Tag: Gemini

Tech Tip : Turn Off Gemini AI Distractions In Google Docs

Posted on by Paul Stradling

If Gemini AI prompts in Google Docs are getting in the way of your writing, there’s a quick way to turn them off and regain a cleaner, more focused workspace.

Why This Matters

Google has been steadily integrating Gemini into Google Docs, Sheets, Gmail, and other Workspace applications. While many users find the AI features useful, others prefer a cleaner writing environment without AI prompts appearing on screen.

Reducing these prompts can make documents feel less cluttered, help you focus on writing, and give you more control over when and how you use AI tools.

How To Hide The Gemini Bottom Bar In Google Docs

If you see a Gemini prompt box at the bottom of your document, you can hide it:

  • Open your Google Doc.
  • Click Gemini in the menu bar.
  • Select Bottom Bar Preferences.
  • Turn off the Gemini bottom bar.

This removes the AI prompt panel from the bottom of the document while allowing you to access Gemini manually if you need it later.

How To Reduce AI Features Across Google Workspace

You can also disable some Workspace smart features that power AI-driven suggestions and personalisation.

  • Open Gmail.
  • Click the Settings cog.
  • Select See All Settings.
  • Scroll down to Google Workspace Smart Features.
  • Click Manage Workspace Smart Feature Settings.
  • Turn off Smart Features in Google Workspace if you no longer want these features enabled.

This setting affects several Google Workspace applications and may reduce some AI-powered suggestions and prompts.

Things To Keep In Mind

Turning off Workspace smart features does not necessarily remove every Gemini capability from your Google account. Some Gemini features may still be available depending on your Google Workspace subscription, administrator settings, and the specific applications you use.

However, these settings can significantly reduce AI prompts and create a cleaner, less distracting workspace for users who prefer to write and work without constant AI assistance.

A Cleaner Way To Work

AI tools can be useful when you need them, but many people don’t want them appearing every time they open a document. Taking a few moments to adjust these settings can help create a simpler, more focused Google Docs experience while still allowing you to use Gemini when you choose to.

Tech Tip : Translate Conversations Live Through Your Headphones

Posted on by Paul Stradling

Google has added a Gemini-powered feature to the Google Translate app that lets you hear real-time translations directly through your headphones, making it much easier to follow conversations in other languages as they happen.

Why It Works

Instead of translating after the fact, this feature listens and processes speech continuously, then plays the translated version straight into your ears. That removes the delay and friction of typing or switching screens, so you can stay focused on the conversation itself.

How To Use It

– Connect your headphones to your phone and open the Google Translate app.

– Tap the Live translate or conversation feature.

– Choose the language you want to translate from and your preferred output language.

– Select the listening mode so translations are played through your headphones.

– Tap ‘Start’, then let the app listen and translate in real time.

You’ll hear the translated speech as it happens, and in most cases the app will also generate a transcript on screen so you have a written record if needed.

When It’s Most Useful

This works well in meetings, travel situations, or any setting where you need to follow spoken language quickly without interrupting the flow. It is particularly helpful when listening to explanations, instructions, or announcements where missing key details could cause problems.

What To Watch Out For

Accuracy can vary depending on background noise, accents, and how clearly people speak, so it is still worth double-checking anything important. It also works best with a stable internet connection, as the translation relies on cloud-based processing.

Tech Insight : Google Integrates Gemini Into Chrome To Enable Agentic Browsing

Posted on by Paul Stradling

Google has announced that it has begun integrating its Gemini artificial intelligence system directly into the Chrome browser as part of a wider effort to turn everyday web browsing into a more automated and assistant-led experience.

Why?

Chrome remains the world’s most widely used web browser, accounting for over 70 per cent of global desktop usage (StatCounter), and Google’s latest changes seem to reflect growing pressure from AI-focused rivals offering built-in assistants and automated task handling. For example, over the past year, browsers and browser features from Microsoft, OpenAI-backed projects, Perplexity and Opera have increasingly promoted AI agents as a way to reduce manual searching, form filling and comparison across multiple websites.

Therefore, rather than thinking about replacing Chrome or launching a separate AI browser, Google is now embedding Gemini directly into the existing product. The aim is to reshape how users interact with websites while preserving Chrome’s central role in daily computing and maintaining continuity for its vast installed user base.

Moving Gemini From A Floating Tool To A Built-In Side Panel

Google first added Gemini to Chrome in 2024, but its early implementation was limited. The assistant appeared in a floating window that sat apart from the main browsing experience and offered only limited contextual awareness. This latest update replaces that approach with a side panel that sits alongside web pages and can be opened across tabs.

According to Parisa Tabriz, Vice President of Chrome, the intention is to allow users to work across the web without losing context. In a Google blog post announcing the changes, she wrote that the new side panel “can help you save time and multitask without interruption” by letting users “keep your primary work open on one tab while using the side panel to handle a different task”.

This design allows Gemini to analyse the page currently being viewed, reference other open tabs, and respond to questions without forcing users to break their workflow. When several tabs originate from the same site or topic, such as product listings or reviews, Gemini can treat them as a related group, making it possible to summarise information or compare options across pages.

When and Where?

The update is rolling out now to Chrome users in the US on Windows, macOS and Chromebook Plus devices, extending availability beyond the platforms supported during earlier testing.

Built On Gemini 3 And Multimodal Capabilities

The new Chrome features are built on Gemini 3, which Google describes as its most capable AI model so far. Gemini is a multimodal system, meaning it can work with text, images and other structured inputs rather than relying solely on written prompts.

Google says this capability supports its aim of making Chrome more useful during complex tasks. In its announcement, the company described Gemini in Chrome as “an assistant that helps you find information and get things done on the web easier than ever before”, particularly when tasks involve multiple steps or different forms of content.

Multimodal understanding also enables Gemini to work directly with images viewed in the browser. For example, through integration with Google’s Nano Banana tool, users can modify images without downloading files or opening separate applications. Google appears to be positioning this as a practical feature for tasks such as visual planning or transforming information into graphics while remaining within the same browsing session.

Tighter Integration With Google Services

A key element of Google’s approach is deeper integration between Chrome and its wider ecosystem of services. Gemini in Chrome supports Connected Apps, including Gmail, Calendar, YouTube, Maps, Google Shopping and Google Flights.

With user permission, Gemini can reference information from these services to help complete tasks. In its announcement, Google highlighted examples such as travel planning, where Gemini can locate event details from an email, check flight options, and draft a message to colleagues about arrival times without requiring the user to move between applications.

