Founded in 1884, the Bureau of Labor Statistics publishes monthly and annual data about American consumers and workers. Historically, the BLS has focused on urban workers and consumers, while the Department of Agriculture covered farmers and agricultural work. But these days, the Bureau of Labor Statistics also collects some data reflecting rural areas too.
These official statistics are often revised in the months that follow as the bureau adopts new methods or more data becomes available.
A recruiter speaks with potential hires at a job fair in Florida in April 2025. Later, that change in employment status could register in the data that the Bureau of Labor Statistics tracks throughout the United States. Joe Raedle/Getty Images
How can data affect markets and the economy?
The bureau’s data on inflation, employment, unemployment and compensation draws the most attention because it answers basic questions about the economy.
For example: Are prices rising? Are employers adding new jobs? Are people finding work? How much are workers getting paid?
Employment and unemployment may seem very similar, but they show you different things. BLS employment data tells you how many jobs there are, where they are and in what lines of work.
BLS unemployment data is about people. How many Americans are looking for work but can’t find a job? How many have part-time jobs but would prefer to work full time?
The BLS also collects, analyzes and releases inflation data that shows how price changes are affecting American consumers. The BLS consumer price index data is weighted so that changes in the prices of items that are a big part of household expenses will have a larger effect on the final results than other changes.
Each BLS statistic has a narrow focus, but, taken together, they can reveal a lot about economic conditions across the country and in specific states.
If job creation starts to slow, the country might be heading toward a recession, and employers might pull back on hiring and production or invest less in new equipment. Policymakers use BLS statistics to guide decisions about government actions, and everyone else may use them to judge whether politicians have succeeded in managing the economy well.
Of course, all of these uses depend on Americans being able to trust the numbers. The BLS goes to great lengths to secure that trust, publishing detailed descriptions of its methods and research papers that try to explain patterns in the data and test new approaches. Until recently, the BLS also had two unpaid advisory committees of economists and statisticians from companies, universities and nonprofits that analyzed BLS methods and offered advice.
However, the Department of Labor disbanded those committees in March 2025, stating that the committees “had fulfilled their intended purpose.”
Even in the early 1970s, the BLS employed artists whose job it was to make charts to clearly convey the data it collected. Library of Congress
What does the BLS commissioner do?
The BLS commissioner oversees all aspects of the bureau’s operations and serves as the primary liaison with Congress and the leadership of the Department of Labor.
Although some early BLS commissioners did not have advanced degrees, all commissioners since the 1930s have had Ph.D.s in economics or statistics, as well as substantial experience using or producing statistical data.
Unlike rank-and-file BLS staff, who are typically career civil servants, the commissioner is appointed by the president and confirmed by the Senate for a four-year term. Due to the timing of those terms, each commissioner’s tenure normally spans two presidential terms. The Senate overwhelmingly approved McEntarfer’s nomination, for example, in an 86-8 vote held in January 2024.
However, this appointment is at will, meaning that a president can legally remove a commissioner at any time.
The data is produced collectively by a large nonpartisan staff who are protected by civil service regulations, so it would be impossible for the commissioner simply to change the numbers.
Nonetheless, the commissioner could shape BLS data indirectly. The commissioner could make certain data harder to access, devote fewer resources to some topics or close some data series altogether.
More significantly, creating national statistics is complicated: There is always uncertainty, and even experts will disagree on many issues. A sufficiently motivated commissioner could potentially nudge the data in favored directions simply by altering the methodology.
If BLS staff thought a commissioner was truly trying to manipulate the statistics, however, I would expect many of them would resign or protest publicly. And there’s no sign of that having happened under McEntarfer’s leadership. She has strong support from former BLS commissioners and leading economists.
What are some possible consequences?
I do not expect to see any immediate consequences from McEntarfer’s firing.
The acting commissioner of the BLS, William Wiatrowski, is a longtime BLS employee who has held this role before.
The rest of the bureau’s staff remain the same. Over the long term, the actions of whomever Trump appoints as McEntarfer’s permanent replacement will determine whether her firing was an aberration or the mark of a new relationship between the White House and the BLS that could eventually undercut trust in its statistics.
To strengthen confidence in the BLS, the new commissioner could reinstate the external advisory committees that the Trump administration has disbanded. But he or she could weaken confidence by making controversial changes, especially regarding employment statistics, that are criticized by leading professional organizations or that cause top BLS officials to quit their jobs.
I believe it’s unlikely that BLS statistics could be faked in ways that would deceive economists. But they could become much less useful, and that would be bad for the United States.
Thomas A. Stapleford 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.
Source: The Conversation – USA (2) – By Michael G. Kozak, Associate Clinical Professor of Educational Administration and Leadership, Drexel University
Artificial intelligence can bring a host of benefits, such as individualized learning, but can also encourage kids to shortcut learning. Jonathan Kirn via Getty Images
Generative AI platforms have sent shock waves through the K-12 education sector since the public release of ChatGPT nearly three years ago.
The technology is taking hold under the belief that students and teachers need to be proficient in these powerful tools, even though many concerns remain around equity, privacy, bias and degradation of critical thinking among students.
As a professor who teaches future educators and is part of an AI-focused working group, I have observed the potential for artificial intelligence to transform teaching and learning practices in K-12 schools. The trends I am seeing – and that I encourage – are for K-12 educators to use AI to shift from memorization and rote learning to instead emphasize critical thinking and creativity.
Students, on the other hand, tended to jump into the deep end of the AI pool. Common Sense Media, which offers recommendations on children’s media consumption, published a report in 2024 showing that students were using AI-supported search and chatbots for homework and to stave off boredom as well as other personal reasons, including “creating content as a joke, planning activities, and seeking health advice.” Most of the teachers and parents of the students in the study were unaware that students were using the technology.
In my work at Drexel University teaching graduate students who are aspiring school principals or superintendents, I found that in 2023, K-12 students were afraid of using AI due to the policies implemented in their districts banning it. However, it quickly became apparent that students were able to mask their use of AI by instructing AI to insert some mistakes to their assignments.
Meanwhile, despite teachers’ initial concerns about AI, approximately 60% of K-12 teachers now admit to using AI to plan lessons, communicate with parents and assist with grading. Concerns over students cheating still exist, but time-strapped teachers are finding that using AI can save them time while improving their teaching.
A recent Walton Foundation and Gallup study revealed that teachers who used AI tools weekly saved an average of 5.9 hours per week, which they reallocated to “providing students more nuanced feedback, creating individualized lessons, writing emails and getting home to their families in a more reasonable time.”
Opening up new ways of teaching
I recommend that my graduate students use AI because I think ignoring emerging trends in education is not wise. I believe the benefits outweigh the negatives if students are taught ethical use of the technology and guardrails are put in place, such as requiring that AI be cited as a source if students use it in coursework.
Advocates say AI is changing teaching for the better, since it forces teachers to identify additional ways for students to demonstrate their understanding of content. Some strategies for students who rely too heavily on AI include oral presentations, project-based learning and building portfolios of a student’s best work.
One practice could involve students showing evidence of something they created, implemented or developed to address a challenge. Evidence could include constructing a small bridge to demonstrate how forces act on structures, pictures or a video of students using a water sampling device to check for pollution, or students designing and planting a community garden. AI might produce the steps needed to construct the project, but students would actually have to do the work.
