Don't Want Your Data Used for AI Training? Here's How to Opt Out Across Apps and Devices

It seems like every software or website update brings new AI features. Some people find these features useful and immediately integrate them into their work. Others find them annoying or in the way. In both cases, you might not want the work you’re doing in that app used for AI training. So, what can you do? Well, that depends, but you do have some options for control.

In general, the more information an LLM-based AI tool trains on, the more accurate and useful it tends to become. By default, many AI tools collect data on how you interact with them, then use that to attempt to make their tools better. It important to note that users data may also be subject to “human review,” a process that most AI companies use where a person manually reviews whatever an AI produces to check for accuracy. Once your data is used to train an AI model, it’s not typically possible to remove its influence on that model.

You should always be able to opt out of that training. And if you don’t want AI features at all, it’d really be nice if you could get rid of them—but that’s only an option sometimes.

Tell Chatbots Not to Train on Your Conversations

AI chatbots collect loads of data about how you use them, and much of that gets used for training to “improve models,” which can also sometimes mean some sort of human review step. Thankfully, most chatbots allow you to turn this off if you don’t want the content of your chats being used for purposes beyond the chat itself.

Because these directions tend to change often, and sometimes are completely different depending on which platform you’re on, we’ve collected the links to each specific tool’s documentation:

ChatGPT

Web (signed in) users: Open your account menu > Select Settings  > Select Data controls (or visit https://chatgpt.com/settings/data-controls directly) > Select Improve the model for everyone, turn it off, the toggle will appear greyed out once disabled. More details about Apple, Android and Signed-out can be found here.

Note: ChatGPT's Voice mode has a separate control for sharing data for model training. Users need to visit the Privacy Portal to make a separate request.

Perplexity

Web (signed in) users: The company claims its "For Free, Perplexity Pro and Perplexity Max users, AI Data Retention is enabled by default". Here's how to opt out:

Navigate to your Account settings > Go to the Preferences page (or simply visit this on web: https://www.perplexity.ai/#settings/preferences) > Locate the AI data retention toggle and turn it off.

More information here.

Gemini

Web users: Visit https://myactivity.google.com/product/gemini and turn off the Keep activity toggle.

Claude

For web users: Go to https://claude.ai/new#settings/data-privacy-controls. Search and turn off this option: Help improve our AI models.

Microsoft Copilot:

At the time of testing (10th November 2026), no visible option to opt out of AI training could be found in the settings of a personal Microsoft account on Copilot.com (tested in Pakistan). The available controls covered personalization, chat history, saved memories, and advertising preferences, but did not include a "Training on conversation activity" setting, despite Microsoft's documentation referencing such a control for some users.

Disable AI Training on Social Networks

Disabling AI training on social networks gets a little trickier. After all, public posts on a variety of social networks were a huge part of the training data sets with LLMs, and the fact they’re public means they can and should be easy to scrape. But that doesn’t necessarily mean you don’t have any sort of control.

In most cases, including sites like Instagram and Facebook, your best option is to set your account type to private (this also helps prevent outside companies from easily scraping your posts too). But other social networks do offer some level of control.

LinkedIn

• Click your profile image, then Settings & Privacy and select the Data Privacy option (or visit https://www.linkedin.com/mypreferences/d/settings/data-for-ai-improvement).
• Click “Data for Generative AI Improvement” and disable the option to “Use my data for training content creation AI models.”

Find more information here.

Snapchat

• Tap the gear icon and choose Settings > Privacy Controls, then “Manage My Information.”
• Disable the option for “Snap using your Public Content to train generative AI models.”

Find more information here.

Twitch

• Click your profile image in the top right and select Settings.
• Click the Security and Privacy tab and uncheck the box for “Training for Generative AI.”

Find more information here.

X

• Open the navigation panel, scroll down to Settings and privacy.
• Click “Privacy and safety.”
• Click the “Grok & Third Party Collaborators” option, or visit it directly via this link https://x.com/settings/grok_settings.
• Uncheck any options you do not want enabled. I'd uncheck at least "Allow your public data as well as your interactions, inputs, and results with Grok and xAI to be used for training and fine-tuning".

Find more information here.

Turn Off Android and iOS AI Features

Phones are getting more and more AI features that depend on collecting your personal data, and it’s increasingly difficult to disable them. But it’s still possible, as long as you’re willing to live with some compromises.

Android

There are a wide variety of Android phones out there and several different manufacturers that implement their own AI features, so you might need to dig around to find specific directions for your device. But if you have a Google Pixel or other phone that supports Gemini, here’s what you can do:

• Gemini: Up until September 2026, the easiest way to get Gemini out of your Android phone was to roll back to Google Assistant. But that’s no longer possible, which means the only option to disable Gemini as a voice assistant is either to turn the feature off entirely or find an alternative.
• Google Messages: Open Google Messages and tap your profile icon. Select Messages settings > General > Gemini in Messages, and disable the option for “Show Gemini button.” to at least remove the button so you don’t accidentally tap it.
  
  
  
  
  
• Google Photos: Open Google Photos and tap your profile icon. Tap Photos Settings > Preferences > Gemini features in Photos, then disable the “Use Gemini in Photos” options.

