For those who know the story of Elizabeth Holmes and Theranos, it may seem hard to remember a time when the company was unstoppable.

Read more: AI Promised the World. It’s Not Delivering.

While her name is now permanently associated with fraud and deception, the truth of the matter is that for a time, the company founded by a 19-year-old Holmes in 2003 seemed poised to change the world. Their promise to revolutionise the healthcare industry by providing fast, accurate and painless blood tests caught the attention of many and led to the company’s peak valuation of nine billion dollars in 2014. Combining the potentially paradigm-shifting technology with Holmes’ captivating public persona, the company seemed poised to change the world. 

Despite claims that they could do a full range of blood tests from a pinprick of blood, the company never developed the technology and instead engaged in a variety of deceptive practices to hide this fact. Of course, as is often the case, Theranos’s secret eventually broke and led to the downfall for a company which had once been praised for its “phenomenal rebooting of laboratory medicine”.¹ Indeed, Theranos and Holmes now serve as a prime example of a company both overpromising and underdelivering—or in this case, failing to deliver at all. 

There was only one problem. It was all a lie. 

One of the most interesting facts about Holmes and Theranos comes not from their downfall, but from the origin of the company. While Holmes may have lied about plenty regarding the company, her stated motivation for creating Theranos seems noble on its face: their attempts to create a blood testing process which used minimal amounts of blood stemmed from Holmes fear of needles—a fear which many can relate to. Unfortunately, at the beginning of the venture, Holmes was told by multiple experts in the field that her hope of creating a full suite of tests which worked from a pinprick of blood was not viable²—advice she ignored, and which would later be proven correct. This, I think, is the most interesting part of the Theranos story: despite knowing that the reality of their dream was impossible, the company continued to sell an impossible promise. 

Another Impossible Promise

On August 8, 2025, OpenAI unveiled the long-awaited next-generation version of their large language model chatbot GPT-5 to the public, claiming it could provide “PhD-level” abilities.³ The world’s richest and most controversial man, Elon Musk, took the claim a step further, hyping up his company’s AI Grok as being “better than PhD level in everything”. In May of the same year, Mark Zuckerberg touted the ability for AI chatbots to replace human relationships and friendships.⁴ Zuckerberg has also made similarly lofty claims about Meta’s other technologies, arguing that in the future, anybody who doesn’t own and use AI glasses will “be at a disadvantage”.⁵

Increasingly, AI is being integrated into every aspect of our daily lives, with its loudest proponents claiming that it will solve all our problems. In the fast-food industry, the owners of KFC, Pizza Hut and Taco Bell claimed that they were adopting an “AI-first mentality”⁶(though the company is reportedly rethinking the approach after a customer used the AI to order 18,000 glasses of water).⁷ Interested in learning a new language? Duolingo believes that AI can help the process, with the CEO claiming AI can make employees “four or five times” as productive⁸ (though once again, their adoption of the technology has led to a significant backlash from customers who doubt its effectiveness⁹). Keen to play some games to relax? EA—the publisher of a wealth of large franchises including EA FC(formerly FIFA) and Battlefield—recently announced a 50-billion-dollar sale, relying heavily on the promise of AI to streamline development costs (though gamers and developers alike are less than thrilled). Everywhere you look, AI promises the world. But promises aren’t reality—and there are plenty of good reasons to be suspicious of those with a vested interest in the success of AI. 

The Unfortunate Truth

As a media scholar (and one of the PhD-level people that OpenAI is aiming to replace), I am deeply sceptical of AI. Many of my doubts stem from fundamental issues with how the technology works. While the title “artificial intelligence” implies a level of thought, and the term “large language model” (LLM) seems to indicate an understanding of language, the reality is that these tools neither think nor understand the meaning of words. 

A full explanation of the ways they work is beyond the scope of this article, but on the most basic level, the ways that LLMs and generative AI view language is more akin to a complex math equation. Your prompt is one side of the equals sign and the technology attempts to “solve” for the most likely response. In addition to this process being extremely power intensive (and having negative environmental impacts¹⁰), it is also the reason that despite the hyped improvements in more recent models, AI continues to suffer from widespread “hallucinations”¹¹—where the chatbot either regurgitates inaccurate information or invents entire falsehoods. Indeed, CEO of Open AI Sam Altman has admitted that hallucinations are not an engineering flaw for LLMs but a “mathematically inevitable”.¹² 

Is AI Making Us Dumber?