Teachers can also use AI to create lessons tailored to students’ interests, quickly translate text to multiple languages, and recognize speech for students with hearing difficulties. AI can be used as a tutor to individualize instruction, provide immediate feedback and identify gaps in students’ learning.
When I was a school superintendent, I always asked applicants for teaching positions how they connected their classroom lessons to the real world. Most of them struggled to come up with concrete examples. On the other hand, I have found AI is helpful in this regard, providing answers to students’ perennial question of why they need to learn what is being taught.
Thought partner
Teachers in K-12 schools are using AI to help students develop their empathetic skills. One example is prompting an AI to “redesign the first-day experience for a relocated student entering a new middle school.” AI created the action steps and the essential questions necessary for refining students’ initial solutions.
In my own classroom, I’ve used AI to boost my graduate students’ critical thinking skills. I had my students imagine that they were college presidents facing the loss of essential federal funding unless they implemented policies limiting public criticism of federal agencies on campus. This proposed restriction, framed as a requirement to maintain “institutional neutrality,” requires students to develop a plan of action based on their knowledge of systems and design thinking. After each team developed their solution, I used AI to create questions and counterpoints to their proposed solution. In this way, AI becomes a critical thought partner to probe intended and unintended outcomes, gaps in students’ thinking and potential solutions that might have been overlooked.
AI researcher Ethan Mollick encourages educators to use AI as a springboard, similar to jazz musicians improvising, as a way to unleash new possibilities. Mollick advises people to partner with AI as co-intelligence, be the human in the loop, treat AI as a co-worker, albeit one that needs to be prodded for evidence, and to learn to use it well. I concur.
I think that further studies are needed, but I have found in my own work and in the work of my graduate students that AI can enhance human-produced work. For example, AI-powered teaching assistants, like Khanmigo or Beghetto Bots, use AI to help students solve problems and come up with innovative solutions without giving away the answers.
My experiences with other educators on the front lines show me that they are beginning to change their perspectives toward students using AI, particularly as teachers realize the benefit of AI in their own work. For example, one of my graduate students said his district is employing a committee of educators, students and outside experts to explore how AI can be used ethically and in a way that won’t erode students’ critical thinking skills.
Educators are starting to realize that AI isn’t going away anytime soon – and that it’s better to teach their students how to use it, rather than leave them to their own devices.
Michael G. Kozak 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.
If you walk the harbour in Hastings in south-east England or the beach further north in Cromer at dawn, you’ll see the signs of a centuries-old way of life: small boats landing their fresh catch and crews unloading crates of crab, lobster or bass.
But there are fewer boats than a generation ago, fewer working fishers, and fewer incentives for young people to enter the industry. What was once the beating heart of a coastal community is at risk of becoming a memory in many areas.
Inshore and small-scale fishing boats are those vessels that fish predominantly within 6 nautical miles of the coastline and are usually under 10 metres in length. They make up nearly 80% of the UK fishing fleet. Since they operate close to shore, these boats supply local markets and often land directly onto beaches and into small harbours. Inshore fisheries don’t just catch fish, they sustain local economies, cultures and ways of life – but they are disappearing.
Research conducted by ourselves and colleagues confirms that the entire fleet is in decline across the UK. However, this decline is being unevenly felt around the country.
In England alone, between 2008 and 2022, 495 active fishing vessels were lost, equivalent to 20% of the total. Smaller boats were hit hardest: vessels less than 10 metres long declined by 22% – nearly double the 13% fall in larger boats.
These losses are even more severe when fishing activity is taken into account. Days at sea for the under-10 metre fleet fell by 44%, and employment dropped by nearly half (47%).
These numbers don’t just reflect a shrinking fleet. Smaller vessels are less able to fish further afield in response to changing fish stocks, bad weather or increasing pressure from other sea users. This suggests that inshore and small-scale fishing families bear a disproportionate share of the challenges faced across the entire fleet.
And once the last boat has gone from a harbour, with all the knowledge of where and how to fish, it is a way of life that could be lost forever.
Why are we losing boats?
The reasons for the decline are complex and shaped by local contexts. Competition for space, restricted access to fishing grounds, insufficient quotas to target diverse fish stocks, limited access to markets, an ageing workforce – all of these things contribute. But there is a deeper problem: a policy framework that prioritises fish stocks and economic yield over people and places.
Too often, fisheries policy in the UK and internationally has focused on sustainability as predominantly a biological problem. Are fish stocks recovering? Are total catch levels within safe limits? These are important questions, but they miss half the story.
A fishery is not just an ecosystem, it’s a community. The people who fish, mend nets, manage harbours and sell seafood are integral to the sustainability of coastal life. Without them, we lose not just jobs but a whole chain of economic and social support. Fish processors, boat builders, local shops and, in more rural or island locations, even the basic viability of essential services like schools and healthcare can depend on the continued presence of fishing families.
While small-scale fisheries may be marginal from the perspective of national GDP, fewer boats often means fewer families – and the erosion of a community which makes a seaside town more than just a tourist backdrop. As fishing fades, so too does a sense of local character and identity: elements that distinguish these towns and connect them to their maritime heritage.
What would it take to stem the loss?
A number of solutions are frequently discussed, including quota systems designed to meet community needs, improved harbour facilities for small boats, more visible training opportunities and clearer pathways for young people to enter fishing.
Inshore and small-scale fishers also need to have their voices heard, and to trust their experiences and insight will help shape the future of coastal communities. But lasting change also requires a shift in mindset: to see fishing not just as a source of seafood but as part of a sustainable future for coastal Britain.
The UK government has an important role to play in recognising and addressing the challenges faced by smaller vessels. This aligns with international commitments the UK has already made to support small-scale fisheries, which call for the fair distribution of marine resources and protection of cultural heritage.
But it is not just policymakers who can make a difference. Buying locally landed fish, supporting fishing festivals, learning about local seafood and simply chatting to fishers on the beach or at the harbour – these small acts all help show that people value this work and want it to continue.
The small fishing boats still seen bobbing in UK harbours are more than working vessels – they are signs of a living culture. For those willing to learn the trade, fishing offers a viable independent livelihood and a strong connection to community and the sea.
If we want our coastal communities to thrive, not just survive, action is required before the last boats leave the shore for good.
Sarah Coulthard receives funding from the Esmee Fairbairn Foundation.
Ainsley Hatt and Phoebe Lewis do not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and have disclosed no relevant affiliations beyond their academic appointment.
Source: The Conversation – UK – By Seamus Higgins, Associate Professor Food Process Engineering, Chemical & Environmental Engineering, University of Nottingham
Baby food pouches came under scrutiny earlier this year, following a report from the University of Leeds and consumer group Which?.
The findings were troubling. Many pouches are high in sugar, nutritionally inadequate, and potentially harmful if consumed regularly. The report also warns that parents are being misled by so-called “halo” marketing claims – labels like “nutritionally balanced,” “no added sugar” and “organic” – which often obscure poor nutritional profiles.
This isn’t the first time these products have raised concerns. A 2023 study published in BMJ analysed 276 baby food pouches from 15 major manufacturers. It concluded that many were “nutritionally poor, high in sugars, and not fortified with iron”. In 2025, a BBC Panorama investigation found that pouches from six leading UK brands failed to meet essential nutritional standards for infant feeding.