Google has also confirmed that its Personal Intelligence feature will be brought to Chrome in the coming months. This feature allows Gemini to retain context from previous interactions and tailor responses over time. Tabriz stated that users remain in control, writing that people can opt in and choose whether to connect apps, with the ability to disconnect them at any time.

From Autofill To Agentic Browsing

The most substantial development is probably Google’s move towards agentic browsing, which refers to software systems capable of carrying out tasks across websites on a user’s behalf. For subscribers to Google AI Pro and AI Ultra in the United States, Chrome now includes a feature called auto browse.

Google is presenting auto browse as an extension of existing automation rather than a replacement for user involvement. In the blog post, Tabriz wrote, “For years, Chrome autofill has handled the small stuff, like automatically entering your address or credit card, to help you finish tasks faster.” She added that Chrome is now moving “beyond simple tasks to helping with agentic action”.

Auto browse is designed to handle multi-step workflows such as researching travel options, collecting documents, filling in online forms, requesting quotes, or managing subscriptions. Google says early testers have used it to schedule appointments, assemble tax documents, file expense reports and renew driving licences.

More advanced scenarios combine multimodal input and commerce. For example, Google describes cases where Gemini can identify items shown in an image, search for similar products online, add them to a shopping basket, apply discount codes and remain within a set budget. When sensitive actions are involved, such as signing in or completing purchases, auto browse pauses and asks the user to take control.

Google has stated that its AI models are not exposed to saved passwords or payment details, even when Chrome’s password manager is used to support these actions. The company says auto browse is designed to request explicit confirmation before completing actions such as purchases or social media posts.

Commercial Context And Industry Resistance

Google’s decision to deepen Gemini’s role in Chrome comes amid intensifying competition around AI-driven browsing and automation, for example Microsoft has integrated similar capabilities into Edge, while newer browsers have been designed from the outset around the use of AI agents.

There is also increasing interest in agent-led online commerce. For example, management consultancy McKinsey has projected that agentic commerce for business-to-consumer retail in the United States could reach $1 trillion by 2030. Google has indicated that Chrome will support its Universal Commerce Protocol, an open standard developed with companies including Shopify, Etsy, Wayfair and Target, which is intended to allow AI agents to carry out transactions in a structured and authorised way.

At the same time, some websites and platforms have begun limiting automated access or requiring explicit human review for transactions. Google appears to be positioning auto browse as a more controlled approach, with human confirmation built into sensitive steps, as it explores how agentic browsing can operate within existing legal and commercial frameworks.

What Does This Mean For Your Business?

Google’s decision to embed Gemini directly into Chrome seems to point to a future where the browser becomes an active participant in work rather than a passive gateway to information. For users, this could concentrate research, comparison and administrative tasks inside a single interface that already sits at the centre of daily digital activity. The immediate impact is likely to be incremental rather than transformational, with benefits most visible in time saved on repetitive or fragmented tasks, balanced against ongoing limits around accuracy, intent recognition and website compatibility.

For UK businesses, the changes could have practical implications across productivity, procurement and digital workflows. For example, tools such as auto browse could reduce the time staff spend on routine administration, travel planning, expense management and supplier research, particularly for small and medium sized organisations without dedicated support teams. At the same time, businesses that rely on web traffic, online forms or e-commerce will need to consider how agent-led browsing interacts with existing processes, security controls and customer journeys, especially as automated interactions become more common.

Website operators, retailers and platforms face a more complex picture, weighing potential efficiency gains against concerns over loss of control, while regulators and standards bodies are paying closer attention to how automated agents access data and complete transactions. Google’s emphasis on user confirmation, permissions and open standards reflects these pressures, while also highlighting that agentic browsing remains an evolving area. Chrome’s scale gives Google a strong position in shaping how this develops, although wider adoption and trust are likely to depend on how reliably these tools perform in real-world conditions rather than on their technical ambition alone.

Company Check : Google Brings Gemini AI To Gmail With A Personalised Inbox

Posted on by Paul Stradling

Google is reshaping Gmail around its Gemini AI models, introducing a personalised AI Inbox, natural-language AI Overviews in email search, and a wider rollout of writing and summarisation tools designed to help users manage rising email volumes more efficiently.

To Help Manage Information Overload

Google says more than 3 billion people now rely on its email service every day, and the company says the way people use email has changed fundamentally since Gmail launched in 2004. In a blog post published on 8 January 2026, Google argued that the challenge today is no longer sending or receiving messages, but managing information overload and turning large volumes of email into clear actions and answers.

The result is what Google describes as Gmail entering “the Gemini era”, with its latest generation of large language models embedded more deeply across inbox organisation, search, and writing assistance.

From Passive Inbox To Proactive Assistant

Google’s central claim is that Gmail is now shifting from a passive repository of messages into a personal, proactive assistant. AI has already been part of Gmail for years, underpinning features such as Smart Reply, Smart Compose, and spam filtering. The latest update expands that role significantly.

According to Google, email volume is now at an all-time high, and users are spending more time searching, scanning threads, and piecing together information than actually acting on it. The new tools are designed to reduce that friction by summarising conversations, surfacing priorities automatically, and allowing users to ask their inbox direct questions in plain language.

These changes are powered by Gemini (Google’s own AI model family), with Google confirming that many of the new capabilities rely on Gemini 3, its latest model generation.

AI Overviews Come To Gmail Search

One of the most significant additions is AI Overviews inside Gmail search. This feature mirrors the AI Overviews Google has been rolling out in its core search product, but is restricted entirely to a user’s own inbox.

For example, rather than just returning a list of emails based on keywords, Gmail can now generate a direct answer to a question by synthesising information across messages. This means that, e.g., a user can ask, “Who was the plumber that gave me a quote for the bathroom renovation last year?” and receive a concise summary highlighting the relevant name, date, and details pulled from past emails.

Google says this is intended to remove the need to manually search through long email histories or open multiple messages to extract basic facts. Conversation-level summaries are also generated automatically for long email threads, presenting key points at the top of the discussion. If it works like it sounds, it could be quite helpful.

AI Overview summaries for threaded emails are rolling out to all Gmail users at no cost. The ability to ask the inbox direct questions using natural language is being limited to Google AI Pro and Google AI Ultra subscribers, reflecting Google’s broader strategy of reserving more advanced reasoning features for paid tiers.

A New AI Inbox Focused On Priorities

Alongside search, Google says it’s also introducing an entirely new AI Inbox view. Rather than replacing the traditional inbox, this appears as an optional tab that users can toggle on and off.

The AI Inbox is designed to act as a personalised briefing. For example, it highlights what Google believes matters most, based on signals such as who a user emails frequently, who appears in their contacts, and relationships inferred from message content.

