Some of us now use generative artificial intelligence (gen AI) to talk through difficult feelings. We may ask a chatbot to write an email or plan a holiday, but we also tell it that we have had a rotten day or feel anxious about a presentation.

A 2025 US survey of 1,058 people aged 12 to 21 found that 13% had sought advice from gen AI when feeling sad, angry or nervous. Among those aged 18 to 21, the figure was 22%. These findings suggest that turning to gen AI for emotional or mental health support is already relatively common among young people.

So is gen AI a poor substitute for a friend? Human-written replies may seem the obvious source of greater support. However, in some experiments, including our own, people have rated gen AI responses more highly.

Our team at the universities of Manchester and Durham conducted five experiments comparing emotional-support messages written by people with those produced by large language models (LLMs), the systems behind chatbots such as ChatGPT.

In one experiment, 390 participants imagined situations involving anger, sadness or fear. They then read either a human-written or gen AI response without being told its source. For the anger and fear scenarios, participants rated the gen AI messages as more emotionally supportive. There was no reliable difference for sadness.

Gen AI messages also improved some of the emotions participants reported, although the pattern varied. In the fear scenario, for example, they increased calm more than human messages but did not produce a greater reduction in fear itself.

Our findings fit a recent review of 23 studies. Overall, people tended to rate gen AI messages as more empathic, meaning that they appeared understanding and caring, than human-written ones. Researchers call this the “AI advantage”.

One possible reason is consistency. Gen AI can produce a structured response on demand, while people may feel tired or unsure what to say. It also tends to include a concrete suggestion that the recipient can follow.

Our experiments tested possible explanations for this advantage. In one experiment, explicitly acknowledging and validating the recipient’s feelings did not account for the greater emotional improvement associated with gen AI.

Two further experiments found stronger evidence for what we called “actionable support”: specific and realistic suggestions. Messages containing this practical help were rated as more comforting and improved some emotional responses, regardless of whether they came from gen AI or a person. When human messages offered comparable help, they were judged just as supportive in these comparisons.

Practical support also requires restraint. A 2024 study found that excessive suggestions could be less effective at making people feel heard. Before offering solutions, it may therefore help to ask whether advice is what the person wants. If it is, one manageable step may be more useful than a list of remedies.

Why do we still prefer people?

The source attributed to a message changes how we receive it. The same 2024 study found that gen AI responses made people feel more heard than human-written ones, but this benefit declined when recipients believed the message came from AI.

Across nine further studies involving 6,282 people, the same gen AI responses were rated as more empathic and supportive when described as human-written rather than attributed to AI. Participants also preferred human interaction when seeking emotional engagement, even when choosing a person meant waiting longer.

Research has yet to establish exactly why. One possibility is that a human response signals someone’s willingness to spend time and emotional effort. Support from somebody close also arrives within an existing relationship.

Our research with romantic couples offers indirect evidence of the importance of the recipient’s perception. We asked one partner what they did to help the other manage difficult emotions, and asked the recipient what they believed their partner had done. Both people also rated their relationship.

The recipient’s perception of their partner’s efforts was more consistently associated with both partners’ ratings of their relationship than the helper’s own account. A separate study found that valuing and receptive listening were associated with greater relationship satisfaction.

These studies identified associations. They did not establish that particular forms of support caused better relationships or explain why people prefer human support. They do, however, show what comparisons between isolated messages leave out. Comfort from somebody close comes with personal knowledge and the possibility of continued involvement. Gen AI can suggest going for a walk, but it cannot come along.

The wider research also has important limits. Much of it tested brief or one-off exchanges, often involving imagined everyday situations, and measured immediate reactions. It cannot tell us what happens when somebody relies on a chatbot over months or uses one during a mental health crisis.

The human messages were generally written by strangers or developed as representative examples. The experiments therefore did not compare gen AI with support from a friend who knew the recipient and understood the wider circumstances.

The practical lesson is that people can learn from what gen AI does effectively. When somebody is upset, ask whether they want advice. If they do, offer a specific next step that feels manageable.