The preservation of food by way of heat treatment dates back to the early 19th century, when Frenchman Nicolas Appert developed heat-based methods to extend shelf life for Napoleon’s army rations. Fast-forward to the 1970s, and the US Army developed the first retort pouch: a flexible, heat-resistant food package made from layers of plastic and metal foil, designed to be sterilised under high heat and pressure.
The retort process kills harmful bacteria and allows food to be stored safely at room temperature for up to 18 months, without the need for refrigeration or preservatives. Originally intended for military rations, this packaging method would later revolutionise the baby food industry.
It’s easy to understand their appeal. These pouches offer ultimate convenience for busy parents: no prep, no refrigeration, no cleanup. Many are designed with built-in spouts, allowing infants to self-feed by sucking directly from the pouch: no spoon or bowl required.
Pouch problems
The trouble lies in how these foods are made. To achieve long shelf life manufacturers subject the pouches to high heat and pressure. To mask any off-tastes caused by this intense processing, they often use fruit concentrates: ingredients high in sugar that appeal to babies and make the product more palatable.
Consider milk as an example. Fresh milk pasteurised at 71°C for 15 seconds tastes natural and requires refrigeration, with a shelf life of about a week. But process that same milk at 130°C–150°C, and it becomes UHT (ultra high temperature) milk – shelf-stable for up to six months, but with a markedly different taste. Process it further in a retort system, and it can last up to 18 months – but at the cost of flavour and nutritional integrity. Now apply the same logic to baby food.
But these pouches don’t just fall short nutritionally – they may also interfere with vital developmental stages.
When infants feed directly from spouts, they miss out on practising essential oral motor skills like chewing, swallowing and tongue lateralisation: the ability to move the tongue from side to side. This movement is crucial for shifting food around the mouth and preparing it for safe swallowing.
Without opportunities to develop these skills, children may struggle to transition to solid foods, increasing the risk of fussy eating and feeding disorders later in childhood.
International child feeding recommendations – from the UK, EU and World Health Organization – all advocate breastfeeding for the first six months where possible, followed by the gradual introduction of safe, nutrient-dense, age-appropriate foods.
These guidelines consistently recommend limiting added sugars and encouraging a variety of tastes, textures and colours to promote long-term acceptance of healthy foods.
But the food industry doesn’t always follow this advice.
Mum’s milk v the market
The global baby food market was worth over US$88 billion (£65 billion) in 2022 and is projected to grow more than 6% annually until 2032. With profits and market share on the line, it’s no surprise that manufacturers prioritise shelf stability and scalability over optimal nutrition.
So how do these pouches compare to breast milk?
Breast milk is a living, dynamic fluid. Its composition changes throughout the day and based on the mother’s diet, helping expose babies to a range of flavours early in life. It contains fat, protein, carbohydrates (mainly lactose), vitamins, minerals and over 200 complex sugars that support gut and immune system development. These sugars are believed to play a crucial role in shaping a baby’s microbiome.
By contrast, baby food pouches processed under high heat and pressure lose many of the original nutrients and flavours found in whole, fresh ingredients, particularly in sterilised, long-life versions.
HPP works by applying intense pressure to destroy harmful bacteria while retaining flavour, texture and nutrients. PEF uses short bursts of electricity to break down microbial cells, gently preserving food without cooking it.
Cold plasma, meanwhile, relies on ionised gas to inactivate pathogens on food surfaces, making it particularly effective for packaging and delicate ingredients. These innovative methods extend shelf life and ensure food safety, all without compromising the quality of the food itself.
This is a pivotal moment for reflection and action. As the science evolves, so too should our policies. By aligning regulation more closely with expert recommendations, we can help ensure that baby food products support the health and development of the children who rely on them.
After all, what we feed our youngest citizens shouldn’t just fill their bellies – it should nurture their growth, development and long-term wellbeing.
Seamus Higgins does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
Source: The Conversation – UK – By Kerry Brown, Professor of Chinese Politics; Director, Lau China Institute, King’s College London
Taiwan has often compared itself to being a “shrimp between two whales”. That expression has never been more apt than today with the US and China – which considers Taiwan to be part of its territory – locked in a standoff over the future of the island.
At an event I attended some years ago, a Chinese scholar remarked when the issue of the US-China rivalry came up that they believed there was an African saying: “When two elephants are either having a fight, or making love, the grass around them gets trampled.”
It was best for everyone, they advised the other attendees, for the two superpowers to have a workmanlike, unexciting relationship rather than take the risk of things getting too friendly or hostile.
But whether or not the current period of conflict continues or the US and China magically become more aligned, the challenges facing Taiwan are severe.
First off, Taiwan is itself in a period of domestic turbulence. The government of Taiwanese president William Lai Ching-te, leader of the Democratic Progressive party, was elected in January 2024 with a little over 40% of the vote. This was considerably less than his predecessor from the same party, Tsai Ing-wen.
One of the main opposition leaders, Ke Wen-je of the Taiwan People’s party, has since then been arrested on corruption charges. He is accused of accepting half a million US dollars in bribes during his term as mayor of Taipei as well as misreporting campaign finances during his presidential run.
Most recently, in late July, recall votes were held where citizens in 24 districts of Taiwan chose whether or not to remove their legislator from office. This is the result of a law in Taiwan stipulating a new vote if 10% of the electorate in a specific constituency express dissatisfaction at the previous outcome. Activists supporting the government mobilised to achieve this.
The votes seem to be associated with frustration that, while the Democratic Progressive party controls the presidency, it cannot get legislation through a parliament dominated by its opponents. All of the votes were directed at seats held by the Kuomintang, the main opposition party in recent years that is accused by its critics of being pro-China. Not a single seat was overturned.
When the steady nationalism of Xi Jinping’s leadership in Beijing is factored in, with its conviction that the global influence of the west is slowly declining and the east – dominated by China – is in the nascent, one can see why the issue of Taiwan might look more precarious and worrying. This is regardless of the various predictions that 2027 is the date that China has set to go for reunification.
Ambiguous US position
For the US, President Donald Trump’s fixation has remained on correcting what he sees as China’s unfair trade advantages with its largest single economic partner – something he has long talked about.
The White House proclaimed in March, when the first set of trade negotiations with China concluded after tariffs were imposed by both sides, that: “for too long, unfair trade practices and America’s massive trade deficit with China have fuelled the offshoring of American jobs and the decline of our manufacturing sector.”
The aim at the most recent set of talks in Stockholm, Sweden, in late July was to drive towards a new deal. Trump has also reportedly talked of taking a huge delegation of business people to China at some point later in 2025. This is despite the fact that so far since his inauguration in January, and despite many reasons to talk, Xi and Trump have yet to physically meet.
Taiwanese people are therefore right to feel increasingly uneasy. Under Trump’s predecessor, Joe Biden, they received verbal commitments that the US would come to Taiwan’s aid if it was attacked. This was not formal US policy, which has long maintained an ambiguous stance on Taiwan.
Ambiguity has returned with a vengeance under Trump. His secretary of defence, Pete Hegseth, has said that the US stands by Taiwan. But these days in Washington all roads lead to the Oval Office, and Trump’s stance is far harder to predict.
If China were to dangle a trade deal in front of the US president – committing to buy more US goods, put in more investment that is non-problematic on security grounds in the US and generally abide by American demands – would Trump be able to resist?