In practice, the AI Inbox is split into two main sections. “Suggested to-dos” surfaces high-priority items that require action, such as bills due, appointment reminders, or requests that have not yet been answered. “Topics to catch up on” groups informational updates such as deliveries, refunds, and financial statements into categories like purchases or finances.

In a recent briefing with reporters, Google described this as Gmail “having your back” by showing users what they need to do and when, without requiring them to manually sort or label messages.

Google has stressed that this analysis happens within what it describes as a secure and isolated environment, with personal email data remaining under the user’s control. The AI Inbox is currently being made available to trusted testers, with a broader rollout planned over the coming months.

Writing, Replying And Proofreading With AI

Google is also expanding access to several AI-powered writing tools. “Help Me Write”, which can draft emails from a short prompt or rewrite existing text, is now rolling out to all users at no cost. Suggested Replies, an evolution of Smart Reply, now generate responses based on the full context of a conversation and attempt to match the user’s writing style.

For example, when coordinating an event, Suggested Replies can draft a tailored response that reflects prior messages, which the user can then edit before sending. Google has framed this as a way to save time on routine communication without removing human oversight.

A new Proofread feature adds more advanced grammar, clarity, and style checks. This tool flags incorrect word usage, suggests simpler phrasing, and recommends breaking up complex sentences. Google has been explicit that this is intended to reduce reliance on third-party tools such as Grammarly or copying text into general-purpose AI chatbots for editing.

Proofread is limited to Google AI Pro and Ultra subscribers, reinforcing the company’s tiered approach to AI capabilities.

When And Where Are These Changes Rolling Out?

Google says that many of these features actually began rolling out in the US in January 2026, starting with English language support. Wider language and regional availability is planned over the coming months.

AI Overviews for threaded emails, Help Me Write, and Suggested Replies will be available to all users but AI Inbox and inbox-wide AI search remain gated, either behind testing programmes or paid subscriptions.

Google AI Pro and Ultra pricing varies by region, but these subscriptions sit within Google’s broader push to monetise advanced AI features across Workspace and consumer services.

Business Users And Google’s Competitors

For business users, the changes reflect Google’s attempt to make Gmail a more effective productivity hub rather than just a communication tool. Faster access to information buried in emails, clearer prioritisation of tasks, and reduced time spent drafting responses all align with wider trends in workplace automation.

These features also place Google in more direct competition with Microsoft, which has been embedding Copilot across Outlook, Teams, and the wider Microsoft 365 ecosystem. Both companies are now positioning email as an interface for AI-driven knowledge retrieval rather than a simple inbox.

The inclusion of proofreading and drafting tools also puts pressure on standalone writing assistants, while AI Inbox overlaps with features offered by third-party email management tools that focus on prioritisation and summarisation.

Challenges And Criticism

Despite Google’s assurances, the move has raised some familiar concerns around privacy, transparency, and control. For example, some users and regulators remain sceptical about AI systems analysing personal communications, even when data is processed locally or in isolated environments.

Accuracy is another challenge. AI-generated summaries and answers risk missing nuance, context, or important details, particularly in professional or legal correspondence. Google has positioned these tools as optional and assistive rather than authoritative, but reliance on automated summaries could still introduce errors.

There is also an ongoing debate about subscription-based access to core productivity enhancements. As more advanced features move behind paid tiers, businesses may face pressure to upgrade simply to maintain efficiency parity.

Also, Google’s expansion of AI Overviews continues to attract some scrutiny following mixed reactions to similar features in Search, where early rollouts drew criticism for incorrect or misleading answers. Applying the same concept to private email data may reduce some risks, but expectations around reliability remain high.

Taken together, Gmail’s move into the Gemini era signals Google’s intention to make AI central to everyday digital work, while testing how far users are willing to trust automated systems with the most personal layer of their online activity.

What Does This Mean For Your Business?

What emerges most clearly here is that Google is no longer treating AI in Gmail as a set of optional extras, but as core infrastructure for how email is organised, searched, and acted upon. By introducing Gemini directly into inbox prioritisation, search, and writing, Google is betting that users want fewer messages on screen and clearer signals about what actually needs attention. That approach reflects a broader shift in productivity software away from manual sorting and towards AI-mediated decision support, where the system actively interprets information rather than simply storing it.

For UK businesses, the potential upside is pretty meaningful. For example, faster access to buried information, clearer visibility of tasks, and reduced time spent drafting routine emails could translate into real efficiency gains, particularly for small and mid sized teams already operating under time pressure. At the same time, the growing split between free and paid capabilities raises practical questions around cost, governance, and consistency across organisations, especially where some staff have access to advanced AI features and others do not. Regulators, IT teams, and compliance leaders will also be watching closely to see how Google’s privacy assurances hold up as AI analysis becomes more deeply embedded in everyday business communications.

More broadly, this move reinforces how central email has become as a battleground in the wider AI productivity race. Google is clearly responding to competitive pressure from Microsoft and others, while also testing how comfortable users are with AI interpreting their most personal and professional data. Whether Gmail’s Gemini powered future is seen as genuinely helpful or uncomfortably intrusive will depend less on the ambition of the technology, and more on how accurately, transparently, and reliably it performs once it reaches wider use.

Tech Insight : Chrome Gets Built-In Gemini

Posted on by Paul Stradling

Google has announced what it calls the biggest upgrade to Chrome in its history, introducing a wide range of Gemini AI-powered features to the browser, and they’re not optional.

AI Becomes Core to Chrome

The new features, now rolling out for desktop users in the US with English set as their Chrome language, are designed to move Chrome beyond being just a browser. According to Google, it’s now a tool that can “understand the web,” take action on the user’s behalf, and surface information across apps and pages without users needing to search manually.

Gemini, Google’s generative AI model, is now embedded directly into Chrome. Once enabled, users can ask Gemini to summarise web pages, compare information across tabs, revisit previously visited sites, or interact with integrated Google apps such as Calendar and Maps without switching tabs. In essence, the browser becomes a conversational assistant.

“Today represents the biggest upgrade to Chrome in its history,” said Google VP Parisa Tabriz. “We’re building Google AI into Chrome across multiple levels so it can better anticipate your needs, help you understand more complex information and make you more productive.”

The update is currently limited to Windows and macOS users in the US, but international rollout is expected in the coming weeks. It will be available to Google Workspace users as well, with enterprise-grade data protections and admin controls.

What Can Gemini in Chrome Actually Do?

At launch, Gemini in Chrome supports the following features:

– Page summarisation, which allows users to simplify the content of any webpage into more digestible points.

– Multi-tab summarisation lets users compare and consolidate information from multiple open tabs into a single overview.

– Web history assistance helps users revisit previously viewed content using natural language prompts such as “What was the article I read last week about walnut desks?”.