The issues caused by these hallucinations are significant and may further exacerbate societal issues rather than solve them. A recent report indicated that 45 per cent of AI responses based on news articles contained “significant” errors—with a whopping 81 per cent of responses having some form of issue.¹³ In this age of misinformation, relying on AI seems like a recipe for disaster. More importantly, current research points towards AI having a negative effect on its users, “eroding critical thinking skills”.¹⁴ Furthermore, while it is often thought of as neutral, numerous studies¹⁵ have exposed biases in AI models¹⁶—an unsurprising reality when one acknowledges the potential biases of their creators which may filter in.  

I could go on and on about the issues with AI (and indeed, some of my poor friends have had to endure my rants on the topic in the past). Ultimately however, all these criticisms can be summed up in one sentence. That is, the reality of AI falls drastically short of the promise its creators espouse. 

With all this in mind, I should acknowledge that I am sympathetic to those that want to believe the promise of AI. The world we live in is fundamentally broken in so many ways with political polarisation, environmental destruction and unspeakable injustice occurring daily. And that’s not even acknowledging the more mundane tasks that it could help with. The promise of a “magic bullet” technology that can ease any of the issues we face—just like the promise of a needle-free blood test—is enticing. And it is true that this technology can help in certain situations. As a tutor to international students, machine learning can be a helpful tool in translating complex ideas discussed in our courses (though it still has imperfections that need correcting). My friends who work in software engineering are adamant that it can help make the tedium of coding less strenuous (which is understandable considering coding, like LLMs, also treats language as a sort of math). AI-assisted live transcription is also potentially revolutionary for the hard of hearing. But these are individual solutions for individual problems—and we should not be forced to swallow all the issues with these AI models in order to benefit from them. 

No Silver Bullet?

The reality is, there is no one solution that will solve all our problems. AI cannot create. Every response it gives is based on the existing work of talented artists, writers and experts who it often fails to properly credit. Working as a tutor, I have seen firsthand its negative effects—seeing students inadvertently turn in assignments with invented information and incorrect sources. In seeing AI as the solution to their problems, they have only created more—and greater—problems. 

This, more than anything, is the danger of AI. Proponents like Zuckerberg and Altman want you to believe that it can enhance—or even replace—human connection, but the opposite is true. If you want to learn, create or connect, you can’t do so through AI. You should go to the source, read what others are saying and listen to the experts who have dedicated their lives to solving these problems. Step outside the tech bubble these companies want to trap you in and connect with the real world.

The truth is, no one machine can save the world, nor can any one individual. So don’t give in to the promise of the technology. Connect with reality. Connect with others.  

Article supplied with thanks to Signs of The Times

About the Author: Ryan Stanton is a PhD Graduate from the University of Sydney. A Media and Communications scholar, he is constantly torn between wanting to believe the promise of new technologies and being disappointed by the reality. 

Feature image: Canva

For years, shopping online followed a predictable pattern. You searched, compared, skimmed reviews, opened too many tabs, got distracted, then either bought something or gave up.

It was clunky, time-consuming and mentally draining, but at least the rules were clear. Ads were ads. Advice lived somewhere else.

That separation is disappearing fast.

AI shopping assistants are moving from the sidelines into the centre of the buying journey. Tools like ChatGPT, Gemini, Perplexity and Microsoft Copilot are no longer just helping people research purchases. They are recommending products, surfacing prices, inserting “Buy” buttons and, in some cases, letting users complete a purchase without ever leaving the conversation.

This shift is happening faster than most people realise. Advances in generative AI, changing consumer expectations and growing frustration with traditional online shopping are converging. Add in a generation comfortable outsourcing decisions to algorithms, and the result is a retail landscape that looks fundamentally different to the one we grew up with.

For professionals, retailers and leaders, the urgency is real. This is not just a new marketing channel. It’s a rewiring of how trust, influence and decision-making work in commerce.

Trend 1: Advice and Advertising Are Merging

The first shift is subtle, and that’s what makes it powerful. The line between genuine advice and paid promotion is becoming increasingly blurred.