Google seems to keep adding more AI stuff in every update and it’s hard to keep up. For some more guidance, check out these guides.

iOS

With the release of iOS 27, removing AI from an iPhone (or iPad) has gotten more complex than it was previously, but it’s still doable. We detail this process more in-depth here, but here’s the short version, which requires that you roll back to a previous version of Siri and then implement some other changes:

• Open up Settings > Screen Time > Content & Privacy Restrictions
• If you have never done so, enable the toggle for “Content & Privacy Restrictions.”
• Tap the Siri option, then “Allowed Siri Version.”
• Select “Siri Classic” if you don't want to use Siri AI anymore.
• Here, you can also control other AI features. You can disable “Writing assistance,” “Math Assistance,” and “Image creation.”

Find more information here.

Special Google-Related Extended Cut

We’ve already covered Android, Chrome, and Google Search, but let’s dig through some of the company’s other tools.

Gmail

Gmail packs all its AI features into one single settings toggle, and disabling it will turn off a whole slew of features you may have been using for years, like “smart compose,” automatic filters, and even spellcheck. Still, if you want to disable it, you can do so:

• Click the cog icon in Gmail and select “See all settings.”
• On the General tab, scroll down to “Smart features,” and uncheck the box. You’ll now also see many other settings turned off with a notice to “Turn on smart features and personalization.”

Find more information here.

Google Workspace

The same goes for Google Workspace. You can disable Google Gemini features in Workspace, but be prepared to lose out on some features, like showing events from Gmail in the calendar automatically and personalized search results in Workspace. You can get to this setting from a few different places, but we’ll show directions from Google Drive.

• From Google Drive click the cog icon, then “Settings.”
• Select the “Privacy” tab, then “Manage Workspace smart feature settings.”
• Disable “Smart features in Google Workspace” and “Smart features in other Google Products.”

Find more information here.

Wrangle the Rest of Your Software

Of course, there’s an endless amount of software out there with AI stuff in it, like Zoom, Adobe Acrobat, and Notion, so there might be something you use everyday that’s not included here. Take a few minutes to dive deep into those settings to see if you can find ways to disable AI training or features, and be sure to share what you learn with others.

Consider Local Models

Maybe you don’t dislike AI so much as you hate the idea of all the major tech companies getting your data. Local models that you can control might be a good solution for your needs. With open weight models, you can run models similar to the big public ones entirely on your desktop or laptop, though the results may be slower and less sophisticated than what you get from models running on someone else’s server.

Running a local model typically involves choosing a local inference engine. Some examples include KoboldCpp, LM Studio, Ollama, or Llamafile. In addition you will have to choose an open weight model that can fit in your computer’s memory. These sorts of tools allow you to run models on your own computer, where you can then use it however you see fit, like for speech to text, grammar checking, or whatever else you dream up.

Other local options include purpose-built software that runs locally, but doesn’t require you to find and choose a model yourself. Examples of this sort of AI tool include the transcription tool OATS or the chat and image tool Off Grid AI Desktop.

Note: Adapted from an article originally published by EFF under the CC BY 4.0 license.

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The Role of Human Guidance in AI-Assisted Learning

By Mitchell Barrick | Reviewed by Irfan Ahmad

Image: Windows - Unsplash

In 2026, it’s fairly common for people in most professions to use AI to help complete a task, draft an email, and even “dumb something down.” But when does AI tap out and human guidance becomes necessary, or even better?

That’s the question a recent survey by language learning platform, Preply, set out to answer. Preply asked over 5,000 working professionals across nine different countries (US, UK, Spain, France, Germany, Italy, Poland, Japan, and Argentina) about their experience with AI-assistance and found that the majority of people, 88%, use AI for learning, but more than half, 63%, didn’t feel they truly learned something and instead simply felt “busy” learning.

So if AI is helping people solve or speed up various tasks and problems, why aren’t people retaining the information AI is giving them? Perhaps human accountability is the answer?

Why and When Is Human Guidance Necessary?

Human guidance offers something AI can’t, accountability. Let’s go back to when you were in school. Did you ever use flashcards to learn biology definitions? If you did, you know that doing them with another person was slightly more difficult than just running through them on your own. Having to explain what the nucleus is to someone who has the definition in front of them is unforgiving, while explaining it in your mind with no one to judge you allows you to shy away from any mistakes you might have made.

Now, imagine you were trying to do this with AI as your study partner. If you fumble the definition, AI will typically correct you but it won’t make sure that you’re asked that definition again thereafter. You’d have to prompt the AI tool to do this, and if you’re not disciplined enough, you might not review that definition enough to pass your test. This is why it’s not surprising to see that Preply’s survey found human guidance and accountability to be the top diver of learning consistency.

This is where human guidance, or more importantly, accountability, becomes necessary. AI is beneficial for a lot of things and it has many capabilities, but at the end of the day, it’s only as good as the prompts you feed it.

Who Needs Human Guidance While Using AI To Learn?

Generally, everyone could benefit from human guidance when using AI to learn. In fact, Preply found that 75% of respondents trusted a learning experience combining AI and human expertise for long-term progress, while only 11% preferred a fully self-directed AI approach.

Learning doesn’t stop when you get your degree. For most working people, continued education is part of the job. It seems that there is always something new to learn whether that's a new topic or even just a new way to perform an old task. The survey asked respondents why they use AI to learn and found that while 41% wanted to improve their performance at work (the number one answer), 26% also wanted to learn because they were personally interested in a topic.

