Category: Analysis

Source: The Conversation – Global Perspectives – By Amy Hume, Lecturer In Theatre (Voice), Victorian College of the Arts, The University of Melbourne

Tilly Norwood officially launched her acting career this month at the Zurich Film Festival.

She first appeared in the short film AI Commissioner, released in July. Her producer, Eline Van der Velden, claims Norwood has already attracted the attention of multiple agents.

But Norwood was generated with artificial intelligence (AI). The AI “actor” has been created by Xicoia, the AI branch of the production company Particle6, founded by the Dutch actor-turned-producer Ven der Velden. And AI Commissioner is an AI-generated short film, written by ChatGPT.

A post about the film’s launch on Norwood’s Facebook page read,

I may be AI generated, but I’m feeling very real emotions right now. I am so excited for what’s coming next!

The reception from the industry has been far from warm. Actors – and audiences – have come out in force against Norwood.

So, is this the future of film, or is it a gimmick?

‘Tilly Norwood is not an actor’

Norwood’s existence introduces a new type of technology to Hollywood. Unlike CGI (computer generated imagery), where a performer’s movements are captured and transformed into a digital character, or an animation which is voiced by a human actor, Norwood has no human behind her performance. Every expression and line delivery is generated by AI.

Norwood has been trained on the performances of hundreds of actors, without any payment or consent, and draws on the information from all those performances in every expression and line delivery.

Her arrival comes less than two years after the artist strikes that brought Hollywood to a stand-still, with AI a central issue to the disputes. The strike ended with a historic agreement placing limitations around digital replicas of actors’ faces and voices, but did not completely ban “synthetic fakes”.

SAG-AFTRA, the union representing actors in the United States, has said:

To be clear, ‘Tilly Norwood’ is not an actor; it’s a character generated by a computer program that was trained on the work of countless professional performers – without permission or compensation.

Additionally, real actors can set boundaries and are protected by agents, unions and intimacy coordinators who negotiate what is shown on screen.

Norwood can be made to perform anything in any context – becoming a vessel for whatever creators or producers choose to depict.

This absence of consent or control opens a dangerous pathway to how the (digitally reproduced) female body may be represented on screen, both in mainstream cinema, and in pornography.

Is it art?

We consider creativity to be a human quality. Art is generally understood as an expression of human experience. Norwood’s performances do not come from such creativity or human experience, but from a database of pre-existing performances.

All artists borrow from and are influenced by predecessors and contemporaries. But that human influence is limited by time, informed by our own experiences and shaped by our unique perspective.

AI has no such limits: just look at Google’s chess-playing program AlphaZero, which learnt by playing millions of games of chess, more than any human can play in a life time.

Norwood’s training can absorb hundreds of performances in a way no single actor could. How can that be compared to an actor’s performance – a craft they have developed throughout their training and career?

Van der Velden argues Norwood is “a new tool” for creators. Tools have previously been a paintbrush or a typewriter, which have helped facilitate or extend the creativity of painting or writing.

Here, Norwood as the tool performs the creative act itself. The AI is the tool and the artist.

Will audiences accept AI actors?

Norwood’s survival depends not on industry hype but on audience reception.

So far, humans show a negative bias against AI-generated art. Studies across art forms have shown people prefer works when told they were created by humans, even if the output is identical.

We don’t know yet if that bias could fade. A younger generation raised on streaming may be less concerned with whether an actor is “real” and more with immediate access, affordability or how quickly they can consume the content.

If audiences do accept AI actors, the consequences go beyond taste. There would be profound effects on labour. Entry- and mid-level acting jobs could vanish. AI actors could shrink the demand for whole creative teams – from make-up and costume to lighting and set design – since their presence reduces the need for on-set artistry.

Economics could prove decisive. For studios, AI actors are cheaper, more controllable and free from human needs or unions. Even if audiences are ambivalent, financial pressures could steer production companies towards AI.

The bigger picture

Tilly Norwood is not a question of the future of Hollywood. She is a cultural stress-test – a case study in how much we value human creativity.