Modern AI assistants don’t just answer questions. They suggest products, rank options and increasingly prompt users to buy. Microsoft Copilot now embeds shopping recommendations directly into conversational responses. Other platforms have experimented with sponsored answers that sit alongside organic suggestions, often without clear visual distinction.

Unlike traditional advertising, these prompts don’t feel like ads. They feel like guidance. When a recommendation arrives in a conversational tone, supported by what looks like reasoning, people lower their scepticism. The persuasive power comes not from interruption, but from integration.

For consumers, this creates a new challenge. How do you tell the difference between impartial advice and a commercial nudge? One practical habit is emerging: ask the AI why it recommended something. Does it explain trade-offs? Does it offer alternatives? Or does it funnel you toward a single “best” option? Real advice explains choice. Advertising pushes outcomes.

For businesses, this trend rewrites influence. Visibility alone is no longer enough. Products must be defensible, explainable and competitive when placed side by side in an AI-generated comparison. If your offering can’t survive transparent scrutiny, AI will expose that quickly.

Trend 2: Transparency Will Be Forced, Not Volunteered

At the moment, regulation in this space is lagging behind reality. There are few clear rules forcing AI shopping tools to disclose what is paid, what is sponsored and what is genuinely impartial.

That lack of clarity matters for two reasons. First, consumers deserve to know when bias or commercial influence is present. Second, accountability becomes murky when AI systems get things wrong.

A recent example highlighted this risk when an AI travel assistant confidently advised tourists to visit a hot spring in Tasmania that simply does not exist. The issue wasn’t just the hallucination. It was the absence of clear responsibility. Who is accountable when an AI invents reality with confidence?

As AI increasingly shapes purchasing decisions, transparency will become unavoidable. Disclosure around sponsorship, data sources and limitations will be demanded by regulators, journalists and consumers alike.

For leaders and organisations, this is an opportunity to move early. Systems that explain recommendations, acknowledge uncertainty and clearly separate advice from advertising will earn trust long before regulation forces compliance.

Trend 3: AI Is Compressing Hours of Shopping Into Minutes

Despite the risks, the consumer upside of AI-powered shopping is undeniable. These tools are dramatically reducing friction.

Tasks that once took hours now take minutes. Comparing prices across retailers. Summarising thousands of reviews. Tracking historical discounts. Monitoring price changes. In some cases, completing a purchase without opening a single browser tab.

Australian consumers are leading this shift. Research shows a significant majority of Australians have interacted with AI while shopping in recent months, well above the global average. More tellingly, more than half of those users have made purchases based on generative AI recommendations.

This is no longer experimental behaviour. It’s habitual. Many households are already using AI to stretch budgets, find better deals and automate parts of the shopping process.

For businesses, this fundamentally changes discovery. Where search engine optimisation once dominated, answer engine optimisation now matters just as much. If an AI model cannot easily surface, explain and justify your product, it effectively disappears from consideration.

Trend 4: The Weekly Grocery Shop Is Being Rewritten

AI-driven shopping is not confined to screens. It is reshaping physical retail too.

Smart carts and supermarket apps already allow shoppers to scan items as they go, track their total in real time, receive personalised discounts and pay without lining up. But the bigger transformation is happening quietly in the background.

Experts predict supermarkets will become smaller and more focused on fresh food. Pantry staples like toilet paper, nappies and cleaning products will increasingly be reordered automatically and delivered to homes without conscious effort.

In practice, in-store shopping becomes about choice, quality and freshness, while AI handles repetition behind the scenes. Two shoppers standing in the same aisle may see different specials because the system understands their habits, preferences and household needs.

AI is also changing how decisions are made in the moment. A shopper considering a new pair of headphones can take a photo, upload it to an AI assistant and instantly receive a comparison across models, prices and stores, including historical data showing whether a discount is likely soon.

For retailers, loyalty will be driven less by location and more by usefulness. The brands that win will be the ones that integrate seamlessly into consumers’ decision-making systems.

Trend 5: Trust Becomes the Ultimate Competitive Advantage

As AI takes on more of the buying journey, trust becomes the scarce resource.

These systems are persuasive by design. They speak with confidence. They explain reasoning. They feel personal. That makes over-reliance a real risk.