Let’s use the increasingly popular game of Mahjong as an example. Human guidance isn’t necessarily needed to learn the rules of this strategic tile game, but human guidance is needed to enforce those rules. Without human guidance, players could accidentally play two tiles that weren’t a real match, which could alter the game significantly. But if a human is paying attention and sees the mistake, they can enforce the rules and ultimately make sure the game is played the right way.

Where Should People Seek Human Guidance From?

Who you’re getting the human guidance from matters as well. If you’re the speaker for a presentation on something complicated, you’d want someone who knows a bit about the subject to be the one giving feedback on your mock presentation. This is why having a colleague or mentor provide feedback on your presentation is important.

Furthermore, let’s go back to the Mah Jongg example above. Human guidance while playing the game is irrelevant if the person offering the guidance doesn’t know the rules. It would be like applying the rules of Go Fish to a game of Uno.

This applies across any topic you’re seeking guidance on. The person giving the guidance needs to be knowledgeable and expert on the topic to offer the guidance.

How Does Human Guidance Work Alongside AI?

As you’ve likely noticed throughout this article, human guidance and AI-assisted learning can work alongside one another and ultimately compliment each other. Afterall, the survey found that 3 out of 5 (60%) daily AI users say they’re learning faster than expected, compared with only 3 out of 10 (31%) who never use AI.

It’s apparent that AI is giving users easy access to information, explaining nuanced topics in more digestible ways, and overall speeding up productivity. But those things shouldn’t come at the expense of accountability.

Two out of three of Preply’s survey respondents agreed that having access to information doesn’t automatically lead to progress. Therefore, AI can be a good option to get started and set the foundation, but human guidance is necessary to establish accountability and true understanding of the subject matter.

About author: Mitchell Barrick is a writer and researcher with over 15 years of experience. He has written for various industries over the years, but has been focused on tech writing and research recently. If he isn't putting together an article or analyzing data, you can find him cooking away in the kitchen and trying new recipes.

Read next: AI Data Centers: Who Controls Land, Water and Electricity, and Who Answers to the Public?

by Guest Contributor via Digital Information World

AI Data Centers: Who Controls Land, Water and Electricity, and Who Answers to the Public?

By Slobodan Kovrlija, Diplo | Fact-checked by Irfan Ahmad

Image: BetterImagesofai

Artificial intelligence is usually experienced as something that appears on a screen. In rural Finland, it recently appeared as a cleared forest. Reports describe the clearing of hundreds of thousands of trees for Google data-center sites in Muhos and Otanmäki, followed by an order from Finland’s Licensing and Supervision Authority to halt environmentally significant preparatory work pending environmental assessments. Google disputes characterizations of the clearing as illegal and says it acted in accordance with Finnish forestry requirements. The controversy is about more than one company or one country. It shows how AI governance is becoming local infrastructure governance: a question of land, water, electricity, public consent, and who is allowed to know the full cost of building AI.

The Finnish case may be unusually dramatic, but it is not an outlier. Across the United States and Europe, data centers are generating conflicts over electricity, water, land, noise, public subsidies, and local consent. Regulating AI models is no longer enough. We also need to ask who is allowed to know what AI infrastructure consumes, where it is built, who benefits from it, and who pays for its grid upgrades.

AI is physical infrastructure

AI is often discussed as if it were weightless: a model, an app, a service available anywhere. Yet every query, generated image, and training run depends on physical infrastructure such as servers, cooling systems, electricity grids, water supplies, land, and transmission capacity.

Data centers are the most visible part of that material base. They require large amounts of electricity, and their cooling systems can also require substantial water. The OECD notes that AI compute infrastructure consumes water both directly, for cooling, and indirectly, through electricity generation. As AI deployment expands, these demands collide with local water scarcity, energy planning, and land-use decisions.

This is why AI governance cannot remain confined to questions of model behavior, safety testing, copyright, or platform regulation. A data center is not simply a private building containing computers. It is utility-scale infrastructure. Its effects extend beyond its fence: it can alter electricity demand, strain water systems, change landscapes, generate noise, and require public investment in grids and other infrastructure.

When a community learns about these effects only after construction has begun, permits have been granted, incentives negotiated, and land cleared, the result is predictable: distrust, opposition, and political conflict.

The transparency gap

Like any major infrastructure, data centers consume resources. The concern is that the public often has too little information to assess the bargain. In many US communities, developers have used nondisclosure agreements, limited public reporting, and opaque ownership structures. Residents may be asked to accept a project without knowing its expected electricity demand, water consumption, cooling technology, ownership, tax treatment, or the full cost of grid upgrades. Even local officials can struggle to obtain a complete picture.

This lack of visibility creates three governance problems:

➣ It undermines planning. Regulators need credible information about peak electricity demand, water use, and infrastructure needs to make sound decisions. Without facility-level data, they are asked to approve projects whose consequences they cannot fully measure.

➣ It raises distributional concerns. Data centers may bring investment and tax revenue. Still, they can also impose costs on communities: higher electricity demand, pressure on water supplies, noise, land-use change, and the risk that ordinary households subsidies infrastructure upgrades through their bills. These costs and benefits should not be assessed in the dark.

➣ Secrecy weakens democratic legitimacy. Communities are not merely stakeholders to be informed after the fact. They live with local impacts and the long-term infrastructure consequences. When decisions are made through confidential agreements and incomplete disclosures, opposition is a reasonable response to exclusion, not a rejection of AI itself.

