Deleted ChatGPT Conversations Weren’t Really Deleted — And Now OpenAI Is Pushing for ‘AI Privilege’

If you’ve ever used ChatGPT’s temporary chat feature thinking your conversation would vanish after closing the window — well, it turns out that wasn’t exactly the case. At least not anymore.

OpenAI is now under fire after revealing it’s been keeping records of deleted and temporary chats, not by choice, but because of a legal mandate tied to a lawsuit. The update, which took more than three weeks to surface publicly, has left many users feeling blindsided.

It all started with a federal court order issued back in May, which requires OpenAI to preserve any and all output data — even if users tried to delete it. That includes chats created in the supposedly private, one-time “temporary” mode.

The move is tied to an ongoing legal battle with The New York Times, which is suing OpenAI and Microsoft over alleged copyright violations. Their argument? That ChatGPT can reproduce copyrighted material almost word for word — and that even “deleted” chats might contain examples that prove their case.

OpenAI complied right away, but didn’t inform users until early June. Only then did a blog post appear, explaining that unless you’re using an enterprise-tier product or an API endpoint with zero data retention (ZDR), your conversations are likely being held in storage — indefinitely, for now.

Users Cry Foul as OpenAI Admits to Storing Supposedly Deleted Chats

On platforms like X (formerly Twitter), users didn’t take the news lightly. Some felt betrayed. Others were confused about how long their data had been sticking around. A few noted the contradiction between what the UI suggested and what was actually happening behind the scenes.

The real issue? OpenAI hadn't made this change transparent when it first happened.

In its defense, the company said it’s simply following the judge’s orders — not harvesting extra data voluntarily. The stored conversations are being isolated under a legal hold, meaning only a small internal team has access. None of it, they stress, is being handed to The New York Times or any other party right now.

Still, for people who thought “delete” really meant delete, the whole thing felt like a bait-and-switch.

Sam Altman Floats a New Concept: ‘AI Privilege’

OpenAI’s CEO, Sam Altman, weighed in not long after the blowback started gaining traction. In a series of late-night posts, he described the court’s request as excessive and said OpenAI would be challenging it.

But more notably, he raised a new idea — something he called “AI privilege.”

The concept? That conversations with AI systems might deserve the same kind of confidentiality you’d get when speaking to a doctor or a lawyer. That’s not a small claim. If it gained legal recognition, it could reshape how AI interactions are handled in everything from lawsuits to internal audits.

Right now, it’s just a concept. But the fact that OpenAI is even bringing it up suggests the company’s looking beyond this case — maybe toward a broader framework that shields AI interactions from unwanted scrutiny.

For Businesses, the Stakes Are Bigger Than One Court Case

While most attention is focused on the user angle, companies integrating ChatGPT into internal tools or customer-facing services now face a much trickier landscape.

Even if a company is using a ZDR endpoint and thinks it’s safe, data could still get caught in logs, analytics systems, or third-party backups. Many CIOs and compliance leads are likely re-evaluating how “temporary” their AI workflows really are — and whether their systems might unintentionally store interactions they promised wouldn’t stick around.

For enterprise users, the current legal carve-outs (like for ChatGPT Enterprise accounts) may offer a buffer. But the bigger picture here is that legal preservation orders are now in play — and that means every assumption about ephemeral AI data might need to be questioned.

Data governance just got a lot more complicated.

What Comes Next?

OpenAI has formally objected to the judge’s order, arguing that the demand to retain user chat data lacks a strong factual basis and places an unnecessary burden on the company.

At a recent hearing, the judge hinted that the preservation order might not be permanent. She asked both sides to come up with a sampling method to determine whether deleted chats differ meaningfully from the ones already stored. OpenAI was expected to submit that plan by June 6.

In the meantime, the company remains in a tight spot. It has to comply with a legal directive it disagrees with, while trying to reassure users and customers that their privacy still matters.

A Pivotal Moment for AI Privacy

This isn’t just another legal footnote. It’s turning into a pivotal moment in how the tech world defines AI privacy. If “AI privilege” gains traction, it could influence everything from app design to data regulation. If it doesn’t, it may still spark a broader reckoning about how people think about what they tell machines.

Right now, OpenAI is caught in the middle — juggling court orders, enterprise expectations, and public trust — while fighting a legal battle that could redefine the rules for everyone building or using AI.

And for anyone who assumed their chats disappeared the moment they hit delete? That assumption just became a lot more complicated.