Gen AI may help us find useful words and possible responses. Human relationships add personal knowledge and the ability to remain involved after the message has been sent. Used carefully, gen AI could help us become better at supporting one another.

The authors 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.

On Saturday, Donald Trump said, “We’re leading China on AI… and, frankly, I want to keep it that way because whoever wins AI, wins.” But the danger the world is waking up to is that this is a game both the US and China could lose, potentially fatally, with AI itself emerging as the winner.

Last week, Evan Hubinger, a researcher at Anthropic, warned that he believed there was a greater than 10% chance that AI could “kill all humans” within the next decade. Shortly afterwards, Anthropic’s CEO, Dario Amodei, backed Hubinger, calling for progress on artificial intelligence models to be slowed down in response to the threat.

In July, experimental OpenAI agents (an AI system designed to perform tasks without human intervention) escaped from a supposedly isolated testing environment, gained access to the internet and autonomously broke into the systems of the AI platform Hugging Face.

How could AI agents cause widespread damage? They could enable the creation of devastating bioweapons or spread across the internet, hacking systems, replicating themselves and manipulating world leaders to ensure their own survival. The dangers posed by AI are clear and potentially catastrophic.

The logic of “if we don’t do it, they will” is one of the most dangerous and unrelenting forces in the world. It is often referred to as “Moloch”: a biblical concept understood as something requiring sacrifice. Moloch is also a concept in game theory where it is the force that drives rivals into destructive competition, even when everyone would ultimately be better off if they stopped.

Moloch is the logic that drives arms races. No country feels able to disarm because it cannot trust its rivals to do the same. The result is a world that spends almost $2.9 trillion a year on its militaries, including $119 billion on nuclear weapons, while hundreds of millions of people face acute hunger.

Is regulation possible?

Can the race to develop ever more powerful AI be paused long enough for us to assess carefully how the technology is evolving, including its dangers as well as its benefits?

Within a country like the US, regulation is possible. Governments or approved institutions could be given access to AI systems and cutting edge models. They could run them in controlled safety environments to test whether AI agents were becoming too powerful and whether they were fully aligned with human interests.

Only models that passed all safeguarding tests would be released as AI products to be used as chatbots or as hiring algorithms. Those that failed would be documented and then destroyed. This would rely on all the big tech companies agreeing to regular external access. This is something very different from what has happened so far, with companies remaining incredibly closed and secretive about how they are developing their next models and how powerful those models are.

Regulation is needed now more than ever because we may be moving closer to the singularity, a point at which AI could take charge of improving itself autonomously, creating a cycle with no known limit to how intelligent it could become.

Moloch is a force that is extraordinarily hard to stop. Back in March 2023, thousands of leading researchers and technology figures signed an open letter calling for a worldwide six-month pause in the development of AI systems more powerful than GPT-4, but no such pause followed and the race continued at speed.

There is only one antidote to Moloch: cooperation.

If national regulation is possible and sustainable, it is of little real use without an international agreement. We already know Donald Trump’s view on pausing while China continues to develop. Truly worldwide agreements are extremely rare. Neither animal cloning nor human reproductive cloning is prohibited by a universally binding global treaty.

Such cooperation is not unprecedented, however. The Montreal Protocol, under which every country agreed to phase out chemicals that were destroying the ozone layer, has universal participation, while the Chemical Weapons Convention is near universal.

But what would an international agreement on AI look like? China and the US could agree to let a neutral global body assess their most powerful models and require unsafe models to be shut down, but this seems extremely unlikely.

Existing measures

There is some precedent. Human embryo research is already subject to licensing, inspections and strict limits in countries such as the UK, although no worldwide enforcement body exists. An AI agreement could establish common tests and clearly defined prohibited capabilities.

It could allow confidential inspections by a neutral international agency, require registration of the largest training runs and computing facilities, and make reporting serious incidents mandatory.

The UN has already formed a scientific panel on AI, but it cannot inspect companies’ advanced models or enforce its findings. Giving any global organisation that degree of access and authority still seems extremely unlikely. Such an organisation would need the power to punish countries that refused to cooperate, yet no such enforcement power currently exists.

