clearai

Fool me once

Tue, 31 Mar 2026 15:27:26 GMT

Fool me once

WRITTEN BY JISOO KIM

THE INTERVIEW

JK: I want to start with the landscape. When you look at AI-generated misinformation and disinformation right now, what are we actually dealing with?

CH: The way you can look at this in a very hopeful sort of way is that yes, there is a lot of mis and disinformation online, but we also don't have a particularly great read as to whether any of it's effective. There is no easy way to measure the effectiveness of any kind of influence operation. That goes back to the Cold War if not before. If you read Thomas Rid's book, Active Measures , both sides were doing leaflet drops over East or West Berlin. It was a specatacle, but we don't know if any of that worked. And the same is true today.

JK: So we don't actually know if mis/disinformation and deepfakes are working?

CH: We don't. And that's actually kind of good news, in a way. But the inverse of that is you can't measure the policy response either. So people don't need to roll over and give up on this – they definitely shouldn't – because people do believe information that runs counter to fact, and that sucks. We need to build up people's media literacy to counter that. A lot of it is in the eye of the beholder, which I find really fascinating. A lot of people in government talk about how difficult it is to counter disinformation emerging from Russia and China, but we have no metric for whether it's doing what it says on the tin.

JK: Let's talk about Romania, because I know you’ve done comparative studies on it and I think it's one of the most concrete recent examples of this playing out at a national level.

CH: Romania is a really instructive case. In 2024, you had false information generated at scale posted to TikTok – a heap of content regarding certain candidates allegedly influenced by foreign powers, all in support of a candidate called Călin Georgescu, who was allegedly backed by Russia. His win in the first round of 2024 Romanian election was ultimately overturned by the Romanian government and judiciary, and was the first real test of the Digital Services Act, with the support of the European Commission. But here's the thing – there was no evidence that the content was necessarily effective or that people believed it en masse. Of course, in anecdotal examples we saw that people were believing it, and that's horrifying. But there was no real evidence it was decisive.

JK: And what did the regulatory response actually look like on the ground?

CH: The Digital Services Act places a number of quite hefty obligations on online service providers. I prefer that term to ‘platforms’, because ‘platforms’ implies a lack of agency on the part of these actors. TikTok was hauled before the European Commission and issued with a please-explain. They collaborated with the EU and the Romanian government to try and address what had occurred. When the re-run elections were held in May 2025, TikTok hired Romanian-language content monitors for the first time. There's a great report from CeTAS (the Centre for Emerging Technology and Security) at the Alan Turing Institute that covers electoral disinformation in 2025 in detail. Mostly what we saw wasn't necessarily deepfakes. It was false content generated at scale. Memes. Volume. Speed.

JK: That's something I want to push on – because there's a common assumption that the deepfake is the threat. The hyperrealistic video. But what you're describing sounds more like a flood of low-quality content that just... overwhelms.

CH: Exactly. And watermarks aren't the silver bullet people think they are. There's a great example with Sora, OpenAI's video generation tool, which always generated watermarked content. And then people just cropped the video to remove the watermark and posted it. The existence of a watermark is not the answer to false information spreading. My colleague Sam Stockwell at the Alan Turing Institute has gone through and found examples from Poland, the Czech Republic, and Canada – deepfake videos, scam promotions using politicians' likenesses – and in most cases the hook was that they weren't watermarked. But that framing misses the point. The harm doesn't require technical sophistication. It requires reach.

JK: So what does actually work? Because when ClearAI wrote the Menzies Research Centre AI policy paper , one of our recommendations was digital literacy – and some pushback we initially got was: it's too sophisticated now, you can't teach people to spot this stuff. What do you think?

CH: I think that's wrong, actually. Media literacy is a core part of the answer and you absolutely can teach it. The Nordic states and the Baltics are the shining example of how you can build whole-of-society capacity against misinformation – and you do it by teaching critical thinking, not by telling people what to believe. You teach people to ask: is this piece of content trying to make me angry? If the answer is yes, that's a signal. Does it look a little blurry? Is the mouth sitting in a funny position? Are there other sources corroborating this? A reverse image search on Google is honestly one of the most powerful open-source intelligence tools available to a regular person. Low barrier to entry. Freely available. Devastatingly effective.

JK: I actually got duped by a deepfake recently – a video of a prominent Australian politician collapsing in the Senate – and I scrolled past it. Didn't investigate. It stuck in the back of my mind until the pollie themselves posted a correction. And I thought, if they hadn't posted that, it just would have sat there in my brain.

CH: So have I. And I think that's actually the key point – you don't have to be able to spot every piece of fake content. You have to have a level of calibrated scepticism. Is this making me feel something strongly? Is it designed to make me angry or afraid before I've even thought about whether it's true? Just taking a breath, stopping before you share is most of the battle. It's good life advice in general, but it's specifically good advice for navigating the information environment we're in now.

JK: I want to talk about Australia specifically. Because the eSafety Commissioner can fine up to $49.5 million. We've got voluntary codes. We're standing up an AI Safety Institute. And yet, I look at what happened with DeepSeek being banned in some countries, Grok's nudification feature being redlined in places like Malaysia, and I think, where are the teeth?

