There have been a number of media reports published recently regarding research from the University of Cambridge which showed the health benefits of reading from pleasure. This research supports what many people thought anecdotally, that reading was good for the mind however there was no collective gathering of data to support this view. Researcher Barbara Sahakian and her colleagues at the University of Cambridge pooled data from five surveys and eight long-term studies covering thousands of participants that has now provided evidence for that insight.
The data did link reading to a greater volume of matter in that part of the human brain which supports thinking and memory including stronger communication between regions of the brain. There is speculation that reading builds cognitive reserve which assists with the brain's ability to defend against ageing and enables better adaptation to damage often caused by modern lifestyles.
Better mental health was also cited as a benefit from reading with one childhood study showing children who started reading earlier in life had moderately large brain surfaces and volumes in emotional control centres.
In summary, reading for pleasure was connected by the research team to reduced stress, greater empathy, enhanced well-being and reduced loneliness. A reduction in cognitive decline was also seen in older adults. In light of other research relating to the health benefits of activity for older adults, reading for pleasure can be added to the list of positive actions that can be taken.
Renewables now contribute more than 40% of the electricity generated in Australia’s main grid. Twenty years ago, that figure was under 10%. Despite this growth, the federal target of 82% by 2030 is slipping out of reach.
This comes down to one reason: uneven investment. Australia is now the world’s third-largest market for grid-scale batteries, while solar farms are proceeding steadily.
But the real problem is wind. Supply chain shortages, financing issues, construction cost increases and political changes have made wind projects much more difficult to build. And that’s going to be a problem – Australia needs more wind projects to fill the gap as old coal plants retire.
It’s not all bad news. Last week, a large new wind farm in Western Australia secured the necessary financing to go ahead. But more needs to be done.
A transition well underway
Huge change has already come to Australia’s power grids.
But the clean energy rebuild isn’t done yet. An estimated A$106 billion of investment will be needed by 2050.
At present, these funds are thin on the ground. The 2026 survey by the Clean Energy Investor Group found the percentage of major investors rating Australia’s clean energy sector as “attractive” fell from 69% in 2025 to 58%, while the percentage regarding it as “somewhat unattractive” more than doubled from 8% to 19%.
That’s a problem. Wind projects have to be financed years before they earn any revenue. On average, wind projects take over a year longer to be built than solar. These longer build times mean, with higher interest rates, these projects have higher upfront costs.
Investors warn that the Coalition’s retreat from net zero threatens a recovery in confidence. The National and Liberal parties have ended their commitment to net zero.
Projects that began under one set of policy assumptions can run into trouble if these change.
Renewables aren’t collapsing – just wind
Australia’s renewable slowdown isn’t uniform. Solar and batteries are going strong, while wind farms are struggling. This year, few new wind farms have reached the stage where construction could actually begin.
Wind is crucial. The Australian Energy Market Operator is counting on wind to generate 47% of the total power from renewables in the main power grid by 2030.
Once wind power is built, it becomes one of the most efficient and reliable sources of energy available. In windy areas, turbines can turn day and night.
But trade data shows Australia’s imports of battery storage roughly quadrupled between 2022 and 2025, while imports of wind turbines and equipment have fallen sharply.
This matches investment figures: in 2025, investment in batteries rose almost 70% to $4.8 billion, while wind investment fell almost 60% to $2.6 billion. Solar farm investment dropped a little, falling 5% to $1.9 billion.
Why is wind tricky?
Solar farms are typically smaller and faster to build. They’re also easier to finance in stages. Wind farms tend to be larger, take longer to plan and build and are harder to finance in stages.
Economics pose another challenge. To be viable, wind farms need electricity prices above $100 per megawatt-hour. But the market is currently offering around $60.
Then there are construction costs, which have risen sharply in recent years. Turbine prices rose almost 40% between 2020 and 2022. Other challenges include the cost of new transmission lines, and a shortage of skilled workers.
Then there’s politics. In February last year, the Queensland government began requiring wind farm backers to do significantly more in terms of full impact assessments and public consultation. It also gave third parties more rights to appeal. In May, the state government axed the large, conditionally approved, Moonlight Ridge wind farm.
