We have seen the current government dump its own in-house digital systems crafted for an indigenous healthcare context in favour of private AI scribe providers in healthcare. Last week’s announcement suggests the ceding of further power in designing government infrastructure and providing frontline government services to big tech. New Zealand’s size means it’s going to be a taker of new technologies. It has little power to negotiate – it will have to accept the technology on the terms it’s given, subject to the whims of whatever updates Open AI or Anthropic roll out. We should be concerned about the delivery of government services left to the impulses of overseas technology companies that do not necessarily have the same values or concerns for what is in New Zealand’s best interests.

Moreover, once these contracts are entered into and companies are providing the digital infrastructure, this lock-in dynamic makes it very expensive for government to exit if it’s not happy. The government has said that AI models will save money on frontline staff, but AI procurement is itself an expensive and ongoing exercise and if prices rise once our services are structured in reliance on them, we will be unable to say no.

There are many studies casting doubt on the productivity gains of AI in the workplace. MIT found that 95% of companies have failed to find revenue generation from AI use. Other studies have shown that AI scribes offer minimal time-savings for doctors. Unsurprisingly, most studies touting productivity benefits are from the developers themselves. Willis has said the civil service has poor digital systems and data governance. This is a sign that government needs to be cautious when introducing AI.

AI is only as good as the quality of the datasets it is running on. Fast productivity gains are more difficult to achieve in government where dataflows are incredibly sensitive and where information is classified and subject to strict authorisation and permission regimes. If Large Language Models have access to classified datasets, when prompted they can produce outputs making that information available. Without careful data silos, security and data breaches can easily occur. There has already been a serious security breach in March of this year after the rolling out of Heidi AI into New Zealand’s hospitals.

There are also concerns with the loss of institutional knowledge in the public sector by outsourcing to AI systems. If AI systems are learning from data and processes, then civil servants themselves are often failing to learn. Judgmental atrophy is the phenomenon whereby individuals lose their ability to make difficult fine-grained judgments and assessments because they outsource those judgments to automated systems.

Efficiency is not the only value of government. The public do not want government making incorrect decisions about them efficiently. The government also owes different obligations from the private sector, as individuals cannot opt out from interacting with them. Values of open government, transparency, fairness and accountability can be impeded by the delivery of government services using opaque and fast-moving AI models hosted in other parts of the world. These are the conversations we need to be having before the government goes ahead with civil service cuts in favour of AI models.

This article was republished from The Spinoff New Zealand. Read the original article.

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Researchers found participants were actively using AI models for work and leisure. They were generally aware of concerns surrounding AI’s high electricity and water use, often through news reports or social media discussions. However, these impacts were largely viewed as distant and abstract rather than immediate consequences connected to daily technology use. 

Many participants said they had never previously considered the physical infrastructure behind generative AI systems, including the scale of data centres and the e-waste generated to support them.

One participant reflected:

Critical AI literacy and environmental literacy

One of the study’s most significant findings was how quickly participants’ perspectives shifted once the hidden infrastructures behind AI models became more visible.

Images of server farms, e-waste dumps and resource-intensive supply chains provided by the researchers during the focus groups helped participants understand generative AI not as a purely digital technology, but as a material system with real environmental consequences.

Researchers found people were more likely to remember vivid comparisons and analogies, such as claims that “just one prompt is enough to kill a tree” or that generating one sentence using a chatbot is “like pouring five litres of water down the drain”.

The findings suggest environmental communication around generative AI needs to make these impacts more visible, embodied and relatable.

Several participants said they reconsidered how often they use generative AI tools after learning more about the environmental footprint associated with AI technologies, particularly for what they described as “unnecessary” or “trivial” tasks.

To help in public understanding, Lupton has also developed an open access explainer for generative AI that provides clear explanations for how these technologies work.

This research is part of the ADM+S ADM, Ecosystems and Multispecies Relationships project

Read the full article “Just One Prompt Is Enough to Kill a Tree”: Knowledge and Attitudes Concerning the Environmental Impacts of Generative AI Among Australians 

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In contrast, journalists highlight risks such as misinformation, source invisibility, and flawed AI outputs – ranging from recommending glue as pizza topping to suggesting that cats live on the moon. 

SEO marketers expressed both concern and adaptation, reporting declining site visibility and engagement, prompting shifts toward Generative Engine Optimisation (GEO). 

Missing voices and broader implications

A key finding of the study is the absence of the user perspective in dominant industry narratives. While companies debate performance, visibility and risk, the experiences of everyday users are largely missing from the discussion.

Researchers also note the lack of attention to environmental costs of training large language models, raised only in passing in two texts,  as well as deeper engagement with the ethical implications of AI deployment.

“Googlisation” of knowledge

Google’s AIOs signal more than a technical upgrade to search – they represent a transformation in how knowledge is curated, delivered, and legitimised in the digital era. 

While Google positions AIOs as intuitive, seamless tools that meet user expectations, it masks deeper shifts in information control and editorial authority. 

At the same time, AIOs fundamentally alter the relationships between users, content creators, and platforms. By synthesising information from multiple sources while heavily curating the output, AIOs reconfigure how information flows and how market relations are structured.

As Google increasingly acts as both infrastructure and editor, critical questions arise about transparency, accountability, and the politics of platform-driven knowledge infrastructures.

The authors note “AIOs are not simply technical enhancements to search but also represent a continuation of broader platformisation logics and discursive and infrastructural interventions that reshape what it means to search, to know, and to trust in the digital age.”

“Understanding these transformations requires not only examining the technologies we use but also interrogating the stories we are told about them, and who gets to tell them.”

This research is part of the ADM+S Australian Search Experience 2.0 project.

Read the full article 

https://journals.sagepub.com/doi/10.1177/17504813261447684 

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Decentralised social media ecosystems allow independently operated communities to communicate across shared protocols without being controlled by a single corporation. One such example is the Fediverse, which includes platforms like micro-blogging site Mastodon and video sharing site PeerTube.

Similarly, the AT protocol, which powers micro-blogging sites Bluesky and Eurosky, aims to separate social networking from platform ownership. It enables users to move identities, content and communities between services more freely.

Open-source office suites such as LibreOffice have provided alternatives to Microsoft Office for more than two decades.

It’s also increasingly possible to run AI systems locally on personal devices or private networks. This reduces reliance on cloud-based AI services controlled by big tech.

In other words, many of the technical foundations for greater digital autonomy already exist. The challenge lies with adoption and coordination. When Twitter was bought by Elon Musk, many users fragmented to other sites – from Mastodon and Threads to Bluesky and others. If your friends are all on different social media sites, which do you choose?