CH: eSafety has, for much of its life, relied on voluntary standards and the compliance of platforms to keep people safe. It's done this with social media, with child safety, and it's probably going to try to do the same with AI. That's never really been effective, if we're brutally honest. The number of times eSafety has put out comms asking industry, "Why haven't you complied with this voluntary code of conduct?" That's not a regulatory posture, that's a request. The fines are technically enforceable, but for the size of these firms you need to be charging maximum penalty units to make that land. And even then, for a company operating across multiple jurisdictions, $49.5 million is a rounding error. What's needed is stronger regulatory controls – whether that's an AI Act or mandatory guardrails that AI platforms must comply with to operate in the Australian market.

JK: And our new AI Safety Institute, what will it need to actually be useful?

CH: It needs teeth . There is only so much benchmarking of models you can do before people start asking: so what? You've measured that this model is more likely to generate harmful content – great. If the AISI isn't plugged into something with genuine enforcement power, the whole thing risks falling over. Allegra Spender [Federal Member for Wentworth in NSW] made this point really clearly – the Commission can't just be an organisation that writes reports. It needs a right hook. Done right, it's a very exciting possibility. But it needs to be willing to go toe-to-toe with industry in the interest of community safety, not scoring points for political reasons.

JK: Last question. For someone reading this who isn't a policy person, isn't a researcher – what's the one thing they should actually do?

CH: Be critical, not paranoid. For any piece of media you consume, regardless of whether it's a newspaper, a TikTok, a WhatsApp forward – ask yourself: is this designed to make me feel something before I've thought about whether it's true? If yes, pause. Use a reverse image search. Check whether other sources are reporting the same thing. The main tool for discerning what's real from what's manipulative is up here, in your head. And it's actually not that difficult to just not believe everything you're spoonfed.

CLOSING THOUGHTS

I left this conversation thinking about something Callum said early on – that we don't actually know if AI-generated mis/disinformation or deepfakes are working. If we can't measure the harm, we can't measure the fix either. We're flying a little blind. But what I do know is that the gap between what's possible and what's governed is real, and it's growing. Australia has the ingredients to do this well: a capable public service, a legitimate shot at an effective AISI, and homegrown researchers like Callum who understand both the technology and the policy levers. What's been missing is urgency. And teeth.

I join many other voices in saying that the AISI needs genuine enforcement power, not just benchmarking capability. Voluntary codes have had their chance.

But to industry, I’d say that they shouldn’t be treating governance as a PR exercise. If you're operating in the Australian market, you have a civic obligation to the people in it. Hire the researchers. Build the policies. Or expect regulators to do it for you, eventually, and less elegantly.

For the rest of us: the workers, the uni students, the executives, the parents, the people just trying to figure out what's real:

Pause before you share. Anger is a signal, not a prompt to act.
Use Google reverse image search. It doesn't take long and it works.
Check whether other sources are reporting the same thing before you let it settle into your memory as fact.
Treat Facebook, TikTok and other social media sites as entertainment, not news infrastructure.
Ask your local MP where Australia stands on mandatory AI safety standards for the tools millions of us use every day.

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

INTRO NOTE

Something has changed in how we relate to information online. Most of us can feel it.
AI-generated images, videos and voices are now cheap, fast and convincing enough to fool anyone on a bad day. The result isn't a world full of people believing everything they see. It's a world where people have stopped trusting anything at all.

That loss of trust has a cost. Democracy doesn't run on perfect information – but it does need a shared baseline of reality. When that erodes, so does everything built on top of it.

So it’s probably good that I sat down with Callum Harvey for a chat. He’s currently doing his PhD at the Oxford Internet Institute researching cyber threat intelligence and AI policy. His prior roles span the Australian Department of Industry, Science and Resources, CyberCX, and the Harris Cyber Policy Initiative at the University of Chicago. We talked about where we are at with mis/disinformation and deepfakes: what's working, what isn't, and why the answer probably starts smaller and closer to home than we think.

OTHER INSIGHTS

Agency in the age of AI

Tue, 17 Mar 2026 09:42:51 GMT

Agency in the age of AI

WRITTEN BY JISOO KIM

THE INTERVIEW

JK: What are Australians most worried about with AI right now?
MN: A lot of it comes down to safety and trust. People are excited about the benefits, but they don’t feel secure. They’re not sure if the systems meet their safety expectations, and they don’t know who to trust. Our data shows it’s not just a skills gap – people have genuine safety concerns and feel like the guardrails aren’t there yet.

JK: Why does trust feel so fragile in the AI space compared with other tech?
MN: Trust matters more when something is unfamiliar. People didn’t trust elevators when they first removed the human operator. They didn’t trust smartphones or social media when they arrived either.

We need experience with a technology to calibrate our trust. Historically, we learned the hard way with planes and cars. Early planes really were dangerous. Cars were extraordinarily dangerous before seatbelts (and they’re still risky today – roughly a 1% lifetime risk of dying in a car crash).

In a way, we should be less trusting of familiar dangerous things, like cars and backyard pools, and more trusting of some new technologies that are actually safer. With AI, people are scared largely because it’s new. That fear is understandable, but it should be balanced against the actual base rates and statistics, not just scary stories.

JK: To help with this, is our government showing leadership on AI?
MN: On some technologies, yes. The social media ban for young people is a good example. The evidence was pretty clear that social media, on average, harms adolescent mental health. Our government looked at the data, saw that this was both necessary and popular, and led the world with the ban. That shows we can do evidence‑based tech policy and even lead globally.