It could be presented as a historic achievement, a new concordant between the world’s two greatest powers who had seemed until then set on conflict and clash. There might even be the much desired Nobel Peace Prize in it for the US leader.
Trump, for his part, appears increasingly reluctant to back Taiwan in ways that risk provoking Beijing. Lai delayed a trip to Latin America in July after the Trump administration reportedly told him to cancel a proposed stopover in New York. And the US cancelled a meeting with Taiwan’s defence minister one month earlier.
The likelihood remains that, if a real crisis occurs, then the US will climb down from the middle wall and do something to defend Taiwan. Any trade deal between Beijing and Washington will also probably be a highly circumscribed one. China is not an easy partner to negotiate with, and it is unlikely to offer Trump the kind of capitulation he is seeking.
Even so, these are very unpredictable times. The key calculation going forward will be the simple one of what the US gains and loses from all its relationships – and that includes Taiwan.
Kerry Brown does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
In the 2024 UK general election, Reform came third with a 14% share of the vote, capturing five seats in the House of Commons. This was a breakthrough election for the party. In the previous general election in 2019, when it was known as the Brexit party, it won a 2% vote share and captured no parliamentary seats at all.
This success is part of a trend. Radical right-wing populist parties are making gains in elections across many democracies and, in plenty of cases, they’re winning power. Giorgia Meloni’s Brothers of Italy has been in government in Italy since the election of September 2022, when they took 26% of the vote and captured 119 seats in the national parliament.
In the National Assembly elections of June 2024, Marine Le Pen’s National Rally increased its representation from 89 seats to 125 seats. And in the Netherlands, the Freedom Party (PVV), led by right-wing populist Geert Wilders won the largest vote share in 2023 with 24%, capturing 37 seats in the House of Representatives.
Perhaps most significantly, Donald Trump won the US presidential election in November 2024 with a rightwing populist agenda – a victory that has created turmoil in American politics and the economy, along with the rest of the world.
Expert views
The American political scientist, Larry Bartels, argued in a recent book that democracy erodes from the top. He explains that contemporary democracies die not by military coups or revolutionary overthrows but by populist leaders winning elections and then subverting the institutions of democracy from within. Once in power, they restrict the freedom of the courts, squeeze the fairness out of elections and attack the press.
The Chapel Hill expert surveys, a database that classifies political parties into ideological groupings, helps illustrate the stakes at play here.
The 2024 survey data covers 31 countries and it was administered in all the European Union member states plus a few others including Britain, Norway and Turkey. It shows that there are more radical right-wing parties than any other kind of party in these countries and they are growing in number and in support.
The 2024 data was compiled by 609 political scientists, who looked at party ideologies, their policy preferences, electoral performances and the extent to which they participate in government. There are 279 parties in the database altogether and so they are classified into “party families” to make the analysis manageable.
A party family is a grouping of parties which the experts think are similar to each other, even though there may be some differences between them. For example, the Alternative for Germany (AfD), the National Rally (RN) in France, the Party for Freedom (VVD) in the Netherlands, the Freedom Party in Austria (FPO) and Reform in Britain are all classified as right-wing populist parties in the dataset. The chart shows the extent to which these 11 party families have been successful in winning votes in the most recent elections.
The Performance of Party Families in 31 Countries in 2024:
The radical right family consisted of 48 parties, and on average they won 11% of the votes and 17% of seats in the various national legislatures. They are growing in support and influence, coming fourth after the conservative, socialist and Christian democrat party families in voting support and representation in parliaments.
The threat to democracy
We can get some idea of how likely such parties are to undermine democracy by looking at responses to a question in the Chapel Hill survey. This asked the experts to judge the extent to which parties think power should or should not be concentrated in the executive. It is measured on a ten-point scale where zero means that the party is strongly in favour of constraining the power of the executive, whereas ten means that a party opposes any restrictions on executive powers.
The chart shows the average scores for each of the party families on this executive power scale. It is readily apparent that the radical right parties are significant outliers on the scale, being very much more likely to support executive dominance than the other party families.
Scores on the Executive Power Scale
The survey showed that parties of the right such as the Conservatives, Agrarian and Religious parties are rather more likely to support executive dominance than parties of the centre or left. But the radical right parties stand out as really strongly supporting this. This is in sharp contrast to radical left parties, which are quite suspicious of such executive dominance.
This is important since it shows that once in power these parties are tempted to subvert the separation of powers between the executive, the legislature and the judiciary. This is likely to be accompanied by attacks on an independent media, the use of the courts against opponents and attempts to gerrymander elections.
All this comes from the belief that a strong leader is the best form of government, a sentiment shared by many Trump supporters in the United States. Anne Applebaum’s recent book Twilight of Democracy illustrates this dynamic in the case of eastern European countries such as Poland and Hungary.
The implication is that if these parties grow stronger and dominate governments they are quite likely to try to subvert democracy. Reform supporters in Britain could get more than they bargained for.
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Paul Whiteley has received funding from the British Academy and the ESRC.
Director Zach Cregger’s new horror film Weapons explores the unsettling notion that the real monsters might not be lurking under your bed, but can instead be found within your own mind.
More than merely a scare tactic, the film illustrates how someone’s own brain can transform them from a decent person into the villain in someone else’s story.
Following his breakout hit with the horror flick Barbarian (2022), in Weapons Cregger presents a psychological nightmare that serves as a twisted exploration of human behaviour. It shows how quickly normal people can turn into agents of cruelty, all while still believing they’re the heroes of the story.
The film opens with the chilling premise of 17 children from the same classroom vanishing without a trace, leaving behind only grainy security footage of them running like helpless little planes. However, the true horror unfolds as the community of Maybrook – a small town in Pennsylvania – spirals into chaos instead of unity.
Parents accuse teachers, neighbours distrust one another and innocent lives are upended in the search for a culprit. This breakdown is grounded in psychological research, showcasing how human behaviour can deteriorate under pressure.
The psychology behind Weapons
Social identity theory is a scientific concept that theorises that your brain is wired to compartmentalise the world into “us” (those we consider good) and “them” (those perceived as threats). This process intensifies when people face fear or stress.
In Weapons, we see this theory in action as the community dismantles itself. Teacher Justine Gandy (Julia Garner) becomes an easy target, not due to concrete evidence, but because she fits neatly into the role of the other – “them”. The parents of the missing children seek someone to vilify, and she becomes the scapegoat of their fears.
The trailer for Weapons.
This idea is based on decades of research showing that even the flimsiest group divisions can trigger vicious “us versus them” thinking. In laboratory experiments, people assigned to completely meaningless groups (like “overestimators” versus “underestimators”) will immediately start favouring their own group and discriminating against the other.
Here’s where things get truly frightening. The film shows characters doing horrible things while convinced they’re being righteous – this is a phenomenon psychologists call “moral disengagement”.
Think of it as your brain’s built-in excuse generator. When you want to do something that violates your normal moral standards, your mind helpfully provides justifications, such as:
“it’s for the greater good”
“they deserve it”
“everyone else is doing it”
“I’m just following orders.”
Recent studies show that this isn’t just about film villains – it’s how ordinary people convince themselves that cruelty is justified.
One 2025 study found that when people are under stress (like, say, dealing with missing children), they become much more likely to make cold, calculating decisions that prioritise results over moral principles. Your stressed-out brain rewrites your ethics in real time.