What can Australia learn from this?

Australia is in a similar position to the EU. We’re heavily reliant on foreign-owned digital infrastructure. We’re also increasingly exposed to the geopolitical tensions surrounding it.

Australia could take a leaf out of the EU’s book and develop its own roadmap for digital sovereignty. This would have to operate at both the policy and public levels.

Australia’s digital policy shouldn’t be dictated by large platforms or external geopolitical actors. There’s also a pressing need to promote local innovation for the future, such as investing in quantum computing.

Publicly funded organisations have already demonstrated Australia can invent globally significant technology. After all, Australia’s national science agency, the CSIRO, patented the technology that led to wifi. Universities and publicly funded institutions should be at the core of future tech innovation as well.

Most importantly, Australia is home to First Nations communities. Their governance systems have long operated through decentralised, relational, and autonomous forms of organisation.

Groups such as Maiam nayri Wingara and the HASS and Indigenous Research Data Commons have already developed internationally significant frameworks for Indigenous data sovereignty. These cover data governance, stewardship, collective benefit, and the rights of communities to control data about their peoples, lands and cultures.

We can learn from these. Respecting Indigenous sovereignty may also open a pathway for all Australians to rethink what our shared digital futures can look like.

Ashwin Nagappa, Postdoctoral Research Fellow, ARC Centre of Excellence for Automated Decision-Making and Society, Queensland University of Technology and Daniel Angus, Professor of Digital Communication, Director of QUT Digital Media Research Centre, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Where AI is usually used in film

The most pervasive uses of AI in contemporary mainstream productions are usually invisible to audiences.

For most studio-produced feature films, AI-assisted platforms handle script breakdown in pre-production. They help with extracting production requirements based on the screenplay, scheduling shoots and modelling budgets. These tasks once took hours, or even days, to complete.

On set, AI may be used to generate the background environments for virtual production stages. Originally used for TV shows such as The Mandalorian, these sets are increasingly used as a cost-effective option in studio productions.

In post-production, AI tools handle first-pass editing, audio clean-up, VFX, and voice modification. For instance, Dune: Part Two (2024) used machine learning to achieve the blue-eye effect – a minor enhancement audiences don’t immediately register.

Arguably the most widespread (yet invisible) use of AI is for localisation, as streaming platforms pursue global audiences at scale. AI-assisted dubbing and subtitle generation are now standard processes.

AI can also influence what films get made. Companies use algorithmic analysis to inform greenlight decisions, predict trailer performance, and optimise release windows. As Vue Cinemas CEO Tim Richards put it, “[AI] determines what we show at what cinema, on what screen and at what time”.

Automation and AI-driven processes have a long history in film. Yet it is only now, amidst the deluge of AI-generated content, that these modes of filmmaking have attracted the public’s attention.

Not a new problem, but a newly visible one

The Academy’s changes do not reflect a resistance to innovation – but a centring of human authorship.

The most publicly legible creative contributions to a film should remain demonstrably human in origin. That’s a reasonable position, with broad support across audiences and industry professionals alike.

But it sits alongside the harder question of consent: not just whether AI was used, but whether the people whose likenesses, voices, and labour are implicated actually agreed to it.

The Oscars’ rules are about disclosure as much as eligibility – and they aren’t alone. Many publishers and creative bodies are now formulating AI principles that emphasise the need for transparency.

The question isn’t whether AI is being used in film and TV production; it is. The question is whether audiences have the right to know — and whether public discourse has caught up enough to know what it’s even asking about.

Generative AI is the latest inflection in a long history of automation — more powerful and fast-moving than its predecessors, but no different in the questions it raises.

The pressing task now is making sure the frameworks for consent, disclosure and creative attribution keep pace with AI technology.

Daniel Binns, Senior Lecturer, Media & Communication, RMIT University and Meg Thomas, PhD Candidate, The University of Queensland

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Presentations 

During the visit, Dr Binns delivered three invited presentations: 

• The international symposium Créativités Artificielles: Approches Critiques de l’IA (Université Côte d’Azur, 27–29 April)
  Presentation proposing an ecological — rather than literacy-based — framework for critical engagement with generative technology.
• TV-IA Journée d’Étude at Université Paris 1 Panthéon-Sorbonne (8–9 April)
  How episodic television form is being reshaped under algorithmic conditions — a paper subsequently invited for publication in translation. 
• The Séminaire HERMES at Campus Condorcet (24 April)
  Media-materialist framework for generative AI image-making alongside European artist-researchers. 

Dr Binns also attended the Noûs Art and AI Festival at the Bibliothèque nationale de France and GenAI Days #3 — an industry-facing AI event where he was the only academic researcher present — providing a grounded view of how French industry and cultural institutions are navigating the generative AI moment.

A joint online seminar organised with Alexandre Gefen (CNRS/THALIM) and curators of the Jeu de Paume’s AI exhibition is scheduled for June 2026 and a research exchange with the University of Groningen is in development.

Dr Binns plans to return to France in late 2026 or early 2027, with funding applications to the PHC FASIC program and the French Embassy’s social sciences initiative currently in preparation.

This research visit was supported by RMIT’s Academic Development Program, ADM+S, Institute for the Study of French-Australian Relations, Inc. (ISFAR), Université Paris 1 Panthéon-Sorbonne, and Université Côte d’Azur.

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The NBI has stronger leverage than the NMBC, which relied on ministerial designation that was never used. At first, the NMBC appeared successful without it, with Meta and Google signing more than 30 deals worth more than A$200 million. But Canada’s Online News Act shows the limits of this model when Canada sought to introduce a similar scheme: Meta removed news from its platforms entirely, avoiding the obligation and exposing its fragility.

The NMBC later weakened as Google became the only major platform doing deals in Australia. The company has recently signalled it will not renew some of these. This shift might help explain the timing of the NBI’s re-emergence and the structural shift from competition to tax law to compel platform compliance.

Now for the risks, of which timing is one. The NBI was drafted in 2024 but put on ice when US President Donald Trump voiced strong opposition to digital services taxes, calling them “discriminatory” measures targeting US companies. For some pundits, including Meta, the NBI is effectively a digital services tax.

Trump has previously threatened tariffs against countries pursuing such measures.

Against that backdrop, and given Australia’s recent exposure to trade tariffs and Trump’s criticisms of Australia over the Iran war, the timing of this renewed announcement is tricky. Meta chief executive Mark Zuckerberg has direct access to Trump, and both Meta and Google have already criticised the NBI.