These concerns are already visible in public comments on data-center proposals across the United States, where water use is among the most common issues raised. Residents in rural Utah, Idaho, Georgia, and elsewhere have raised worries about water pressure, electricity supply, noise from cooling systems and backup generators, and their limited role in decisions that could reshape their communities.

Governments are beginning to respond

The good news is that policymakers are beginning to treat data centers as infrastructure that requires public accountability.

California has enacted a package of laws designed to give communities more information about proposed data centers. The measures require reporting on energy consumption and efficiency, as well as disclosure of water use and land-use impacts. The state’s approach does not ban data centers; it tries to make their resource demands visible before permits are approved and construction begins.

Texas has taken a different route. Governor Greg Abbott ordered a pause on approvals for data centers seeking grid interconnection. At the same time, state agencies audit projected electricity demand, water use, tax incentives, ownership, cooling technology, and measures that impact the community. The pause signals that grid capacity and public costs are now central to assessing AI infrastructure.

Virginia has also moved in this direction. Its 2026 executive order on data-centre accountability emphasizes that communities should have meaningful, timely information and a genuine role in decisions about proposed developments. That language reframes data-centre governance as a question of public participation, not merely technical permitting.

In Europe, the issue is also becoming one of access to information. Lighthouse Reports has filed an Aarhus Convention complaint against the European Commission, arguing that EU rules prevent the public from seeing energy and water use by individual data centers. The complaint frames the issue in familiar democratic terms: people cannot meaningfully participate in decisions about infrastructure whose environmental footprint is hidden from them.

These developments show that data centers are no longer being treated only as investment projects or symbols of technological ambition. They are increasingly treated as politically sensitive infrastructure, closer in governance terms to power plants, water systems, and transmission networks than to ordinary commercial buildings.

What transparency should look like

Transparency does not mean publishing every technical detail or compromising legitimate security interests. Data centers do have genuine security needs, and commercial confidentiality can sometimes be legitimate. But there is a wide difference between protecting sensitive operational information and hiding information the public needs to evaluate a project’s impact.

Building on measures introduced in Virginia and California, a reasonable transparency agenda would include:

• Standardised reporting of electricity consumption, water use, cooling systems, onsite generation, and backup fuel use.
• Disclosure of ownership structures, especially where public incentives, tax breaks, or public infrastructure are involved.
• Publicly available assessments of grid impact, water availability, and environmental effects before irreversible construction work begins.
• Clear information about who pays for grid upgrades, road improvements, water infrastructure, and other public costs.
• Meaningful community consultation, with enough time and information for residents to understand the trade-offs.
• A clear boundary between security-sensitive details and information required for democratic accountability.

This agenda would not slow AI development for its own sake. It would make development more legitimate by ensuring that communities, regulators, and investors can see the real costs and benefits before decisions become irreversible.

AI’s legitimacy problem is physical

The debate about AI governance has often focused on what models say, what they predict, and how they might be misused. Those questions remain important. But the Finnish forest-clearing controversy, water concerns in Georgia, noise disputes in rural America, and grid strain in Texas point to another dimension of AI governance.

AI has a physical footprint. It consumes electricity and water. It occupies land. It changes local environments. It can require public infrastructure and public money. And when its resource use is hidden behind nondisclosure agreements or incomplete reporting, it creates a democratic deficit.

Data centre development should be governed in ways that allow communities to understand, scrutinise, and shape it. If AI is to earn public trust, its infrastructure cannot remain a black box. The public needs to see the utility bill.

Editor's Note: The article's content may be AI-generated or AI-assisted. Its authorship and use of AI tools have not been independently confirmed.

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• Devices aren’t lasting as long as they should. Here’s why

by External Contributor via Digital Information World

Devices aren’t lasting as long as they should. Here’s why

By Margherita Feleppa, University of Wollongong | Fact-checked by Irfan Ahmad

Is your new phone already slowing down or your expensive earphones acting up?

You’re not imagining it. Our products are no longer designed to last, with some barely working a few years before ending up in landfill.

Shortening the lifespan of a product is a strategy known as planned obsolescence.

My new research takes a closer look at this concept and argues that, by strengthening existing laws, it is possible to make products that last while reducing costs for consumers and the environment.

Image: Tasha Kostyuk - Unsplash

Mountains of e-waste

Modern devices like laptops and smartwatches are made of a combination of rare materials, toxic substances and flammable batteries, such as mercury and arsenic. When released into the environment, these toxic chemicals can pollute the soil and waterways.

This should make us think twice about throwing out broken devices. Yet, Australians produce almost three times the global average of electronic waste, known as e-waste. Globally, we generated 62 million tonnes of e-waste by 2022. That amount could fill more than one million trucks, about enough to wrap around the earth’s equator. E-waste worldwide is set to rise by another 32%, reaching 82 million tonnes by 2030.

In Australia, reducing waste must be a priority to meet its net zero goal and transition to a circular economy, where belongings are reused, repaired or recycled instead of piling up in landfill.

Faulty by design

Planned obsolescence is one way technology companies pull people into a loop of constant consumption. When our new device quickly breaks, we simply buy a new one.

But planned obsolescence is one problem with many facets.

For starters, companies can design products that aren’t sustainable. Think wireless earphones with batteries that quickly break down. Their design can make it very difficult to replace the battery, making them “disposable gadgets” once they’re unable to hold a charge.