– App integration provides access to Google Maps, Calendar and YouTube details directly within Chrome, without switching tabs.

– In-page queries enable users to ask questions about the page they are viewing and receive AI-generated answers directly from the address bar.

Google says the more advanced features are still in development. These include what Google calls agentic browsing, i.e., where Gemini can act on the user’s behalf to complete web-based tasks like booking appointments or ordering groceries. It should be noted here that users still retain control, with the ability to cancel or override these actions at any time.

AI Search for the Address Bar

Another major change is coming to Chrome’s omnibox / the address bar. For example, users will soon see a new AI Mode button on the right-hand side. This feature will allow them to ask more complex questions and receive detailed, AI-generated responses, similar to using Google’s Gemini chatbot.

However, this has prompted concerns among some publishers and SEO professionals. For example, a key question is whether hitting Enter in the omnibox will default to AI answers instead of standard search results. Google has clarified by saying that pressing Enter will still load normal Google Search, while AI Mode will only activate if the user clicks the new button.

Contextual prompts and AI-powered suggestions based on the page being viewed will also be added. For example, when viewing a product page, Chrome might suggest questions like “Is there a warranty for this?” or “What are the delivery times?”.

Safety, Passwords, and Spam

Beyond productivity, Google says AI will also be used to improve safety and reduce online nuisance. For example, Gemini Nano, an efficient AI model designed for device-level tasks, is already part of Chrome’s Enhanced Safe Browsing mode. It detects phishing scams, misleading websites, and so-called “tech support scams” that attempt to trick users into downloading harmful software. This protection is being expanded to cover fake virus alerts and scam giveaways.

Chrome is also using AI to assess and suppress spammy notification requests. Google claims this update has already reduced unwanted notifications by around 3 billion per day for Android users. A similar AI-based signal system will help Chrome decide whether to present website permission requests, such as those asking for camera or location access.

Another new addition is a one-click password changer. Chrome already flags compromised credentials, but now AI will be able to automatically navigate to the password reset page of supported sites and fill in a new secure password with a single click. Supported platforms currently include Spotify, Duolingo, Coursera, and H&M.

Opt-In or Not?

One of the recurring criticisms from both users and commentators is the extent to which these features will be optional. Google has not provided full clarity on whether all AI functions will be opt-in, opt-out, or enabled by default. However, based on recent Chrome behaviour, many expect at least some features to be automatically turned on unless manually disabled.

That raises broader questions about how much of a user’s browsing data could potentially be used to improve AI models. Google says data protections will be built in, particularly for Workspace customers, but has not offered detailed transparency on what personal or behavioural data might be involved in Gemini’s functions across tabs and history.

Mike Torres, Google’s VP of Product for Chrome, commented: “You tell Gemini in Chrome what you want to get done, and it acts on web pages on your behalf, while you focus on other things. It can be stopped at any time so you’re in control.”

While that may be reassuring, some users are already asking how easily these features can be disabled altogether, or whether it will be possible to use Chrome without any AI integration at all.

Microsoft’s AI Moves in Notepad

Meanwhile, it seems that Microsoft is quietly transforming Notepad, its long-standing lightweight text editor, into an AI-enhanced writing assistant. The latest update, now available to Windows Insiders, introduces three AI tools – Summarise, Write, and Rewrite.

Microsoft says these tools are context-sensitive and can be accessed via right-click in Notepad. On newer Copilot+ PCs, which include dedicated AI hardware, the models run locally and do not require a subscription. For everyone else, a Microsoft 365 subscription is required, and the AI processing is done in the cloud.

The rewrite tool can change the tone or clarity of a paragraph, summarise long notes, or generate first drafts from basic prompts. Although these features are optional and can be disabled in Notepad’s settings, their arrival marks a significant change in how even the simplest Windows apps are being redesigned for the AI era.

What Does This Mean For Your Business?

Although the rollout is still limited to the US, Google’s direction is now quite clear. It seems that Google sees Chrome as no longer just a gateway to the web, but a platform in which AI takes an active role in what users see, do, and even decide. While many of these features promise genuine time savings and better productivity, the change raises important questions about user control, data handling, and the transparency of AI decision-making. Whether businesses or individuals fully trust Gemini to act on their behalf is likely to depend on how configurable these tools turn out to be once they arrive more widely.

For UK businesses, the developments could offer some clear operational gains, particularly for teams juggling research, cross-tab work, or repetitive browser-based tasks. Deeper integration with Google apps may also benefit firms already embedded in the Workspace ecosystem. However, there will be just as much interest in how these features are governed. For example, firms will need to assess whether data from staff browsers is being used to train AI models, and how easily administrators can enable or restrict access to these tools across teams.

For Microsoft, the story is less dramatic but still significant, i.e., giving Notepad AI capabilities changes expectations of even the simplest applications. The split between free local use on Copilot+ PCs and paid cloud access for everyone else is a change in how AI is being packaged into the Windows environment. Businesses that rely on standardised software deployments may now have to take closer account of hardware and licensing when managing new AI tools, especially if even core utilities like Notepad become divided by capability.

As both tech giants continue to expand AI into familiar software, the trade-offs between convenience, control and commercial interest are becoming harder to ignore. The features may be free at the point of use, but the long-term implications for trust, competition, and user experience are far from settled.

Featured Article : Grok Blocked! Quarter Of EU Firms Ban Access

Posted on by Paul Stradling

New research shows that one in four European organisations have banned Elon Musk’s Grok AI chatbot due to concerns over misinformation, data privacy and reputational risk, making it far more widely rejected than rival tools like ChatGPT or Gemini.

A Trust Gap Is Emerging in the AI Race

The findings from cybersecurity firm Netskope point to a growing shift in how European businesses are evaluating generative AI tools. While platforms like ChatGPT and Gemini continue to gain traction, Grok’s higher rate of rejection suggests that organisations are becoming more selective and are prioritising transparency, reliability and alignment with company values over novelty or brand recognition.

What Is Grok?

Grok is a generative AI chatbot developed by Elon Musk’s company xAI and built into X, the social media platform formerly known as Twitter. Marketed as a bold, “truth-seeking” alternative to mainstream AI tools, Grok is designed to answer user prompts in real time with internet-connected responses. However, a series of controversial and misleading outputs (along with a lack of transparency about how it handles user data and trains its model) have made many organisations wary of its use.

Grok’s Risk Profile Raises Red Flags

While most generative AI tools are being rapidly adopted in European workplaces, Grok appears to be the exception. For example, Netskope’s latest threat report reveals that 25 per cent of European organisations have now blocked the app at network level. In contrast, only 9.8 per cent have blocked OpenAI’s ChatGPT, and just 9.2 per cent have done the same with Google Gemini.

