S.M.A.C.C. NEWS DESK | Monday, 2 November 2026
Four major developments. Four countries and industries affected. One fundamental question: Just because technology can do something, does that mean it should?
Artificial intelligence companies are introducing new ways for website owners to restrict the use of their content.
Meta has settled another lawsuit alleging that social-media platforms cause harm to young users.
Australian police have scanned nearly 1.4 million faces in public places.
And Indigenous artists are warning that AI-generated imitations threaten not only their livelihoods but also their cultural heritage.
These developments might appear unrelated.
But they all concern the same fundamental issue.
Who has the right to collect, analyse, reproduce and commercially exploit information about other people — and who is accountable when things go wrong?
Welcome to the S.M.A.C.C. News Desk.
IN THIS EDITION
- AI GIANTS AGREE ON A COMMON ‘DO NOT TRAIN’ SIGNAL: OpenAI, Google, Microsoft and Anthropic back a shared mechanism allowing website owners to express preferences about AI training.
- META SETTLES ANOTHER SOCIAL-MEDIA HARM LAWSUIT: The company reaches a confidential agreement, leaving Snapchat’s parent company facing a significant US trial.
- 1.38 MILLION FACES SCANNED BY AUSTRALIAN POLICE: Facial recognition helps police report 122 arrests, but raises important questions about privacy and surveillance.
- INDIGENOUS ARTISTS CHALLENGE AI IMITATIONS: Australian creators warn that artificial intelligence can reproduce cultural artwork without respecting its origins, meaning or ownership.
1. AI GIANTS AGREE ON A COMMON ‘DO NOT TRAIN’ SIGNAL
YOUR WEBSITE. YOUR CONTENT. YOUR CHOICE?
For years, independent creators have faced a difficult question.
How do you make your work available on the internet without automatically making it available for every possible use by artificial intelligence companies?
A photographer wants potential customers to find their website.
A journalist wants readers to discover their investigations.
A filmmaker wants audiences to watch their trailers.
But none of those activities necessarily means the creator wants their original work used to train commercial AI systems.
Now four major technology companies have announced support for a common mechanism intended to make those preferences easier to communicate.
OpenAI, Google, Microsoft and Anthropic are backing a shared AI-training preference signal through the familiar robots.txt system used by websites.
The proposal builds on work being undertaken through the Internet Engineering Task Force (IETF).
Instead of configuring separate instructions for each AI company, website owners would be able to express a common preference recognised by participating providers.
Anthropic has already adopted the mechanism.
OpenAI expects to implement it in the coming months.
Google and Microsoft are targeting implementation during 2027.
Meta has expressed support for the idea of a common standard but has not confirmed that it will honour this particular signal.
Why is this important?
Consider a professional photographer who has spent 20 years developing a distinctive style.
Their website contains thousands of original photographs.
They want those photographs to be discoverable by prospective customers.
But they may not want them used to help train systems capable of generating competing images.
Until now, the practical choices have been complicated.
Blocking access too broadly can interfere with legitimate discovery.
Allowing unrestricted automated access may create concerns about how original work is subsequently used.
The proposed common signal offers a potentially simpler way to express the creator’s wishes.
But there is an important limitation
A technical preference is not the same as a legal prohibition.
The proposed mechanism does not create new copyright rights.
It does not guarantee that every AI developer will comply.
It does not automatically prevent all automated access.
And it does not establish a right to payment.
It is a method for communicating preferences, which participating companies say they will respect.
The proposal is also still an Internet-Draft rather than a completed international standard.
Microsoft introduces another distinction
Microsoft has announced plans to provide separate controls for AI training and AI grounding.
Grounding involves retrieving external information to support AI-generated answers.
That is different from using information to train a model.
Microsoft says website owners will be able to control these activities separately while retaining eligibility for conventional Bing search results.
This distinction could become commercially important.
An independent publisher might welcome an AI service referring readers to its articles.
But it might object to the same material being used to train a commercial model.