On AI, they’re doing some good things – putting effort into training people and incentivising business adoption, and standing up an AI Safety Institute to fund experts to assess risks. But when you look at the serious risks on a 1-5 year horizon, there hasn’t been much substantial movement yet.

JK: What AI safeguards are still missing in Australia?
MN: A really obvious one is safety testing for the biggest, most capable models before deployment. California, for example, has brought in a rule that the really large, potentially dangerous models need to be tested for safety before they’re rolled out. That’s completely normal in every other high‑impact industry: f ood, pharmaceuticals, engineering and aviation.

We always expect serious safety testing before powerful technologies are deployed at scale. We don’t have that same culture or standard yet for AI in Australia, and it’s strange, because it’s such a basic, common‑sense expectation .

JK: How do AI companies themselves feel about regulation?
MN: Many of them actually want a level playing field. Some companies are already spending real money on safety testing, risk assessments, and audits. Others are doing an abysmal job and just racing ahead.

If one company invests in safety and another doesn’t, the unsafe one can move faster and pick up more market share. In any other sector, we would regulate the renegades. That’s essentially what thoughtful AI regulation is trying to do: set minimum safety standards, require testing and transparency and stop a race to the bottom on risk. It’s not about banning everything. It’s about holding AI to the same standards we expect from any other powerful technology.

JK: Going back to Aussies having low trust in AI, how big a role does data privacy play in that?
MN: It’s massive. It’s one of the top things stopping people from using AI at work. They see that the tools are amazing, but they don’t know where the data is going, and unless you’re already a privacy or data expert, it’s really opaque.

We also see that people are often worried about the wrong things. Some won’t use WhatsApp because it’s owned by Meta, but they happily post all their kids’ photos and birthdays on Instagram. What we really need is calibrated trust. Be doubtful where you should be – like companies clearly using your data to sell ads. Be trusting where you should be – for example, paid AI tools with training turned off, where data is held briefly then deleted.

If it’s true that using a modern AI model with training turned off is as safe as sending a Gmail, that would be really comforting for people, because they’ve been using Gmail for 10-15 years without worrying too much about data security.

JK: So is this just a communications problem or do our privacy laws need to change?
MN: Probably both. Either we need laws that are better adapted to AI so you can clearly explain to people what’s okay and what’s not, or we need to translate the existing laws into language and analogies people actually understand. Right now, it’s too hard for a normal person to know whether it’s safe to put their data into an AI tool.

JK: Going back to what you said about 'calibrated trust'. How does that play out with everyday AI use?
MN: A good example is someone doing their tax. I spoke to a guy whose wife was spending the whole weekend sorting tax receipts. I threw Claude’s Cowork feature at a folder of receipts, made a coffee, and came back three minutes later – it had filed them exactly the way he would have expected.

But he still felt nervous about his tax data “going up into somewhere”. In reality, that kind of use – especially with a paid subscription and training turned off – is closer to how we already use Gmail. Your email is in the cloud, it can theoretically be subpoenaed, but day‑to‑day, it’s a reasonable, well‑understood risk.

A lot of what we’re seeing is a skill and literacy issue, not necessarily a law issue – like people accidentally sharing ChatGPT chats publicly so they get indexed by Google. That’s more like having your Google Docs set to “anyone with the link” and then blaming Google when it leaks. People need both clearer rules and better mental models.

JK: Beyond privacy, why are some people resisting AI in their work?
MN: Job insecurity is a big psychological driver. I’ve got a colleague who built a tool that can plan a whole semester of university teaching content. The first reaction from some staff wasn’t: “Great, this saves time,” but: “What does this mean for my job?”

There’s a famous idea that a person can’t believe something if their salary depends on them not believing it. For some people, using AI feels like cooperating in their own redundancy. That creates a strong, very human resistance.

I don’t know exactly what the employment market will look like in five years. But my personal solution isn’t to avoid AI; it’s to expect governments to build a safety net and for society to adapt. If anything, avoiding AI just puts you further behind the curve on tools everyone will need to be familiar with.

JK: How are people generally responding to AI right now?
MN: Broadly, I see three rough profiles. The first are those in denial, and always say: "This won't happen." These are the people who said AI would never do creative work, and then we got Midjourney and modern language models proving them wrong. The second are the fatalists. This group thinks there’s nothing we can do, so we might as well just enjoy it while it lasts. That’s pretty defeatist. The last group are agency-focused. They think, “This is coming, and I can influence it.” This is where I try to sit. Yes, AI is coming, and yes, it could be huge, but things we do now can influence both our personal futures and society’s trajectory. It’s not about ignoring the problem or admitting defeat; it’s about recognising we still have agency.

JK: What would 'good leadership' on AI look like in Australia over the next 6-12 months?
MN: In a perfect world, we’d see c lear, enforceable safety standards for high‑risk models, mandatory pre‑deployment testing for the biggest systems, independent auditing – through something like a well‑resourced AI Safety Institute, and communication that translates all of this into normal language Australians can understand.

The goal is to create an environment where people feel safe to use AI – at home, in business, in government – because they trust that the systems meet reasonable safety expectations. Just like aviation safety helps us feel okay getting on a plane, AI safety standards could help Australians feel okay putting AI to work .