What do we want art to be? Is it about efficiency, or human expression? If we accept synthetic actors, what stops us from replacing other creative labour – writers, musicians, designers – with AI trained on their work, but with no consent or remuneration?

We are at a crossroads. Do we regulate the use of AI in the arts, resist it, or embrace it?

Resistance may not be realistic. AI is here, and some audiences will accept it. The risk is that in choosing imitation over human artistry, we reshape culture in ways that cannot be easily reversed.

Amy Hume 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.

– ref. Would you watch a film with an AI actor? What Tilly Norwood tells us about art – and labour rights – https://theconversation.com/would-you-watch-a-film-with-an-ai-actor-what-tilly-norwood-tells-us-about-art-and-labour-rights-266476

Source: The Conversation – Global Perspectives – By Qiang Tang, Associate Professor, Computer Science, University of Sydney

Nowadays data breaches aren’t rare shocks – they’re a weekly drumbeat. From leaked customer records to stolen source code, our digital lives keep spilling into the open.

Git services are especially vulnerable to cybersecurity threats. These are online hosting platforms that are widely used in the IT industry to collaboratively develop software, and are home to most of the world’s computer code.

Just last week, hackers reportedly stole about 570 gigabytes of data from a git service called GitLab. The stolen data was associated with major companies such as IBM and Siemens, as well as United States government organisations.

In December 2022, hackers stole source code from IT company Okta which was stored in repositories on GitHub.

Cyberattackers can also quietly insert malicious code into existing projects without a developer’s knowledge. These so-called “software supply-chain” attacks have turned development tools and update channels on git services into high-value targets.

As we explain in a new conference paper, our team has developed a new way to make git services more secure, with very little impact on performance.

The gold standard

We already know how to keep conversations private: secure messenger services such as Signal and WhatsApp use end-to-end encryption, which locks messages on your device and only unlocks them on the recipient’s device. This protects the data even if the service platform is hacked, which is why it’s considered the gold standard to protect data.

But git services, which are widely used by major tech companies and startups, currently don’t use end-to-end encryption. The same is true for most of the other tools we use to work together, such as shared documents.

Because git services allow a huge number of collaborators to work on the same project at the same time, the software codes they host are constantly written and updated at a very rapid rate. This makes using standard encryption impractical. To do so would take up too much bandwidth to transmit all of the data for even one word change, and make the services very inefficient.

But our new encryption method overcomes this challenge.

Striking an important balance

The method we have developed uses what’s known as “character-level encryption”. This means only edits to a software code stored on the git service are treated as new data to be encrypted – rather than the entire code.

Think of it as encrypting the tracked changes in a word document, instead of a new version every time.

This method strikes an important balance. It keeps the updated code private and secure while reducing the amount of communication between user and git services, as well as the amount of storage required.

Importantly, this new method is also compatible with existing git services, making it easy for people to adopt. It also doesn’t interfere with other functions of git servers, such as hosting, saving bandwidth and indexing, so people can keep using these servers as they normally would – just with the added benefit of extra security.

A broader end-to-end encrypted internet

This new tool is currently free and open-source for all users. It can be installed easily like a patch when using git services, and will run in the background as users access git services just like before.

But this is just the starting point for a broader shift towards online collaboration that is secured by end-to-end encryption.

Extending the same guarantees to shared documents, spreadsheets and design files is possible, but will require sustained research and investment.

One complication to ensure security is managing encryption keys or credentials for users to decrypt encrypted data. Fortunately, our previous research shows us how to create a secure cloud storage system that will allow users to safely store their credentials.

Just as importantly, we must balance security with compliance and accountability. Universities, hospitals and government agencies are required to retain and, in some cases, provide lawful access to certain data. Meeting these obligations, without weakening end-to-end encryption, pushes us to research new techniques.

The goal is not secrecy at all costs, but verifiable controls that respect both privacy and the rule of law.

We don’t need a brand new internet to get there. We need pragmatic upgrades that fit the tools people already use – paired with clear, provable guarantees.