While traditional media has welcomed the announcement through a signed joint statement, some platform criticisms warrant attention.

Why are multinational digital platforms that also distribute news and with more than $250 million in Australian revenue, such as Apple and LinkedIn, carved out of the scheme? And why is AI, with its rapidly growing user base and reliance on news content to train and refine systems, not included?

The explanations offered so far – that AI will be addressed separately and that Apple and LinkedIn employ editorial teams – are unconvincing.

Questions to answer

Then there are system design questions that the consultation period is sure to raise. For example:

• how do you define journalism in an age of influencers, social media and chatbots?
• who qualifies for funding?
• are the current eligibility criteria fit for purpose under the NBI to ensure the scheme supports continued investment in public-interest news, diversity of media voices, and quality journalism?
• will this include influencers such as Konrad Benjamin, who has large audiences for his explainer reporting?

This is a live debate that the short three-week consultation period is sure to raise before closing on May 18.

And perhaps the biggest risk of all: backfire. The NBI needs to avoid unintended consequences, such as when news was pulled from Meta’s platforms in Canada. The unintended outcome was long-term smaller audiences for professional journalism. Australia cannot risk backfire effects at a time when quality journalism has never been more critical for safeguarding democracy.

Andrea Carson, Professor of Political Communication, La Trobe University and Diana Bossio, Associate Professor of Digital Communication, RMIT University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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The Australian Government became a member of the OGP in 2015, committing to support its goals of increasing the transparency and accountability of government. After governments join the OGP, they work with civil society to create national action plans setting out concrete steps that will be taken to increase openness over the next 2 years. 

“Open government, loosely described as our right to engage with and scrutinise government actions, is the aspiration of every thoughtful citizen. This is so because transparency and accountability always improve our community’s lived outcomes,” stated Professor Kate Auty, Civil Society Co-Chair 2024-2025.

“We know, and research tells us, that government will make better and more informed decisions when civil society is involved in the matters that affect us.”

Australia’s Third National Action Plan (NAP3), published on 15 December 2023, runs from 2024-2025. The new forum will develop Australia’s Fourth OGP National Action Plan (NAP4) by the end of 2026.

The forum’s first meeting will take place on 19 May 2026, where members will establish and agree on the forum’s terms of reference.

More information about Australia’s Open Government Forum is available from the Attorney-General’s Department.

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Dr Carlon said that the thoughtful discussions involved in building consensus are very promising. 

“This kind of deliberative, informed approach helps ensure that AI adoption is not driven by convenience or efficiency alone, but instead takes a future‑focused lens that is aligned with humanitarian principles, and avoids inadvertently introducing new harms or data and security risks that would compromise fundamental values,” said Dr Carlon.

The webinar marks the start of a coordinated program to build consensus around a forthcoming Resolution on the Principled and Accountable Use of ICTs in Humanitarian Action. 

It is being jointly developed by the International Committee of the Red Cross, IFRC, and a coalition of national societies including the Australian Red Cross, American Red Cross, British Red Cross, Kenyan Red Cross, and others.

The webinar brought together participants from across the global Red Cross and Red Crescent Movement, including those working in conflict settings, alongside representatives from organisations such as UNHCR and Médecins Sans Frontières.

The series will continue over the coming months as momentum builds toward the 2026 Council of Delegates, where the Resolution is expected to play a key role in shaping the future of responsible AI in humanitarian action.

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SOCIA addresses a key challenge in policy and planning: building simulations that are not only technically functional but also robust, transparent, and grounded in real-world evidence. It semi-automatically translates social and urban policy requirements into simulation code, supported by human-in-the-loop refinement. 

A co-authored paper on this research titled SOCIA-EVO: Automated Simulator Construction via Dual-Anchored Bi-Level Optimization (Devin Yuncheng Hua, Sion Weatherhead, Mehdi Jafari, Hao Xue, Flora D. Salim)  has been accepted for presentation at the 64th Annual Meeting of the Association for Computational Linguistics, a leading international conference in computational linguistics and natural language processing in July. The event brings together global experts to present cutting-edge research in AI language technologies and their real-world applications. 

Flora Salim, Chief Investigator at ADM+S, said the fellowship represents a valuable opportunity to translate research into practical impact.

Dr Hua’s research areas include Natural Language Processing (NLP), Large Language Models (LLMs), Knowledge Graphs, Dialogue Systems, Machine Learning, Deep Learning, Reinforcement Learning, and Causality.

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What email is actually for

Email, like many forms of communication, is as much about maintaining everyday relationships as it is about the transfer of information.

At work, it’s often about signalling competence, responsiveness, collegiality and authority. “Just looping someone in” or “circling back” are all part of our absurd office vocabulary, a shared dialect that helps us navigate hierarchy, soften demands and keep things moving – all without saying what we really think.

If AI lowers the effort required to produce these signals, it won’t necessarily reduce their importance, but it could unsettle things in rather odd ways.

If more people use AI to draft emails they don’t particularly want to write, we end up with a game of bureaucratic “mime”: everyone performing sincerity and quietly outsourcing it, and no one entirely sure how much of their inbox was actually written by a human.

The labour of email was never just about crafting sentences. It’s always been the scanning, the sorting and the deciding. AI doesn’t remove this burden. If anything, it amplifies it.

When everything arrives polished, everything looks important. That points to a deeper question for the future of work: if AI can perform responsiveness, why are we generating so many situations that still require it?

Looking forward

What would a workplace look like if email wasn’t the default solution to every coordination problem? Perhaps fewer performative check-ins, “just touching base”, “looping you in” or “following up on the below”. More clearer expectations about what actually requires a response, and what doesn’t.

Email, like paper, is likely to persist for good reasons. It is simple, flexible and universal. It allows things to be deferred, revisited, forwarded and quietly ignored.

But if AI is going to change any of this, my hope is that it makes visible how much of this is ritual, how much is habit, and how much has long been unnecessary.

And if the machines are happy to keep saying “hope this finds you well” to each other, we might finally have permission to stop.

Daniel Angus, Professor of Digital Communication, Director of QUT Digital Media Research Centre, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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In a major milestone for national data infrastructure, the Australian Bureau of Statistics incorporated the Australian Digital Inclusion Index into its key indicators for digital preparedness and economic resilience. ADM+S’s Mapping the Digital Gap project also helped drive new investment in digital infrastructure for First Nations remote communities.