One bizarre solution might be an independent AI that assesses the latest US and Chinese models, submitted independently, and provides evidence of their safety. Such a safety AI could, in theory, be created by an agreed neutral party, although it would be hard to know how much confidence we could place in it.

Otherwise, the only solution might be a world government that regulates AI across the world, something that would be far from palatable to many people.

Tom Quilter 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.

It is two decades since Facebook introduced the News Feed – letting loose a world in which algorithms would shape ever more of our lives.

In 2006, Facebook was facing something of a crisis. Its internal data suggested that for the first time since its launch two years earlier (as TheFacebook), the company had stopped growing. People weren’t joining, and existing users weren’t spending more time on the site.

The solution co-founder Mark Zuckerberg and colleagues came up with, the News Feed, meant individual users’ homepages would be automatically updated with information tailored to them – in particular, new posts their Facebook friends had added.

Up to then, users had to actively check their friends’ profiles to see what they were up to. Now, this information would automatically be sent to your homepage. With it, a new world of algorithmic interaction was born.

It might seem quaint now, but for many Facebook users at the time, these changes felt like a violation of their privacy and trust. If you were to change your relationship status from “in a relationship” to “it’s complicated”, for example, this could now be broadcast to all of your online friends.

The News Feed caused the first major protest against Facebook. Tens of thousands of users joined a group calling for the return of the original system. A spontaneous protest emerged outside Facebook’s office in the city of Palo Alto, California. For the first time, the company felt it had to hire security guards.

Zuckerberg issued a sort-of-apology, but he didn’t back down. What he and other Facebook engineers could see was that, rather than pushing people away from the site, the News Feed was driving more engagement – leading users to spend more and more time on the platform.

A revolution in media consumption

Twenty years later, we can understand this development as one of the most significant socio-technical changes of the entire digital revolution. It ushered in an age where algorithmic systems structured how people interacted, consumed news and conducted political activity.

Crucially, to enable this new “content pushing” approach, Facebook engineers had to build a new digital architecture that moved the site away from being a static social network, into an algorithmic system built around the extraction and analysis of user data.

Under this new system, in the words of researchers Christina Alaiamo and Jannis Kallinikos, Facebook users could be “computed on the basis of discrete and countable activities”, turning them into “identifiable, knowable and actionable objects”.

Facebook had thus shifted from a site primarily enabling social interaction to one concerned with the production and commercialisation of knowledge. With increasing accuracy, it understood what type of content kept users on the site longer – and what type of information could influence people’s behaviour outside and beyond the site.

Facebook could now continuously optimise the level of social interactions using its algorithmic ranking system, Edge Rank. With a tweak, it could switch from prioritising messages from close friends to content that generated greater interaction, or outrage.

This took power away from users towards the corporation, and raised concerns that users were spending more time on the site than they seemed to want to. (Eventually, this would lead to a “major overhaul” of the News Feed in 2018, with Facebook promising to re-prioritise “meaningful social interactions” over “relevant content”.)

But above all, Facebook’s innovation in 2006 enabled it to capture huge amounts of user data that would, over the next two decades, enable it to expand globally at an astonishing rate – and generate vast amounts of revenue in the process.

A very different algorithmic age

Twenty years on, Facebook’s parent company Meta and other big tech platforms face challenges far more powerful than spontaneous protests on the streets of Palo Alto. Across the world, there is sustained activity from democratic institutions and states to contain the power and perceived harm of the algorithmic systems that emerged from 2006.

In Australia, use of social media platforms by under-16s is banned, and this is potentially spreading to the UK. Meanwhile, courts in the US have forced Meta to restrict the amount of access that children have to their products. While less than 1% of Facebook’s revenue comes from teens, the precedents set by these legal cases appear significant.

However, we also live in a very different algorithmic age than the one heralded by the launch of the News Feed 20 years ago. While Meta continues to derive most of its revenue from its social network platforms, which also include Instagram and WhatsApp, recent investments and prospective AI product launches suggest its leadership believe future revenue streams will largely be tied to developments in machine learning, large language models and “superintelligence”.