Image: DIW-Aigen

Read next: 

• ChatGPT Might Know More About You Than You Think — Here’s How to Check and Erase It

• Google Expands Gemini with Scheduled Actions, Taking on ChatGPT’s Automation Edge
by Irfan Ahmad via Digital Information World

Google Expands Gemini with Scheduled Actions, Taking on ChatGPT’s Automation Edge

Google has rolled out a scheduling capability for Gemini, marking a clear step toward matching features already available in rival AI platforms. The new tool allows users to assign time-based tasks to the assistant, enabling it to execute prompts automatically at set times — a concept that closely mirrors the scheduled tasks OpenAI launched earlier this year in ChatGPT.

Users who subscribe to Google’s premium AI tiers — such as the AI Pro and Ultra plans — along with those on Workspace business or education accounts, can now set up these actions by issuing a direct command. Whether through typed instructions or voice input, Gemini responds by queuing up the request to trigger at the specified time. Regular recurring tasks are supported as well, offering a hands-off approach to routine reminders and updates.

This update follows OpenAI’s release in January, where ChatGPT users gained the ability to schedule prompts that trigger automatically — for example, requesting daily news summaries or setting future reminders. That functionality is currently limited to the o3 and o4-mini models and capped at ten active tasks per user. Users can manage their task queue by pausing or deleting existing entries to make space for new ones.

As of now, Google hasn’t published details about usage limits for scheduled actions in Gemini. It remains unclear whether users will face task caps or be given tools for granular task management. Still, the parallel development suggests a tightening race between AI assistants vying to become central to how users manage time, memory, and productivity.

As both platforms sharpen their automation tools, the line between passive assistance and active task execution continues to blur — pushing AI deeper into daily routines, not just as reactive tools, but as proactive participants in people’s schedules.

Image: DIW-Aigen

Read next:

• Influencer Marketing Hits a Crossroads: Consumers Want Real, Not Scripted

• Traditional Search Holds Firm At 10% Use; AI Lags While Zero-clicks And Internal Google Clicks Rise
by Irfan Ahmad via Digital Information World

Influencer Marketing Hits a Crossroads: Consumers Want Real, Not Scripted

Typeform has launched a new report that rethinks how data and storytelling intersect in the age of digital influence. Titled Get Real: The Data on Influencer Marketing, the report blends statistics and insights from over 1,300 contributors across the influencer economy — including creators, brand marketers, and consumers.

The report makes one thing clear i.e. people are choosing real connections over polished appearances. As synthetic content becomes more prevalent and overly staged influencer promotions flood timelines, trust is slipping — and audiences are starting to walk away.

Authenticity Trumps the Algorithm

While follower counts still dominate many brand briefs, the findings suggest reach is no longer enough. Consumers are increasingly looking past numbers to assess whether influencers actually connect with their audience. Nearly 40% said relatability was the number-one reason they trusted a creator — not celebrity, not production value, and certainly not follower size.

One in two consumers said they would cut ties with an influencer known to have bought followers. That instinct aligns with admissions from the creator side: roughly one-third of influencers surveyed acknowledged using artificial methods to boost metrics. For brands, the takeaway is clear — inflated numbers can't build lasting trust.

The AI Dilemma

Despite the growing use of generative tools among content creators — with 81% of influencers saying they’ve leaned on AI in some form — a credibility gap is growing. More than a third of consumers express discomfort with AI-crafted content in influencer campaigns, and most want disclosure when it's used.

Audiences aren’t rejecting technology outright; they’re rejecting artificiality. In a landscape already saturated with stylized, overly curated experiences, algorithmic content seems to widen the disconnect. Consumers want to believe that the person behind the camera genuinely means what they say — and that belief is harder to hold when a script, or a bot, is doing the talking.

When Scripts Backfire

Brand control may be a necessary part of campaign management, but when content feels rehearsed or unnatural, audiences don’t just notice — they disengage. The data shows that inauthentic engagement is the most common reason viewers tune out. Behind the scenes, many influencers feel the same frustration. One in four said that being forced to act out of character or promote products they don't trust is their biggest professional challenge.

Consumers aren’t unaware, anymore. Only about a third believe that influencers actually use the products they showcase — and more than half of influencers confirmed they’ve recommended items they didn’t personally support. That disconnect has consequences: over 70% of consumers admitted regretting purchases made based on influencer advice.

A Shift in the Power Dynamic

The report marks a turning point in how marketing teams might approach partnerships. Rather than seeing creators as ad channels, the data suggests a growing need to treat them as collaborators — ones who can bring real voice and emotional insight into the conversation. In a post-AI world where trust has become a rare commodity, what matters isn’t the gloss — it’s whether viewers feel something genuine.

Typeform’s methodology underlines this shift. By using open-ended video prompts instead of traditional surveys, they captured not just what people said, but how they said it — tone, hesitation, emotion. The approach mirrors the very demand shaping today’s digital behavior: less performance, more presence.

