers noted that starspots – cooler, active regions on the stars – may disturb the transit measurements.
In 2018 and 2019, then-Ph.D. student Benjamin V. Rackham, astrophysicist Mark Giampapa and I published a series of studies showing how darker starspots and brighter, magnetically active stellar regions can seriously mislead exoplanets measurements. We dubbed this problem “the transit light source effect.”
Most stars are spotted, active and change continuously. Ben, Mark and I showed that these changes alter the signals from exoplanets. To make things worse, some stars also have water vapor in their upper layers – often more prominent in starspots than outside of them. That and other gases can confuse astronomers, who may think that they found water vapor in the planet.
In our papers – published three years before the 2021 launch of the James Webb Space Telescope – we predicted that the Webb cannot reach its full potential. We sounded the alarm bell. Astronomers realized that we were trying to judge our wine in light of flickering, unstable candles.
The birth of Pandora
For me, Pandora began with an intriguing email from NASA in 2018. Two prominent scientists from NASA’s Goddard Space Flight Center, Elisa Quintana and Tom Barclay, asked to chat. They had an unusual plan: They wanted to build a space telescope very quickly to help tackle stellar contamination – in time to assist Webb. This was an exciting idea, but also very challenging. Space telescopes are very complex, and not something that you would normally want to put together in a rush.
Pandora breaks with NASA’s conventional model. We proposed and built Pandora faster and at a significantly lower cost than is typical for NASA missions. Our approach meant keeping the mission simple and accepting somewhat higher risks.
What makes Pandora special?
Pandora is smaller and cannot collect as much light as its bigger brother Webb. But Pandora will do what Webb cannot: It will be able to patiently observe stars to understand how their complex atmospheres change.
By staring at a star for 24 hours with visible and infrared cameras, it will measure subtle changes in the star’s brightness and colors. When active regions in the star rotate in and out of view, and starspots form, evolve and dissipate, Pandora will record them. While Webb very rarely returns to the same planet in the same instrument configuration and almost never monitors their host stars, Pandora will revisit its target stars 10 times over a year, spending over 200 hours on each of them. https://www.youtube.com/embed/Inxe5Bgarj0?wmode=transparent&start=0 NASA’s Pandora mission will revolutionize the study of exoplanet atmospheres.
With that information, our Pandora team will be able to figure out how the changes in the stars affect the observed planetary transits. Like Webb, Pandora will observe the planetary transit events, too. By combining data from Pandora and Webb, our team will be able to understand what exoplanet atmospheres are made of in more detail than ever before.
After the successful launch, Pandora is now circling Earth about every 90 minutes. Pandora’s systems and functions are now being tested thoroughly by Blue Canyon Technologies, Pandora’s primary builder.
About a week after launch, control of the spacecraft will transition to the University of Arizona’sMulti-Mission Operation Center in Tucson, Arizona. Then the work of our science teams begins in earnest and we will begin capturing starlight filtered through the atmospheres of other worlds – and see them with a new, steady eye.
Over the course of 2025, deepfakes improved dramatically. AI-generated faces, voices and full-body performances that mimic real people increased in quality far beyond what even many experts expected would be the case just a few years ago. They were also increasingly used to deceive people.
For many everyday scenarios — especially low-resolution video calls and media shared on social media platforms — their realism is now high enough to reliably fool nonexpert viewers. In practical terms, synthetic media have become indistinguishable from authentic recordings for ordinary people and, in some cases, even for institutions.
And this surge is not limited to quality. The volume of deepfakes has grown explosively: Cybersecurity firm DeepStrike estimates an increase from roughly 500,000 online deepfakes in 2023 to about 8 million in 2025, with annual growth nearing 900%.
I’m a computer scientist who researches deepfakes and other synthetic media. From my vantage point, I see that the situation is likely to get worse in 2026 as deepfakes become synthetic performers capable of reacting to people in real time.
Dramatic improvements
Several technical shifts underlie this dramatic escalation. First, video realism made a significant leap thanks to video generation models designed specifically to maintain temporal consistency. These models produce videos that have coherent motion, consistent identities of the people portrayed, and content that makes sense from one frame to the next. The models disentangle the information related to representing a person’s identity from the information about motion so that the same motion can be mapped to different identities, or the same identity can have multiple types of motions.
These models produce stable, coherent faces without the flicker, warping or structural distortions around the eyes and jawline that once served as reliable forensic evidence of deepfakes.
Second, voice cloning has crossed what I would call the “indistinguishable threshold.” A few seconds of audio now suffice to generate a convincing clone – complete with natural intonation, rhythm, emphasis, emotion, pauses and breathing noise. This capability is already fueling large-scale fraud. Some major retailers report receiving over 1,000 AI-generated scam calls per day. The perceptual tells that once gave away synthetic voices have largely disappeared.
Third, consumer tools have pushed the technical barrier almost to zero. Upgrades from OpenAI’s Sora 2 and Google’s Veo 3 and a wave of startups mean that anyone can describe an idea, let a large language model such as OpenAI’s ChatGPT or Google’s Gemini draft a script, and generate polished audio-visual media in minutes. AI agents can automate the entire process. The capacity to generate coherent, storyline-driven deepfakes at a large scale has effectively been democratized.
This combination of surging quantity and personas that are nearly indistinguishable from real humans creates serious challenges for detecting deepfakes, especially in a media environment where people’s attention is fragmented and content moves faster than it can be verified. There has already been real-world harm – from misinformation to targeted harassment and financial scams – enabled by deepfakes that spread before people have a chance to realize what’s happening. https://www.youtube.com/embed/syNN38cu3Vw?wmode=transparent&start=0 AI researcher Hany Farid explains how deepfakes work and how good they’re getting.
The future is real time
Looking forward, the trajectory for next year is clear: Deepfakes are moving toward real-time synthesis that can produce videos that closely resemble the nuances of a human’s appearance, making it easier for them to evade detection systems. The frontier is shifting from static visual realism to temporal and behavioral coherence: models that generate live or near-live content rather than pre-rendered clips.
Identity modeling is converging into unified systems that capture not just how a person looks, but how they move, sound and speak across contexts. The result goes beyond “this resembles person X,” to “this behaves like person X over time.” I expect entire video-call participants to be synthesized in real time; interactive AI-driven actors whose faces, voices and mannerisms adapt instantly to a prompt; and scammers deploying responsive avatars rather than fixed videos.
As these capabilities mature, the perceptual gap between synthetic and authentic human media will continue to narrow. The meaningful line of defense will shift away from human judgment. Instead, it will depend on infrastructure-level protections. These include secure provenance such as media signed cryptographically, and AI content tools that use the Coalition for Content Provenance and Authenticity specifications. It will also depend on multimodal forensic tools such as my lab’s Deepfake-o-Meter.
Simply looking harder at pixels will no longer be adequate.
Learning from Dogs 