Content Moderation Issue

Part of the issue appears to lie in Grok’s content moderation, or lack thereof. For example, the chatbot has made headlines for spreading inflammatory and false claims, including the promotion of a “white genocide” conspiracy theory in South Africa and casting doubt on key facts about the Holocaust. These incidents appear to have deeply shaken confidence in the platform’s ethical safeguards and prompted scrutiny around how the model handles prompts, training data and user inputs.

Companies More Selective About AI Tools

Gianpietro Cutolo, a cloud threat researcher at Netskope, said the bans on Grok highlight a growing awareness of the risks linked to generative AI. As he explained, organisations are starting to draw clearer lines between different platforms based on how they handle security and compliance. “They’re becoming more savvy that not all AI is equal when it comes to data security,” he said, noting that concerns around reputation, regulation and data protection are now shaping AI adoption decisions.

Privacy and Transparency

Neil Thacker, Netskope’s Global Privacy and Data Protection Officer, believes the trend is indicative of a broader shift in how European firms assess digital tools. “Businesses are becoming aware that not all apps are the same in the way they handle data privacy, ownership of data that is shared with the app, or in how much detail they reveal about the way they train the model with any data that is shared within prompts,” he said.

This appears to be particularly relevant in Europe, where GDPR sets strict requirements on how personal and sensitive data can be used. Grok’s relative lack of clarity over what it does with user input, especially in enterprise contexts, appears to have tipped the scales for many firms.

It also doesn’t help that Grok is closely tied to X, a platform currently under EU investigation for failing to tackle disinformation under the Digital Services Act. The crossover has raised uncomfortable questions about how data might be shared or leveraged across Musk’s various companies.

Not The Only One Blocked

Despite its controversial reputation, it seems that Grok is far from alone in being blocked. The most blacklisted generative AI app in Europe is Stable Diffusion, an image generator from UK-based Stability AI, which is blocked by 41 per cent of organisations due to privacy and licensing concerns.

However, Grok’s fall from grace stands out because of how stark the contrast is with its peers. ChatGPT, for instance, remains by far the most widely used generative AI chatbot in Europe. Netskope’s report found that 91 per cent of European firms now use some form of cloud-based GenAI tool in their operations, suggesting that the appetite for AI is strong, but users are choosing carefully.

The relative trust in OpenAI and Google reflects the degree to which those platforms have invested in transparency, compliance documentation, and enterprise safeguards. Features such as business-specific data privacy settings, clearer disclosures on training practices, and regulated API access have helped cement their position as ‘safe bets’ in regulated industries.

Musk’s Reputation

There’s also a reputational issue at play, i.e. Elon Musk has become a polarising figure in both tech and politics, particularly in Europe. For example, Tesla’s EU sales dropped by more than 50 per cent year-on-year last month, with some industry analysts attributing the decline to Musk’s increasingly vocal support of far-right politicians and his role in the Trump administration.

It seems that the backlash may now be spilling over into his other ventures. Grok’s public branding as an unfiltered “truth-seeking” AI has been praised by some users, but in a European context, it risks triggering compliance concerns around hate speech, misinformation, and AI safety.

‘DOGE’ Link

Also, a recent Reuters investigation found that Grok is being quietly promoted within the US federal government through Musk’s (somewhat unpopular) Department of Government Efficiency (DOGE), thereby raising concerns over potential conflicts of interest and handling of sensitive data.

What Are Businesses Doing Instead?

With Grok now off-limits in one in four European organisations, it appears that most companies are leaning into AI platforms with clearer data control options and dedicated enterprise tools. For example, ChatGPT Enterprise and Microsoft’s Copilot (powered by OpenAI’s models) are increasingly popular among large firms for their security features, audit trails, and compatibility with existing workplace platforms like Microsoft 365.

Meanwhile, companies with highly sensitive data are now exploring private GenAI solutions, such as running open-source models like Llama or Mistral on internal infrastructure, or through secured cloud environments provided by AWS, Azure or Google Cloud.

Others are looking at AI governance platforms to sit between employees and GenAI tools, offering monitoring, usage tracking and guardrails. Tools like DataRobot, Writer, or even Salesforce’s Einstein Copilot are positioning themselves not just as generative AI providers, but as risk-managed AI partners.

At the same time, it shows how quickly sentiment can shift. Musk’s original pitch for Grok as an edgy, tell-it-like-it-is alternative to Silicon Valley’s AI offerings found some traction among individual users. But in a business setting, particularly in Europe, compliance, reliability, and reputational alignment seem to matter more than iconoclasm.

Regulation Reshaping the Playing Field

The surge in bans against Grok also reflects a change in how generative AI is being governed and evaluated at the institutional level. Across Europe, regulators are moving to tighten rules on artificial intelligence, with the EU’s landmark AI Act expected to set a global precedent. This new framework categorises AI systems by risk level and could impose strict obligations on tools used in high-stakes environments like recruitment, finance, and public services.

That means tools like Grok, which are perceived to lack sufficient transparency or safety mechanisms, could face even greater scrutiny in the future. European firms are clearly starting to anticipate these regulatory pressures, and adjusting their AI strategies accordingly.

Grok’s Market Position May Be Out of Step

At the same time, the pattern of bans has implications for the competitive dynamics of the GenAI sector. For example, while OpenAI, Google and Microsoft have invested heavily in enterprise-ready versions of their chatbots, with controls for data retention, content filtering and auditability, Grok appears less geared towards business use. Its integration into a consumer social media platform and emphasis on uncensored responses make it an outlier in an increasingly risk-aware market.

Security and Deployment Strategies Are Evolving

There’s also a growing role for cloud providers and IT security teams in shaping how AI tools are deployed across organisations. Many companies are now turning to secure gateways, policy enforcement tools, or in some cases, completely air-gapped deployments of open-source models to ensure data stays within strict compliance boundaries. These developments suggest the AI market is maturing quickly, with an emphasis not only on innovation, but on operational control.

What Does This Mean For Your Businesses?

For UK businesses, the growing rejection of Grok highlights the importance of due diligence when selecting generative AI tools. With data privacy laws such as the UK GDPR still closely aligned with EU regulations, similar concerns around transparency, content reliability and compliance are just as relevant domestically. Organisations operating across borders, particularly those in regulated sectors like finance, healthcare or legal services, are likely to favour tools that not only perform well but also come with clear safeguards, documentation and support for enterprise-grade governance.