The report draws from a diverse sample of respondents across industries like fashion, travel, tech, and finance. Most responses came from North America and Europe, and the blend of consumers, marketers, and influencers paints a layered picture of an ecosystem under pressure — but also one ready for change.

Read next: When LLMs Lies Smoothly: Study Reveals Gaps Between AI's Decisions and Explanations

by Irfan Ahmad via Digital Information World

iOS 18 Nears Full Adoption on New Devices, Android Remains Scattered

The vast majority of iPhone and iPad users are already running the latest versions of Apple’s mobile software, according to newly shared figures. The numbers show most users haven’t waited around to upgrade, with iOS 18 and iPadOS 18 making quick strides in just a few months.

Among iPhones launched in the past four years, nearly nine in ten now run iOS 18. When looking at all iPhones still in use — regardless of age — around eight in ten have made the leap.

Things look nearly as healthy on the iPad front. Around 81% of newer iPads now use iPadOS 18, while 71% of all iPads have installed it. These figures suggest users haven’t dragged their feet when it comes to staying current.

Looking back, iOS 17 and iOS 16 had strong showings too, but iOS 18 is holding its own. For instance, this time last year, iOS 17 was on 86% of newer iPhones. iOS 16, the year before, hit 90% — a high-water mark Apple hasn’t quite matched this round.

iPads have followed a similar pattern. iPadOS 17 had reached 86% on recent models last year, a notch higher than iPadOS 18’s current mark. But in terms of all iPads in circulation, both iPadOS 18 and iPadOS 16 stand level at 71%.

Several reasons help explain this fast uptake. First, iOS 18 works on older devices like the iPhone Xs, giving long-time users a chance to upgrade without splashing out on new kit. Second, software updates can be triggered straight from the settings menu — no need for tech know-how or cables. And third, Apple doesn’t rely on phone networks or third parties to push updates. It handles the lot in-house, speeding things up.

From a security point of view, staying up to date matters more than ever. Each new update patches bugs and tightens defences against the latest threats. There’s also the added bonus of new features landing with every major release.

Even so, not everyone wants to rush ahead. For those who prefer to tread carefully, Apple’s been offering a middle ground. When iOS 18 rolled out, users were also given the option to move to iOS 17.7 instead — a more familiar option that still delivers stability and fixes, without jumping headfirst into something new.

All told, these adoption rates show that Apple still holds the reins when it comes to rolling out software at scale. Whether for features, security, or just peace of mind, most iPhone and iPad users don’t seem to need much convincing to stay up to date.

While Apple’s software rollout stays tight and streamlined, the Android landscape, on the other hand, tells a more tangled tale.

As of May 2025, Android 14 holds the largest share, running on just under 30% of phones and tablets. But the rest of the platform is scattered across multiple versions, including Android 13 (17%), Android 12 (12%), and even Android 10, which still clings to life on more than 5% of devices.

This uneven spread isn’t new. Android’s open structure means phone makers like Samsung, Xiaomi, Motorola, and others all run their own shows. Each brand customises Android, adds its own features, and controls when — or whether — users get updates.

That process often slows things down. Some devices wait months for new software. Others never receive it at all.

For users, it means getting the latest version isn’t always in their hands. Factors like carrier approval, regional policies, and manufacturer priorities all come into play. While some premium Android models are now getting better long-term support, the broader market — especially at lower price points — still sees patchy and inconsistent update paths.

So, although Android 14 leads the version chart, the platform as a whole remains fragmented, with millions of users still running older builds — and missing out on the latest security protections, features, and performance boosts that newer versions bring.

Read next:

• Are Creators the New Brands? How Gen Z and Millennials Are Rewriting Consumer Trust

• ChatGPT Might Know More About You Than You Think — Here’s How to Check and Erase It

by Irfan Ahmad via Digital Information World

Are Creators the New Brands? How Gen Z and Millennials Are Rewriting Consumer Trust

A growing number of shoppers aren’t buying into traditional branding anymore. They’re buying into people. That’s the main takeaway from a new Adobe Express study that digs into how younger generations are reshaping trust in commerce. As the line between influencer and entrepreneur keeps blurring, creators are no longer just the face of a brand — they are the brand.

Adobe’s People Trust People report explores how Gen Z and millennials are shifting loyalty away from legacy companies and toward creator-led businesses. And it’s not a fringe trend. According to the survey, over half of U.S. consumers have already purchased from a creator-led brand. Among younger age groups, that number is even higher.