Those are not necessarily identical permissions.
The S.M.A.C.C. question
Should the default assumption be that everything published on the internet is available for AI development unless its owner objects?
Or should companies obtain permission before using protected material for certain commercial purposes?
There are legitimate arguments about innovation, access to information, copyright exceptions and licensing.
But creators should at least be able to understand the choices available to them.
This new proposal is a potentially useful development.
Whether it becomes meaningful protection will depend on adoption, compliance and the legal frameworks surrounding it.
Original sources:
OpenAI — Making it easier for websites to express AI training preferences:
https://openai.com/index/helping-websites-express-ai-training-preferences/
Google Search Central — Supporting a shared AI training control:
https://developers.google.cn/search/blog/2026/10/ai-training-control
IETF — Machine-Readable Training Preference Signal:
https://datatracker.ietf.org/doc/html/draft-kelley-aipref-training-preference-signal
2. META SETTLES ANOTHER SOCIAL-MEDIA HARM LAWSUIT
WHEN ENGAGEMENT BECOMES A LEGAL QUESTION
Meta has reached another confidential settlement in litigation concerning the alleged effects of social-media platforms on young users.
The latest agreement was announced on Friday, 30 October, after jury selection had begun in Los Angeles.
Two young plaintiffs alleged that social-media companies designed their services to encourage compulsive use and contributed to serious mental-health difficulties.
The defendants originally included Meta, Snap, TikTok and YouTube.
TikTok and YouTube had already reached settlements.
Meta subsequently settled with both plaintiffs.
That leaves Snap, the company behind Snapchat, as the remaining defendant in the consolidated trial.
Opening statements are scheduled for 4 November, unless the proceedings change.
The terms of Meta’s settlement have not been disclosed.
Importantly, reaching a settlement is not an admission of liability.
Meta disputes the allegations and says it has spent years introducing protections for younger users.
Snap also contests the claims against it.
Why this case matters
Social-media platforms operate through systems designed to attract and retain audiences.
Recommendations, notifications, autoplay and continuous scrolling are familiar features.
For independent creators, these systems can be enormously valuable.
They help distribute videos, photographs, journalism and entertainment to audiences who might never otherwise discover that work.
But the same features can encourage people to spend longer using a service.
And longer engagement can create additional commercial opportunities for the platform.
That raises a difficult question.
At what point does designing a service to encourage engagement become designing a service in a way that creates unacceptable risks?
The commercial conflict
Imagine an independent filmmaker publishing a documentary.
The filmmaker wants people to watch it.
They want audiences to discover their other productions.
And they may hope to generate advertising revenue or attract paying customers.
Those are legitimate commercial objectives.
The platform also wants people to remain engaged.
But should there be limits on the techniques used to achieve that objective, particularly when children are involved?
The plaintiffs argue that certain platform features encouraged compulsive behaviour.
The companies reject the allegation that they deliberately designed their services to addict young users.
These are contested legal questions.
What could change?
Thousands of related claims have been brought against technology companies in the United States.
The Los Angeles proceedings form part of a series of test cases that could influence how other claims are handled.
The outcomes may eventually affect expectations about platform design, safety features and accountability.
For independent creators, changes to recommendation systems or engagement features could also affect how content reaches audiences.
The S.M.A.C.C. question
Should a technology company be responsible for harm allegedly caused by the way its platform is designed, rather than simply the content published on it?
This is a significant distinction.
For years, debates about social-media responsibility have often concentrated on individual posts, videos and comments.
Increasingly, attention is turning towards the systems deciding what people see, how frequently they see it and how long they remain engaged.
The legal outcomes remain uncertain.
But the issue is unlikely to disappear.
Sources:
AFP — Meta settles, leaving Snap sole defendant in new social-media trial:
https://www.afp.com/en/meta-settles-leaving-snap-sole-defendant-new-social-media-trial
California Courts Newsroom — Meta settles second social-media trial:
https://newsroom.courts.ca.gov/news/meta-settles-2nd-social-media-trial
3. AUSTRALIAN POLICE SCAN 1.38 MILLION FACES — AND REPORT 122 ARRESTS
SMART POLICING OR MASS SURVEILLANCE?