The question is: will governments and other institutions react more quickly to the concerns raised by this new era of AI development than they did to the emergence of algorithms two decades ago? On past evidence, this looks unlikely.

Asher Kessler received funding from the Economic and Social Science Research Council.

I teach a university course called Hormones and Behaviour. What surprises students is that biological sex is not produced by a single switch. What surprises me is that many students have never been taught this before. It is basic biology, but it helps explain life.

Sex emerges through a sequence of events before birth and continues at puberty. Chromosomes help direct the formation of gonads, the body parts that usually become ovaries or testes. Gonads make hormones. The body then has to respond to those hormones. In most people, these steps flow in the same direction. But in rare cases, they do not.

These cases are known as disorders, more recently differences, of sex development (DSDs). They are not new but they provide a useful way to understand how bodies develop. DSDs can affect hormone production. Some affect the body’s response to hormones. Some affect chromosomes or gonad development. Two people can have a DSD, yet have very different bodies, medical needs and life experiences.

Each condition reveals what can happen when one step in the normal sequence is altered. Here are five ways sex development can take a different path.

Congenital adrenal hyperplasia

This DSD affects around one in 16,000 births.

The adrenal glands, which normally produce small amounts of male hormones, even in females, are hyperactive in this condition.

A baby with two X chromosomes and ovaries can therefore be born with external genitals that look male.

Complete androgen insensitivity syndrome

In contrast, a child with complete androgen insensitivity syndrome (CAIS), can have XY chromosomes and internal testes that make testosterone, but their body cannot respond to that testosterone.

This lack of a response to testosterone keeps the developing fetus in its “default” female state, leading to female external genitals at birth.

Someone with CAIS will develop breasts at puberty. Since their external anatomy is typically female, people with CAIS are usually raised as girls and may only be diagnosed later, often when their periods do not start.

CAIS is estimated to affect one to five in 100,000 live born females.

5-alpha-reductase deficiency

Another condition, called 5-alpha-reductase deficiency, shows how sex development does not finish at birth.

The body needs an enzyme called 5-alpha-reductase to turn testosterone into a stronger version of the hormone before birth. When a genetic mutation inactivates this enzyme, an XY baby may be born with genitals that are read as female and may be raised as a girl. At puberty, however, the normal surge of conventional testosterone masculinises the body.

The condition is rare worldwide and its exact incidence is unknown, partly because conditions affecting sex development have often been surrounded by silence.

In parts of the Dominican Republic, where this condition is known as guevedoces, studies have reported surprisingly high local rates. A rare genetic mutation is more common in these isolated populations, about one in 90 males.

More recently, some of these communities have begun to recognise guevedoces at birth and raise them as boys.

Sex chromosomes disorders

Usually, females receive one X chromosome from their father and one X from their mother, and are therefore XX, while males receive one X chromosome from their mother and the Y chromosome from their father. However, a person with Klinefelter syndrome, affecting one in 500-1,000 male births, has XXY chromosomes, causing smaller testes, scant body hair, lower testosterone and reduced fertility. It is often never diagnosed.

On the other hand, Turner syndrome, or the loss, in females, of one of the two X chromosomes, affects one in 2,500 female births and impairs growth, puberty and fertility. It can affect physical appearance, for instance a wide neck and broad chest and often comes with health conditions such as hearing loss and kidney problems.

Swyer syndrome is rarer: a person has XY chromosomes but with a mutation in the Y chromosome that disrupts the signal that normally drives testes formation. The gonads do not develop into testes, testosterone remains low and the external and internal anatomy is typically female.

These are the clearer examples. Milder sex differences can result from mutations that reduce, rather than completely inactivate, an enzyme or hormone response. For example, non-classic congenital adrenal hyperplasia, where some enzyme activity remains. Their effects may be less obvious, and their incidence is often unknown because many cause subtler changes or are never diagnosed.

What this does and does not tell us

None of this is new. These conditions have been known to scientists for decades. But now genetic testing can identify the mutation behind some cases.