Creator Brands Aren’t Celebrity Vanity Projects

There’s a big difference between a celebrity endorsement and a creator-led brand. This isn’t about a famous person slapping their name on a perfume bottle. Creator-led brands are built on identity, transparency, and relationships. These creators aren’t just selling — they’re engaging, connecting, and showing their audience the “why” behind their products.

They build trust slowly, through content. On YouTube, Instagram, and TikTok, creators talk directly to their followers. They review products, share routines, show behind-the-scenes footage, and invite fans into their lives. So when they launch a product, it doesn’t feel like a cash grab. It feels personal.

That personal connection is driving real purchases. Adobe’s study shows that 56% of U.S. consumers have bought from a creator-led brand. Among Gen Z, that number climbs to 66%. Millennials follow close behind at 61%. These are the buyers setting trends and reshaping how people think about brand loyalty.

Discovery Starts With Social

The way people find these brands also matters. Discovery is driven by social media — not ads or store shelves. YouTube leads the pack (48%), followed by Instagram (42%) and TikTok (33%). These platforms aren’t just scroll-and-forget. They’re storytelling tools. Video and visuals help creators explain not just what they’re selling, but why it matters.

A skin care creator might walk viewers through their daily routine using their own product. A coffee brand might show the founder tasting beans and adjusting roast profiles. These moments aren’t filtered through agencies or marketing teams. They’re real. That realism builds trust, and trust drives action.

The Most Trusted Names Aren’t Who You’d Expect

Some of the most successful creator-led brands come from names you already know, but the products aren’t just resting on fame. Rihanna’s Fenty Beauty and Savage X Fenty stand out as leaders across all generations. They’ve maintained popularity because they deliver on what they promise: inclusivity, quality, and transparency.

For Gen Z specifically, brands like MrBeast Burger, Feastables, and Chamberlain Coffee are just as influential. These ventures span industries — beauty, fashion, food — and each reflects the personality of the creator behind it. That’s what ties them together. Whether it’s through playful branding, product transparency, or community involvement, the common thread is realness.

A New Definition of Trust

Trust used to come from brand history, size, or polish. Now, it comes from consistency and honesty. Adobe’s study found that 13% of consumers already trust creator-led brands more than traditional ones. Even more telling, one in four shoppers has switched brands in favor of one led by a creator.

That loyalty isn’t just about hype. It’s grounded in three major factors:

• Transparent reviews (42%). Buyers want firsthand insight, not scripted endorsements.

• Creator integrity (30%). Trust builds over time. Followers learn what a creator values, how they behave, and what they’re willing to stand behind.

• Authenticity (30%). Personal storytelling beats ad copy. Consumers want to feel like they know the person behind the product.

This shift isn’t just about branding. It’s about who consumers believe — and why.

Money Talks: Young Consumers Are Spending More

If you want proof this trend isn’t just talk, look at the numbers. Millennials spend about $109 a month on creator-led brands. Gen Z follows at $104. In contrast, Gen X spends $30, and baby boomers average just $16.

That spending gap shows more than generational preference. It reflects a broader change in shopping habits. Gen Z and millennials are comfortable discovering products online, trusting creators they follow, and making purchases based on emotional connection.

They grew up with social media. They’re used to parasocial relationships — those one-sided digital bonds with creators they follow. For them, a recommendation from a YouTuber they’ve watched for years carries more weight than a TV ad from a faceless brand.

Good Products Still Matter

Popularity doesn’t guarantee success. Creator brands still have to deliver. Fortunately, most do.

According to Adobe’s study, 70% of consumers feel creator-led brands live up to their promise. Forty percent plan to keep buying from them.

Consider Rare Beauty, launched by Selena Gomez. It boasts an 84% satisfaction rate. Fenty Beauty isn’t far behind at 81%, with Savage X Fenty at 80%. These brands' recipes for success include a combination of creator connection with solid product performance. The creators' fame gets shoppers in the door, but the product experience keeps them coming back.

Can Traditional Brands Compete?

Old models focused on brand identity, polished campaigns, and control. New models prioritize conversation, transparency, and flexibility. Creator-led brands don’t operate on quarterly campaigns. They respond in real time, they listen, and they evolve with their audiences.

That’s a challenge for legacy brands. It’s hard to build intimacy at scale, but it's not impossible. It starts with asking new questions:

• How can we speak directly to our audience?

• Can we put a real person at the center of our story?

• Where should we invest to build relationships — not just reach?

These tweaks require a new mindset where trust isn’t assumed, but earned.

Trust Is the New Brand Equity

Adobe’s research shows that creator-led brands work because they meet consumers where they are — online, engaged, and skeptical of polished promises. They succeed by being transparent, consistent, and personal.