Weapons taps into these, and other, unsettling psychological findings. Take, for instance, the controversial 1971 Stanford prison experiment, where participants tasked with being “guards” quickly adopted sadistic behaviours towards the “prisoners”. Or the equally contentious obedience experiments by American psychologist Stanley Milgram, which demonstrated how ordinary people administered what they thought were lethal electric shocks under authority’s command.
Both the Milgram obedience experiment and Stanford prison experiment are now universally condemned by psychologists as deeply unethical, with experts agreeing that ethics gatekeepers would swiftly bar such studies from proceeding if they were proposed today. These controversial experiments were so harmful to participants that they directly led to major reforms in research ethics, including the National Research Act of 1974 and modern institutional review boards that protect human subjects.
But many still believe that these experiments revealed a chilling truth – almost anyone can become a “bad guy” under the right circumstances. Alarmingly, in Milgram’s tests, around 65% of participants proceeded to maximum voltage shocks, indicating that normal people are vulnerable to psychological manipulation within group settings.
Weapons presents this same dynamic, but within the context of a seemingly idyllic suburban neighbourhood.
The empathy trap
Weapons also shows that the people who care the most about a situation can become the biggest targets. The film doesn’t punish characters for being cruel – it punishes them for being kind.
Take teacher Justine Gandy (Julia Garner). Her downfall isn’t that she’s evil or incompetent. It’s that she cared too much about a neglected student and crossed the invisible boundaries of the “proper” teacher-parent relationship. Her empathy makes her an outsider, and outsiders make perfect scapegoats. The community turns her compassion into evidence of her guilt.
Even more chilling is what happens to Marcus (Benedict Wong), the school principal. In a moment where he shows concern for a child, his care gets twisted into something sinister. His empathy is punished with extreme prejudice, transforming his human decency into malice and destruction.
Recent studies have explored “virtue signaling”: when people perform moral outrage not because they genuinely care, but because it makes them look good socially. The research shows that online moral crusades often have little to do with actually helping anyone and everything to do with personal image management.
Even worse, psychologists have identified “weaponised empathy” – using people’s natural desire to help others to manipulate them into supporting harmful causes. Your compassion becomes the weapon someone else uses against you.
Weapons succeeds as horror because it doesn’t rely on supernatural monsters or gore. Instead, it shows us the real monsters – the ones we become when our psychology works exactly the way evolution has led it to.
The film suggests that the greatest threat to any community isn’t some external evil. It’s the collective decision to abandon empathy, critical thinking and basic human decency in favour of tribal warfare and moral theatre.
As the credits roll over the film’s blood-soaked finale, you’re left with an uncomfortable question: In a crisis, which side of that warfare would you be on? And more importantly, would you even know?
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Edward White is affiliated with Kingston University.
Eight months into Donald Trump’s second presidency of the United States, truth and science are again under attack – with global consequences. USAID, which tackled HIV, TB, malaria and child malnutrition is gone. Funding has been withdrawn from GAVI, a public–private global alliance that helps buy vaccines for the world’s poorest children. Malnourished children are already dying.
Besides these brutal consequences, the scientific machine that delivered America’s scientific and technological dominance is being ruthlessly dismantled. Any research project that mentions diversity, equity and inclusion (DEI), climate change or addresses the causes of vaccine hesitancy is a prime target. But even US space science, once the pride of the nation, is facing “an extinction-level event,” according to the US Planetary Society.
Across the spectrum of science, some 4,000 research grants have been cancelled. Unbelievably, bird-flu experts were fired in the middle of an outbreak. That was topped last May by cancelling a US$600M grant to the company Moderna to develop an mRNA vaccine against bird flu.
And this Tuesday, US$500 million was cancelled for 22 more projects developing mRNA vaccines. Bear in mind that under Operation Warp Speed, the first Trump administration funded the development of Moderna’s mRNA vaccine against COVID. Moderna and Pfizer-BioNTech both delivered mRNA vaccines in the record time of less than a year, winning mRNA vaccine technology a Nobel Prize in 2023.
It’s not just American science that’s being dismantled.
Threats to Australian science, too
In March, the Trump administration sent a questionnaire to researchers receiving US funding in Australia, the European Union, the United Kingdom and Canada. The 36 questions included whether their project related to climate, whether it is taking “appropriate measures” to defend against “gender ideology” and whether the organisation receives funding from China.
US funding for collaborative science projects with Australia amounts to AUD$386 million. So, the threat of losing those substantial funds is dire. As the Australian Academy of Science warned last March, if US–Australian collaboration ceases, “it will directly threaten […] strategic capability in areas of national interest such as defence, health, disaster mitigation and response, AI and quantum technology”.
By June, Australian medical research institutes were “suspending projects on malaria, tuberculosis and women’s health”. It’s like “having a bomb thrown into the middle of science”, noted Professor Brendan Crabb, director of the Burnet Institute, a Melbourne-based global health research centre.
The fallout for US medical research is worse. The Trump administration’s proposed funding cut, to the National Institutes of health, the largest funder of medical research in the world, will see its budget slashed by 40% – and over 2,400 projects cancelled. They include research into cancer, Parkinson’s disease, Alzheimer’s disease, tuberculosis, HIV prevention, COVID vaccines and long-COVID.
Experts have been summarily fired and replaced by sycophants. And of course, the Department of Health and Human Services is now led by America’s most prominent anti-vaxxer, Robert F. Kennedy Junior. Elite research universities, including Harvard, Columbia, Princeton and Cornell, continue to be prime targets.
“It’s hard to overstate how serious this is […] Today, as we’re witnessing kind of the destruction of the institutions behind American science, it’s hard to believe. It’s hard to believe any administration would do this,” noted Alan Bernstein, director of global public health at Oxford University, in April.
Indeed, how could this be happening?
Erika Nolan, a MAHA (Make America Healthy Again) stalwart and YouTube influencer, provides a candid answer: “Facts no longer matter.” Nolan plies her 200,000 strong audience with idyllic scenes of herding chickens and goats while snuggling her baby in a front pack.
Like Kennedy, Nolan believes America’s big health issues relate to food dyes and seed oils. Hopefully she does not live in a part of the US where measles or whooping cough is raging, and that her chicken flock won’t come down with bird flu.
She says it was COVID, and the pressure to be vaccinated, that “fast-tracked” her. And when asked about the 14 million lives saved in the first year, as reported in peer-reviewed medical journal, the Lancet, her answer is, “Everything can be manipulated.”
What Nolan doesn’t understand is that modern science emerged precisely to deal with the way everything can be manipulated. The very word science comes from scientia, Latin for knowledge. The gist of it is captured by the motto adopted in 1663 by the Royal Society in London: “Nullius in verba.”. That’s Latin for “Take nobody’s word for it.” In other words, experimentation and observation is what counts, not the opinions of influencers.
Nolan might be surprised to find her scepticism over “facts” goes all the way back to Socrates.
Knowledge, power and science
He left no written works, but we hear his voice through the “dialogues” of his student Plato. Ever so gently, Socrates probes the beliefs of his conversation partner, methodically laying bare their logical fallacies. It has come to be known as the Socratic method.
One of the most famous dialogues employs the allegory of a cave to teach Socrates’ primary lesson: knowledge can be based on false beliefs.