Consumers will increasingly judge platforms not by how clever they are, but by how transparent and controllable they feel. Can users understand why something is being recommended? Can they override it? Can they see alternatives?

For professionals building or deploying these tools, the goal should not be to remove humans from the loop, but to keep them meaningfully informed. Trust grows when people feel empowered, not nudged.

Brands that over-optimise for persuasion may win short-term sales, but they risk long-term credibility. Restraint, clarity and honesty will prove more valuable than cleverness.

What This All Means

AI-powered shopping is not a future scenario. It is already reshaping how people research, decide and buy. The five trends are clear. Advice and advertising are merging. Transparency will be demanded. Shopping is becoming faster and more automated. Physical retail is being re-engineered. And trust is becoming the defining differentiator.

The challenge for leaders and professionals is not technical. It is behavioural. Understanding how people make decisions when AI is in the room, and designing systems that support rather than exploit that reality.

The question is no longer whether AI will influence what we buy. It already does. The real question is whether we build a shopping ecosystem that is helpful, honest and human, or one that quietly nudges us while pretending not to.

The difference will come down to the choices being made now, while the rules are still being written.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

Not long ago, humanoid robots sat firmly in the category of “cool demo, wildly impractical.” They dazzled on conference stages, tripped over their own feet on YouTube, and then quietly disappeared back into research labs. That phase is ending fast.

Humanoid robots are moving from spectacle to systems. From factories and hospitals to aged care facilities and, eventually, our homes, they are inching closer to everyday life. Goldman Sachs estimates there could be more than 13 million humanoid robots in use globally by 2035. That’s less than a decade away. While most of these robots will appear in workplaces first, the ripple effects will be felt across households, cities and entire industries.

The drivers are converging rapidly. Advances in AI vision, balance and hand dexterity are accelerating. Labour shortages are intensifying as populations age and fewer people enter physically demanding roles. Cultural expectations are shifting around convenience, care and the value of time. And younger generations are far more comfortable sharing space with machines than any before them.

For leaders and professionals, the question is no longer whether humanoid robots will matter, but how quietly and quickly they will reshape expectations. 

1. From Sci‑Fi Spectacle to Quiet Utility 

The first major shift is psychological. Humanoid robots are not arriving with dramatic flair or cinematic ambition. They’re slipping in through side doors, doing the dull jobs no one wants to talk about at dinner parties.

We already live with robots, even if we don’t think of them that way. They vacuum our floors, mow our lawns and assist surgeons. In fact, more than 80 percent of prostate surgeries are now performed using robotic systems. COVID accelerated this trend, particularly in agriculture and logistics, where closed borders and labour shortages forced rapid adoption.

Humanoid robots represent the next logical step because they fit into environments built for humans. Factories, warehouses and hospitals don’t need to be redesigned when the robot has two legs, two arms and can use existing tools. That’s why companies like BMW, Hyundai and Tesla are already trialling humanoid robots on factory floors for repetitive and physically demanding tasks. Hyundai has publicly stated it plans to deploy humanoid robots in US factories from 2028.

China offers a glimpse of what early adoption looks like at scale. Humanoid robots are already working as tour guides, retail assistants, warehouse staff and service workers, with some even assisting in policing and security roles. Dedicated robot training centres allow machines to learn by observing humans rather than being painstakingly programmed line by line. 

The implication is clear. Early adoption will be quiet and practical rather than flashy. Organisations that treat humanoid robots as boring infrastructure rather than futuristic mascots will extract far more value from them. 

2. Cobots, Not Job Stealers 

It’s impossible to discuss humanoid robots without confronting workforce anxiety. Elon Musk has said Tesla aims to build up to 100,000 humanoid robots per month within five years. Numbers like that naturally raise concerns about job losses.

But the reality is more nuanced. Humanoid robots are particularly good at jobs humans increasingly struggle to fill. Dirty, dangerous and repetitive work. Heavy lifting. Night shifts. Tasks that lead to injury, burnout or high turnover.

Robots are already being used for warehouse picking, post‑surgery rehabilitation support and repetitive assembly. Deloitte predicts physical AI and humanoid robots will play a major role in addressing labour shortages, especially as populations age and healthcare demand grows. 

Rather than replacing humans, most experts expect robots to change the nature of work. This is where the idea of “cobots” becomes critical. Collaborative robots that work alongside humans, taking on physical or repetitive tasks while people move into supervision, creativity, problem‑solving and decision‑making roles.