Unsurprisingly, no new wind farm applications have been lodged in Queensland since.
Cost increases are threatening Australia’s wind farm construction pipeline.ZU_09/Getty
Wind has to be ready for coal to exit
It’s common for wind projects to take about five years to become reality. If investors are reconsidering, Australia may not have enough clean energy in the pipeline to replace increasingly unreliable coal plants slated for retirement.
Victoria’s Yallourn power station will close in 2028, while Australia’s largest coal plant, Eraring will close in 2029, after a two-year extension. Queensland’s Gladstone plant may be retired in 2029, six years early.
These three large plants produce about 30 terawatt-hours a year between them – roughly twice South Australia’s total annual power generation.
If the present wind drought isn’t resolved soon, it will leave a large gap that won’t show up in energy statistics until it’s too late to fix.
Wind is key
If these worrying investment trends continue, wind will produce less power than authorities expected. Solar and batteries could take up some of the slack, but not all.
Overcoming these doldrums won’t be easy. But it has to be done. To do this, investors need certainty. That will mean giving clearer commitments to long-term climate policy at a national level.
More predictable state planning rules would help, as would allowing contracts to better reflect real construction costs.
Australia has come a long way down the path to a renewable energy future. But it’s not yet job done. To complete the transition, we will need wind.
Artificial
intelligence is best understood as a general-purpose technology with built-in inherent risks. The system that helps draft a
work email can also help draft a scam. At the moment, public discussion often centres on AI
acting on its own, but the more immediate risk is human: what people
deliberately do with these tools, and how carelessly they sometimes use them.
This article covers three areas: criminal use, military use, and negligent use.
Criminal Use
Fraud is the
clearest example. Language models can write fluent, personalised phishing
messages, removing the spelling errors that once exposed many scams.
Voice-cloning tools can imitate a person from a short audio sample, and cloned
voices have been reported in “family emergency” and payment-authorisation
scams. Image and video generators can produce forged documents, fabricated
evidence and non-consensual intimate imagery.
AI also lowers
the skill barrier. Someone with limited technical ability may get help writing
malicious code or planning a social-engineering attack. How much extra
capability this gives criminals is still debated. Developers build safeguards
into their products, but safeguards are imperfect, and openly released models
can be modified to remove them.
Military Use
Armed forces
are adopting AI for intelligence analysis, logistics, surveillance, cyber
operations and, in some systems, target identification. The concerns are
specific:
Speed:
Automated systems can
compress the time humans have to deliberate, increasing the risk of escalation
by error.
Accuracy
at scale: A
misidentification by one soldier is a single mistake. A flawed model can repeat
the same mistake thousands of times.
Accountability:
When a system
contributes to a harmful decision, responsibility is harder to assign.
Arms-race
pressure: States may
deploy systems before they are adequately tested because they fear falling
behind rivals.
International
discussion of autonomous weapons is ongoing, however there is no binding global
agreement governing the use of such weapons.
Negligence and misuse
Not all misuse
is intentional. Large language models generate plausible text, not verified
facts, and they can state falsehoods with complete confidence. This is often
called “hallucination.” In 2023, lawyers in a New York, US federal case were
sanctioned after submitting a brief containing case citations that a chatbot
had invented. The tool did not fail unusually; the users simply did not check
its output and this is by no means an isolated example.
Three negligent
habits recur:
Over-trust:
Relying on AI output
for medical, legal or financial decisions without independent verification.
Vague
instructions: Poorly
specified prompts tend to produce answers that look right but miss the actual
need, and the user may not notice.
Excess
access: Connecting AI
agents to email, files or payment systems without limiting permissions or
monitoring actions. A mistake then becomes an action with real consequences.
Psychologists
call the underlying tendency 'automation bias': people defer to automated systems
even when their own judgement would have caught the error.
Reducing the risk No single
measure removes these risks, but several help:
Treat
AI output as a draft that needs checking, especially where errors are costly.
Keep
a human responsible for consequential decisions.
Give
AI tools the minimum access required for the task.
Be
specific about what you want, and test the result against known facts.
Support
clear rules and transparency from developers, businesses and governments.