More broadly, the story of Grok is a reminder that in today’s AI landscape, branding and ambition are no longer enough. The success of generative AI tools increasingly depends on trust, i.e. trust in how data is handled, how outputs are generated, and how tools behave under pressure. For developers and vendors, that means security, transparency and adaptability must be built into the product from day one. For businesses, it means asking tougher questions before deploying any new tool into day-to-day operations.

While Elon Musk’s approach may continue to resonate with individual users who value unfiltered output or alignment with particular ideologies, enterprise buyers are clearly playing by a different rulebook. They’re looking for stability, accountability and risk management, not provocation. As regulation tightens, that divide is likely to widen.

Featured Article : Gemini … Overblown Hype?

Posted on by Paul Stradling

Two new studies show that Google’s Gemini AI models may not live up to the hype in terms of answering questions about large datasets correctly.

Google Gemini 

Google Gemini is an advanced AI language model developed by Google to enhance various applications with sophisticated natural language understanding and generation capabilities. It features multimodal capabilities, enabling it to process and integrate information from text, images, and possibly audio for more comprehensive and context-aware responses. The model also boasts a deep contextual understanding, allowing it to generate relevant and accurate answers in complex conversations or tasks.

Google has highlighted Gemini’s scalability and adaptability as being its strong points, and how its highly scalable architecture can help with handling large-scale data efficiently and fine-tuning for specific tasks or industries.

Also, Gemini is thought to deliver superior performance in speed and accuracy due to advancements in machine learning techniques and infrastructure.

Studies 

However, the results of two studies appear to go against Google’s narrative that Gemini is particularly good at analysing large amounts of data.

For example, the Cornell University “One Thousand and One Pairs: A ‘novel’ challenge for long-context language models” study, co-authored by Marzena Karpinska, a postdoc at UMass Amherst, tested how well long-context Large Language Models (LLMs) can retrieve, synthesise, and reason over information across book-length inputs.

The study involved using a dataset called ‘NoCha’, which consisted of 1,001 pairs of true and false claims about 67 recently published English fiction books. The claims required global reasoning over the entire book to verify, posing a significant challenge for the models.

Unfortunately, the research revealed that no open-weight model performed above random chance, and even the best-performing model, GPT-4o, achieved only 55.8 per cent accuracy. Also, the study found that the models struggled with global reasoning tasks, particularly with speculative fiction that involves extensive world-building.

The models were found to frequently fail to answer questions correctly about large datasets, with accuracy rates between 40-50 per cent in document-based tests.

The research results suggest that while models can technically process long contexts, they often fail to truly understand the content. Also, the results may highlight the limitations of current long-context language models such as Google Gemini (Gemini 1.5 Pro and 1.5 Flash).

The Second Study 

The second study, co-authored by researchers at UC Santa Barbara, focused on the Gemini models’ performance in video analysis and their ability to ‘reason’ over the videos when being asked questions about them. However, the results also proved to be poor, highlighting difficulties with transcribing and recognising objects in images, thereby perhaps indicating significant limitations in the models’ data analysis capabilities.

Discrepancies Between Claims And Performance? 

Both studies appear to highlight possible discrepancies between Google’s claims and the actual performance of the Gemini models, thereby raising questions about their efficacy and shedding light on the broader challenges faced by generative AI technology.

Posted On X 

Marzena Karpinska, also noted (on X/Twitter) other interesting points about LLMs from the research, including:

– Even when models output correct labels, their explanations are often inaccurate.

– On average, all LLMs perform much better on pairs requiring sentence-level retrieval than global reasoning (59.8 per cent vs 41.6 per cent), but still their accuracy on these pairs is much lower than on the “needle-in-a-haystack” task.

– Models perform substantially worse on books with extensive world-building (fantasy and sci-fi) than contemporary and historical novels (romance or mystery).

What Does Google Say? 

Google has not directly commented on the specific studies that critique the performance of its Gemini models. However, Google has highlighted the advancements and capabilities of the Gemini models in their official communications. For example, Sundar Pichai, CEO of Google and Alphabet, has emphasised that Gemini models are designed to be highly capable and general, featuring state-of-the-art performance across multiple benchmarks. Google asserts that Gemini’s long context understanding, and multimodal capabilities significantly enhance its ability to process and reason about vast amounts of information, including text, images, audio, and video.

Google has tried to highlight its focus on the continuous improvement and rigorous testing of Gemini models, showcasing their performance on a wide variety of tasks, from natural image understanding to complex reasoning. The company has also been actively working on increasing the models’ efficiency and context window capacity, allowing them to process up to 1 million tokens (the basic units of text that the model processes). Google hopes these improvements will enable more sophisticated and context-aware AI applications.

What Does This Mean For Your Business? 

The findings from these studies may have significant implications for businesses relying on AI for data analysis and decision-making. The apparent underperformance of Google’s Gemini models in handling large datasets suggests that businesses might not be able to fully leverage these AI tools for complex data analysis tasks just yet. This could impact sectors like finance, healthcare, and any industry requiring detailed and accurate data interpretation, where businesses may need to reassess their dependence on such models for critical operations.

For Google, these studies may highlight a gap between their promotional claims and the actual capabilities of their AI models. This could prompt Google to accelerate its research and development efforts to address these shortcomings and enhance the practical utility of their models. It also places pressure on Google to maintain transparency about the limitations of their technologies while continuing to push the boundaries of AI performance.

Other AI companies might view these findings as both a caution and an opportunity. On one hand, the discrepancies in performance underline the inherent challenges in developing robust AI models. On the other hand, they provide a competitive edge for companies that can deliver more reliable and accurate AI solutions. This competitive landscape could drive innovation and lead to the emergence of more capable AI models that better meet the complex needs of businesses.

In summary then, while the current limitations of AI models like Google Gemini pose challenges, they also highlight areas ripe for innovation and improvement. Businesses should stay informed about these developments and be prepared to adapt their strategies to harness the full potential of evolving AI technologies.

Featured Article : Don’t Ask Gemini About The Election

Posted on by Paul Stradling

Google has outlined how it will restrict the kinds of election-related questions that its Gemini AI chatbot will return responses to.

Why? 

With 2024 being an election year for at least 64 countries (including the US, UK, India, and South Africa) the risk of AI being misused to spread misinformation has grown dramatically. This problem extends to a lack of trust by various countries’ governments (e.g. India) around AI’s reliability being taken seriously. There are also worries about how AI could be abused by adversaries of the country holding the election, e.g. to influence the outcome.

Recently, for example, Google’s AI made the news for when its text-to-image AI tool was overly ‘woke’ and had to be paused and corrected following “inaccuracies.” For example, when Google Gemini was asked to generate images of the Founding Fathers of the US, it returned images of a black George Washington. Also, in another reported test, when asked to generate images of a 1943 German (Nazi) soldier, Google’s Gemini image generator returned pictures of people of clearly diverse nationalities (a black and an Asian woman) in Nazi uniforms.