Police in Western Australia have released the results of a five-month trial involving live facial-recognition technology.
The figures are extraordinary.
1,380,882 faces scanned.
100 deployments across 43 locations.
292 alerts generated.
122 arrests reported.
Police also identified and engaged with 146 registered sex offenders and conducted 10 welfare-related checks.
The force reported nine incorrect alerts.
The technology was deployed using visible cameras mounted on or near marked police vehicles.
As people passed the cameras, their faces were compared with predetermined police alert lists.
Police say images of people who did not match the lists were automatically pixelated and deleted without being stored.
The trial concluded on 31 October.
Police are now evaluating its effectiveness, safeguards and community impact.
The case for facial recognition
There is an obvious potential benefit.
Police need to identify wanted individuals.
They also have responsibilities to protect vulnerable people and locate those who may be at risk.
Technology that helps officers identify someone they are lawfully seeking could improve public safety.
The Western Australian Police Force argues that the trial demonstrates the technology’s operational value.
And the reported results deserve serious consideration.
But there is another side.
What about the other 1.38 million faces?
The overwhelming majority of people scanned were not subsequently identified as individuals police were seeking.
They were ordinary members of the public going about their lives.
They had not necessarily committed any offence.
They were not necessarily suspected of wrongdoing.
Yet their faces were automatically analysed.
This raises an important distinction.
Being visible in a public place is not necessarily the same as agreeing to automated biometric identification.
A person walking down a street expects other people to see them.
They may expect to appear incidentally in CCTV footage.
But live facial recognition can transform that ordinary observation into an automated comparison with police databases.
The technology changes what is possible.
The question is how that capability should be controlled.
What do the error figures really mean?
Police reported nine incorrect alerts among approximately 1.38 million scans.
That produces the very low percentage highlighted by the force.
However, the accuracy of a facial-recognition system cannot necessarily be assessed using only the total number of faces scanned.
It is also important to examine how many alerts were incorrect, how those alerts were handled and what happened to the individuals involved.
Using the police’s published figures, nine incorrect alerts among 292 total alerts represents approximately 3.1% of alerts.
That does not mean 3.1% of all scans were incorrect.
It illustrates why the denominator matters when interpreting performance statistics.
Civil-liberties organisations have also raised questions about privacy, safeguards and the consequences of incorrect identification.
And an arrest, of course, does not establish guilt.
The bigger issue
This is not simply a question of whether facial recognition works.
It is a question of proportionality.
What level of public surveillance is justified to achieve a particular policing objective?
Who decides where the cameras can operate?
Should they be used at demonstrations?
How transparent should the alert lists be?
What independent oversight is required?
And what happens if someone is incorrectly identified?
These questions deserve careful consideration rather than automatic support or rejection of the technology.
The S.M.A.C.C. question
If technology can identify almost everyone passing through a public space, should the authorities be permitted to use it simply because it is available?
There may be circumstances in which facial recognition provides substantial public benefit.
But that does not eliminate the need for clear rules, meaningful safeguards and public accountability.
This is another example of technological capability developing faster than the legal and ethical consensus surrounding its use.
Sources:
Western Australia Police Force — Official trial results and methodology:
https://www.wa.gov.au/organisation/western-australia-police-force/live-facial-recognition-technology
The Guardian Australia — Facial-recognition trial investigation, 2 November 2026:
https://www.theguardian.com/australia-news/2026/nov/02/wa-police-facial-recognition-technology-trial
4. INDIGENOUS ARTISTS CHALLENGE AI IMITATIONS
AI CAN COPY THE ART. BUT CAN IT COPY THE CULTURE?
A new investigation from Australia raises questions extending beyond conventional copyright infringement.