Summing up: AI’s risks come largely from how people choose to use it and how
carefully they supervise it. Criminals exploit its capabilities, militaries may
deploy it faster than they can test it, and ordinary users may trust it more
than its reliability justifies. Understanding these patterns is a practical
first step toward using the technology responsibly
CRISPR-Cas9 is a method for making targeted
changes to genetic DNA. It was adapted from a defence system in bacteria, which use it
to recognize and cut the DNA of invading viruses. The tool has two main
parts: a guide RNA, a short molecule designed to match a specific DNA sequence,
and Cas9, an enzyme that cuts the DNA at that location. After the cut, the
cell's own repair machinery takes over which enables researchers to disable a gene or
alter its sequence.
In terms of the origin of this biotechnology, in 2012 Emmanuelle Charpentier and Jennifer Doudna demonstrated that the bacterial
system could be reprogrammed to cut any DNA molecule at a chosen site. They
received the 2020 Nobel Prize in Chemistry for the work . Refinements have since followed such as Base editing, for example, that changes a single DNA letter without making
a complete double-strand cut.
The first approved CRISPR medicine is Casgevy
(exagamglogene autotemcel), from Vertex Pharmaceuticals and CRISPR
Therapeutics. The US Food and Drug Administration approved it on December 8,
2023 for sickle cell disease, and on January 16, 2024 for transfusion-dependent
beta thalassemia. Both approvals cover patients aged 12 and older. Both
diseases stem from mutations in the HBB gene, which encodes part of adult
hemoglobin.
Casgevy works outside the body, a method
called ex vivo editing. A patient's blood-forming stem cells are collected,
edited in a laboratory at a regulatory region of the BCL11A gene, and returned
to the patient. The edit allows the body to produce fetal hemoglobin, which
lacks the abnormality behind these diseases. Before infusion, patients
receive the chemotherapy drug busulfan to make room for the edited cells.
In the phase 3 sickle cell trial, 44 patients
were treated. Of the 30 with enough follow-up to be evaluated, 29 had no severe
pain crises for at least 12 consecutive months, and all 30 avoided
hospitalization for them. Median follow-up was 19.3 months.
CRISPR-based treatment has costs. As an example, it list price is
$2.2 million, and it must be given at authorized centres experienced in stem
cell transplantation. The most common side effects for patients are mouth sores, fever with
low white blood cell counts, and reduced appetite.
Personalized therapy and future uses
In May 2025, physicians at the Children's Hospital
of Philadelphia and Penn Medicine reported the first personalized CRISPR-based
treatment. The patient was an infant, known as KJ, with severe CPS1 deficiency,
a metabolic disease usually treated with a liver transplant. The team designed
and manufactured a base-editing therapy, delivered to the liver in lipid
nanoparticles, within six months. No serious side effects had been
reported at the time of this blog article. The lead physician-researcher described the
hope that this approach can be scaled to fit individual patients' needs. However the result comes from just one patient, so its' general applicability is unproven.
Current use in health care
Other researchers see base editing as a
possible durable treatment for single-gene liver diseases that conventional
gene therapy handles poorly. Three constraints are visible in the current
evidence. First, most advanced examples target blood or liver. Second, follow-up is measured
in months to a few years, so long-term durability and safety remain open. Third, prices on the order of millions of dollars limit access. Whether personalized
editing can become routine will depend on the cost, speed, and efficacy of designing
therapies one patient at a time.
Around 12% of the world’s total cancer cases in 2024 were likely caused by an infection, according to new research from the World Health Organization (WHO).
The study, published today in The Lancet Oncology, analysed the frequency and causes of different cancers, specifically examining the role of infections.
It linked 2.3 million new cancer cases to an infection. Most were caused by just five pathogens: Helicobacter pylori (4%), human papillomavirus, or HPV (4%), hepatitis B (2%), Epstein-Barr virus (1%) and hepatitis C (under 1%). These infections can cause more than 20 different types of cancer, including stomach, liver, blood and cervical cancers.
So, how can an infection cause cancer? And does this mean these cancers are preventable?
Did we already know about this link?
Some of the study authors have been researching this field for around thirty years. Their previous work investigated cancer cases caused by infections in 1990, 2002, 2008, 2012, and 2018.