For organisations, the real opportunity lies in redesigning jobs, not eliminating them. Professionals who focus on skills like judgement, empathy, oversight and systems thinking will become more valuable, not less.

3. Impressive, Fallible and Still Learning

The technology behind humanoid robots has advanced rapidly, particularly in vision systems, balance and hand dexterity. Some recent demonstrations have been so realistic that audiences questioned whether they were watching a robot or a human in disguise.

At the same time, viral clips of robots face‑planting, freezing mid‑task or dropping objects are not anomalies. They are part of the learning curve. This is what early‑stage intelligence looks like in physical form.

Robots perform best in controlled environments like factories and warehouses. Homes are far more challenging. Pets move unpredictably. Children run. Objects shift. Lighting changes. Most humanoid robots today still rely on some level of human supervision or remote assistance for complex tasks.

This phase closely mirrors the early days of self‑driving cars. Highly impressive in certain contexts, unreliable in others. The risk is not that robots will fail, but that humans will assume they won’t.

Organisations that succeed will design systems that assume occasional failure and build safeguards accordingly. 

4. The Home Robot Will Sell Time, Not Wow 

When humanoid robots enter homes, affordability and accessibility will dominate the conversation. Today, a humanoid robot like Neo costs around $20,000. By 2035, that figure is expected to fall closer to $10,000 as manufacturing scales and components become cheaper. 

But ownership won’t be the starting point for most people. Early home robots will be aimed at wealthy households, aged care facilities and people with mobility needs. LG has already demonstrated prototype home robots capable of folding laundry and preparing simple meals, while projects like Tombot, a robotic puppy designed to support people with dementia, show how emotionally intelligent design can support care settings. 

For most households, the first exposure will likely be shared robots in apartment buildings, hotels or assisted living environments rather than owning one outright. Leasing models and robot‑as‑a‑service offerings will play a significant role in improving accessibility.

The real appeal is not novelty. It’s time. Even saving 30 to 60 minutes a day by offloading repetitive tasks changes how people live, work and rest.

5. Trust Will Matter More Than Life-like Design

Safety, privacy and psychological trust will ultimately determine whether humanoid robots are accepted into daily life. Most are designed to be lightweight, slow and compliant, stopping when they encounter resistance.

Privacy is a genuine concern. Robots rely on cameras and sensors to navigate spaces, raising questions about data storage, access and ownership. There is also the risk of over‑trust. Robots that look human can trigger emotional responses even when people know they are machines.

Experts agree humans will remain in the loop for a long time, particularly in homes and healthcare settings. Acceptance will depend less on realism and more on whether people feel in control of the technology.

There is also a genuine fear response to consider. An estimated 20 percent of the population experiences some degree of robophobia. Ignoring that reality would be a mistake. 

What This All Adds Up To

Humanoid robots are not coming to replace us, impress us or entertain us. They’re coming to quietly reshape how work gets done, how care is delivered and how time is reclaimed.

The trends are clear. Practical utility over spectacle. Collaboration over replacement. Rapid progress with real limitations. Time as the killer feature at home. Trust as the deciding factor everywhere. 

The future won’t arrive with a dramatic unveiling. It will arrive task by task, shift by shift, home by home. The robots are learning fast. We should too.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

When news broke that Disney had signed a landmark agreement with OpenAI, the reaction across the creative industries was mixed.

At a time when much of Hollywood is resisting artificial intelligence, launching legal challenges, or warning of creative collapse, Disney chose a very different path.

Rather than treating AI as an existential threat, Disney treated it as a question.

How could this technology help us tell better stories? How might it expand creativity rather than diminish it? And how do we engage with it early, thoughtfully, and on our own terms?

The agreement allows OpenAI to work with Disney’s vast library of characters and storytelling assets across emerging AI animation and generative video tools. It is an extraordinary move, not just because of the scale of the deal, but because of what it signals.

Disney is once again choosing partnership over protectionism. Exploration over resistance. Curiosity over certainty.

To understand why this decision matters so much, you need to see it not as a one off, but as the latest chapter in a pattern that stretches back more than a century.

This is not a company dabbling in disruption. Disney is a company that has always believed the future belongs to those willing to rethink first.