Manufacturers may also make it harder to repair their products. For instance, parts of a device can be glued together so it can’t be taken apart and repaired. What’s more, some companies require a repairer to be “authorised” to get access to the parts, software locks or information needed to repair a specific product. You can try and fix a device yourself, but repair manuals can be subject to copyright and manufacturers may prevent third parties from sharing them online.

Beyond the actual product, there’s the behavioural side of planned obsolescence. Technology companies regularly update models so your current device quickly looks out of date, a strategy known as psychological obsolescence. Companies use advertising to convince you to buy their latest product and market newer devices as status symbols, such as a smartphone with accessories that are only compatible with the “new generation” of phones.

A systemic problem

Planned obsolescence is typically viewed as a company strategy.

In Europe, consumer associations launched a complaint against Nintendo for premature obsolescence, claiming its Nintendo Switch controllers were quickly becoming unresponsive. After the European Commission and other authorities contacted Nintendo, the company agreed to offer free repairs.

The federal court of Australia ordered Apple to pay A$9 million for making false or misleading representations to iPhone users affected by a software fault about their rights to have their device repaired or replaced under the Australian Consumer Law. These rights don’t simply stop applying because your phone has been repaired by a third party.

But planned obsolescence is not necessarily the fault of any one person or company. Rather, it’s the result of our current produce-and-consume system. Fixing such a complex, systemic problem will require intervention from various sectors, including product design, consumer law, competition law and intellectual property law.

We must also factor in consumer behaviour. After all, it’s ultimately the consumer who decides whether a broken product goes to a repair shop, in the junk drawer or straight in the bin. But consumers can’t always make an informed decision. For example, a person may be forced to replace a product because they can’t afford to repair it.

So, what can we do about it?

Stronger laws are key to ensuring products last. However, it’s difficult to change legislation. What’s more, lawmakers often fail to recognise the many aspects of planned obsolescence.

Consider Australia’s first right to repair law. This legislation aims to help people repair their vehicles more easily and at a lower price. This is a win for motorists, who would otherwise be forced to go to authorised dealerships.

The government recently asked for public feedback on whether the law should be expanded to agricultural machinery. But there has been no discussion about repairing devices and other everyday products. Importantly, this law doesn’t address what happens to products that simply can’t be fixed or help consumers tell if a product can be repaired before they buy it.

The European Union has made some progress. New rules aim at making all products placed on the EU market sustainable by design. It has also introduced a right to repair law with stronger rules around certain electronics, including mobile phones and washing machines, and a reparability score to help consumers choose fixable products.

We know our devices don’t last forever. But too often they break down in a few short years or even months, leaving consumers with little choice but to throw them away. It’s time Australia tightened its laws around planned obsolescence – for the sake of people’s hip pockets and the planet.

Margherita Feleppa, Lecturer, School of Law, University of Wollongong

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

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• The Google Whistleblower Taking on Big Tech Over Its Role in Gaza

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The Google Whistleblower Taking on Big Tech Over Its Role in Gaza

By Evie Breese, UK Reporting Fellow at Tech Policy Press and openDemocracy | Fact-Checked by Irfan Ahmad

Image: Unsplash @Samtakespictures

The day Google DeepMind research engineer Sofia Liguori returned to work following the birth of her first child was the day her activism began.

The 32-year-old was part of the London-based frontier AI lab’s sustainability-focused Impact Accelerator team, tasked with identifying new ways the technology can be used for good. These range “from pathogen detection and crop resilience to medical countermeasure acceleration”, according to a LinkedIn post advertising new roles in the team.

Liguori’s own project focused on how AI could optimize electricity power flow to allow the national grid to use less energy and reduce overall carbon emissions. She told openDemocracy she now refers to her work as “building the nice face of the devil”.

“I felt so hypocritical that we were just talking about all these good things and not even mentioning Project Nimbus”, she said, speaking to openDemocracy from her home in south London, a Palestinian Keffiyeh scarf draped on the wall behind her.

Project Nimbus is a $1.2bn deal that Google and Amazon Web Services signed with Israel to build data centres in the country and provide public entities with cloud-based data storage in 2021. The contract stipulated that neither company could shut down their services in Israel or deny them to particular government entities.

Google has said its work with Israel is “not directed at highly sensitive or classified military workloads relevant to weapons or intelligence services”, as a spokesperson told Time magazine this year. Yet training materials leaked to The Intercept in 2022 revealed the full suite of Google Cloud AI tools are available to Israeli state departments, including the Ministry of Defense, for face detection, object tracking and “sentiment analysis.”

The ministry could have used these tools to identify and surveil Palestinians across the West Bank, East Jerusalem, and Gaza, including since 7 October 2023, according to reporting in the New York Times and the Center for Constitutional Rights. Israeli military officials have said they have killed 70,000 people in Gaza since the Hamas attack on October 7 2023 that killed approximately 1,200 Israelis.

As she sat at home with her new baby, Liguori said she “watched a live-streamed genocide for a year, knowing that my company was complicit”. She added: “If we accepted this modus operandi, we were basically legitimizing what has been tested in Gaza to become the standard.”

Returning to work in August last year, she said she implored her colleagues: “If our aim is AI for good, trying to stop genocide is one of the ultimate goods we can do, right?”

Ultimately, having been unable to convince executives to end Google’s role in Israeli military actions, Liguori left the company this year. In recent weeks, she has acted as a whistleblower, speaking out despite being subject to the strict lifetime non-disparagement agreement signed by Google employees.