Indigenous artists are warning that artificial intelligence is reproducing visual styles and cultural artwork without adequately recognising the people and communities from which those works originate.
Pitjantjatjara artist Sally Scales has criticised AI-generated imitations of First Nations artwork.
The concern is not simply that technology can produce images resembling existing paintings.
It is that the images may reproduce visual elements without understanding the cultural knowledge, history and relationships behind them.
Artwork associated with Indigenous communities can contain stories, traditions and meanings that are not freely interchangeable.
Some elements may be connected with particular families or communities.
Others may have cultural significance that cannot be understood simply by examining the finished image.
The commercial problem
The investigation identifies concerns about imitations appearing on online marketplaces, sometimes without clear attribution.
Artists and advocates also report instances of Indigenous art-centre material allegedly being collected, altered or reused without appropriate permission.
These allegations raise both economic and cultural concerns.
An original artist may lose commercial opportunities when inexpensive imitations compete with authentic work.
Customers may struggle to distinguish genuine artwork from synthetic reproductions.
And cultural imagery may be presented inaccurately or in inappropriate contexts.
Why conventional copyright may not be enough
Copyright law generally protects original creative expression.
But it does not automatically provide exclusive ownership of every artistic style, technique or cultural tradition.
That distinction creates complications.
An AI-generated image may resemble the visual characteristics of a particular artistic tradition without necessarily reproducing a legally protected portion of one identifiable work.
The legal analysis can be difficult.
But for Indigenous communities, the concern may go further.
The issue can involve collective cultural knowledge, community authority and the appropriate use of traditional imagery.
These interests do not always fit neatly into copyright systems designed primarily around individual authors and identifiable works.
What protections are being proposed?
Australian researchers and arts organisations are exploring stronger arrangements.
Suggestions include greater transparency about AI training data, improved mechanisms for refusing unauthorised use, compensation arrangements and more effective removal of misleading imitations.
Some advocates argue for protections extending beyond conventional copyright.
These are proposals, not established new legal rights.
Why this matters to every creator
Although this investigation concerns Indigenous artwork, the commercial questions are relevant internationally.
Consider a photographer whose distinctive images have become widely recognised.
Or an illustrator who has spent decades developing a particular visual approach.
Or a filmmaker whose productions have a recognisable creative identity.
AI systems can generate material resembling those styles.
But the original creators may have limited control over the process.
There is an important distinction between drawing inspiration from creative traditions and unlawfully reproducing protected material.
There is also a difference between what is legally permissible and what is commercially or ethically appropriate.
The S.M.A.C.C. question
If artificial intelligence can imitate the appearance of someone’s creative work, what responsibilities should exist towards the people and communities who developed it?
The answer may involve copyright, cultural protections, licensing, attribution and commercial fairness.
It may also require recognising that some creative works have significance beyond their monetary value.
Source:
The Guardian Australia — AI imitation and Indigenous artwork, 2 November 2026:
https://www.theguardian.com/artanddesign/2026/nov/02/ai-stealing-indigenous-australian-art-temu-slop-artist-says-ntwnfb
THE BIGGER PICTURE: TECHNOLOGY CAN DO ALMOST ANYTHING. BUT WHO GIVES PERMISSION?
Four developments.
Four different questions.
And one increasingly important principle.
Technological capability does not automatically establish a right to use that capability without restriction.
AI companies can collect and analyse enormous quantities of online material.
Social-media platforms can develop systems that influence how long people remain engaged.
Police can deploy technology capable of comparing millions of faces against databases.
And generative AI can reproduce visual characteristics associated with existing creative work.
All these capabilities may have legitimate uses.
AI can improve access to information and reduce production costs.
Social-media platforms can help independent creators build international audiences.
Facial recognition may help police identify wanted individuals or protect vulnerable people.
And generative technology can create new forms of art and entertainment.
The issue is not whether innovation should be allowed.
The issue is whether innovation is accompanied by appropriate rights, responsibilities and safeguards.