The ADM+S research program continued to evolve in response to the rapid diffusion of generative AI technologies. Our Signature Projects are now well established and are producing new insights into how AI systems are used, deployed, governed and experienced.

One major focus has been the growing importance of social and institutional capabilities for inclusive, responsible and ethical AI. Building on the Centre’s extensive research on digital inequality, ADM+S researchers have begun mapping patterns of generative AI adoption across Australia.

The Centre also made progress in translating research into practice.  Through projects such as the Inclusive AI Capabilities Lab and the development of new evaluation frameworks and toolkits, ADM+S researchers are working with partner organisations to translate research into practical approaches for responsible and inclusive AI deployment. 

These collaborations span sectors including telecommunications, humanitarian organisations, health advocacy groups, libraries and community organisations, and play a crucial role in ensuring that automated systems are developed in ways that serve community interests.

Looking ahead, ADM+S emphasises the need for stronger international collaboration to address the global challenges of AI governance. In 2025, researchers secured new international grants, launched joint initiatives with global partners and contributed to international policy discussions.

We are proud of the achievements of ADM+S researchers, students and staff throughout the year. None of this would be possible without the dedication of our remarkable operations team and the ongoing support and engagement of our partner organisations and collaborating Universities.

View the 2025 ADM+S Annual Report

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As part of this process, the government will establish a technical advisory group to advise on eligibility thresholds. It has promised to “engage with the community” – although when and what this will involve remains unclear.

While we have little detail on the design of the tool, one thing Butler has specified is that the new test will be “standardised”. Typically, this means a rules-based system in which a computer algorithm applies fixed criteria to determine outcomes.

A similar approach has been announced for NDIS planning supports, for people who have been deemed eligible. The controversial new tool for support plans, called I-CAN, will be introduced on April 1 2027. It has already stoked concerns that opaque algorithms are increasingly shaping decisions about who gets support and who is left out.

So while we don’t know exactly what kind of “standardised” tool will be used to assess a person’s functional capacity, we have a glimpse of what might come.

The challenge of standardising need

Such tools can be effective at containing costs. But when applied to something as complex and nuanced as disability, they often fail to give a full picture of individual needs.

When this happens, the consequences show up elsewhere in the system, for example, in rising, costly and time-consuming challenges at the Administrative Review Tribunal over poor-quality support plans. These challenges are happening even before I-CAN has been implemented. The current system has some elements of automation – and it looks as though this is only set to increase.

The shift to a more needs-based approach to assessment is a welcome one. But its effectiveness will ultimately depend on the integrity of the assessment tools and, crucially, the professionals using them.

Where computational systems are used to support decision-making, they must be carefully designed to augment professional expertise and be flexible enough to accommodate individual circumstances.

Aged care offers a cautionary example. In a system aged care workers describe as “cruel” and “inhumane”, experienced assessors have little scope to override algorithms with a proven track record of failing to capture need, leaving people without access to essential care.

There are legitimate concerns the NDIS may be heading in a similar direction.

If algorithms are going to determine who gets support and who goes without, then the entire apparatus – including the algorithm itself, its modelling, classification rules and training data – must be open to scrutiny.

And before the new system is rolled out, people with disability must be at the table shaping its design.

Georgia van Toorn, Senior Lecturer in Public Policy and Politics, UNSW Sydney

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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We asked: what if AI was built around care, cultural knowledge, and responsibility to community, instead of speed and efficiency?

But the reaction of our participants was blunt. Who would that Elder speak for? Who would it answer to? How could it have any real relationship to community?

Elders aren’t just people who hold knowledge. They are part of community: they are trusted because of their relationships, their responsibilities, and their accountability over time.

AI can’t be in relationship in that way, can’t be held accountable, can’t carry obligation. It can’t stand in connection to Country or community.

Even when we try to imagine better versions of AI, there are some things that just don’t translate.

A way forward

AI governance cannot be limited to technical standards or compliance frameworks. It has to engage with authority, responsibility, harm and care.

If AI systems can be designed in ways that are safe, accountable and beneficial for Aboriginal and Torres Strait Islander peoples – who are often the most surveilled and marginalised within systems – they are far more likely to be safe and effective for everyone.

Designing for those at the margins is not a niche concern. It is a test of whether these systems work at all.

As one participant told us:

My biggest concern is that we get left behind. It’s easy to frame AI negatively, seeing it as a threat. It is just as easy to see the benefits it stands to offer. Clearly we need to be involved positively (we risk being left out otherwise) on how AI systems are designed, trained and used, otherwise there is a risk that existing power imbalances will be reproduced through technology.

Relational Futures offers both a warning and a way forward.

Without Indigenous leadership and relational approaches to governance, AI will continue to reproduce the kinds of harms already seen in systems like Robodebt. The way forward is less about slowing technology down, and more about rethinking what it is for, who it serves and how it is held to account.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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For example, the 2Apply form says providing personal information will “help speed up your application process”. Conversely, it also says not providing the information may “affect whether you are considered as a suitable tenant for the property”. The commissioner said these statements, while not necessarily untrue or misleading, suggest the volume and type of personal information provided are indicators of an applicant’s suitability as a tenant.

Tactics like this haven’t been adequately addressed by existing consumer protections, despite ample evidence of digital platforms being designed to manipulate or place undue pressure on consumers.

A bill currently before federal parliament is intended to address unfair trading practices that manipulate or unreasonably distort consumers’ decision-making practices. But it’s noteworthy the commissioner deployed the Privacy Act to address these harms.

The commissioner also found the circumstances in which 2Apply collects personal information are characterised by significant power imbalances, limited choice and security risks relating to the real estate sector. She added:

In the absence of any legislated right to housing, the competitiveness of the current rental market means that individuals are at a disadvantage when trying to rent a home and are more vulnerable.

The commissioner directed 2Apply to stop collecting unnecessary personal information within 60 days. She also required that the platform must appoint an independent privacy expert to review its practices.

The Conversation contacted InspectRealEstate for comment.

Systemic change is needed

The commissioner emphasised the need for other rent tech providers to improve their privacy practices.

But there is a risk these providers won’t heed this advice. More needs to be done to protect renters’ rights.

The Privacy Act’s protections must be strengthened. They must also be complemented by robust laws at the state and territory level that are specifically targeted at the rental tech sector.

Some jurisdictions – including Queensland, South Australia and Victoria – have taken the first steps towards strengthening the protection of renters’ personal information under residential tenancies law. Other jurisdictions must follow.

A promising bill is currently awaiting debate and passage in NSW. If legislated, it could offer some of Australia’s strongest protections.