CLOSING THOUGHTS

I left that conversation with a clearer view of what fighting the white looks like from where we stand. In Australia, we have the luxury of not having a Silicon Valley-Wall Street nexus forcing the hand of leaders. We’re a trusted middle power sitting on the sidelines of the Great Power Competition with many other likeminded partners. We can use this to our advantage. We can shape our own rules and norms around how we use AI.

We shouldn't just be going along with what is happening just because we’re not writing the scenario. There's a lot we can do to understand the AI landscape and what it means for our interests: which tools are actually safe, where our data is going, which laws need changing, which global partnerships matter.

On an individual level, simple steps to increase agency include:

Choosing tools from companies whose values you're willing to back,
Just saying no – like many of us millennials are doing now with Instagram and TikTok by deactivating our accounts and living our analogue lives,
Reading the terms and conditions to see where your data goes or where the opt-out options are,
Asking your employer whether there are genuine feedback loops for staff to voice their concerns with AI,
Telling your local MP that mandatory AI safety standards are a reasonable ask – because most Australians would agree, and
Staying informed and making decisions with the view that agency is better than denial or fatalism.

It all adds up to getting as much of a full picture as possible from those you trust – which is what we hope to provide at ClearAI.

We have to remind ourselves that this isn't a simulated exercise. The scenario isn't fixed. We have agency. We can fight the white.

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

INTRO NOTE

When I was a civilian policy adviser in Defence, I had the privilege of participating in a number of military exercises. Playing alongside my Army, Navy and Air Force colleagues, my role was to provide diplomatic and foreign policy advice to navigate a scenario as the 'blue team', pitted against the enemy on the 'red team'. These exercises were designed by a 'white cell' – a neutral team of planners writing the scenario, targeting our weaknesses and vulnerabilities to see how we would respond.

On my first exercise, I was bogged down arguing the scenario was unfair, possibly unrealistic. My ever-patient and more experienced military colleagues told me it was best not to fight the scenario – the script handed to us by the white cell – which became a mantra I had to repeat to myself: "Don't fight the white." In doing so, I felt a loss of agency but I went along with it for the sake of the exercise.

Sometimes, reading AI news feels exactly like this. A ‘white cell’ somewhere in the US or China is writing the scenario – and it can feel like we have no agency here in Australia. Yet we do. This isn’t a simulated exercise. This isn’t a game with a rigid script. We can change the outcome. We can vote with our feet, send strong signals to our leaders, say no to big tech, and prepare our institutions.
We can fight the white.

I wanted to delve into this further, particularly after I caught up with Associate Professor Michael Noetel to discuss UQ’s latest Survey Assessing Risks from Artificial Intelligence 2025 . Amongst key findings, the study found:

Amongst key findings, the study found:

Australians want robust safety measures (89% would trust AI more if there were mandatory safety testing, independent audits, an AI Safety Institute [which the Government is currently setting up]), and
Demand for transparency and media coverage is strong (80-85% want more reporting on AI’s societal effects and on how government is managing AI regulation).

I believe there are five main sentiments that drive the distrust underpinning the study’s findings:

We’ve been burnt before.
Big tech promised social media would bring connection. Instead it delivered anxiety, addiction and polarisation. People aren’t being paranoid applying that same lens to AI.
It speaks like us and sounds correct. But it isn’t us and it can be wrong.
Natural language was made for humans so it’s disconcerting when a machine can speak it fluently, and also has the audacity to make mistakes so confidently with no ‘remorse’.
We can’t trust what we’re seeing anymore.
AI generated content is actively degrading the information environment we share. When hyperrealistic synthetic media ‘floods the zone’, healthy scepticism tips into not being able to believe anything. The shared reference points holding societies together come under assault.
We don’t trust other humans holding the tool.
AI doesn’t cut jobs. Employers do. AI doesn’t surveil citizens. Governments do. AI widens existing power asymmetries between the people making decisions and the people living with them.
We’re being told something is coming that we can’t imagine.
AGI. Superintelligence. Systems that exceed human capability across every domain. The people building it can’t agree on when or whether it’s safe or what it even means. Do you feel uneasy yet? But also, did anyone even ask for this?

Now, let's jump into the interview.

OTHER INSIGHTS

Perplexity vs ChatGPT

Mon, 10 Nov 2025 07:00:52 GMT

Perplexity vs ChatGPT

CONTENTS

OVERVIEW

PERPLEXITY

Perplexity is designed to function like a sophisticated search engine, offering precise and current information. It connects to the internet, allowing it to pull data from various sources, including social media platforms like Reddit and X (formerly Twitter).

This makes it particularly useful for:

Research and data gathering
Complex queries in specialised domains (where accuracy is crucial)
Organising information (i.e. sorting queries into collections)

Despite its strengths, Perplexity may struggle with synthesising complex information compared to some other AI models and it’s conversational capabilities are limited.

CHATGPT

Renowned for its versatility, ChatGPT is capable of performing a wide range of tasks, including:

Creative Writing: Generates human-like text for various scenarios.
Problem Solving: Assists with logic and mathematical problems.
Coding Support: Helps write and troubleshoot code.

ChatGPT's dataset is extensive but updated in real-time, which can limit its ability to provide the most current information. However, its ability to mimic human dialogue makes it an excellent choice for interactive and engaging user experiences.

ChatGPT has a well documented history of issues with citation accuracy, however, many of these issues are overcome through the use of Deep Research capabilities.