Messaging proved that end-to-end encryption can scale to billions. Code and cloud files are next, and with continued research and targeted investment, the rest of our everyday collaboration can follow.

So before too long, you will hopefully be able to work on a shared document with colleagues with the peace of mind that it, too, has gold standard security.

Qiang Tang receives funding from Google via Digital Future Initiative to support the research on this project.

Moti Yung works for Google as a distinguished research scientist.

Yanan Li is supported by the funding from Google via Digital Future Initiative for doing this research at the University of Sydney.

– ref. The world’s most sensitive computer code is vulnerable to attack. A new encryption method can help – https://theconversation.com/the-worlds-most-sensitive-computer-code-is-vulnerable-to-attack-a-new-encryption-method-can-help-266236

Source: The Conversation – Global Perspectives – By Cameron Shackell, Sessional Academic, School of Information Systems, Queensland University of Technology

The electrification boom of the 1920s set the United States up for a century of industrial dominance and powered a global economic revolution.

But before electricity faded from a red-hot tech sector into invisible infrastructure, the world went through profound social change, a speculative bubble, a stock market crash, mass unemployment and a decade of global turmoil.

Understanding this history matters now. Artificial intelligence (AI) is a similar general purpose technology and looks set to reshape every aspect of the economy. But it’s already showing some of the hallmarks of electricity’s rise, peak and bust in the decade known as the Roaring Twenties.

The reckoning that followed could be about to repeat.

First came the electricity boom

A century ago, when people at the New York Stock Exchange talked about the latest “high tech” investments, they were talking about electricity.

Investors poured money into suppliers such as Electric Bond & Share and Commonwealth Edison, as well as companies using electricity in new ways, such as General Electric (for appliances), AT&T (telecommunications) and RCA (radio).

It wasn’t a hard sell. Electricity brought modern movies, new magazines from faster printing presses, and evenings by the radio.

It was also an obvious economic game changer, promising automation, higher productivity, and a future full of leisure and consumption. In 1920, even Soviet revolutionary leader Vladimir Lenin declared: “Communism is Soviet power plus the electrification of the whole country.”

Today, a similar global urgency grips both communist and capitalist countries about AI, not least because of military applications.

Then came the peak

Like AI stocks now, electricity stocks “became favorites in the boom even though their fundamentals were difficult to assess”.

Market power was concentrated. Big players used complex holding structures to dodge rules and sell shares in basically the same companies to the public under different names.

US finance professor Harold Bierman, who argued that attempts to regulate overpriced utility stocks were a direct trigger for the crash, estimated that utilities made up 18% of the New York Stock Exchange in September 1929. Within electricity supply, 80% of the market was owned by just a handful of holding firms.

But that’s just the utilities. As today with AI, there was a much larger ecosystem.

Almost every 1920s “megacap” (the largest companies at the time) owed something to electrification. General Motors, for example, had overtaken Ford using new electric production techniques.

Essentially, electricity became the backdrop to the market in the same way AI is doing, as businesses work to become “AI-enabled”.

No wonder that today tech giants command over a third of the S&P 500 index and nearly three-quarters of the NASDAQ. Transformative technology drives not only economic growth, but also extreme market concentration.

In 1929, to reflect the new sector’s importance, Dow Jones launched the last of its three great stock averages: the electricity-heavy Dow Jones Utilities Average.

But then came the bust

The Dow Jones Utilities Average went as high as 144 in 1929. But by 1934, it had collapsed to just 17.

No single cause explains the New York Stock Exchange’s unprecedented “Great Crash”, which began on October 24 1929 and preceded the worldwide Great Depression.

That crash triggered a banking crisis, credit collapse, business failures, and a drastic fall in production. Unemployment soared from just 3% to 25% of US workers by 1933 and stayed in double figures until the US entered the second world war in 1941.

The ripple effects were global, with most countries seeing a rise in unemployment, especially in countries reliant on international trade, such as Chile, Australia and Canada, as well as Germany.

The promised age of shorter hours and electric leisure turned into soup kitchens and bread lines.