The cave is home to a group of prisoners who have been chained up for their entire lives. All they have ever been allowed to see is the cave wall in front of them. Shadows dance across it, representing the reality of the external world. The prisoners have no idea that the images are created by puppets paraded past a blazing fire just behind them.
One prisoner breaks free and climbs out of the cave. Dazed by the sunlight, it takes time for his sensitive eyes to adapt. At first, he is only able to look at shadows, then reflections, then real objects. He dashes back to the cave to enlighten his fellow captives. But his eyes have not readjusted to the dark and he stumbles around.
The prisoners perceive a blinded, deranged man, raving about a parallel world. They want nothing to do with him and become aggressive. This is Plato’s second lesson: the danger of trying to enlighten those wedded to pre-existing beliefs. Poignantly, Socrates would pay with his life for trying to enlighten others.
It would take over 2,000 years to come up with satisfactory responses to some of Socrates’ questions about the nature of knowledge. They appeared in the form of the scientific revolution.
Stars of the scientific revolution
The scientific revolution was ushered in by the exacting astronomical measurements of Copernicus, Galileo and Kepler, which revealed that Earth and the other planets were in orbit around the sun, rather than the other way round.
Brilliant as these astronomers were, they were just the warm-up acts. The starring role in the scientific revolution goes to Isaac Newton, who honoured his debt to those who came before with the timeless words: “If I have seen further, it is by standing on the shoulders of giants.” Standing on the shoulders of Copernicus, Galileo and Kepler, Newton glimpsed the sun-centred universe and pondered a new question: why did the planets orbit the sun?
The French philosopher Descartes had suggested an answer in 1633. He deemed that something like a giant tornado of dust particles raged around the sun, dragging the planets along with them.
Newton was seven years old when Descartes died. By the time Newton was 26, he was the Lucasian Professor of Mathematics at Cambridge, no doubt for the stunning discoveries he made during the plague years, which he spent in isolation at his mother’s farm in Lincolnshire. “Truth is the offspring of silence and unbroken meditation,” he noted.
His unbroken meditation gave birth to calculus, optics (in the pursuit of which he stuck a blunt needle into his eye), his laws of motion and the beginnings of his theory of gravity. Seeing an apple fall from a tree was famously his Eureka moment. The force that made the apple fall to the earth, he mused, was likely the same as the one binding the planets to the elliptical solar orbits described by Kepler.
Today, most people have no problem with the idea of gravity as a force that pulls the apple to the ground or the earth to the sun. It was a different story in Newton’s time. Descartes’ tornado seemed the more rational explanation.
Seeing an apple fall from a tree was famously Isaac Newton’s Eureka moment for his theory of gravity. Markus Winkler/Pexels
How could the sun reach out across the vastness of space to pull on our planet? This was “barbaric physics”, opined German mathematician and philosopher Gottfried Leibniz. Admittedly, Leibniz was peeved with Newton; they had rival claims as the first to develop calculus. But Leibniz was far from being the only one to label Newton’s theory unscientific.
What vindicated Newton’s theory was that it made testable, precise predictions. It specified that the gravitational force between two objects increases with their masses and decreases as they grow further apart.
Newton’s maths proved correct. It accurately predicted how long it would take for the moon to orbit the earth and the coming of Halley’s comet. His formula also predicted that the warped orbit of Uranus was due to the gravitational pull of a ghost planet. A century and a half later, Neptune was found. For 300 years, Newton’s predictions kept hitting the mark. And for most earth-bound situations, they still do.
Newton represents a watershed in the development of science. The peculiar thing about him, and what made him the lead actor of the scientific revolution, was that his theory, unlike those of Aristotle or Descartes, was limited to what could be accounted for by mathematical predictions. He did not attempt to go beyond the data to explain what gravity is or whether it really existed: “I have not as yet been able to deduce from phenomena the reason for these properties of gravity, and I do not feign hypotheses,” he wrote.
Philosophy of science
This notion of science as being light on theory is familiar to me. As a scientist (before I was a science writer, I was a molecular biologist), my contribution to theory was limited to what could be induced from my last successful experiment. In my ten years as a working scientist, I never encountered the philosophy of science. Nor did I encounter it much in my decades writing about the work of other scientists.
But in researching my book Prove It, which would see me roam widely, from theoretical physics to human evolution, and deeply, across the centuries, I knew I would have to reckon with the philosophy of science. I did not relish the task: reading philosophy can be challenging.
Moreover, I was not convinced that there was much philosophy at work in modern science. According to Michael Strevens, a philosopher of science based at New York University, when scientists themselves are placed under the microscope to dissect their philosophical impulses, nothing coherent emerges beyond a compulsion to test, test, test. As physicist Richard Feynman put it, “the philosophy of science is about as useful to science as ornithology is to birds”.
To my surprise, delight and relief, however, once I started investigating, philosophy emerged unbidden, first in the form of the Scottish enlightenment philosopher David Hume, whose ideas provided a natural kick-off point for the chapters that followed.
Like other Enlightenment philosophers, Hume valued individual reasoning over dogma and drew inspiration from the scientific revolution, particularly Newton, whom he described as “the greatest and rarest genius that ever arose for the ornament and instruction of the species”.
Newton inspired Hume, and Hume in turn inspired Albert Einstein to do what Newton could not: develop a theory of gravity.
Einstein’s ‘intellectual habits’
Einstein discovered Hume in 1902 while working as a patent clerk in Bern, Switzerland, in his early twenties. For fun, he and two colleagues formed a reading group to discuss philosophy. They paid particular attention to Hume’s 1739 A Treatise of Human Nature, in which Hume warned about the dangers of induction, the practice of extrapolating from observations to formulate general laws of the universe.
It may have been the method Newton employed, but it was an “intellectual habit” without a solid philosophical foundation, Hume argued. A well-known example concerns the colour of swans. Since Roman times, the whiteness of swans was held by European writers to be a self-evident truth. But in 1697, Dutch sea captain Willem de Vlamingh, while searching for shipwreck survivors on Australia’s west coast, sailed up a river and, lo, beheld black swans! The incident provided the name of Perth’s Swan River and a salutary philosophical lesson.
For Einstein, Hume’s ideas helped him to let go of his “intellectual habits”, a breakthrough that contributed to his theories of Special Relativity and General Relativity. Had he not read Hume, Einstein reflected, “I cannot say that the solution would have come.”
Einstein freed himself from the intellectual habit of induction by using a “deductive” process instead. It relied not on observations but on the mathematical certainty of the constant speed of light. All very well for Einstein – but the vast majority of scientists do not have the luxury of starting from mathematical certainties. While Einstein’s theory of relativity has endured unchanged for more than a century, the same cannot be said of any of the other theories explored in Prove It.
I needed Einstein to introduce me to David Hume, but Karl Popper needed no introduction. He is the most famous philosopher of science of the 20th century. If you’ve come across the idea that scientific theories can’t be proven, only disproven or “falsified”, that’s courtesy of Popper.
Karl Popper: science as search for truth
Popper has a poignant personal story that resonates strongly with my motive for writing a scientific guide for the post-truth era.
Born in 1902 into a cultivated, scholarly home – his mother a pianist, his father a lawyer – Popper’s first decade was lived in Vienna’s golden age. As the capital of the Austro-Hungarian Empire, Vienna was the seat of political power, but also a cauldron of European cultural and intellectual ferment.