Overall, Perplexity is designed more as a search engine, focusing on accurate information retrieval with cited sources. This makes it suitable for research and information-centric tasks. ChatGPT, on the other hand, is a broad conversational AI chatbot that excels in generating human-like dialogue and creative content.

Accuracy and Reliability:

Perplexity: Emphasises factual accuracy and citation of sources, making it suitable for users who prioritise precision.
ChatGPT: Offers a broad spectrum of conversational scenarios but may not always provide the latest data due to its dataset limitations.

Interaction Style:

Perplexity: Provides a structured, information-centric interaction, beneficial for detailed research.
ChatGPT: Engages users with natural, human-like dialogue, ideal for creative and conversational applications.

User Preferences:

Users seeking the most current and accurate information might prefer Perplexity.
Those looking for a versatile AI capable of handling various language tasks may find ChatGPT more suitable.

Price:

Both tools offer free versions and premium subscription plans (US$20/month).
ChatGPT offers a teams plan with easy collaboration, enhanced privacy and security features (pricing starts at US$30/month per seat)
Perplexity offers an enterprise plan with similar features (pricing starts at US$40/month or $400/year per seat.)

KEY DIFFERENCES AND CONSIDERATIONS

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

Perplexity vs ChatGPT compared: Both tools serve different purposes and excel in distinct areas.

There are a lot of AI chatbots out there, and most of them look and feel the same. ChatGPT is well-known and used, along with Claude, Microsoft's Copilot, Google's Gemini and Meta's in-app AI. But there's another tool, Perplexity, that's growing in popularity as an alternative to both ChatGPT and traditional search.

While both Perplexity and ChatGPT are built on advanced AI models, they serve different purposes and excel in distinct areas. This quick guide will explore their features, strengths, and ideal use cases, helping you determine which tool is best suited to use in your business:

OTHER INSIGHTS

How Local Governments Can Use AI

Mon, 10 Nov 2025 06:38:36 GMT

How Local Governments
Can Use AI

CONTENTS

DELIVER BETTER CUSTOMER SERVICE

One of the most immediate applications of AI in local government is enhancing customer service.

AI-powered agents on council websites can handle routine inquiries, freeing up staff for more complex case-by-case issues. These agents can use natural language processing to analyse sentiment of resident feedback and complaints, identifying trends and areas for improvement.

Agents can be configured to operate like virtual assistants, guiding website visitors through processes including:

applying for a permit application
lodging a complaint
making a rate payment online

These agents can also be used internally for service staff to find resources, increasing performance and delivering high quality outcomes for ratepayers.

STREAMLINE ADMINISTRATION

AI can significantly reduce the administrative burden on staff. A few example include:

Automate document processing and data entry using optical character recognition (OCR) and machine learning.
AI-driven scheduling and fleet management systems.
Predictive analytics to forecast budget needs and optimise resource allocation.

The digitisation of councils has brought some efficiencies, but also new complexities and data overwhelm. Administration costs in many councils are still ballooning. AI will be the technology that helps councils wade through the vast amounts of collected data and process work efficiently at scale.

ENHANCE URBAN PLANNING

Urban planning will be revolutionised by AI assisted decision making and modelling. Machine learning algorithms can analyse historical data and predict future development trends, from population to water flow, traffic congestion and more.

Two major uses for AI in planning:

AI-powered Geographic Information Systems (GIS) can be implemented for more accurate land-use planning and zoning decisions.
AI-trained regulation bot that assists town planners with building plans and ensures compliance with local regulations. With computer vision, AI can recognise building plans, analyse and review within seconds, not days.

Waste management is a critical service with many moving parts. AI can be used to learn and predict waste generation patterns and adjust services accordingly. AI-powered sorting systems at recycling facilities could also increase efficiency and reduce contamination.

Some councils have trialled smart bins with sensors that alert collection teams when they're full, optimising collection routes. Adding AI to this process with further aid waste management teams moving about the city without wasting (pun intended) time, fuel and money.

IMPROVE WASTE MANAGEMENT

AI can play a crucial role in maintaining public safety. New technology is emerging to conduct surveillance and ‘predictive policing’ by leveraging algorithms to allocate law enforcement resources more effectively. The jury is still out on the efficacy and ethics of this technology.

Two important use cases for AI in public safety are:

AI-powered video surveillance systems that can detect and alert authorities to potential safety hazards or criminal activities.
Use machine learning to analyse traffic patterns and optimise traffic light timings to reduce congestion and accidents.

IMPROVE PUBLIC SAFETY

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

Local governments are looking to Artificial Intelligence (AI) to increase efficiencies and enhance services and operations. Local governments, despite their limited revenue-raising capacity, are expected to provide a wide range of services to residents including roads, waste management, town planning, and community facilities. State governments collect about 16% of total tax revenue in Australia, while local governments only collect 3-4%, a relatively small proportion of the total.

The high expectations for service delivery to local communities, alongside ongoing financial pressures has led some local governments to look to Artificial Intelligence (AI) to increase efficiencies. This can be realised with productivity gains led by AI assistants, such as ChatGPT or Microsoft Copilot.

Here are 7 ways local governments can use improve efficiency, decision-making, and engagement with residents.