The collapse exposed fraud and excess. Electricity entrepreneur Samuel Insull, once Thomas Edison’s protégé and builder of Chicago’s Commonwealth Edison, was at one point worth US$150 million – an even more staggering amount at the time.

But after Insull’s empire went bankrupt in 1932, he was indicted for embezzlement and larceny. He fled overseas, was brought back, and eventually acquitted – but 600,000 shareholders and 500,000 bondholders lost everything.

However, to some Insull seemed less a criminal mastermind than a scapegoat for a system whose flaws ran far deeper.

Reforms unthinkable during the boom years followed.

The Public Utility Holding Company Act of 1935 broke up the huge holding company structures and imposed regional separation. Once exciting electricity darlings became boring regulated infrastructure: a fact reflected in the humble “Electric Company” square on the original 1935 Monopoly board.

Lessons from the 1920s for today

AI is rolling out faster than even those seeking to use it for business or government policy can sometimes manage properly.

Like electricity a century ago, a few interconnected firms are building today’s AI infrastructure.

And like a century ago, investors are piling in – though many don’t know the extent of their exposure through their superannuation funds or exchange traded funds (ETFs).

Just as in the late 1920s, today’s regulation of AI is still loose in many parts of the world – though the European Union is taking a tougher approach with its world-first AI law.

US President Donald Trump has taken the opposite approach, actively cutting “onerous regulation” of AI. Some US states have responded by taking action themselves. The courts, when consulted, are hamstrung by laws and definitions written for a different era.

Can we transition to AI being invisible infrastructure like electricity without a another bust, only then followed by reform?

If the parallels to the electrification boom remain unnoticed, the chances are slim.

Cameron Shackell works primarily as a Sessional Academic at the QUT School of Information Systems. He also works one day a week as CEO of Equate IT Consulting, a firm using AI to analyse brands and trademarks.

– ref. Today’s AI hype has echoes of a devastating technology boom and bust 100 years ago – https://theconversation.com/todays-ai-hype-has-echoes-of-a-devastating-technology-boom-and-bust-100-years-ago-265492

Source: The Conversation – Global Perspectives – By Guido Carim Junior, Senior Lecturer in Aviation, Griffith University

“It is the closest all of us passengers ever want to come to a plane crash,”
a Qantas flight QF1889’s passenger said after the plane suddenly descended about 20,000 feet on Monday September 22, and diverted back to Darwin.

The Embraer 190’s crew received a pressurisation warning, followed the procedures, and landed normally – but in the cabin, that rapid drop felt anything but normal.

The truth is, in-flight technical problems such as this one are part of flying. Pilots train extensively for them. Checklists contain detailed instructions on how to deal with each issue. Aircraft are built with layers of redundancy, and warning systems alert pilots to problems. It is because of these safety systems that the vast majority of flights that experience technical issues end with a safe arrival rather than tragic headlines.

Here are four scary-sounding failures you might hear about (or even experience) and how they are actually dealt with in the air.

1. Air-conditioning and pressurisation hiccups

What it is

At cruising altitudes (normally around 36,000 feet), aeroplane cabins are kept at a comfortable “cabin altitude” of 8,000 feet using air from the engines that is cooled through the air conditioner.

This artificial air pressure allows us to survive while the atmosphere outside the plane is highly hostile to human life, with temperatures around -55°C and no breathable air. However, if the system misbehaves or the cabin altitude starts to rise for whatever reason, crews treat it as a potential pressurisation problem and initiate the preventive procedures immediately.

What you might feel/see

A quick, controlled descent (it can feel dramatic), ears popping, and sometimes oxygen masks – these typically drop automatically only if the cabin altitude exceeds roughly 14,000 feet. Similar to QF1889, a rapid descent without masks being deployed is the most common outcome.

What pilots do

As soon as they notice a problem with the cabin pressurisation, the pilots put on their own oxygen masks, declare an emergency, and follow the emergency descent checklist, bringing the aircraft as quickly as possible to about 10,000 feet. This is usually followed by a diversion or return to the departure airport.