Modernism exploded: there was the stylised eroticism of Gustav Klimt’s shimmering gold paintings and the raw sexual canvases of Egon Schiele; the absurdist literature of Franz Kafka and the meltingly poetic work of Rainer Maria Rilke; the hauntingly beautiful music of Gustav Mahler and the atonal work of Arnold Schoenberg; the philosophy of Ludwig Wittgenstein; and of course, Sigmund Freud’s revolutionary theories about the life of the unconscious mind.
“In those first fourteen years of the twentieth century, Vienna, more than anywhere else, was the fulminating, bewitching crucible where the modern world was invented,” writes William Boyd.
Popper witnessed its destruction. He was 12 when the first world war broke out and 37 when the second one came around. In between, he flirted with and rejected Marxism, tried his hand at carpentry and teaching, and managed to complete a PhD in the philosophy of psychology. With the rise of Nazism, his Jewish ancestry erased his job prospects. To build a reputation, he wrote a book, The Logic of Scientific Discovery.
Published in 1934, it introduced his theory that the way to distinguish science from non-science is falsification. His ideas struck a chord and won him an offer to teach philosophy at Canterbury University College in Christchurch, New Zealand. He emigrated with his wife in 1937, a year before Austria was annexed by Hitler. In 1946, he moved to the United Kingdom to found the department of philosophy at the London School of Economics.
Popper experienced firsthand what can happen to the most intellectually progressive of civilisations when a populist ideology takes hold. How could a philosopher protect future generations from such an assault on truth? Like the Enlightenment thinkers before him, his answer was the scientific method. “Truth is therefore the aim of science; science is the search for truth,” he wrote.
Testing Einstein
I was delighted to discover that Popper’s theory was inspired by Einstein! As a teenager, Popper heard Einstein expound on his astonishing theory of General Relativity in Vienna in 1919.
Gravity was not a force, Einstein suggested, but a consequence of the way mass causes a curvature in spacetime. A fantastical theory! But in the same breath, Einstein proposed a way to prove his theory wrong. During an eclipse, the moon blocks the sun, and the dark sky makes the stars near the sun suddenly visible. Although the stars themselves are very far away from the sun, their light rays must pass close by it to be seen by people watching the eclipse.
Einstein predicted that the starlight would curve along the spacetime warped by the sun’s huge mass. As a result, the apparent positions of the stars would be shifted by an exact amount predicted by Einstein’s equations.
Bottom line: Einstein’s theory could be falsified, and Einstein offered his critics a way to do it. As Popper put it, “Thus I arrived, by the end of 1919, at the conclusion that the scientific attitude was the critical attitude, which did not look for verifications but for crucial tests; tests which could refute the theory tested, though they could never establish it.”
Science cannot prove theories, because, as Hume pointed out, what’s true today may not be true tomorrow. Just because we observe a phenomenon once doesn’t mean we can assume it will happen again. But science can certainly disprove things.
That’s what distinguishes scientific theories from, say, Freud’s theory of the unconscious or Marx’s theory of historical materialism. Those theories do not offer falsifiable predictions. You might agree or disagree with them, but there is no way to disprove them. Science, by contrast, offers predictions that can be tested and therefore falsified. “I believe I have solved the problem of induction,” Popper declared.
Popper had his detractors. One was his former student Imre Lakatos, who embraced the importance of falsification but argued that in practice, theories are rarely overturned by contradictory data. “Scientists have thick skins,” he wrote. “They do not abandon a theory because facts contradict it. They normally either invent some rescue hypothesis to explain what they then call a mere anomaly and if they cannot explain the anomaly, they ignore it.”
The philosopher most diametrically opposed to Popper was the American, Thomas Kuhn. No doubt you’ve heard the term “paradigm shift”? That’s thanks to Kuhn and his 1962 book The Structure of Scientific Revolutions, which sold over a million copies. According to Kuhn, modern scientists, rather than attempting to falsify their theories, do the exact opposite: they design experiments to affirm them.
These disputes notwithstanding, the hunt for the origins of COVID-19 showed me Popper is alive and well in the modern science lab. “Popperian” scientists were among the first to propose that the virus came from a lab. They then tried to see if they could disprove their own theory – and largely succeeded. The weight of evidence points to the virus spilling into the human population from an animal source.
Shared reality and true science
The scientific method doesn’t just apply to science. In his book, The Constitution of Knowledge, Jonathan Rauch, a senior fellow in governance at Brookings Institute, notes that the institutions that underpin democracies – academia, law, journalism and government – need to operate based on a shared reality. To do so, they employ the scientific method the gathering and testing of facts.
The Trump administration seems to have declared war on every aspect of the scientific method. It has declared war on fact-checking, triggering a global pile-on. Meta announced in January it would scrap its fact-checking programs. And last month, Google announced it will not renew its fact-checking contract with Australian Associated Press.
The Trump administration has also taken an axe to the workings of the scientific machine. In a breathtaking example of Orwellian “double speak”, on May 23, Trump issued an executive order to restore “gold standard science”.
What this means, explains New York University bioethicist Arthur Caplan, is that “instead of independent expert reviews of research, a Trump functionary can look at any peer-reviewed work and declare it to be in violation of the President’s gold standard”. He concluded that the US “has never had a situation in which political and ideological nonscientists got the last word about what is credible science”.
The history of authoritarian regimes tells us when ideologues take over science, it does not end well. It was the Nazi takeover of German universities that saw the likes of Einstein seek refuge in the US – and turned America into a scientific superpower.
The scientific method, designed to keep human failings in check, is the best guide for navigating the present era. Here are my guiding principles:
Go to the experts. See what is being published in leading journals, find a good plain-language summary and check several sources. Science and Nature both offer excellent free reporting, as does The Conversation and The New York Times.
Expert opinion seeks consensus. Consensus may be tough to obtain among scientists, but it is based on a convergence of evidence from different sources.
Anyone who tries to whip up an emotional response, or who has a predetermined opinion or conflict of interest, is a red flag. Scientific evidence is generally measured. It comes with margins of error and estimates of effectiveness and risk. A scientist who offers opinions outside their field of expertise is also one to whom I would give less weight.
Our health, our agriculture, our environmental safety, our ability to ameliorate and adapt to climate change, to regulate AI and to fight the next pandemic, all rely on the proper functioning of the scientific machine. We must not stand by and see it dismantled.
Elizabeth Finkel does not work for, consult, own shares in or receive funding from any company or organisation that would benefit from this article, and has disclosed no relevant affiliations beyond their academic appointment.
Have you ever sat in a meeting where someone half your age casually mentions “prompting ChatGPT” or “running this through AI”, and felt a familiar knot in your stomach? You’re not alone.
There’s a growing narrative that artificial intelligence (AI) is inherently ageist, that older workers will be disproportionately hit by job displacement and are more reluctant to adopt AI tools.
But such assumptions – especially that youth is a built-in advantage when it comes to AI – might not actually hold.
While ageism in hiring is a real concern, if you have decades of work experience, your skills, knowledge and judgement could be exactly what’s needed to harness AI’s power – without falling into its traps.
What does the research say?
The research on who benefits most from AI at work is surprisingly murky, partly because it’s still early days for systematic studies on AI and work.
Some research suggests lower-skilled workers might have more to gain than high-skilled workers on certain straightforward tasks. The picture becomes much less clear under real-world conditions, especially for complex work that relies heavily on judgement and experience.