Ownership is not the same as access
Publishing something online does not necessarily mean surrendering every right associated with it.
Appearing in a public place does not automatically resolve every question about biometric surveillance.
Agreeing to use a social-media service does not necessarily mean users have accepted every possible risk associated with its design.
And the ability to reproduce an artistic style does not eliminate the cultural or commercial interests associated with its origins.
These distinctions matter.
The law is struggling to keep pace
Technology frequently develops faster than legislation.
New capabilities emerge.
Businesses find commercial applications.
Consumers begin using them.
And only afterwards do courts, regulators and governments attempt to establish appropriate boundaries.
That is not necessarily evidence that the technology itself is harmful.
But it creates uncertainty.
Creators may not understand how their work is being used.
Businesses may not know which practices will ultimately be considered lawful.
And ordinary members of the public may discover that their personal information can be analysed in ways they never anticipated.
The importance of accountability
There is no single solution that applies to every technology or jurisdiction.
Some issues require legislation.
Others may be addressed through commercial agreements, technical standards, professional codes or independent oversight.
But accountability must be part of the process.
Technology companies should explain what their systems do.
Creators should understand the rights associated with their work.
Public authorities should justify intrusive uses of technology.
And individuals should have meaningful ways to challenge misuse.
THE S.M.A.C.C. CONCLUSION
At S.M.A.C.C., we support technological innovation.
Artificial intelligence, social media and digital production tools have created extraordinary opportunities for independent creators.
We do not believe innovation should be prevented simply because it introduces unfamiliar questions.
But we also believe that those questions must be answered.
Who owns the content?
Who controls the technology?
Who has given permission?
Who receives the commercial benefit?
And who accepts responsibility when something goes wrong?
These are not obstacles to progress.
They are essential questions if technological progress is to benefit society fairly.
The future of the creator economy cannot be determined solely by the companies developing the technology.
The people creating the content, the audiences consuming it and the communities affected by it must also have a voice.
YOUR CONTENT. YOUR FACE. YOUR RIGHTS.
BUT WHO IS REALLY IN CONTROL?
That is the question we should all be asking.
ABOUT S.M.A.C.C.
S.M.A.C.C. — Social Media and Content Creators Global Community
S.M.A.C.C. is a global community supporting people who create, publish and build businesses through digital media.
Our mission is to encourage professional recognition, responsible content creation, commercial opportunities and stronger representation for independent creators.
We examine the technological, legal, ethical and commercial developments shaping the digital economy.
Our community welcomes creators, photographers, filmmakers, journalists, digital publishers, industry professionals and organisations interested in supporting the creator economy.
Membership is free.
Join S.M.A.C.C. and become part of the conversation.
EDITORIAL DISCLAIMER
This article contains independent reporting, commentary and analysis based on publicly available information.
Legal allegations are distinguished from established findings. Settlements do not necessarily constitute admissions of liability. Technical proposals are not presented as enacted laws or binding standards.
Police operational statistics are attributed to the relevant authority and do not establish criminal guilt or independently validate every claim of system effectiveness.
Copyright and privacy protections differ between jurisdictions.
The article is provided for general information and discussion and does not constitute legal, financial or professional advice.
S.M.A.C.C. encourages readers to consult original sources and consider competing perspectives when evaluating developments in technology, regulation and digital rights.
RELEVANT ORGANISATIONS AND MENTIONS
@OpenAI | @Google | @Microsoft | @Anthropic | @Meta | @Snap Inc. | @The Guardian
LinkedIn mentions may need to be selected manually from LinkedIn’s organisation suggestions to activate the tags.
HASHTAGS
#SMACC #CreatorEconomy #ContentCreators #ArtificialIntelligence #CreatorRights #Copyright #Meta #OpenAI #PrivacyRights #FacialRecognition #DigitalRights #IndigenousArt #AIRegulation #SocialMedia #IndependentCreators #DigitalMedia #ResponsibleTechnology #PowerAndResponsibility