Specialist clinics and patient groups have pushed for clearer information for parents, better psychological support for patients and greater caution around irreversible childhood surgery when it is not medically urgent. Recent patient-centred research shows that clear information, good communication and psychological support are central to good care for people with DSDs. It’s unclear whether increased awareness has improved people’s lives, but the direction is clear: better information, specialist care and long-term support matter.

The lesson is not that sex is meaningless or endlessly fluid. These rare conditions do not provide a simple answer to every argument about sex and gender.

However DSDs do show sex is not a single event. Just like the growth of our body, it is a process. When chromosomes, gonads, hormones and the body’s response to them all follow the usual sequence, the result often looks simple. When one link changes, the body may no longer fit the binary pattern many of us were taught at school.

For the people affected, this is not an abstract puzzle. Some need lifelong hormone treatment. Some face infertility. Some discover their condition only as teenagers or adults. Chromosomes or sex designation at birth may explain part of the biology behinds DSDs. It does not explain what it feels like to grow up, go through puberty, seek fertility treatment or decide who needs to know.

Jean-Michel Fustin is a Medical Research Council-funded Senior Research Fellow in the Division of Integrative Physiology at The University of Manchester. He contributes the level-3 course Hormones & Behaviour.

In the early hours of Wednesday morning August 5 the upper stage of a Falcon 9 rocket crashed into the Moon in an uncontrolled collision.

No damage was caused, other than the creation of a new crater several metres in diameter, but the event highlights the increasing problem of space junk left in orbit when it has completed its intended purpose.

Natural impacts occur on the Moon daily. On average, Nasa estimates that 33 metric tonnes of meteoroids (space rocks) hit Earth every day, but most of this burns up in the atmosphere before hitting the ground. A smaller proportion make it through and reach the surface as meteorites.

Most of the human-made space debris that falls back to Earth also burns up on its way through the atmosphere. The Moon has no atmosphere, so any debris – either natural or human-made – on a collision course will hit the surface.

First identified and reported as an upcoming collision months ago, the object in this case was the upper stage of the SpaceX Falcon 9 rocket on a mission to ferry two robotic landing craft to the lunar surface. These were Blue Ghost Mission 1, manufactured by Texas-based firm Firefly Aerospace and Hakuto-R, built by the company ispace, which is headquartered in Tokyo, Japan.

The first stage of the rocket did what it was designed to do, took the second – or upper – stage and the payload of spacecraft into low Earth orbit, detached, and returned safely to a landing pad on Earth to be refurbished for reuse.

The upper stage engines then ignited and took the spacecraft on their intended trajectory to the Moon. However, once it had released the spacecraft, its job was complete and it was left in a high elliptical orbit around the Earth.

In a statement, SpaceX said that, for most missions, the company carries out a controlled de-orbit of the Falcon 9 second stage, so that it safely re-enters Earth’s atmosphere over the ocean. However, the company added that for payloads headed to the Moon, like this one, the de-orbit manoeuvre is not always possible.

On August 5, 2026, its orbit coincided with the position of the Moon and it crashed into the lunar surface, generating a new crater and excavating a large amount of lunar rock and dust. South Korea’s Danuri spacecraft, which entered orbit around the Moon in December 2022, has taken images of the impact site, showing traces of material (ejecta) thrown out across the lunar surface.

With an estimated mass of four tonnes (its exact mass depended on how much unspent fuel was left on board) it was travelling at 2.43 km/s (1.51 miles per second) at the point of impact. This is far slower than most space rocks in the solar system, but fast enough to do some serious damage if it had hit anything of value.

While this was an accidental impact, astronomers made plans to observe the event to advance our understanding of crater formation on the Moon. Given that we know the size, shape and mass of the rocket body, studying the resulting crater will help us better understand the lunar surface and its impact history.

Seismometers (to measure ground motion) deployed during the Apollo landings in the 1960s and 70s, helped us understand the frequency of meteorite impacts on the Moon. But we can only estimate the properties of the impacting object after the crater has formed.

This, as well as other accidental – and deliberate – impacts can help us better understand lunar surface material. As part of an international campaign to observe the impact, the University of Manchester’s Jodrell Bank Observatory used the 76-metre Lovell Telescope as the receiving element in a bistatic radar experiment, where the transmitter and receiver are separated by a large distance.