Google also says that its restrictions of election-related responses are being used out of caution and as part of the company’s commitment to supporting the election process by “surfacing high-quality information to voters, safeguarding our platforms from abuse, and helping people navigate AI-generated content.” 

What Happens If You Ask The ‘Wrong’ Question? 

It’s been reported that Gemini is already refusing to answer questions about the US presidential election, where President Joe Biden and Donald Trump are the two contenders. If, for example, users ask Gemini a question that falls into its election-related restricted category, it’s been reported that they can expect Gemini’s response to go along the lines of: “I’m still learning how to answer this question. In the meantime, try Google Search.” 

India 

With India being the world’s largest democracy (about to undertake the world’s biggest election involving 970 million voters, taking 44 days), it’s not surprising that Google has addressed India’s AI concerns specifically in a recent blog post. Google says: “With millions of eligible voters in India heading to the polls for the General Election in the coming months, Google is committed to supporting the election process by surfacing high-quality information to voters, safeguarding our platforms from abuse and helping people navigate AI-generated content.” 

With its election due to start in April, the Indian government has already expressed its concerns and doubts about AI and has asked tech companies to seek its approval first before launching “unreliable” or “under-tested” generative AI models or tools. It has also warned tech companies that their AI products shouldn’t generate responses that could “threaten the integrity of the electoral process.” 

OpenAI Meeting 

It’s also been reported that representatives from ChatGPT’s developers, OpenAI, met with officials from the Election Commission of India (ECI) last month to look at how OpenAI’s ChatGPT tool could be used safely in the election.

OpenAI advisor and former India head at ‘X’/Twitter, Rishi Jaitly, is quoted from an email to the ECI (made public) as saying: “It goes without saying that we [OpenAI] want to ensure our platforms are not misused in the coming general elections”. 

Could Be Stifling 

However, Critics in India have said that clamping down too much on AI in this way could actually stifle innovation and could lead to the industry being suffocated by over-regulation.

Protection 

Google has highlighted a number of measures that it will be using to keep its products safe from abuse and thereby protect the integrity of elections. Measures it says it will be taking include enforcing its policies and using AI models to fight abuse at scale, enforcing policies and restrictions around who can run election-related advertising on its platforms, and working with the wider ecosystem on countering misinformation. This will include measures such as working with Shakti, India Election Fact-Checking Collective, a consortium of news publishers and fact-checkers in India.

What Does This Mean For Your Business? 

The combination of rapidly advancing and widely available generative AI tools, popular social media channels and paid online advertising look very likely to pose considerable challenges to the integrity of the large number of global elections this year.

Most notably, with India about to host the world’s largest election, the government there has been clear about its fears over the possible negative influence of AI, e.g. through convincing deepfakes designed to spread misinformation, or AI simply proving to be inaccurate and/or making it much easier for bad actors to exert an influence.

The Indian government has even met with OpenAI to seek reassurance and help. The AI companies such as Google (particularly since its embarrassment over its recent ‘woke’ inaccuracies, and perhaps after witnessing the accusations against Facebook after the last US election and UK Brexit vote), are very keen to protect their reputations and show what measures they’ll be taking to stop their AI and other products from being misused with potentially serious results.

Although governments’ fears about AI deepfake interference may well be justified, some would say that following the recent ‘election’ in Russia, misusing AI is less worrying than more direct forms of influence. Also, although protection against AI misuse in elections is needed, a balance must be struck so that AI is not over-regulated to the point where innovation is stifled.

Tech News : Google Pauses Gemini AI Over ‘Historical Inaccuracies’

Posted on by Paul Stradling

Only a month after its launch, Google has paused its text-to-image AI tool following “inaccuracies” in some of the historical depictions of people produced by the model.

‘Woke’ … Overcorrecting For Diversity? 

An example of the inaccuracy issue (as highlighted by X user Patrick Ganley recently, after asking Google Gemini to generate images of the Founding Fathers of the US), was when it returned images of a black George Washington. Also, in another reported test, when asked to generate images of a 1943 German (Nazi) soldier, Google’s Gemini image generator returned pictures of people of clearly diverse nationalities in Nazi uniforms.

The inaccuracies have been described by some as examples of the model subverting the gender and racial stereotypes found in generative AI, a reluctance to depict ‘white people’ and / or conforming to ‘woke’ ideas, i.e. the model trying to remove its own bias and improve diversity yet ending up simply being inaccurate to the point of being comical.

For example, on LinkedIn, Venture Capitalist Michael Jackson said the inaccuracies were a “byproduct of Google’s ideological echo chamber” and that for the “countless millions of dollars that Google spent on Gemini, it’s only managed to turn its AI into a nonsensical DEI parody.” 

China Restrictions Too? 

Another issue (reported by Al Jazeera), noted by a former software engineer at Stripe on X, was that Gemini would not show the image of a man in 1989 Tiananmen Square due to its safety policy and the “sensitive and complex” nature of the event. This, and similar issues have prompted criticism from some that Gemini may also have some kind of restrictions related to China.

What Does Google Say? 

Google posted on X to say about the inaccurate images: “We’re working to improve these kinds of depictions immediately. Gemini’s AI image generation does generate a wide range of people. And that’s generally a good thing because people around the world use it. But it’s missing the mark here.” 

Google has, therefore, announced that: ”We’re already working to address recent issues with Gemini’s image generation feature. While we do this, we’re going to pause the image generation of people and will re-release an improved version soon.” 

Bias and Stereotyping 

Bias and stereotyping have long been issues in the output of generative AI tools. Bias and stereotyping in generative AI outputs exist primarily because AI models learn from vast amounts of data collected from human languages and behaviours, which inherently contain biases and stereotypes. As models mimic patterns found in their training data, they can replicate and amplify existing societal biases and stereotypes.

What Does This Mean For Your Business? 

Google has only just announced the combining of Bard with its new Gemini models to create its ‘Gemini Advanced’ subscription service, so this discovery is likely to be particularly unwelcome. The anti-woke backlash and ridicule are certainly something Google could do without about now, but the issue has highlighted the complications of generative AI, how it is trained, and the complexities of how models interpret the data and instructions they’re given. It also shows how AI models may be advanced, but they don’t actually ‘think’ (as a human would), they can’t perform ‘reality checks’ as humans can because they don’t ‘live’ in the ‘real world.’ Also, this story shows how early we still are in the generative AI journey.