DELIVER BETTER ENVIRONMENTAL OUTCOMES

AI can assist councils in their environmental initiatives by deploying AI-powered sensors to monitor air and water quality in real-time. Machine learning algorithms can predict and help mitigate the impacts of natural disasters like bushfires or floods.

AI can be used within electrical systems to optimise energy usage in council buildings and public spaces. This can including routing power between a network of battery storage at council properties.

DATA PROCESSING AND DECISION MAKING

Local councils collect and manage vast amounts of data from various sources. AI can be leveraged to process this data more efficiently and derive actionable insights to support decision-making processes.

Applications of AI include:

Analysing historical data to forecast future trends e.g. population growth, service demand, and budget requirements.
Machine learning that recognises patterns in large datasets, helping councils detect anomalies in service usage, pinpoint areas requiring attention, or recognise emerging community needs.
Natural Language Processing (NLP) to analyse resident feedback from various channels (e.g., social media, emails, surveys) to gauge public sentiment and identify key issues of concern.
Assist in complex decision-making processes by simulating various scenarios and their potential outcomes, helping council leaders make more informed choices.

As Artificial Intelligence continues to evolve and become more accessible, local governments can leverage this technology to enhance their services and navigate the complexities of local issues with greater accuracy and foresight.

Clear AI is here to help Australian councils navigate the use cases of AI and position themselves as the forefront of smart city innovation, delivering more efficient services to their communities.

Book a call with our team today.

OTHER INSIGHTS

Practical AI Tools for Business Productivity

Mon, 10 Nov 2025 02:00:23 GMT

Practical AI Tools for Business Productivity

CONTENTS

CHATGPT

ChatGPT, developed by OpenAI, is a versatile language model that can assist with a wide range of tasks. While many people use it for basic applications like drafting emails or providing customer support, its capabilities extend far beyond that.

What to use it for:

Automating customer service interactions
Generating detailed reports and summaries
Creating content for blogs and social media
Conducting market research through data analysis
Personalising marketing campaigns

Alternatives: Claude, Meta Llama 3.1, Microsoft Copilot, Google Gemini

Tip: Ensure you disable model training. Instructions here.

CLAUDE

Claude is an AI assistant designed to provide insightful and context-aware responses. It excels in understanding nuanced queries and delivering comprehensive answers, making it a valuable tool for businesses.

What to use it for:

Enhancing customer support with detailed responses
Conducting in-depth research on industry trends
Assisting in decision-making with data-driven insights
Providing training and onboarding support
Automating routine administrative tasks

Alternatives: ChatGPT, Meta Llama 3.1, Microsoft Copilot, Google Gemini

PERPLEXITY

Perplexity is an AI-powered search engine that offers precise and comprehensive answers. It is particularly useful for businesses needing quick access to reliable information.

What to use it for:

Conducting competitive analysis
Gathering market intelligence
Verifying facts and figures
Exploring new business opportunities
Summarising complex documents

Alternatives: Microsoft Copilot, Google Gemini

Nano Banana is an AI tool that focuses on generating high-quality images and artwork. It is particularly useful for businesses in need of creative and visually appealing content. It can be accessed through Google Gemini and selecting “Create Image” under the Tools button.

What to use it for:

Creating unique and custom illustrations
Designing marketing materials and advertisements
Enhancing brand visuals with creative artwork
Developing concept art for projects
Producing engaging social media content

Alternatives: ChatGPT, Adobe Firefly, Microsoft Designer (via Copilot), Meta Llama 3.1

GOOGLE GEMINI NANO BANANA

Notion AI enhances the functionality of the popular Notion productivity platform. It offers features like writing assistance, content summarisation, and database autofill to streamline workflows. Learn More

What to use it for:

Generating and improving written content
Summarising lengthy documents
Answering questions based on workspace information
Automatically filling in database properties
Enhancing project management with AI insights

NOTION AI

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

Adopting AI tools across your business can significantly enhance productivity and streamline operations. Here are seven general AI tools that can help your team work more efficiently and effectively.

AI Tools for Business Productivity

Granola provides real-time transcription and powerful AI tools to enhance productivity and streamline conversations. It automatically transcribes meetings, making it easier to capture and review important discussions.

What to use it for:

Transcribing meetings and interviews in real-time
Generating automated meeting summaries
Collaborating with team members on transcribed notes
Organising conversations into searchable folders
Tagging speakers for easy identification in future meetings

Alternatives: Copilot (paid) for Teams, Gemini

GRANOLA.AI

CURSOR

Cursor is a powerful coding tool powered by AI. It allows users to write and modify code in natural language and makes development faster than was previously possible.

What to use it for:

Writing and editing code
Generating documentation for code
Analysing and understanding existing codebases
Fixing bugs and errors in code
Answering questions about a specific part of a codebase
Creating entire functions based on natural language

Alternatives: GitHub Copilot, Windsurf

By incorporating these AI tools into your business operations, you can increase efficiency, reduce manual workload, and focus on strategic growth initiatives.

OTHER INSIGHTS

Is your team using AI safely?

Mon, 10 Nov 2025 01:32:27 GMT

Is your team using AI safely?

CONTENTS

HOW TO LEAD RESPONSIBLE USE OF AI IN YOUR WORKPLACE.

AI is transforming the workplace by delivering significant productivity gains for employees, allowing them focus on more meaningful and engaging tasks. According to the Freshworks 2024 Global AI Workplace Report , more than half of employees are using some form of AI-enhanced software at work.