This article is part of The Conversation’s series on jobs in the age of AI. Leading experts examine what AI means for workers at different career stages, how AI is reshaping our economy – and what you can do to prepare.
Through our Skills Horizon research project, where we’ve been talking to Australian and global senior leaders across different industries, we’re hearing a more nuanced story.
Many older workers do experience AI as deeply unsettling. As one US-based CEO of a large multinational corporation told us:
AI can be a form of existential challenge, not only to what you’re doing, but how you view yourself.
But leaders are also observing an important and unexpected distinction: experienced workers are often much better at judging the quality of AI outputs. This might become one of the most important skills, given that AI occasionally hallucinates or gets things wrong.
The CEO of a South American creative agency put it bluntly:
Senior colleagues are using multiple AIs. If they don’t have the right solution, they re-prompt, iterate, but the juniors are satisfied with the first answer, they copy, paste and think they’re finished. They don’t yet know what they are looking for, and the danger is that they will not learn what to look for if they keep working that way.
Experience as an AI advantage
Experienced workers have a crucial advantage when it comes to prompting AI: they understand context and usually know how to express it clearly.
While a junior advertising creative might ask an AI to “Write copy for a sustainability campaign”, a seasoned account director knows to specify “Write conversational social media copy for a sustainable fashion brand targeting eco-conscious millennials, emphasising our client’s zero-waste manufacturing process and keeping the tone authentic but not preachy”.
This skill mirrors what experienced professionals do when briefing junior colleagues or freelancers: providing detailed instructions, accounting for audience, objectives, and constraints. It’s a competency developed through years of managing teams and projects.
Younger workers, despite their comfort with technology, may actually be at a disadvantage here. There’s a crucial difference between using technology frequently and using it well.
Many young people may become too accustomed to AI assistance. A survey of US teens this year found 72% had used an AI companion app. Some children and teens are turning to chatbots for everyday decisions.
Without the professional experience to recognise when something doesn’t quite fit, younger workers risk accepting AI responses that feel right – effectively “vibing” their work – rather than developing the analytical skills to evaluate AI usefulness.
So what can you do?
First, everyone benefits from learning more about AI. In our time educating everyone from students to senior leaders and CEOs, we find that misunderstandings about how AI works have little to do with age.
A good place to start is reading up on what AI is and what it can do for you:
If you’re not even sure which AI platform to try, we would recommend testing the most prominent ones, OpenAI’s ChatGPT, Anthropic’s Claude, and Google’s Gemini.
If you’re an experienced worker feeling threatened by AI, lean into your strengths. Your decades of experience with delegation, context-setting, and critical evaluation are exactly what AI tools need.
Start small. Pick one regular work task and experiment with AI assistance, using your judgement to evaluate and refine outputs. Practice prompting like you’re briefing a junior colleague: be specific about context, constraints, and desired outcomes, and repeat the process as needed.
Most importantly, don’t feel threatened. In a workplace increasingly filled with AI-generated content, your ability to spot what doesn’t quite fit, and to know what questions to ask, has never been more valuable.
Kai Riemer is co-author of the annual “Skills Horizon” research project, which identifies key leadership skills (including in AI), based on interviews with global and Australian leaders and executives across various fields. He also educates leaders in AI fluency through Sydney Executive Plus at the University of Sydney.
Sandra Peter is co-author of the annual “Skills Horizon” research project, which identifies key leadership skills (including in AI), based on interviews with global and Australian leaders and executives across various fields. She also educates leaders in AI fluency through Sydney Executive Plus at the University of Sydney.
You might have seen an interesting phrase popping up in your social media feeds lately: “Chiron is in retrograde.” If you’re anything like me, you’ve never heard of Chiron before – and I’m a professional astronomer.
So what is Chiron, and what does it mean to be in retrograde? The short answer is that Chiron is an asteroid-slash-comet orbiting somewhere past Jupiter and Saturn. And until January 2026, it’s going to look like it’s going backwards in the sky. If you can spot it.
But there’s a bit more to the story.
What is Chiron?
Chiron’s official name is (2060) Chiron. First things first: it’s pronounced “kai-ruhn”, with a hard K sound.
It was discovered by astronomer Charles Kowal in 1977. This was long after the system of Western astrology was developed, which probably explains why people who check their daily horoscopes are also blissfully unaware of its existence.
It was initially classified as an asteroid, or a rock in space. In 1989 astronomers discovered Chiron sometimes has a tail or “coma”, which tells us that it’s actually a comet or a “dirty snowball”. Since then, Chiron has been classified as both an asteroid and a comet.
In 2023, more than 45 years after it was first discovered, astronomers confirmed Chiron has rings. This makes it the fourth non-planet in the Solar System to have rings. (The planets Jupiter, Saturn, Uranus and Neptune have rings, as do the asteroid Chariklo and the dwarf planets Haumea and Quaoar.)
Artist’s impression of the Centaur asteroid 10199 Chariklo. Chariklo was the first asteroid and fifth object in our Solar System, after Saturn, Jupiter, Uranus and Neptune, found to have a ring around it. NASA, ESA, CSA, Leah Hustak (STScI), CC BY-SA
Chiron orbits the Sun in an oval-shaped orbit. The closest it gets to the Sun is about 1.3 billion kilometres (about eight times the distance between Earth and the Sun) and the furthest it gets from the Sun is a whopping 2.7 billion km (about 19 times the distance between Earth and the Sun).
This puts it between the orbits of Jupiter and Uranus, cutting through the orbit of Saturn.
Centaurs in space
Chiron is a member of the Centaurs. This is a group of small Solar System bodies that orbit the Sun between Jupiter and Neptune. Their orbits are highly unstable: they change over time because of gravitational interactions with the giant planets.
In Greek mythology, centaurs were creatures with the lower body and legs of a horse and the torso and arms of a human. Chiron was the oldest centaur, the son of the Titan Kronos. He was considered the wisest centaur.
The orbits of various centaurs, including Chiron. We can see the orbits of Jupiter, Saturn, Uranus and Neptune as well of the orbits of various Small Solar System bodies and dwarf planets. Nick Anthony Fiorenza, CC BY-SA
Chiron in retrograde
In astronomy, retrograde motion is when something is going backwards compared with everything else.
Apparent retrograde motion is where an object in the sky, such as a planet, appears to be going backwards when we look at it from Earth. The object hasn’t actually changed direction; it just looks like it from our perspective.
All the planets (and Chiron) orbit the Sun in the same direction. This means the planets typically look like they are moving in a west-to-east direction across the sky. But when Earth “catches” up to a planet (or a planet catches up to Earth) and overtakes it, the planet temporarily appears to move in a west-to-east direction in the sky.
This temporary illusion is apparent retrograde motion. It’s just like when you’re driving in a car and overtake a slower car, that slower car looks like it’s going backwards as you overtake it.
Animation demonstrating apparent retrograde motion. We can see the Earth and an outer planet orbiting the Sun in a circular motion on the left. On the right, we can see the direction the planet appears to be moving from Earth’s perspective. Dominic Ford, CC BY-SA
Chiron went into retrograde (that is, apparent retrograde motion) on July 30 2025 and will go back to normal on January 2 2026. But unless you have a telescope or do some long-exposure photography, you’d never know which way Chiron is travelling. Chiron is very faint, so you can’t see it with your eyes.