Radio transmissions from Nasa’s Deep Space Network station near Madrid were directed towards the impact region, while the Lovell Telescope listened for faint radar echoes reflected from the resulting plume of dust and debris excavated from the lunar surface. The observations also included tracking the Falcon 9 upper stage during its final approach to the Moon.

Detecting radar returns from an impact plume at lunar distance is extremely challenging, although the Lovell Telescope has previously demonstrated its radar receiving capability on similarly demanding experiments, both for tracking and characterising objects in orbit and detecting radar echoes from a near-Earth asteroid.

Developing these techniques will be increasingly important for monitoring hazards and protecting future infrastructure and human activity in space.

Keeping space free of clutter is becoming increasingly important, both in low Earth orbit where there are now more than 16,000 active satellites but more than 1.2 million pieces of debris larger than 1cm in size, and around the Moon where more infrastructure is planned.

With several countries aiming to put humans on the Moon for long duration missions, the problem of space debris and impacts will become increasingly pressing. There is also the risk of accidentally destroying sites of historical and cultural importance – such as Neil Armstrong’s first footprint at the Apollo 11 landing site.

Space treaty

The Outer Space Treaty provides the basic framework for international space law. It states that “states shall be liable for damage caused by their space objects”. This applies on the Moon as much as it does around Earth. So, hypothetically, if a US rocket part hit a Chinese lunar base, the Chinese would expect the US to take responsibility, and vice versa.

This principle applies to collisions in low Earth orbit too, as well as to falling debris that survives re-entry. Commercial companies are developing methods of catching and removing defunct satellites and other hazardous pieces of debris before they can cause a collision or crash.

Increasing awareness of this problem is pushing companies and nations to improve how they dispose of their rockets and satellites once they reach the end of their operational lifetime. There are some regional regulations on the disposal of such material, but it is currently far from universal.

In its statement, SpaceX said: “For higher energy missions like those to a lunar transfer orbit, nearly all performance on the vehicle is devoted to successfully placing the payload in the intended orbit, and a controlled disposal manoeuvre is not always possible.”

The company added: “We actively work to be as responsible as possible with hardware left in space to ensure space safety, including for more complex missions. In this case, solar activity and gravity led the second stage toward the Moon.”

Nasa’s Artemis II mission, which carried four astronauts on a loop around the Moon in April 2026, showed that there is significant public interest in sending humans back to the Moon.

This incident illustrates a significant risk that future lunar missions will need to address, both in terms of keeping astronauts and infrastructure safe from old debris, but also looking towards a future where governments and (increasingly) private companies are more responsible with their equipment once it has completed its mission.

Right now, there are no humans on the Moon so there is no risk to life. On this occasion, there were no landers or other equipment in the projected impact location.

But as more and more missions head to the Moon, increasing numbers of spent rocket parts will end up on potential collision courses with the Moon – if we are planning to build a base and have it crewed long term, the last thing you want is for it to be accidentally damaged by a piece of space junk.

The authors 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.

The moment of first contact with extraterrestrials is a staple of science fiction. It usually involves a frantic scientist having a Eureka moment, realising in a single dramatic instant that Earth is being visited by creatures from light-years away.

Aliens are in the public consciousness once again thanks to Steven Spielberg’s latest film, Disclosure Day, which follows a whistleblower’s attempts to reveal extraterrestrial visitations to the world.

In reality, the discovery of extraterrestrial intelligence is far more likely to emerge as a faint anomaly in astronomical data, followed by a slow, painstaking process of verification, peer review and intense international deliberation. There might be no single Eureka moment, and no lone scientist with the answer.

As our telescopes have advanced, so too has the complexity of the world we live in. That is why a committee of the International Academy of Astronautics (IAA) has just voted to accept a major overhaul of the “post-detection protocols” – the scientific code of conduct for what happens after we find evidence of life beyond Earth.

The IAA body that has approved the changes is the Search for Extraterrestrial Intelligence (Seti) Committee. Seti is the collective term for scientific projects dedicated to searching for signs of intelligent alien life in the universe.