2. Most feared: engine failures

What it is

Twin-engine airliners are certified to fly safely on one engine. Yet, one-engine failures are treated seriously and thoroughly rehearsed in flight simulators at least annually.

Dual failures, however, are exceptionally rare. The 2009 “Miracle on the Hudson”, for example, was a once-in-a-generation bird strike event that led to both engines stopping. The plane safely landed on the Hudson River in New York with no casualties.

What you might feel/see

A loud bang, vibration, sparks coming out of the engine, smell of burning or a sudden quietening. This may result in a turn-back and an emergency services welcome. Recent headlines on engine failures – from a 737 in Sydney to a multiple bird-strike-related return in the United States ended with safe landings.

What pilots do

After being alerted by the warning system, pilots identify the affected engine and follow the checklist. The checklist typically requires them to shut down the problematic engine, descent to an appropriate altitude and divert if in cruise, or return to the departure airport if after takeoff.

Even when an engine failure damages other systems, crews are trained to manage cascades of warnings – as Qantas A380 flight QF32’s crew did in 2010, returning safely to Singapore.

3. Hydraulic trouble and flight controls

What it is

The many aeroplane flight controls move because of multiple hydraulic or electric systems. If one system misbehaves – for example the left wing aileron, which is used to turn the aircraft, won’t move – redundancy keeps the aeroplane flyable because the right wing aileron will still work.

Crews use specific checklists and adjust speeds, distances and landing configurations to ensure a safe return to the ground.

What you might feel/see

A longer hold while the crew troubleshoots, a return to the departure airport or a faster-than-normal landing. In July, a regional Qantas flight to Melbourne made an emergency landing at Mildura after a hydraulics issue.

What pilots do

After the warning system’s detection, pilots run through a checklist, decide on the landing configuration, request the longest suitable runway and emergency services just in case.

All these resources are available because lessons learned from extreme events – such as United 232’s 1989 loss of all hydraulic systems – were brought into the design of modern aeroplanes and training programs.

4. Landing gear and brake system drama

What it is

Airliners have retractable landing gears that remain inside a compartment for most of the flight. Those are the wheels that come out of the aeroplane belly before landing. Assembled in the wheels are the brakes. They aim to reduce the aircraft speed after touchdown, like in a car.

With so many moving parts, sometimes the landing gear doesn’t extend or retract properly, or the braking system loses some effectiveness, such as the loss of a hydraulic system.

What you might feel/see

A precautionary return, cabin preparation for potential forced landing, or “brace for impact” instruction from the cabin crew right before landing can happen.

While scary, these are preventive measures if something doesn’t go as planned. Earlier this year, a Qantas flight returned to Brisbane after experiencing a problem with its landing gear; passengers were told to keep “heads down” while the aircraft landed safely.

What pilots do

They’ll use long checklists and eventually contact maintenance engineers to troubleshoot the problem. There are also redundancies available to lower the landing gear and to deploy the brakes.

In extreme cases, they may be required to land at the longest runway available (in case of brake problems) or land on the belly (if the landing gear can’t be lowered).

The big picture

Most in-flight failures trigger a chain of defences aimed at keeping the flight safe. Checklists, extensive training and decades of expertise are backed by multiple redundancies and robust design. And these flights typically end like QF1889 did: safely on the ground, with passengers a little shaken.

A dramatic descent or an urgent landing doesn’t mean disaster. It usually means the safety system (aircraft + crew + checklist + training + redundancy) is doing exactly what it’s supposed to do.

Guido Carim Junior 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.

– ref. These 4 aeroplane failures are more common than you think – and not as scary as they sound – https://theconversation.com/these-4-aeroplane-failures-are-more-common-than-you-think-and-not-as-scary-as-they-sound-265866

Source: The Conversation – Global Perspectives – By Jason Weismueller, Lecturer, UWA Business School, The University of Western Australia

There’s been a striking decline in public confidence in social media platforms, according to the 2025 Ethics Index published by the Governance Institute of Australia. One in four Australians now rate social media as “very unethical”.