But after being introduced in June 2025, it appears to be in limbo, leaving NSW renters without adequate safeguards.

Lina Przhedetsky, Postdoctoral Research Fellow, Melbourne Law School, University of Melbourne and ARC Centre of Excellence for Automated Decision-Making and Society, The University of Melbourne

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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An example of how the Australian Internet Observatory supports independent monitoring and information integrity was provided by a submission from the ARC Centre of Excellence for Automated Decision-Making + Society (ADM+S) which highlighted the challenge of monitoring political advertising.

This week the ADM+S Australian Ad Observatory project published a full report on 2025 Australian Election Advertising on Social Media based on their analysis of 22,000+ real ads collected directly from voters’ smartphones using AIO’s Mobile Observation Ad Toolkit. As a result the report provides rare insight into what Australians actually saw on platforms like Facebook, Instagram and TikTok.

As lead researcher Professor Daniel Angus explains: “Online political advertising is largely invisible… voters are being targeted with messages that are difficult to track, poorly disclosed, and often misleading.”

The research was enabled by the Mobile Online Advertising Toolkit (MOAT), developed with the Australian Internet Observatory, enabling researchers to capture real-world ad exposure beyond platform ad libraries.

Key findings from the research:
• Political ads are often invisible to public scrutiny
• Widespread use of misleading and decontextualised claims
• Growth of astroturfing, with lobby groups posing as grassroots organisations
• Evidence of scam ads, impersonation, and emerging AI-generated content

The Senate report emphasised that the complex and multifaceted nature of climate mis/disinformation requires a systemic response that includes governments, knowledge institutions, civil society, industry and particularly greater accountability from media companies and digital platforms.

This inquiry echoes the findings of other inquiries and international campaigns. Australia is a signatory to the 2023 UNESCO Global Declaration on Information Integrity Online (Global Declaration), which deals with information integrity as a whole. In 2025 COP30 was the first COP to include information integrity as a core agenda item. Australia has not yet signed the Declaration on Information Integrity on Climate Change (Declaration) which calls on endorsing countries to promote the integrity of information on climate change at the international, national and local levels.

View the original article published by the Australian Internet Observatory 

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“The inclusion of the Australian Internet Observatory signals a maturing policy response. We are seeing recognition that platform power cannot be governed without independent, national-scale capacity to observe and analyse it,” said Professor Angus.

Established through an initiative from the ADM+S, AIO is a co-investment partnership with the Australian Research Data Commons (ARDC) through the HASS and Indigenous Research Data Commons and a cohort of Australian universities. The AIO is designed to provide independent, large-scale insight into digital platforms and influence ecosystems. Its inclusion in the report signals a shift toward evidence-based infrastructure for understanding and responding to online harms.

“For over a decade, humanities and social science researchers have warned that opaque platform systems can undermine public debate. This report shows that governments are finally catching up, but only if they are willing to invest in the infrastructure and expertise needed to act.”

Several of the report’s central recommendations align directly with areas the ADM+S has championed and led nationally, including:

• Increased funding for social sciences research relating to threats to climate and energy information integrity including potential solutions. (Recommendation 6)
• Funding models for independent monitoring support (for example, via the Australian Internet Observatory) to track hidden digital influence ecosystems and provide independent transparency and accountability of platforms. (Recommendation 7)
• Broaden the Australian Curriculum ‘digital literacy’ general capability to strengthen media literacy through the regular Education Ministers’ Meeting curriculum review cycle (Recommendation 8)
• Incorporate the information integrity framework with examples from the climate and energy domain in the upcoming National Media Literacy Strategy (Recommendation 9)

Read the full report: The Integrity Gap: Restoring Trust in the Climate and Energy Debate – Parliament of Australia 

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Building on this discussion, a Public Service Media Summit was held on 12 March. The summit convened an international cohort of speakers, including representatives from the European Broadcasting Union, RNZ, the ABC, the Responsible Innovation Centre (hosted at the BBC), and leading universities across Europe, the United States and Australia.

Across the summit, participants explored how public service media can respond to rapid technological change, particularly the rise of artificial intelligence and platform-based distribution, while maintaining core democratic values such as universality, accessibility and independence.

ADM+S Chief Investigator James Meese said “It was a pleasure to welcome leading thinkers from across the world to Melbourne to discuss the future of public service media.”

“By convening this week of events, ADM+S has made a key contribution to the global debate around these important challenges”.    

“The week also provided a valuable opportunity for ADM+S colleagues from across the Centre to build new connections, while our early career researchers benefited from Georgie and Fernando’s generous engagement with their work.” 

Summit speakers included: Professor Georgina Born (UCL), Sasha Scott (European Broadcasting Union), Victor Pickard (University of Pennsylvania), Michał Głowacki (University of Warsaw), Patrick Crewdson (RNZ), David Sutton (ABC), Fernando Diaz (Carnegie Mellon) and Helen Jay (University of Westminster/BBC).

Following these discussions, a follow-up global summit is scheduled to take place in London in September 2026.

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CC Signals could operate in much the same spirit. But, as with any system, it has potential benefits as well as drawbacks.

The pros

The framework provides more nuance and flexibility than the current scrape/don’t scrape environment we’re in. It offers creators more control over the use of their content.

It also has the potential to affect how much high-quality content is available for scraping. Without access to high-quality data, AI’s biases are exacerbated and make the technology less useful.

The framework might also benefit smaller players who don’t have the bargaining power to negotiate with big tech companies but who, nonetheless, desire remuneration, credit, or visibility for their work.

The cons

The greatest challenge with CC Signals is likely to be a practical one – how to calculate, and then enforce, the monetary or in-kind support required by some of the signals.

This is also a major sticking point with content industry proposals for collective licensing schemes for AI. Calculating and distributing licence fees for the thousands, if not millions, of internet works that are accessed by generative AI systems around the world is a logistical nightmare.

Creative Commons has said it plans to produce best-practice guides for how to make contributions and give credit under the CC Signals. But this work is still in progress.

Where to from here?

Creative Commons asserts that the CC Signals framework is not so much a legal tool as an attempt to define “manners for machines”. Manners is a good way to look at this.

The legal and practical hurdles to implementing effective copyright management for AI systems are huge. But we should be open to new ideas and frameworks that foreground respect and recognition for creators without shutting down important technological developments.

CC Signals is an imperfect framework, but it is a start. Hopefully there are more to come.