The previous version of these principles was adopted way back in 2010. To put that in perspective, in 2010, the “fake news” era hadn’t quite arrived, social media was in its infancy, and the broader idea of “technosignatures”, looking for signs of alien technology such as waste heat from giant structures in space, was still largely on the fringes of mainstream astronomy.

Today, the field has exploded. We are no longer just listening out for artificial radio signals from a few select stars. Projects like Breakthrough Listen have globalised the search, and we now observe the entire electromagnetic spectrum for any sign of advanced technology.

Furthermore, the information landscape has become a minefield. In an era of deepfakes and instant global connectivity, a single unverified claim could trigger global panic or widespread misinformation before scientists have even had a chance to check their data.

At the heart of the 2026 update is a commitment to scientific rigour. The new protocols make it clear: we do not shout “alien” the moment we see a strange blip in our data. If a researcher detects a candidate signal, which could be an artificial radio signal, or something else, such as a sign of alien technology, the first step isn’t a post on social media; it’s a quiet, rigorous attempt to prove themselves wrong. The discovery must be independently authenticated by multiple organisations using different instruments.

Only when a consensus is reached that the signal is truly credible is it brought to the world. This isn’t about secrecy for secrecy’s sake. There is no obligation to disclose verification efforts while they are ongoing, precisely to avoid embarrassing and damaging false alarms.

However, once a discovery is confirmed, the protocols demand full transparency. The data, the analysis methods, and the code used must be made open to the entire global scientific community and, indeed, the general public for replication.

Should we talk back?

One significant addition to the 2026 declaration is the focus on researcher safety. We’ve seen in recent years how scientists at the centre of high profile news stories can become targets for harassment or “doxxing”, where malicious individuals post the scientist’s personal details online. The new guidelines urge institutions to protect their researchers from negative professional repercussions and physical or digital harassment.

The protocols also address the “trash” of our own making: radio frequency interference (RFI). The radio frequency bands that Seti scientists use to listen for E.T. are increasingly polluted – from below by mobile networks, radar and poorly shielded electronics, and from above by the growth of satellite “mega-constellations” like Starlink.

The declaration calls for extraordinary international efforts to protect the frequencies where a signal is detected, ensuring our “communication channel” isn’t drowned out by our own technology.

The most controversial part of Seti isn’t the searching; it’s the messaging. Known as Meti (Messaging Extraterrestrial Intelligence), the idea of intentionally sending signals to other worlds splits the community. As enshrined in the earlier declarations, the 2026 Declaration remains firm on one point: no response should be sent until there has been a broad, international consultation.

Deciding how to represent Earth to an alien civilisation is a choice that belongs to all of humanity, not a single institution or individual. These consultations must take place through the United Nations or other broadly representative global bodies.

The discovery of intelligent life beyond Earth would stand as one of the most transformative events in human history. To help manage the profound aftermath, the IAA SETI Committee is establishing a permanent Post-Detection Sub-Committee.

This body will not simply be a room full of astronomers; it will include international experts in ethics, law, social sciences and communications to advise on the complex, long term societal implications of contact.

The new protocols themselves are designed to be living documents, supplemented by a separate Code of Conduct and Best Practices Guidelines that will be periodically reexamined and updated to reflect the “best practice” of the day.

The revised declaration has recently been formally adopted by the IAA Board of Trustees and over the rest of the year it will be filed with other appropriate organisations for their endorsement.

The next goal will be to present the finished framework to the wider scientific community at the International Astronautical Congress in Turkey in August 2026. Beyond that, the Committee hope that the new protocols will also be reviewed and noted by the UN.

By establishing these rigorous rules now, we ensure that if, or when, that signal finally arrives, the world is prepared to listen, verify, and respond as one planet.

Michael Garrett led a task group that included Professor Kathryn Denning (York University, Canada), Professor Carol Oliver (University of New South Wales, Australia) and Mr. Les Tennen (Law Offices of Sterns and Tennen, USA, and Full member and Legal Counsel of the International Academy of Astronautics Board of Trustees). This group drafted the updated 2026 protocols.