Liguroi had always been prepared to be fired for her activism, but, she said, the real risk of “being sued by Google is different”. The tech giant’s parent company, Alphabet, is consistently ranked as the third or fourth most valuable globally, with a reported market worth of around $3.5trn.

This week, she was delivered some good news: a Google executive told the company’s UK staff that it will not enforce the NDA’s clause against workers who criticize the company after leaving. Speaking to openDemocracy after the news was announced, Liguori details what it took to get Google to back down.

The final straw

Liguori, whose background is in theoretical physics and reinforcement learning for video games, told openDemocracy she never set out to work with frontier AI models and knew “nothing” about Project Nimbus when she joined Google DeepMind in May 2023.

After becoming increasingly aware of the project’s impact in Gaza while on maternity leave, Liguori sent her immediate colleagues a letter urging them to take action shortly after she returned to work in August last year.

“This team is full of mothers,” she wrote. “I am not going to describe how it feels to become a mother for the first time while watching snipers targeting children, children dying of starvation, and all the rest of the horrors. What’s happening is lacerating my heart, really.”

The letter, which openDemocracy has seen, continues: “How can we do AI for good, and not even talk about Project Nimbus? How can we do AI for good in a company that is officially recognized and listed [as] complicit in the ongoing genocide in Palestine?”

Liguori also asked to discuss Nimbus in a team meeting. When her request was denied by a senior manager, she began sharing links to news articles about the project in internal channels. If they contained the word “genocide”, she said, they were deleted for “violating internal policies” prohibiting “aggressive language.”

Two months after her return to work, documents were leaked to Israeli-Palestinian publication +972 Magazine and Hebrew-language outlet Local Call revealing that Google and Amazon had agreed to use a secret code to “effectively sidestep legal obligations” and tip off the Israeli government if they were ever ordered to share Israeli data shared on their cloud services with law enforcement authorities anywhere in the world.

Then, in late April 2026, it was announced that Google had signed a contract with the US Department of War that would allow the Pentagon to use Google’s AI for “any lawful government purpose”, including mission planning and weapons targeting.

That was the day Liguori decided enough was enough. The petition she and over 600 colleagues had sent to CEO Sundar Pichai opposing the partnership had fallen on deaf ears.

“I really believe there is a value of infighting from the inside,” she said, “I tried to stay and do activism and raise awareness”, but the mental toll was becoming too great. “I reached a level of disgust with my company that was just incompatible with me continuing to stay there.”

Liguori used a combination of sick and holiday leave to cease undertaking work for Google, officially resigning on 20 October.

“I no longer believe that our technology will have a net positive impact on society. I think there’s a fantasy world where AI can help decarbonize grids, cut waste, protect ecosystems, and benefit humanity,” she wrote in her publicly posted resignation letter.

“But it’s not this world, and it’s not this type of general-purpose AI we are racing to develop.”

The growing revolt inside Google DeepMind

Google hasn’t always been so resistant to employee dissent.

Back in 2018, after 3,000 employees signed a petition seeking a policy that would stop Google and its contractors from “ever build[ing] warfare technology”, the tech firm announced that it would no longer be renewing its contract with the Pentagon on controversial military drone Project Maven.

Shortly after, the company published its AI Principles, a set of internal guidelines that prohibited the use of its technology for AI weapons or for human rights abuses.

But weeks after Donald Trump’s second term began in January last year, the Silicon Valley-based company appeared to have a change of heart, with the AI principles updated to remove references to weapons or surveillance.

“We believe democracies should lead in AI development, guided by core values like freedom, equality, and respect for human rights,” Google DeepMind chief Demis Hassabis and research labs senior vice president James Manyika wrote in a blog post announcing the updated policy.

Soon after, Google announced that Gemini would be used for both classified and unclassified purposes at the AI factory of Lockheed Martin, a US weapons company that primarily builds military aircraft, missiles, satellites, and defense technology for the US armed forces.

Then, in June of this year, a partnership between Google and US military contractor Palantir was expanded to integrate Palantir platforms across Google Cloud and Google Cloud Marketplace.

“You never know then how your technology will be used in Palantir’s systems,” Liguori told openDemocracy. “Workers need to know what the technology they are building on will contribute, and we want the right to abstain on ethical grounds”.

Since then, a number of UK Googlers have left the company on ethical grounds, but were gagged from speaking about the firm by strict NDAs. Feeling strongly that the public needed to know about Google’s dealings with Israel, Liguori said she decided to breach her own NDA to publish her resignation letter, knowing that Google could retaliate.

But this week Google told its staff in the UK that it will not take legal action against those who criticize the company or its AI products after leaving. “We’ve always encouraged an open dialogue about safety and responsibility,” a Google spokesperson told The Washington Post. “Recently, we’ve updated our terms for new hires, which included removing the post-termination aspect of non-disparagement clauses.”

Liguori sees the move as a win that “happened because of collective action”. After an employee’s attempts to raise concerns about the clause through internal channels did not lead to any change, DeepMind members of the United Tech and Allied Workers (UTAW) coordinated with the No Tech for Apartheid campaign group and whistleblowing non-profit Psst to pressure Google from multiple directions, Liguori told openDemocracy.

It’s only because of this support network that Liguori says she was able to “find the courage to take the risk” of a public resignation.