Surveyed employees estimated that AI is saving them approximately 3 hours and 47 minutes each week, which over the course of a year, amounts to nearly 24 business days. Common use cases for AI include: summarising reports, recommending action steps, managing repetitive tasks, among other efficiencies.

YOUR TEAM IS ALREADY USING AI

The benefits are clear: AI can cut workloads by nearly four hours a week, allowing teams to focus on more strategic activities. However, most adoption is silent, which raises questions about oversight and security.

The research from Freshworks found almost half of employee were using unpaid AI tools, such as ChatGPT, despite the risk that sensitive business data could be used to train large language models or shared widely.

One reason why employees are not disclosing their use of AI is because many companies have yet to introduce training and policies around the proper use of AI.

With this new, disruptive and rapidly changing technology, many leaders are yet to drive significant and valuable adoption of AI.

This means that the productivity gains that can be realised with AI fall short of the opportunity.

SILENT ADOPTION IS A RISK TO YOUR BUSINESS

When your business doesn’t openly embrace AI, but employees choose to use it anyway, your business could be exposed:

Data Security Breaches: Employees using unauthorised AI tools may inadvertently input sensitive company data, potentially exposing it to external parties or using it to train public AI models.
Compliance Violations: Unregulated AI use could lead to breaches of industry regulations or data protection laws, resulting in hefty fines and reputational damage.
Inconsistent Output Quality: Without proper guidelines, the quality and consistency of AI-generated work may vary widely, potentially affecting your company's standards and reputation.
Ethical Concerns: Unchecked AI use might lead to ethical issues, such as bias in decision-making or the creation of misleading content, which could harm your company's integrity.
Dependency and Skill Erosion: Over-reliance on AI without proper training could lead to a decline in critical thinking and problem-solving skills among your workforce.
Lack of Oversight: Without visibility into AI usage, management cannot effectively monitor its impact on productivity, costs, or strategic alignment.
Missed Opportunities: Silent adoption means your company isn't strategically leveraging AI's full potential, potentially falling behind competitors who are implementing it more effectively.

The challenge for management is to harness the benefits of AI now, while ensuring responsible use.

Here are some tips to how you can lead this change:

Set Clear Guidelines: Define how AI should be used in your company. Policies should cover data security and ensure compliance with industry standards.
Foster Open Dialogue: Create an environment where employees feel comfortable discussing their AI use. This transparency can help identify both risks and opportunities.
Enhance Skills: Offer training to boost your team's AI capabilities. This empowers them to use AI effectively and responsibly.
Evaluate Impact: Regularly review how AI affects your business. Use metrics like productivity and work quality to assess its value.

By taking these steps, you can guide your organisation towards safe and effective AI integration, unlocking its potential while safeguarding your business.

Clear AI is supporting Australian businesses as they adopt AI, from general awareness training through to strategy and implementation.

EMBRACING AND LEADING AI RESPONSIBLY

Duis ac mi augue. In orci ipsum, consectetur eget congue et, volutpat id turpis. In lectus nibh, consectetur sit amet tortor et, eleifend tempus sem. Integer consequat nunc sit amet sapien mattis auctor. Vestibulum sapien velit, iaculis vel varius sed, porta sit amet metus. Fusce fermentum condimentum est. Interdum et malesuada fames ac ante ipsum primis in faucibus. Aenean arcu ligula, efficitur a odio ut, dapibus auctor diam. Cras nec bibendum leo. In hac habitasse platea dictumst. Ut a tincidunt sem, et cursus nisi. Aliquam non mi bibendum, fringilla velit id, mollis est. Nullam in ipsum quam. Vivamus rutrum dui ac libero dictum, pellentesque tincidunt quam euismod. Mauris eu elit aliquet, cursus justo ac, feugiat mauris.

Cras dolor erat, consectetur vitae egestas quis, lacinia in nisl. Sed semper mollis elementum. Ut mollis dictum faucibus. Praesent vitae urna ac ipsum dictum elementum in ut ipsum. Aliquam bibendum purus ut nisi lacinia, quis consectetur arcu accumsan. Nunc eget mi in ante porta laoreet. Curabitur ornare porta consequat. Mauris dictum venenatis diam id ullamcorper. In pellentesque interdum massa, sed blandit enim auctor fermentum. Fusce in nunc diam. Pellentesque habitant morbi tristique senectus et netus et malesuada fames ac turpis egestas. Nunc sed justo vel tellus pretium ultrices a non dui. Proin blandit ipsum id risus tincidunt, vel auctor lectus finibus. Morbi id rutrum massa.

HEADING 5

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

How to lead responsible use of AI in your workplace.