The proportion of cancer cases caused by infections may appear to have dropped during those years (from a high of 18% in 2002), but the authors stress these comparisons cannot really be made confidently, as the sources and quality of the data have changed over time.
In fact, the latest study wasn’t trying to compare between the years. Instead, it aims to highlight where controlling and preventing infections can help to reduce cancer rates.
To make sense of this, it helps to know how infection is linked to cancer. Extensive research has dissected the molecular mechanisms behind this link, and we now know there are various ways infections can cause cancer.
How can a virus cause cancer?
A virus can (directly or indirectly) change the genes of the cell it infects (the host cell), making that cell more likely to grow out of control and eventually become a cancer.
The first is by turning off the ability of a cell to destroy itself (for example, by inactivating the TP53 protein) or to stop dividing (for example, by inactivating the RB protein). A healthy cell would normally try to do these things if infected by a virus.
The second way a virus can cause cancer is by inserting its own DNA into the host cell’s DNA, which can accidentally disrupt genes that control cell death or division (like those above).
The third way is when the virus itself carries a gene that causes cancer (an oncogene). In many cases, the virus has picked up these by accident from another organism.
It’s not just viruses that cause cancer. Infections from bacteria or parasites – such as Helicobacter pylori (best known for causing stomach ulcers), or Opisthorchis viverrini (a liver fluke, a type of parasitic worm) – can also lead to cancer.
However, these work more indirectly than viruses. Long-term (chronic) infection by these types of organisms can cause significant stress to different tissues.
Inflammation, normally a part of the body’s immune response, can then become overactive, damaging the tissues further.
These stresses can result in cancer-causing DNA damage in cells, or lead to mistakes during cell division as the body tries to rapidly produce new cells to repair tissue damage.
In both cases, the cells acquire genetic mutations that put them on the road towards becoming cancer.
Many cancers are preventable
Of course, there may be other mechanisms linking infections and cancer that we don’t know about but, overall, the connection between infections and cancer is indisputable.
Critically, what this tells us – and what this new study into the rates of cancers caused by infections reinforces – is that many cancers are preventable.
In Australia, one of the best examples of preventing cancers caused by infections is the human papillomavirus (HPV) vaccine.
This vaccine protects against certain strains of HPV strongly associated with cervical cancer, and is available to adolescents in Australia.
Sadly, the new study also highlights that around 75% of cancers caused by infections were found in low- and middle-income countries.
Treating infections that can lead to cancer – such as HIV, H. pylori, and hepatitis B and C – is one way to reduce cancer rates. Preventative measures also play a major role, including vaccinations, condoms and disease screening.
However, the availability of these programs in poorer countries can be limited, and so access continues to be a major equity issue in combating cancer.
The authors would like to acknowledge the contribution of Amali Cooray from the Olivia Newton-John Cancer Research Institute to this article.
Earlier this month, artificial intelligence (AI) researcher Jacob Coxon resigned from Anthropic after just four months. In an announcement on X, he stated:
The people building AI earnestly believe that it could kill us all by the end of the decade.
A senior member of Anthropic’s staff, Evan Hubinger, actually agreed with Coxon, adding he personally thinks the chance of this happening in the next decade is more than 10%.
But how exactly might AI kill us all? There’s no shortage of fantastical scenarios, and most of them involve the concept of “superintelligent” AI – that is, AI that’s more capable than humans.
I’ve distilled these scenarios down to the top five, ordering them roughly from most vague to most precise. And I’d argue the list is also ordered from least probable to most probable.
1. We’ll never know
AI doomers often justify their concerns by means of an annoying catch-22 paradox: how can we possibly imagine what a superintelligence might do to take out less intelligent beings like us?
We’d have to be superintelligent to predict what a superintelligence would be able to do. It’s like asking your family dog to imagine thermonuclear war.
The good news here is that superintelligence is still perhaps some distance away. Current AI models are really good at solving particular problems, but that’s not the same as being more intelligent than a human in all domains.
However, AI did recently solve one of the seven most challenging maths problems known. It’s apparently closing in on others, which might leave you feeling less optimistic here.