Google’s explanation has shed some light on the thinking behind the issue and at least it’s admitted to being wide of the mark in terms of historical accuracy – which is clear from some of the examples. It’s all likely to be an embarrassment and a hassle for Google in its competition with Microsoft and its partner OpenAI, nevertheless, Google seems to think that with a pause plus a few changes, it can tackle the problem and move forward.

Featured Article : Google’s AI Saves Your Conversations For 3 Years

Posted on by Paul Stradling

If you’ve ever been concerned about the privacy aspects of AI, you may be very surprised to learn that conversations you have with Google’s new Gemini AI apps are “retained for up to 3 years” by default.

Up To Three Years 

With Google now launching its Gemini Advanced chatbot as part of its ‘Google One AI Premium plan’ subscription, and with its Ultra, Pro, and Nano LLMs now forming the backbone of its AI services, Google’s Gemini Apps Privacy Hub was updated last week. The main support document on the Hub which states how Google collects data from users of its Gemini chatbot apps for the web, Android and iOS made interesting reading.

One particular section that has been causing concern and has attracted some unwelcome publicity is the “How long is reviewed data retained?” section. This states that “Gemini Apps conversations that have been reviewed by human reviewers…. are not deleted when you delete your Gemini Apps activity because they are kept separately and are not connected to your Google Account. Instead, they are retained for up to 3 years”. Google clarifies this in its feedback at the foot of the support page saying, “Reviewed feedback, associated conversations, and related data are retained for up to 3 years, disconnected from your Google Account”. It may be of some comfort to know, therefore, that the conversations aren’t linked to an identifier Google account.

Why Human Reviewers? 

Google says its “trained” human reviewers check conversations to see if Gemini Apps’ responses are “low-quality, inaccurate, or harmful” and that “trained evaluators” can “suggest higher-quality responses”. This oversight can then be used “create a better dataset” for Google’s generative machine-learning models to learn from so its “models can produce improved responses in the future.” Google’s point is that human reviewers ensure a kind of quality control both in responses and how and what the models learn in order to make Google’s Gemini-based apps “safer, more helpful, and work better for all users.” Google also makes the point that the human reviewers may also be required by law (in some cases).

That said, some users may be alarmed that their private conversations are being looked at by unknown humans. Google’s answer to that is the advice: “Don’t enter anything you wouldn’t want a human reviewer to see or Google to use” and “don’t enter info you consider confidential or data you don’t want to be used to improve Google products, services, and machine-learning technologies.” 

Why Retain Conversations For 3 Years? 

Apart from improving performance and quality, other reasons why Google may retain data for years could include:

– The retained conversations act as a valuable dataset for machine learning models, thereby helping with continuous improvement of the AI’s understanding, language processing abilities, and response generation, ensuring that the chatbot becomes more efficient and effective in handling a wide range of queries over time. For services using AI chatbots as part of their customer support, retained conversations could allow for the review of customer interactions which could help in assessing the quality of support provided, understanding customer needs and trends, and identifying areas for service improvement.

– Depending on the jurisdiction and the industry, there may be legal requirements to retain communication records for a certain period, i.e. compliance and being able to settle disputes.

– To help monitor for (and prevent) abusive behaviour, and to detect potential security threats.

– Research and development to help advance the field of AI, natural language processing, and machine learning, which could contribute to innovations, more sophisticated AI models, and better overall technology offerings.

Switching off Gemini Apps Activity 

Google does say, however, that users can control what’s shared with reviewers by turning off Gemini Apps Activity. This will mean that any future conversations won’t be sent for human review or used to improve its generative machine-learning models, although conversations will be saved with the account for up to 72 hours (to allow Google to provide the service and process any feedback).

Also, even if you turn off the setting or delete your Gemini Apps activity, other settings including Web & App Activity or Location History “may continue to save location and other data as part of your use of other Google services.”

There’s also the complication that Gemini Apps is integrated and used with other Google services (which Gemini Advanced – formerly Bard, has been designed for integration), and “they will save and use your data” (as outlined by their policies and Google’s overall Privacy Policy).

In other words, there is a way you can turn it off but just how fully turned off that may be is not clear due to links and integration with Google’s other services.

What About Competitors? 

When looking at Gemini’s competitors, retention of conversations for a period of time by default (in non-enterprise accounts) is not unusual. For example:

– OpenAI saves all ChatGPT content for 30 days whether its conversation history feature is switched off or not (unless the subscription is an enterprise-level plan, which has a custom data retention policy).

– Looking at Microsoft and the use of Copilot, the details are more difficult to find but details about using Copilot in Teams it appears that the farthest Copilot can process is 30 days – indicating a possibly similar retention time to ChatGPT.

How Models Are Trained

How AI models are trained, what they are trained on and whether there has been consent and or payment for usage of that data is still an ongoing argument with major AI providers facing multiple legal challenges. This indicates how there is still a lack of understanding, clarity and transparency around how generative AI models learn.

What About Your Smart Speaker? 

Although we may have private conversations with a generative AI chatbot, many of us may forget that we may have many more private conversations with our smart speaker in the room listening, which also retains conversations. For example, Amazon’s Alexa retains recorded conversations for an indefinite period although it does provide users with control over their voice recordings. For example, users have the option to review, listen to, and delete them either individually or all at once through the Alexa app or Amazon’s website. Users also have the option to set up automatic deletion of recordings after a certain period, such as 3 or 18 months – but 18 months may still sound an alarming amount of time to have a private conversation stored in distant cloud data centres anyway.

What Does This Mean For Your Business? 

Retaining private conversations for what sounds like a long period of time (3 years) and having unknown human reviewers look at those private conversations are likely to be the alarming parts of Google’s privacy information about how its Gemini chatbot is trained and maintained.

The fact that it’s a default (i.e. it’s up to the user to find out about it and turn off the feature), with a 72-hour retention period afterwards and no guarantee that conversations still won’t be shared due to Google’s interrelated and integrated products may also not feel right to many. The fact too that our only real defence is not to share anything at all faintly personal or private with a chatbot, which may not be that easy given that many users need to provide information to get the right quality response may also be jarring.

It seems that for enterprise users, more control over conversations is available but it seems like businesses need to ensure clear guidelines are in place for staff about exactly what kind of information they can share with chatbots in the course of their work. Overall, this story is another indicator of how there appears to be a general lack of clarity and transparency about how chatbots are trained in this new field and the balance of power still appears to be more in the hands of tech companies providing the AI. With many legal cases on the horizon about how chatbots are trained, we may expect to see more updates to AI privacy policies soon. In the meantime, we can only hope that AI companies are true to their guidelines and anonymise and aggregate data to protect user privacy and comply with existing data protection laws such as GDPR in Europe or CCPA in California.