OTHER INSIGHTS

Building Trust in AI Across Local Government Authorities

Tue, 04 Nov 2025 09:28:34 GMT

Building Trust in AI Across Local Government Authorities

CONTENTS

HEADING 1

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse tempus suscipit urna, a tincidunt ipsum facilisis eget. Curabitur risus erat, vulputate dapibus urna sed, porttitor cursus tellus. Nulla libero diam, lacinia a est posuere, efficitur fermentum nibh. Pellentesque ac velit turpis. Nunc in porta velit. Duis iaculis varius orci, vel blandit lorem pellentesque ut. Donec ornare quam risus, vitae rhoncus leo dignissim ac. Ut quis dui quam. Nunc vel purus interdum, gravida lorem et, interdum nibh. Curabitur sollicitudin rutrum ex, eu convallis nisi efficitur vel. Curabitur vitae nisl a neque ultrices interdum. Fusce malesuada dolor diam, in congue mauris dapibus id. Suspendisse non odio volutpat, imperdiet enim eget, cursus libero. Donec efficitur sagittis massa.\

HEADING 2

HEADING 3

Phasellus et dolor venenatis, mattis lorem id, imperdiet purus. Nullam nec tincidunt tortor. Curabitur blandit mauris id turpis posuere pretium. Vivamus placerat viverra dapibus. Quisque fringilla dolor vitae pharetra eleifend. Vivamus rutrum placerat libero, laoreet congue velit lobortis sit amet. Sed scelerisque ante quis augue laoreet rhoncus. Vivamus ultrices justo eget sapien semper, eu consequat sapien efficitur. Quisque luctus suscipit eros at convallis. Duis tristique risus in condimentum viverra. Nam egestas semper bibendum.

Morbi ac est ipsum. In non purus at nibh sodales elementum. Nullam felis nisi, lacinia ac felis ac, gravida ultrices quam. Pellentesque tristique cursus ex, eu suscipit arcu pharetra eu. Ut eget blandit nisi. Phasellus quis sodales mauris, in interdum ligula. Praesent feugiat pharetra odio, id pretium nibh ultrices id. Phasellus vitae lorem augue.

HEADING 4

HEADING 5

Take this further. Download our extended resource and explore how human-centred intelligence can work inside your organisation.

OTHER INSIGHTS

Hazer Group

Tue, 14 Oct 2025 04:20:08 GMT

Hazer
Group

CLEAR OUTCOMES FOR

AI Adoption and Implementation Strategy

A SHORT SUMMARY

Secure AI implementation strategy with governance, training, and pilot programs.

OBJECTIVE

Prove that AI could be implemented securely (sensitive IP is a concern) and that their team could realise value through the use of the selected tools.

OUTCOMES

40%

certified frameworks

Established AI governance framework aligned with ISO42001.

Delivered comprehensive AI training program.

effective upskilling

Validated impact

Developed and validated priority use cases.

Operationalised innovation

Deployed pilot AI agents and operational playbooks.

“Working with Clear AI wasn’t about technology for technology’s sake, it was about people. Their team helped us cut through the complexity of AI, making it practical, ethical, and human-centred. The systems we built together gave our staff more time to focus on passengers, and our passengers noticed the difference.”

AI ADVISORY

OTHER CASE STUDIES

Lockyer Valley Regional Council

Tue, 14 Oct 2025 04:07:34 GMT

Lockyer Valley Regional Council

CLEAR OUTCOMES FOR

Copilot Trial Program

A SHORT SUMMARY

Copilot trial delivering 2.7-5.1x ROI with use case development and AI upskilling.

OBJECTIVE

Prove AI value and develop use cases within their context.

OUTCOMES

40%

Empowered capability

Increased staff AI confidence across organisation.

Achieved 2.7-5.1x ROI on Copilot licenses.

Measured success

Targeted impact

Identified and developed targeted use cases.

effective frameworks

Established responsible AI framework with measurable value.

ROI

Confidence

Integrity

Focus

AI ADVISORY

OTHER CASE STUDIES

Anonymous NFP

Tue, 14 Oct 2025 01:44:13 GMT

Anonymous NFP

CLEAR OUTCOMES FOR

AI Adoption and Implementation Strategy

A SHORT SUMMARY

Safe AI adoption with governance framework, efficiency gains, and deployed AI agents.

OBJECTIVE

Drive safe AI adoption across the organisation resulting in effectiveness and efficiency gains.

smart delivery

sustaining value

Deployed generative AI agents delivering ongoing value.

OUTCOMES

40%

Built organisational confidence in AI adoption.

Human Confidence

Improved deliverable speed and quality.

Ethical Direction

Established AI governance principles.

Confidence

Clarity

Momentum

Continuity

AI ADVISORY

OTHER CASE STUDIES

City of Stirling

Tue, 14 Oct 2025 01:30:41 GMT

City of Stirling

CLEAR OUTCOMES FOR

Hackathon

A SHORT SUMMARY

One-day hackathon boosting AI skills and enthusiasm, driving Copilot license uptake.

OBJECTIVE

Increase the uptake, excitement and skills of AI at City of Stirling.

OUTCOMES

40%

increased licenses

100% of unlicensed participants requested Copilot licenses.

Increased prompting skills across all team members.

Improved prompting capability

AI ADVISORY

OTHER CASE STUDIES

Thankyou

Tue, 14 Oct 2025 00:48:18 GMT

Thankyou

CLEAR OUTCOMES FOR

AI ADOPTION

A SHORT SUMMARY

AI adoption program driving cross-functional AI use and team understanding.

OBJECTIVE

Increase understanding of AI tools and adoption across all teams.

Increased team confidence in AI tools

Teams grew more assured in using AI, empowered by transparency and shared understanding of how systems worked.

40%

OUTCOMES

ADOPTION ACROSS ALL TEAMS

Achieved cross-team adoption including previously reluctant teams.

Confidence

Adoption

AI ADVISORY

OTHER CASE STUDIES