2. Paperclips
A superintelligent AI would likely be extraordinarily competent at achieving its goals. But it might be indifferent to human survival.
A classic example of such indifference comes from Oxford philosopher Nick Bostrom’s imagined superintelligent AI that’s been designed to optimise paperclip production. To produce its preferred form of office supplies, it quickly converts all available matter – including humans, planets and stars – into paperclips.
What we have here is the perfect execution of improperly specified objectives. The AI doesn’t hate humanity; it simply recognises we’re composed of atoms that could be better utilised for paperclips. It’s not personal.
The good news here is that this scenario confuses intelligence with power. A superintelligent AI doesn’t necessarily have the power to achieve its goals. Turning the planet into paperclip factories would require planning permissions.
Even if it got the permissions, building too many paperclip factories would lead to inevitable public outcry. Interest groups would block the proceedings in the courts. Environmental activists would block the bulldozers.
There’s a lot of friction in the world that prevents even the very intelligent from imposing their will on the rest of us. In fact, you could think of data centres as a current embodiment of the theoretical paperclip scenario. And humans are increasingly pushing back against turning the planet over to data centres.
3. Bioweapons
Humanity could be killed by a superintelligent AI making and releasing some dangerous new bioweapon into the atmosphere. This is, in fact, one outcome of the AI 2027 scenario by the AI Futures Project, a non-profit dedicated to forecasting the impacts of advanced AI.
Worryingly, they just sent the genetic sequences off to a mail-order lab and it sent the viruses back in test tubes. The whole experiment cost a couple of hundred thousand dollars at most.
The good news here is that it’s remarkably hard to kill everyone with a new virus. To do that, you need a virus that’s very transmissible, so it spreads far and wide. But it’s a rule of biology – viruses that spread easily are typically less fatal. By contrast, if a virus is very fatal, transmissibility tends to go down, as most people infected die before there’s time to spread the infection.
COVID killed less than 1% of humanity. The deadliest pandemic in recorded history was the Black Death, when the plague killed more than one-third of Europe’s population in the 13th century. However, even the plague would likely be much less deadly today due to our increased medical knowledge and better sanitation.
4. Nuclear war
What if AI got into the nuclear command and control chain and started a nuclear war? We’ve come close to nuclear war by mistake several times in the past 50 years.
Perhaps the most likely risk is that we take ourselves out. And AI might precipitate this.
Imagine – and it doesn’t take a lot of imagination – that AI causes massive job losses, pollutes the information space with misinformation, fractures our politics, and destroys human relationships with fake synthetic companionship.
Society might easily break. Slowly but surely, we’d stop being able to support human life at any scale.
What then to take away from all these scenarios? There are some things to be worried about for sure. But not to be too worried, I hope.
The Climate Group is hosting Climate Week NYC from September 20th to the 27th, 2026 obviously in New York City, United States of America. The theme this year is energy, the impact and the action that is needed to address climate change. The week long event has various sessions, side events and round tables covering six streams -
American Innovation and Abundance: This stream is promoted as being a first-in-kind approach to provide a focal point to elevate and explore the next generation of US leadership in innovation, investment and resiliance. Worldwide, this sentiment might considered to be unduly optimistic considering ongoing political activities in the US in respect of climate change.
Energy: This stream is considering how as demand rises from electrification and AI, the challenge is no longer just generating clean power but delivering it reliably, affordably at scale and pace. For the US this is challenging given the continuing use of fossil fuels despite also having nuclear power and renewable energy generation.
Food: Food security must be treated with the same urgency as energy security. The focus of this stream is finding scaleable solutions from regenenerative agriculture to protein diversification and tackling food waste. Some elements of this problem are solveable with many steps (such as seed banks and crop genetics research) already in progress.
Leadership and Green Growth: According to the conference papers "..driving the transition at pace requires bold leadership, smart strategy, and collaborative action". A true statement but one at odds with US Federal Government direction.
Nature and Health: Perhaps stating the obvious, the conference sees "nature and human health as deeply interconnected, underpinning resilient economies and societies". The objective of this conference stream is "find solutions that deliver measureable benefits for both people and societies". A admirable goal if somewhat blue sky.