T.J. Thomson, Associate Professor of Visual Communication & Digital Media, RMIT University; Daniel Angus, Professor of Digital Communication, Director of QUT Digital Media Research Centre, Queensland University of Technology; Jake Goldenfein, Associate Professor, Melbourne Law School, The University of Melbourne, and Kylie Pappalardo, Associate Professor, School of Law, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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This allowed researchers to collect more than 22,000 ads, providing rare insight into what Australians actually saw on platforms like Facebook, Instagram and TikTok.

Professor Angus said this method was critical to understanding modern election campaigning.

“Most political content online is unpaid and organic, and even paid advertising is often poorly disclosed,” he said.

“By collecting ads directly from participants’ devices, we were able to see how political influence operates in practice, not just what platforms choose to report.”

The report found that while political advertising made up only a small proportion of total ads, it was dominated by third-party groups, many of which appeared to present themselves as grassroots organisations while obscuring their political or financial backing, a practice known as astroturfing.

Researchers also identified widespread use of misleading and decontextualised claims, particularly around cost-of-living issues, by both major political parties and third-party advertisers.

The study further detected scam advertisements and impersonation, raising concerns about the growing use of artificial intelligence and deepfake-style content in political messaging.

“These practices undermine trust and make it harder for voters to make informed decisions,” Professor Angus said.

“Without stronger oversight, this kind of opaque campaigning risks becoming the norm rather than the exception.”

The study was conducted through the Australian Ad Observatory, part of the ARC Centre of Excellence for Automated Decision-Making and Society (ADM+S). The research was led by Professor Angus in collaboration with colleagues from Monash University, the University of Queensland and the University of Melbourne, with participant recruitment supported by the Susan McKinnon Foundation.

Read the full report 2025 Australian election advertising on social media: An Australian Ad Observatory report

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The research team is now conducting a short online survey for Australian adults to better understand public attitudes and experiences with AI-generated voices in audio media.

Take part in the survey

The research team is conducting a short online survey for Australian adults to better understand public attitudes and experiences with AI-generated voices in audio media.

Participants will be asked about:

• audio listening habits;
• level of experience with AI;
• whether they think they have heard a synthetic voice; and 
• the contexts and conditions in which you feel most strongly about Voice AI

The results will help researchers design future studies examining how generative AI is reshaping media production, audience trust, and online authenticity.

Your participation matters

Participation in the survey is voluntary and can be completed anonymously. Participants who are interested in future research on this topic can also choose to provide their email address to be contacted about follow-up studies planned for later in 2026.

The study has received ethics approval from Queensland University of Technology (Ethics Approval Number 10602).

If you listen to podcasts, radio, audiobooks or other audio media, the researchers would love to hear from you.

Read more about the study Voice AI Authenticity and Media

For more information about the study, contact the research team at p.matich@qut.edu.au

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Other ads were in partnership with prominent retailers, directing people to online shopping interfaces through “buy now” buttons.

Most formula brands made some kind of claim regarding the nutritional or behavioural benefits of their products. These claims prey on the anxiety parents commonly feel to ensure their children are meeting nutritional, sleep and developmental milestones.

Some manufacturers claimed their product was fortified with vitamins and prebiotics that would “improve gut health” or help a toddler sleep longer at night.

Others claimed their formula would provide mothers with “a moment of calm” or strengthen their toddler’s immune system. This is despite scientific evidence that shows breastmilk can provide necessary antibodies to a sick child in real time.

Starting them young

Many of the ads used pictures of very young toddlers who could easily be mistaken for infants aged 12 months or under. In one instance we discovered an ad clearly promoting formula designed for babies under 12 months.

This, alongside the use of images of very young children to promote “toddler milk” (formula marketed for children aged 1–3 years), highlights some of the issues with a voluntary advertising agreement.

Since toddler milk marketing was exempt, brands could target parents of newborns. They’d gain brand awareness and consumer trust, which could then result in a parent choosing to start their child on formula instead – or earlier than they otherwise would.

Enforcement has also been an issue. The consequences for breaching the agreement – publishing the breach on the Department of Health website – are not considered meaningful enough by the Australian Competition and Consumer Commission.

At the same time, the digital advertising environment provides very little visibility into what marketing is actually circulating or who is exposed to it.

Outside of specialised research tools, such as our Ad Observatory and the Australian Internet Observatory, there’s no systematic way to observe infant formula ads that appear on personalised social media feeds.

What might the government end up doing about it?

The government is considering the following options:

1. keep the status quo – no regulation
2. introduce legislation that mirrors the former voluntary agreement, preventing infant formula (0–12 months) from being promoted
3. introduce legislation that also limits toddler milk marketing (1–3 years).

We’ve provided all our data to the government to aid the decision-making process. However, while the ads we found are a peek behind the curtain, they likely underrepresent the scale of formula marketing happening online.

Infant formula can be an essential and sometimes life-saving intervention for families who need it. But health interventions don’t depend on persuasive advertising to fulfil their purpose.

The real policy question is whether a product designed to support infants should be promoted through the same marketing systems that sell snack foods, cosmetics and financial products.

Acknowlegement: The Australian Ad Observatory is a team effort. The authors wish to acknowledge the contribution of Khanh Luong, Giselle Newton, Phoebe Price-Barker, Lara Skinner, Abdul Obeid and Dan Tran.

Madeleine Stirling, Research Assistant, ARC Centre of Excellence for Automated Decision-Making & Society, The University of Melbourne; Christine Parker, Professor of Law, The University of Melbourne, and Daniel Angus, Professor of Digital Communication, Director of QUT Digital Media Research Centre, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Lead investigator Associate Professor Daniel Featherstone said the project gives communities better tools to access essential services and make informed decisions in an increasingly digital society.

“By mapping all ways people communicate, we’re seeing how place-based solutions can best address local context and needs rather than relying on one-size-fits-all models,” he said.

Partnership with local organisations is central
Working with First Nations organisations across remote communities, the team employs community‑based co‑researchers to collect and interpret data.

Indigenous leadership is embedded at every stage, from shaping research questions to deciding how findings are used.

The Mapping the Digital Gap reports have been a powerful advocacy tool for the Wujal Wujal community in Far North Queensland.

Former Wujal Wujal Aboriginal Shire Council CEO Kylie Hanslow said the research reports helped them advocate for improved services.

“They were one of the main resources we relied on for the increase in the speeds and the requirements for improvements to digital connectivity,” she said.

Ormond-Parker said the work has highlighted the need for coordinated action.

“We’ve seen it’s really important to ensure industry, governments and communities are on board, and that these initiatives are run and led by the communities themselves,” he said.