Walt Disney built an empire not by predicting the future, but by being relentlessly curious about what might be possible.

Long before Disney became synonymous with global entertainment, Walt Disney was an outsider. He was not backed by powerful studios, nor was he working within accepted industry rules. His success came from repeatedly asking questions others dismissed as impractical or reckless.

What if animation could carry emotional weight? What if stories could live across multiple platforms? What if entertainment could be experienced as a place, not just a performance?

These were not safe questions.

In the 1930s, when Disney decided to create Snow White and the Seven Dwarfs, industry insiders openly mocked the idea. Feature length animation was considered commercial suicide. Cartoons were short, disposable novelties. No one believed audiences would sit through ninety minutes of illustrated storytelling.

Disney nearly bankrupted his company bringing Snow White to life. He invested in new animation techniques, new camera technology, and unprecedented levels of artistic detail. What he was really investing in, however, was a belief that curiosity about emotional realism would be rewarded.

It was. Snow White did not just succeed. It created an entirely new category of cinema.

That same pattern repeated in the 1950s, when television emerged as a disruptive force. Hollywood studios panicked. Cinema attendance declined. Executives treated television as a threat to be resisted.

Disney Again Went The Other Way.

Rather than rejecting television, he partnered with ABC to create a weekly television series. On the surface, it was entertainment. In reality, it was something far more strategic. The show helped finance, promote, and emotionally prepare audiences for Disneyland, a physical place that did not yet exist.

Television was not competition. It was infrastructure.

That deal helped fund Disneyland’s construction and made Walt Disney himself a household name. At a time when business leaders remained largely invisible, Disney became the face of his vision. Not as a corporate executive, but as a guide, a storyteller, and a trusted presence in people’s homes.

Again, Curiosity Reshaped The Rules.

Disneyland itself was another audacious experiment. Walt Disney rejected the idea of building an amusement park. He disliked the chaos, the noise, and the transactional nature of existing parks. Instead, he imagined something different.

A theme park. A place where architecture, psychology, storytelling, and movement worked together to create a coherent emotional experience.

Buildings were deliberately designed to feel welcoming rather than overwhelming. Pathways controlled anticipation and discovery. Attractions were not rides, but experiences. Guests could spend an entire day immersed in story without stepping onto a single attraction.

It was entertainment designed around humans, not hardware.

Since opening in 1955, more than one billion people have visited Disneyland. That number alone tells a powerful story about the enduring appeal of human centred design driven by curiosity.

Crucially, Disney’s culture did not fossilise after Walt’s death.

When the company acquired Pixar in 2006, it faced a choice. Absorb Pixar and impose corporate discipline, or protect the very culture that made Pixar special.

Disney Chose Protection.

Pixar’s creative model rewarded questioning, dissent, and rethinking. Hierarchy mattered less than ideas. Disagreement was not seen as disloyalty, but as a necessary ingredient for excellence. Some of Pixar’s most successful films emerged precisely because creators were encouraged to challenge assumptions rather than conform to them.

This was curiosity embedded at scale.

Under Bob Iger’s leadership, that philosophy continues. Listening to an interview with Iger recently, I was struck by his admission about how Disney evaluates new ideas. The first question is not about cost. It is not about risk mitigation.

The First Question is Simple: Can we make this great?

That mindset explains why Disney’s response to artificial intelligence looks so different to many of its peers.

Where others see loss of control, Disney sees creative leverage. Where others fear displacement, Disney sees expansion. Where others hesitate, Disney experiments.

The OpenAI partnership echoes the ABC television deal of the 1950s. In both cases, Disney encountered a new technology that unsettled an industry. In both cases, it chose engagement over retreat.

This does not mean blind optimism. Disney has learned from missteps, including the difficult early years of Disneyland Paris. But even those moments reinforced a deeper truth. Curiosity must be paired with accountability. Experimentation must be paired with learning.

That balance is what allows curiosity to endure.

Walt Disney once said that Disneyland would never be finished, as long as there was creativity left in the world. He was not talking about a park. He was talking about a posture.

A refusal to believe the story is ever complete. A willingness to revisit assumptions. An understanding that relevance is not preserved through protection, but through exploration.

The OpenAI partnership is not a departure from Disney’s identity. It is proof that the identity still holds.