The concession comes as the Employment Rights Act 2025 comes into effect in the UK, allowing unions to enter workplaces across the country to speak to workers in person about joining a union. At Google and Google DeepMind, the new law will likely support UTAW and Unite’s drive for formal recognition.

For Liguori, who joked that she had considered “disappearing in the Italian countryside”, the news that she won’t face legal action for her activism has come as a “big relief”. She added: “... it’s also a sign that our collective effort had an effect, and that it's worth challenging the rules.”

Google has not responded to openDemocracy’s request for comment at the time of publication.

Read next:

• Hate Speech Still Pays on YouTube. Regulators Should Follow the Money

• How to Navigate Difficult Family Relationships During Holiday Gatherings

by External Contributor via Digital Information World

How to Navigate Difficult Family Relationships During Holiday Gatherings

By Marina Zhukova, UTHealth Houston | Reviewed by Irfan Ahmad

Image: Rein Krijgsman - Unsplash

Family gatherings can bring joy, togetherness, and celebration, but they can also bring unexpected stress and unresolved conflicts. Conflicts are normal in any relationship, but they don’t have to overshadow the holiday.

What does unhealthy family conflict look like? How can you differentiate it from typical family stress?

Disagreements are a normal part of any relationship, including relationships with family members. In fact, we may react more strongly to disagreements with loved ones because we often expect them to share our values and beliefs. There is a growing trend on social media to label relationships that involve conflict as “toxic.” However, experiencing conflict does not necessarily mean that a relationship is unhealthy. Disagreements are inevitable, and maintaining meaningful relationships requires effort. We can care deeply about someone while holding very different opinions or making different life choices.

The key distinction is not whether conflict occurs, but how it unfolds. Typical family stress may involve occasional arguments or frustration, but family members can generally move past disagreements while maintaining mutual respect. Unhealthy conflict, on the other hand, tends to involve recurring patterns of criticism or hostility, particularly when one person’s feelings or needs are consistently dismissed. It may leave someone feeling afraid to express themselves or constantly anticipating the next confrontation. Rather than focusing on a single unpleasant interaction, I encourage people to consider the overall pattern of the relationship.

Why does family conflict intensify during the holiday season?

Three main things come to mind when thinking about family conflict around the holidays:

First, we’re spending time with relatives we don’t see regularly. When we don't interact with someone often, we may be less familiar with how to communicate effectively with them or navigate differences in opinions.

The holidays can also mean returning to familiar environments. In psychology, we know that environmental cues can trigger learned patterns of behavior. For example, returning to your childhood home may bring back old family dynamics. You might find yourself responding to your parents or siblings much like you did as a teenager, even though you are now an adult. Parents may fall back into their old roles, as well.

This time of year also brings increased stress and changes in routine. The holidays often involve travel, disrupted routines, and additional responsibilities. All of this can leave us with fewer resources to regulate emotions and, in turn, to manage disagreements.

What are some strategies for coping with family conflict?

• Cope ahead: Anticipate difficult situations and plan how to respond. For example, if you expect uncomfortable questions about your career, marriage, or plans to have children, prepare a few responses. You might start with humor, redirect the conversation, or politely say you would rather not discuss it. If the topic has come up many times before, it is okay to remind the person that your perspective has not changed.

• Maintain routines that help you manage stress: Even during busy family visits, try to make time for activities you enjoy, whether that is a morning walk, meditation, or listening to your favorite podcast. Taking breaks from family interactions can also help you recharge.

• Plan some downtime before and after family gatherings: If possible, avoid rushing straight from a stressful visit back into work or other responsibilities. Giving yourself time to decompress can make the experience more manageable.

What are some healthy ways to de-escalate conflict?

• Pick your battles: Not every disagreement needs to be resolved, especially during the holidays. Sometimes it is better to acknowledge that you have different opinions and move on. Humor can be a great way to diffuse tension and redirect the conversation, as long as it is not at someone else’s expense.

• Validate the other person’s feelings without necessarily agreeing with them: For example, saying, “I know this is important to you,” can help someone feel heard. At the same time, be direct about your own feelings. In dialectical behavior therapy, we teach communication skills that emphasize describing the situation without judgment and clearly expressing what you need. Instead of saying, “You always criticize my choices,” try, “When you bring up my career decisions, I feel pressured. I'd appreciate it if we could talk about something else.”

• Know when to take a break: If you notice yourself becoming frustrated or raising your voice, step away from the conversation. Even a short pause can help you regulate and respond more thoughtfully. You do not need to resolve years of family disagreements over one holiday dinner.

How can someone set boundaries without escalating conflict?

It is important to remember that healthy boundaries are about managing our own behavior, not controlling someone else’s. There is an old saying that “our freedom ends where another person’s nose begins.” I think this applies well to boundaries. We have the right to decide what we are comfortable with, but we also need to respect other people’s autonomy.

Be clear and specific about what you need, without blaming the other person. For example, instead of saying, “You need to stop asking about my personal life,” you might say, “I know you care about me, but I’m not comfortable discussing this. I’d rather talk about something else.”

Setting a boundary does not guarantee that the other person will agree with it. You can communicate your limits respectfully, but you cannot control their reaction. If someone continues to push, it is okay to calmly end the conversation or step away.

What advice do you have for someone navigating a difficult family member?

The approach would depend on how much you value the relationship and what you hope to get out of the interaction.