Five years in, Mapping the Digital Gap is reshaping how digital inclusion in remote Australia is understood.

By generating detailed, community‑driven evidence, it is helping remote First Nations communities secure better services, strengthen local decision making and influence national policy on digital inclusion.

The next Mapping the Digital Gap report is expected towards the end of 2026.

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In an initial workshop, participants explored how a bot designed to “always agree” responds differently from one designed to be “careful” in its responses. Children were then invited to suggest how chatbots might respond in better ways, and to imagine ways of helping other young children understand and explore the possibilities and limitations of chatbots. 

Professor Danby said collaborating directly with children is essential as AI becomes embedded in everyday life.

“Children understand their digital worlds often in ways adults often don’t.”

“ As AI becomes part of everyday life and shapes the digital tools they use, collaborating with children about AI helps guide how these technologies are designed and respects children’s rights and helps them move through digital spaces with safety and confidence.”

The project focuses on voice as a primary interface with Generative AI for young children. AI voice interfaces are increasingly embedded in toys and other ’smart’ objects encountered by children and families. 

The team will now build on this pilot to develop publications, educational materials, and future iterations of the game and workshop activity. 

This project is being led by Dr Henry Fraser (QUT), Associate Investigator at the ADM+S, aligned with the Critical Capabilities for Inclusive AI project, with Prof Tama Leaver (Curtin University), Dist. Prof Susan Danby (Centre Director, QUT), Dr Kristy Corser and Dr Irina Silva (QUT), and Dr Suzanne Srdarov (Curtin University), from Digital Child; and Dist. Prof Jean Burgess (Associate Director), William He and Kathy Nickels (QUT), from ADM+S.

Special thank you to Maria Pinto for assistance with the video script and providing voice-over. 

View the AI explainer video Alex and the AI Chatbot video

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To further develop the partnership, the delegation invited ADM+S students and staff to attend the upcoming Peking University Summer Program in July 2026. The program, delivered in English, will focus on topics including advertising and AI, internet governance, AI and human interaction, and media and society Participants will also visit leading technology companies such as ByteDance and Tencent, alongside cultural sites including the Summer Palace.

ADM+S Chief Operating Officer Nick Walsh said, “We were delighted to host this delegation and the visit was a terrific success. It created meaningful opportunities to strengthen connections, share ideas, and identify areas for future collaboration.”

“It was particularly wonderful seeing the students from Peking University engaging with our researchers at the annual Summer School. We look forward to working closely together in the years ahead.”

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In other words, AI systems and tools can be covered by the rules we already have, such as consumer protections against all misleading and deceptive practices. The government suggested this option back in 2024. (We have previously argued this view, favoured by the Productivity Commission, is not well supported and was not our preferred option.)

Problems with the plan

However, the challenges for applying existing laws, which the government identified years ago, have not gone away.

As we identified in 2023, the existing regulatory frameworks have limitations when it comes to AI.

AI systems are complex, they can act semi-autonomously, and it can be difficult to understand why they do what they do. This makes it very hard to effectively attribute liability or responsibility for AI risks or harms using existing laws and processes.

Regrettably, those limitations have not been addressed systematically – if at all.

Fragmented rules and limited resources

As things stand, the regulatory landscape is highly fragmented and uncertain.

For instance, there are at least 21 mandatory (or quasi-mandatory) state and federal policies about the use of AI in government. Courts have so far had little opportunity to clear things up, with almost no test cases in crucial areas of existing law, including negligence, administrative law, discrimination law, and consumer law.

The new plan is accompanied by a clear commitment to monitor the development and deployment of AI “and respond to challenges as they arise, and as our understanding of the strengths and limitations of AI evolves”.

The issue is: how will that monitoring happen? Will the government really “empower every existing agency across government to take responsibility for AI”?

Dealing with issues such as privacy, consumer protection, anti-discrimination will take money and commitment and a degree of coordination between agencies we have not witnessed to date.

An uncertain future

For predictability, signals matter. A lot.

If there is a change in government in the US in 2028, will that change how Australia regulates AI – in the same way the beginning of the Trump presidency coincided with the abandonment of Australia’s mandatory AI guardrails proposals?

Is a laissez-faire regulatory approach creating predictability, when we have so many stalled and part-completed regulatory processes?

The government seems to expect courts, government agencies, businesses and individuals to work out on their own how to retrofit old laws and institutions to a new technological landscape.

There is some hope for regulation of automated decision-making in the public sector (promised after the Robodebt Royal Commission). For the rest, it’s a “wait and see” approach to AI regulation. We’ll have to wait and see if it works.

José-Miguel Bello y Villarino, Senior Research Fellow, Sydney Law School, University of Sydney and Henry Fraser, Research Fellow in Law, Accountability and Data Science, Queensland University of Technology

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Through his support, these initiatives have generated significant outcomes in knowledge exchange, network building, and sustained collaboration, exceeding all expectations.

Announcing the award, Distinguished Professor Calum Drummond AO, Deputy Vice-Chancellor Research and Innovation and Vice-President, said that deciding a winner for this category was not an easy task.

“The selection panel received many strong nominations from across the organisation. After careful consideration, Mathew’s outstanding effort in fostering collaboration was selected as the winner.”

“His dedication has made a significant impact on the research community.”

All awards were presented by Distinguished Professor Calum Drummond, AO the Deputy Vice-Chancellor in Research and Innovation, and Vice-President of RMIT University.

Learn more about the RMIT Research Service Awards and Prizes.

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It potentially also helps with cognitive overload. Rather than having to spend the time and mental energy to decide on a case-by-case basis whether each source you encounter is trustworthy, making this decision once for particular news brands or organisations can make engaging with search results more relevant and efficient.

But a lack of balance is risky

However, the voices people want to hear from aren’t necessarily the ones that are best for them. As with any choice, you need a level of maturity and critical thinking to act responsibly.

As data companies, search engines benefit from knowing ever more information about user behaviour and preferences. Knowing which media outlet you prefer may in some cases indicate your political party preferences. Knowing that you prefer sports news over celebrity news can help companies target you with advertising more effectively.

In addition, more choice could potentially affect the diversity of people’s media diets. Just like with food diets, if people rely too much on low-quality media, over time that may affect their opinions, attitudes and behaviours. This has important implications for democracies that rely on well-informed and engaged citizens to cast votes.

There’s also a risk in conflating news sources with other types of sources. Journalists at news organisations are often held accountable to professional codes of conduct that, for example, aim to prevent reporters from personally benefiting from their reporting.