In a world obsessed with prediction, Disney continues to bet on curiosity. And history suggests that is a very good bet indeed.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

Feature image: Canva

The future of privacy has arrived quietly, woven into our daily routines so seamlessly that most of us barely notice how much of ourselves we are giving away. Workplaces, cars, shops, neighbourhoods and even our own devices are now part of a growing ecosystem of surveillance reshaping how we live and work.

This shift is being fuelled by rapid advances in technology, a cultural appetite for convenience and personalisation and a regulatory system still scrambling to catch up. For leaders, employers and professionals, the message is clear. These changes are accelerating and recognising them early is essential.

1. Worker Monitoring Is Becoming Everyday

Digital oversight has become surprisingly normal. Employers are now using everything from Microsoft Teams’ new location tracking to keystroke loggers, webcams and GPS tools. Around two-thirds of companies use at least one form of monitoring. What started as a temporary pandemic solution has evolved into an everyday feature of remote and hybrid work.

The issue is not legality. Most of this is legal because Australia’s workplace privacy laws are years behind the technology. The issue is trust. When people feel watched, the home office can start feeling like an open-plan cubicle with better lighting. Some states are finally starting to consider tighter rules around what employers can reasonably track, but the cultural impact is already here. Teams perform better when trust is high and surveillance rarely builds trust.

2. Cars Are Becoming Data Factories

Modern vehicles are now data-hungry machines. A typical car produces about 200GB of data per hour and vehicles with advanced driver-assist or autonomous capabilities can generate up to 1.4TB in the same timeframe. They record where you drive, how you brake, how fast you take corners, the tone of your voice commands and even how you interact with the entertainment system.

Employers are increasingly tracking staff in work vehicles and sometimes after hours. Manufacturers are collecting even more. One major carmaker was caught storing and sharing photos and videos recorded inside customer vehicles. This wasn’t a technical glitch. It was a glimpse into just how much visibility companies now have into our personal lives. Cars used to be private spaces. Now they are mobile data centres and most drivers have little idea what is being captured, where it goes or who can access it.

3. Facial Recognition Is Moving Into Everyday Life

Once a futuristic idea, facial recognition has slipped quietly into daily routines. Several major Australian retailers were found to be scanning customer faces in-store without proper consent. The Privacy Commissioner ruled it illegal, setting a major precedent.

Yet the technology continues to spread. In parts of the United States, you can already board a plane with a face scan instead of a boarding pass. Many stadiums use it to manage crowds and security. One fast-food chain even used facial recognition to identify hungover customers and offer them discounts, which is either clever marketing or a sign we have overcorrected on personalisation.

Public sentiment is shifting fast. More than half of Australians say facial recognition in retail feels like an invasion of privacy. The technology is moving faster than public comfort and far faster than updated regulations.

4. Cameras Are Everywhere and the Idea of Public Space Is Changing

CCTV used to belong to governments and shopping centres. Today, anyone with a doorbell camera or home security system is contributing to a rapidly expanding layer of community surveillance. We are filmed dozens of times a day. Sydney has roughly one camera for every 80 residents. London has one for every 13. In Shanghai and Beijing, it is one for every two people.

Doorbell footage that once lived on a small local device now sits in cloud databases managed by large tech companies. Overseas, police have increasingly requested access to this footage, raising complicated questions about consent, ownership and the rights of people captured incidentally while simply walking past.

The line between safety and surveillance is getting thinner and many people do not realise how visible their everyday movements have become.

5. The Debate Over Whether Our Devices Are Listening

Ask almost anyone whether their phone is listening to them and you will hear the same story. They mention a product once and find it following them around the internet shortly after. Tech companies insist they are not using phone microphones to target ads. Yet public suspicion is growing and the stories keep multiplying.

Whether microphones are involved or not, voice is becoming the next frontier of data capture. Smart speakers, phones, watches, TVs and cars are equipped with microphones that are always partially awake, listening for wake words. Every new layer of surveillance, from face to movement to voice, generates highly sensitive personal data and individuals have very little control over how long it is kept or who it is shared with.

Hyper-personalisation may be convenient, but many are beginning to question the cost.