Transport and Industry: Noting that transport and heavy industry are at the heart of the global emissions challenge, the conference lays down the direction "from electification and clean fuels to green construction and circular supply chains, we must reimagine how we move goods and people, build and manufacture at scale''. Nicely expressed but can they produce the workable results ?
The website for the event can be accessed at this link: climate week nyc
Coffee is best known, and perhaps most valued, for its caffeine and its ability to make us feel more awake and alert.
But coffee is much more than caffeine dissolved in hot water.
Coffee is a chemically complicated plant extract containing hundreds of bioactive compounds. These can have all kinds of weird and wonderful effects in your body, even when you’re drinking decaf.
Here are seven of the strangest.
1. Coffee can make you poo
One study shows about three in ten people say they get the urge to poo shortly after drinking coffee.
This happens quickly, and with both regular and decaf. So it’s down to more than just the caffeine. But it’s not clear exactly which coffee compounds cause this.
Your colon can also be more active in the morning, and this is when most people drink their first coffee.
What you add to your coffee can also affect your bowels. The lactose in milk or some sugar-free sweeteners can also get the bowels moving, particularly if you consume a lot.
2. Coffee can affect your reflux, eyes and ears
Coffee can worsen reflux symptoms for some people. Reflux, when your stomach acid flows back up into your food pipe, isn’t always just felt as heartburn. It can contribute to coughing, wheezing and other respiratory symptoms when reflux affects the throat and airways.
Caffeine can temporarily increase pressure inside the eye in some people with glaucoma or ocular hypertension, where pressure in the eye can already be high. Controlling this pressure is an important part of protecting the major nerve of the eye from damage. So some people with these conditions might be advised to limit their coffee and caffeine intake.
There’s also an ear condition where the tube connecting the middle ear to the back of the nose stays abnormally open, which can make you hear your own voice, or your breathing, unusually loudly. People with this condition, known as patulous Eustachian tube dysfunction, are sometimes advised to drink fewer caffeinated drinks and stay well hydrated, because dehydration can worsen symptoms. However, there is little direct evidence coffee itself causes the condition.
Caffeine’s relationship with migraine is complicated: caffeine can help relieve a migraine, but too much, or suddenly having less than usual, can trigger one in some people.
3. Coffee can interact with your medicines
Coffee can change the way some medicines behave in the body. For instance, it can reduce absorption of the thyroid medication levothyroxine and the osteoporosis drug alendronate.
Caffeine can slow the metabolism of the antipsychotic clozapine, increasing its concentration in the blood.
Sometimes medicines change the way your coffee behaves. For example, the antibiotic ciprofloxacin slows your breakdown of caffeine. So, your usual coffee may stay in your system for longer.
4. Coffee can affect your cholesterol
Coffee contains compounds called diterpenes. Two of these, cafestol and kahweol, can increase total and LDL (“bad”) cholesterol.
But in short-term trials, the same compounds lower lipoprotein(a), which may indicate a lower risk of a heart attack or stroke.
Coffee contains complex carbohydrates and roasting products called melanoidins that can reach the colon, where gut microbes can ferment them.
Small human studies suggest drinking coffee can also change the composition of the gut microbiome. But the evidence is still developing, so it’s too early to call coffee a prebiotic.
This isn’t primarily a caffeine effect. Polyphenols in coffee, including chlorogenic acids, can bind with iron in the digestive tract, making it harder to absorb.
This matters most for people who already have low iron stores or rely heavily on plant sources of iron, rather than being a reason for everyone to give up coffee with breakfast.
7. Coffee can kick-start the gut
Coffee can kick parts of your digestive system into action even when there’s no food to digest. It can stimulate the pancreas to release trypsin, an enzyme involved in digesting protein.
This happens with both regular and decaffeinated coffee, suggesting other compounds in your cup are talking to your digestive system.
Whether this digestive “heads-up” changes how hungry you feel isn’t clear.
Caffeine and feeling more alert might be coffee’s most popular feature, but this is far from the whole story. Caffeine can do much more than that.
A cup of coffee contains hundreds of compounds that can interact with our digestive system, microbes, medicines, nutrients and more – sometimes in confusing and unexpected ways.