In theory, this allows audiences to receive independent analysis on important topics with confidence that the source has fact-checked claims and doesn’t have a vested interest in the reporting.

But if you select a business – such as the blog of a hardware store or a bank – as a source, you don’t have those same guarantees around editorial codes of conduct and professional ethics.

Should you use this feature?

Overall, allowing users more control over what they see is a good thing. But appropriate governance and regulation – possibly championed by Australia’s Digital Platform Regulators Forum – is needed to ensure people’s privacy and that their source preferences aren’t unfairly monetised.

Being more involved in your media diet is a positive step, as is thinking about its balance and diversity.

Ensuring a mix of sources across types (think local, regional, national, and international) and varieties (political, social, sports, entertainment news, and so on) can lead to a better balance.

Also think about whether the sources you are relying on are based on opinions or on facts. Doing this and actively creating a high-quality media diet is better for you and for others in your community.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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The report concludes that without clearer publication practices and stronger compliance mechanisms, the policy risks falling short of its intended transparency and accountability goals.

Recommendations:

• AI transparency statements should be published in one central location.
• The DTA should reconsider the entities subject to the Policy and have an explicit list of the entities that are strictly bound by the policy.
• The DTA should explore mechanisms to ensure that the policy and requirements are complied with, including by considering what consequences flow from non-compliance.
• The Standard for AI transparency statements should be revised to ensure it cannot just be ‘formally’ complied with, without providing meaningful information.

This report was authored by Prof Kimberlee Weatherall, José-Miguel Bello y Villarino, and Alexandra Sinclair with research assistance provided by Shuxan (Annie) Luo from the University of Sydney node and aligns with the Regulatory Project at the ADM+S

Read the full report AI Transparency in Practice

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He said limited infrastructure, low household connectivity and high reliance on pre‑paid mobile services make it much harder for people in remote communities to get online.

“In the 12 remote communities visited under our Mapping the Digital Gap research, nearly three in four people were impacted by digital exclusion,” Featherstone said.

“The biggest contributors to the digital gap were low rates of household connectivity and reliance on pre‑paid mobile services, with affordability another key factor.

“Free public Wi‑Fi begins to relieve some of that pressure, but it needs to be paired with investment in local infrastructure and affordable home connections if we’re serious about closing the digital gap.

“In the meantime, many remote communities still go without reliable internet and phone services, so there is a long way to go.”

Organisations and communities can use an interactive dashboard tracking First Nations digital inclusion to inform local decision making.

Access the First Nations Digital Inclusion Dashboard developed as part of the Australian Digital Inclusion Index project at the ADM+S

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ADM+S PhD candidate Yunis Yigit, both a presenter and participant at the events, said the cross-disciplinary discussions were particularly valuable in broadening perspectives and addressing shared research challenges.

“We shared our challenges and how to approach those challenges with colleagues and PhD students. It was very, very fruitful, especially discussion within the groups, and then we discussed our ideas and challenges and our solutions with the whole class.”

“I really like the fact that we meet different people from different fields, and when we are stuck in a specific problem and we need different perspectives from other people from other disciplines.” 

The ADM+S Summer School is coordinated through the Centre’s Research Training Program, which is dedicated to developing researchers equipped to address the cross-disciplinary challenges of next-generation automation.

ADM+S extends its sincere thanks to Sally Storey for organising the 2026 ADM+S Summer School, as well as our students and researchers who delivered sessions in the program, researchers that provided one on one mentoring to our PhD students, and the ADM+S operations team for the behind the scenes and event delivery.

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“The rapidly changing technology, evolving regulatory landscape and breadth of issues added to the challenge of this inquiry.”

Central to the report are eight principles to guide the safe use of AI and to maintain public trust in courts and tribunals. Guidelines are recommended to support court users, judicial officers and court and tribunal staff to implement the principles. 

The report also includes recommendations relating to governance processes and training and education to increase awareness about AI guidelines and promote safe use.

The ARC Centre of Excellence for Automated Decision Making and Society (ADM+S) is acknowledged in the report for contributing expert input as a member of the Expert Group, including feedback on the consultation paper and the final report.

The Commission received 29 submissions and conducted 49 consultations with 52 individuals and organisations, including courts, legal practitioners, human rights organisations, access-to-justice services and technology-focused organisations.

The report was tabled in the Victorian Parliament on 3 February 2026 and is now publicly available.

Expert group members from the ADM+S: Dist. Prof Julian Thomas (RMIT), Prof Christine Parker, Dr Jake Goldenfein (University of Melbourne), Prof Kimberlee Weatherall (University of Sydney), Dr Aaron Snoswell (QUT) and Will Cesta (University of Sydney).

Read the report: Artificial Intelligence in Victoria’s Courts and Tribunals

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@australianassociatedpress

4. User practices change

Over time, user practices have also changed in response to cultural trends and changes of the platform design itself.

An example of this is social media accounts starting to insert hashtags in a post comment rather than directly in the post description. This is supposed to help the post’s algorithmic ranking.

Another key change over this timeframe was Instagram’s decision in 2019 to hide “likes” on posts. The thinking behind this decision was to try to reduce the pressure on account owners to make content that was driven by the number of “like” interactions a post received. It was also hypothesised to help with users’ mental health.

In 2021, Instagram left it up to users to decide whether to show or hide “likes” on their account’s posts.

5. The platform became more commercialised

Instagram introduced a Shop tab in 2020 – users could now buy things without leaving the app.

The number of ads, sponsored posts, and suggested accounts has increased over time. Looking through your own feed, you might find that one-third to one-half of the content you now encounter was paid for.

6. The user experience shifts with algorithms and AI

Instagram introduced its “ranked feed” back in 2016. This meant that rather than seeing content in reverse chronological order, users would see content that an algorithm thought users would be interested in. These algorithms consider aspects such as account owner behaviour (view time, “likes”, comments) and what other users find engaging.

An option to opt back in to a reverse chronological feed was then introduced in 2022.

To compete with apps such as Snapchat, Instagram introduced augmented reality effects on the platform in 2017.

It also introduced AI-powered search in 2023, and has experimented with AI-powered profiles and other features. One of these is turning the content of a direct message into an AI image.

Looking ahead

Overall, we see more convergence and homogenisation.

Social media platforms are looking more similar as they seek to replicate the features of competitors. Media formats are looking more similar as the design of smartphones and software favour vertical media. Compositions are looking more multimodal as type, audio, still imagery, and video are increasingly mixed.

And, with the corresponding rise of AI-generated content, users’ hunger for authenticity might grow even more.

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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