The Choices We Make Now Matter Most

Taken together, these five trends show a world moving rapidly toward deeper monitoring and a growing tension between convenience and control. The benefits are real. Better safety, smoother travel, more personalised services and more efficient workplaces. The challenge is finding balance.

Surveillance becomes harmful when it is invisible, unregulated or unchecked. The real issue is consent. Not the tick-a-box kind but genuine, informed consent where people understand what is being collected and why.

This moment calls for curiosity rather than complacency. For leaders, it means being transparent and thoughtful about how monitoring technologies are used. For governments, it means updating laws at the speed of technology rather than the speed of bureaucracy. For individuals, it means paying attention.

The future of privacy will not be defined by the technology itself but by the choices we make about it. We can embrace innovation without surrendering autonomy. We can enjoy convenience without forfeiting trust. The question is not whether surveillance will grow. It is how intentionally we manage it so the future we build still feels like our own.

Article supplied with thanks to Michael McQueen.

About the Author: Michael is a trends forecaster, business strategist and award-winning conference speaker. His most recent book Mindstuck explores the psychology of stubbornness and how to change minds – including your own.

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“It’s a great question, but I need to be honest up front and say, folks, I think the phrase is the horse has bolted. We live in a tech world,” said the National Grandparenthood Movement’s Ian Barnett.

That doesn’t mean parents and grandparents are powerless though. 

“We can’t avoid technology altogether, but we can create spaces that prioritise connection, real-world connection,” he said.

Creating Spaces of Connection

In Ian’s home, he and his wife have tried something many families might find refreshing. 

“When people come around to visit, they actually put all their phones in a basket,” he said. It’s a simple way to avoid distractions. 

“That means you’re not going to get distracted. That’s the problem with iPhones and iPads, you get distracted. Including the parents, including the grandparents!”

Instead, the Barnetts plan activities. “My wife has one of our granddaughters involved in making stuff, cooking, working in the garden,” he said.

“Or I’ll take one of the grandkids to play putt-putt golf. You’ve got to think about what you’ll do if you’re not going to use devices.”

The Value of Tech-Free Moments

The goal isn’t about punishment or nostalgia. It’s about reclaiming space for conversation and imagination. 

“We used to talk over the fence; we used to talk on the streets. It’s all changed. But [parents and] grandparents can model something different.”

Even the Australian Government is taking screen time seriously, introducing new age-based restrictions on platforms like Instagram and TikTok for under-16s from December 2025. 

“If a secular government is concerned about access, then we as parents and grandparents have to be concerned, too,” he said.

That means thinking intentionally about when and how technology is used.

Finding Balance, Not Banning Devices

While some may dream of a completely screen-free zone, Ian warned against extremes. 

“Can I live in Utopia where there’s actually no technology whatsoever in my home? Probably not,” he laughed.

He pointed out that technology has its place, even for bonding. 

“I bought a Nintendo Switch so I could play sports games with my grandkids. There’s good stuff you can do.”

The key is balance. “Technology itself isn’t the problem; it’s the love of technology. It’s how you engage with it that matters.”

Giving Kids “a taste of something better”

For parents and grandparents wanting to create healthier tech habits for their grandkids, Ian offers these tips:

• Plan activities in advance. “Have things set up before they visit, it makes it easier to say no to screens.”
• Talk about what they’re seeing and doing. “When I used to push my kids in the pram, I’d talk about what they could see. Today, parents and kids are both staring at screens.”
• Set limits without shame. “Don’t make the screen so important in their lives. Use it as a reward after doing something active or creative.”
• Keep conversations flowing. “Your kids and grandkids still want to connect. They’re watching how we use our phones too.”

“Give them a taste of something better… Mums and dads and grandparents, give them a taste of heaven.”

A Home That Feels Like an Oasis

It’s encouraging to remember that a home can be an “oasis of engagement and enchantment”, not a place of restriction, but of restoration.

“When my grandkids visit, they know they’re stepping into a different environment,” he said. 

“We play games, go bike riding, or work in the garden. It’s a whole other experience. And I think it’s a break they actually enjoy.”

“Think about how you can give your [kids or] grandkids real-world experiences,” Ian said. “That’s the kind of connection that lasts.”

Article supplied with thanks to Christian Media & Arts Australia.

This article was prepared with AI assistance and carefully reviewed by our Digital team.

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