If this is someone you rarely see and don’t have a particularly close relationship with, it may be best to focus on keeping the interaction manageable. Be polite, pick your battles, and remind yourself that the gathering is temporary.

If the relationship is important to you, it may be worth investing more effort into improving communication. We call this interpersonal effectiveness. Approach the person with curiosity rather than judgment, try to understand their perspective, and acknowledge their feelings without necessarily agreeing with them. Be open about your own feelings, as well. Remember that improving a relationship takes effort from both sides, and you can do your part without taking responsibility for the other person’s behavior.

Do not put additional pressure on yourself to have a perfect holiday. It is okay to experience mixed emotions, including frustration or disappointment, while still enjoying time with your family.

By: Marina Zhukova, PhD, psychologist and assistant professor, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School at UTHealth Houston. All quotes should be attributed to her.

Read next: Hate Speech Still Pays on YouTube. Regulators Should Follow the Money
by External Contributor via Digital Information World

Hate Speech Still Pays on YouTube. Regulators Should Follow the Money

By Richard Woods, Tech Policy Press | Fact-Checked by Irfan Ahmad

Image: Sora Shimazaki - Pexels

For every dollar an advertiser spends on a YouTube video, the platform keeps 45 cents. YouTube is not a neutral host that occasionally misses bad actors. It is a business partner in every monetized video, and it profits when those videos perform, including, new research suggests, ones that could break its own rules.

A new report from the Global Disinformation Index (GDI), “Monetizing Hate,” puts a price on that partnership. GDI estimates that 100 English-language channels publishing what it classifies as hate speech are on track to earn about $13.3 million in ad revenue in 2026: $7.3 million for creators, $6 million for YouTube. One channel, earning an estimated $2.2 million a year, carried content that may breach YouTube’s Community Guidelines and German law. In September, it was still online, still showing ads and still viewable in Germany.

The report’s most revealing finding is not the size of these sums. It is how little anyone outside YouTube can know about them, and how conveniently that serves the company.

Little money, strong incentives

Six million dollars is a rounding error for a platform that took in $60 billion from ads and subscriptions in 2025 alone. The more plausible explanation for weak enforcement is not that hate is too lucrative to give up, but that enforcement costs time, staff and creator goodwill, while inaction costs little.

For creators, though, $2.2 million a year is a career. Recommendation systems tend to reward content that edges toward a platform’s policy line, and because YouTube shares the revenue, its interest in a high-performing video is aligned with the creator’s, not with the people that video targets.

GDI’s numbers deserve scrutiny. Five large language models labeled 19,297 videos; analysts manually reviewed 200. Its definition of hate speech follows the Council of Europe’s and is broader than YouTube’s, so much of what it flagged is permitted on the platform. Critics will say GDI is counting lawful speech. But that gap is the point: YouTube’s narrow definitions decide what is monetizable, and only YouTube can test GDI’s estimates against real data.

YouTube’s repeat-offender clause applies in “rare cases” and never defines “repeatedly.” GDI found no evidence it had been used against the content it reviewed. A rule with an undefined trigger and unreported use is not really a rule. It is discretion. YouTube pledged to tighten its rules on monetizing hateful content after an advertiser revolt in 2017 and again in 2019. The pattern suggests enforcement tightens when revenue is threatened, then slackens when attention moves on.

What meaningful transparency would look like

YouTube’s transparency reports count removals, not videos that stay online but lose ads. Meaningful transparency would measure money, not takedowns. In practice, that means:

• Enforcement data that matches the business model: how many videos and channels are demonetized under the hate speech policy, by country of viewing.
• A defined repeat-offender threshold, with annual figures on how often it is triggered. A rule YouTube must report on is a rule it must use.
• A measure of delay: how much a video earned before demonetization, and how long it took. This shows whether enforcement removes the incentive or arrives after the money is made.
• Video-level placement reports, so advertisers can see, and stop paying for, what their budgets fund.

Much of this sits within existing law. The Digital Services Act (DSA) requires platforms to explain any “restriction of monetary payments” to the affected user (Article 17), and those explanations feed the Commission’s public Transparency Database. Regulators could check whether YouTube logs hate speech demonetizations there at all. The Commission can demand data on viewer location and revenue under Article 67, and a delegated act adopted in July 2025 lets vetted researchers request non-public platform data. In the UK, Category 1 transparency reports under the Online Safety Act, due in 2027, give Ofcom a chance to require demonetization figures, not just removals.

Disclosure has limits. YouTube’s own DSA audit, as GDI summarizes it, found trusted-flagger notices alleging illegal hate speech were not prioritized. Reporting can harden into box-ticking, and a demonetization figure means little without an independent sense of how much violating content exists. That is why researcher access matters as much as company reporting.

Following the money sidesteps the censorship fight

US-based creators account for 81% of the estimated revenue, an easy target in the transatlantic row over the DSA. But EU users were shown ads on sampled videos. If even 10% of views came from the EU, GDI estimates, that would mean $0.9 million in hate-linked ad revenue from January to August. This is only an estimate because YouTube alone knows where its viewers are.

Demonetization removes no video and silences no one. It asks a company to stop paying for, and profiting from, content that breaks its own rules or the law where it is viewed. That shifts the question from “what should come down” to “what should be paid for.” A platform that cannot answer it with data has already told regulators something.

This story was originally published by Tech Policy Press.

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by External Contributor via Digital Information World