This is consistent with other reports on Australian attitudes towards social media. For example, the Digital News Report 2025 similarly identified widespread concern about misinformation and distrust in news shared on social media.

And such distrust isn’t limited to Australia. The sentiment is evident worldwide. The 2025 Edelman Trust Barometer, based on an annual global survey of more than 30,000 people across 28 countries, reports a decline in trust in social media companies.

So where does this negativity come from? And are other ways of consuming information online, such as podcasts, any better? Podcasts are booming in Australia and around the world, and are often perceived much more positively than social media.

Let’s look at what the evidence says about the impacts of social media, what it does and doesn’t yet tell us about podcasts, and what this reveals about the need for accountability across digital platforms.

Where does this distrust stem from?

While social media has enabled connection, creativity and civic participation, research also highlights its downsides.

Studies have shown that, on certain social media platforms, false and sensational information can often spread faster than truth. Such information can also fuel negativity and political polarisation.

Beyond civic harms, heavy social media use has also been linked to mental health challenges. The causes are difficult to establish, but studies report associations between social media use and higher levels of depression, anxiety and psychological distress, particularly among adolescents and young adults.

In 2021, Frances Haugen, a former Facebook product manager, made public thousands of internal documents that revealed Instagram’s negative impact on teen mental health. The revelations triggered global scrutiny and intensified debate about social media accountability.

Whistleblowers such as Haugen suggest social media companies are aware of potential harms, but don’t always act.

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Read more:
Facebook data reveal the devastating real-world harms caused by the spread of misinformation

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Podcasts have a much better reputation

In contrast to social media, podcasts appear to enjoy a very different reputation. Not only do Australians view them far more positively, but podcast consumption has significantly increased over the years.

More than half of Australians over the age of ten engage with audio or video podcasts on a monthly basis. It’s not surprising that the 2025 Australian election saw political leaders feature on podcasts as part of their campaign strategy.

Why are podcasts so popular and trusted? Several features may help explain this.

Consumption is often more deliberate. Listeners choose specific shows and episodes instead of scrolling through endless feeds. Podcasts typically provide longer and more nuanced discussions compared with the short snippets served by social media algorithms.

Given these features, research suggests podcasts foster a sense of intimacy and authenticity. Listeners develop ongoing “relationships” with hosts and view them as credible, authentic and trustworthy.

Yet this trust can be misplaced. A Brookings Institution study analysing more than 36,000 political podcast episodes found nearly 70% contained at least one unverified or false claim. Research also shows political podcasts often rely on toxic or hostile language.

This shows that podcasts, while often perceived as more “ethical” than social media, are not automatically safer or more trustworthy spaces.

Rethinking trust in a complex media environment

What’s clear is that we shouldn’t blindly trust or dismiss any online platform, whether it’s a social media feed or a podcast. We must think critically about all the information we encounter.

We all need better tools to navigate a complex media environment. Digital literacy efforts must expand beyond social media to help people assess any information, from a TikTok clip to a long-form podcast episode.

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Read more:
Critical thinking is more important than ever. How can I improve my skills?

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To regain public trust, social media platforms will have to behave more ethically. They should be transparent about advertising, sponsorships and moderation policies, and should make clear how content is recommended.

This expectation should also apply to podcasts, streaming services and other digital media, which can all be misused by people who want to mislead or harm others.

Governments can reinforce accountability through fair oversight, but rules will only work if they are paired with platforms acting responsibly.

Earlier this year, the Australian government released a report that argued social media platforms have a “duty of care” towards their users. They should proactively limit the spread of harmful content, for example.

A healthier information environment depends on sceptical but engaged citizens, stronger ethical standards across platforms, and systems of accountability that reward transparency and reliability.

The lesson is straightforward: trust or distrust alone doesn’t change whether the information you receive is actually truthful – particularly in an online environment where anyone can say anything. It’s best to keep that in mind.

Jason Weismueller 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.

– ref. People trust podcasts more than social media. But is the trust warranted? – https://theconversation.com/people-trust-podcasts-more-than-social-media-but-is-the-trust-warranted-266791