Gen Z and millennials want to know the people behind what they buy. They want values that match their own, and that comes from stories, not slogans.

That means traditional brands may have to evolve. Trust, once a byproduct of scale, now depends on connection. And in a market driven by loyalty, attention, and belief, creators have the edge.

People trust people, and that’s always been true. But what’s changed is who consumers see as trustworthy — and who they see as worth buying from.

Read next: Breaking Down Billion-Dollar Revenues: How Much Top Tech Companies Earn Per Employee

by Irfan Ahmad via Digital Information World

Google AI Overviews Rely Heavily on Established News Sources, Report Shows

Google’s AI-generated search summaries appear to be giving a clear advantage to big-name news outlets, making it difficult for smaller publishers to get noticed. A recent study, conducted by SERanking, has revealed that a handful of major media brands dominate nearly all the citations in these AI Overviews, leaving very little room for others.

The analysis, which examined more than 75,000 AI responses, found that only about one in five even included a news source. Among those that did, just a small group of publishers accounted for the vast majority of mentions. The BBC, The New York Times, and CNN made up almost a third of all references to media, with the BBC alone responsible for more than 11.37 percent.

Despite the study focusing on search queries in the United States, UK-based outlets like the BBC still came out on top. The findings show that only 12 news organisations received nearly 90 percent of all citations. In contrast, the other 18 included in the analysis were left to split the remaining 10 percent between them. The Financial Times, for instance, was cited 195 times less than the BBC for the same set of keywords.

Several other well-known names, such as MSNBC, Vice, and TechCrunch, also struggled to break through. Together, those brands appeared in less than one percent of all media mentions. Researchers say the issue lies in how Google’s AI system prioritises sources that are already well-established. It tends to rely on outlets with high authority and recognisable names, making it much harder for lesser-known sites to gain visibility—even if they cover the same stories.

What’s more, this pattern doesn’t always match traditional search results. Around 60 percent of the media links cited in AI Overviews didn’t appear in the top 10 organic search results for the same terms. That suggests Google’s AI doesn’t simply rely on page rankings but draws instead on a mix of perceived trustworthiness and content quality.

Inequality in citation was measured using a Gini coefficient, a common tool used to study economic inequality. The score came in at 0.54—signalling a significant imbalance in how attention is spread across news providers. A perfect score of zero would mean all sources were treated equally.

There are concerns too about how the AI handles content from paywalled sites. In many cases, long segments of text were copied from behind paywalls and included in AI Overviews. Of those responses that pulled from subscription-only material, nearly seven in ten contained copied phrases of five words or more. Some even went beyond ten words. Despite this, fewer than one in six of those examples gave proper credit, raising questions around fair use and licensing.

When AI Overviews do include news links, most of them are pushed to the bottom of the response. Fewer than two links are typically used, and over 90 percent are tucked into a links section rather than the main text. Media brands are also more likely to be linked than named outright. In fact, more than a quarter of media mentions appear without any clickable link at all, especially when the AI pulls information from aggregators instead of original reporting.

The type of search query also plays a part. People looking for news are more likely to see AI responses that include media citations, with news-related searches being more than twice as likely to contain media references compared with general ones. This opens the door slightly for outlets that specialise in breaking news or niche topics. Still, the broad trend heavily favours the larger players.

Although smaller publishers face clear challenges, the researchers point out a few ways they might improve their chances. Getting backlinks from sites already cited in AI Overviews could help. So could refining technical signals on their own websites—like properly using metadata to mark whether content is freely accessible. Publishers who focus on specific topics or underserved areas may also see better results over time, as Google’s AI seems to reward expertise in well-defined subject areas.

With Google’s AI Overviews now appearing in nearly one in five publisher-related searches, these patterns are likely to shape the future of online visibility. The old rules of SEO still apply, but increasingly, success depends on trust, authority, and depth of content—qualities that the AI appears to prioritise above all else.

Read next: Apple Rejects More Government Push Data Requests Amid Growing Demand
by Irfan Ahmad via Digital Information World

WhatsApp to Let Users Build Custom AI Assistants Without Coding

WhatsApp is getting ready to introduce a new feature that will let people build their own AI chatbots directly inside the app, without needing to write any code, as first spotted by WBI. This move follows similar efforts from other tech companies, like OpenAI with its custom GPTs and Google with its Gemini Gems. The idea is to make it easier for everyday users to create assistants or characters they can talk to, all through a few guided steps within WhatsApp itself.

The tool is part of Meta’s wider AI Studio platform, which until now has mainly been used through the web or on apps like Messenger and Instagram. With this update, WhatsApp will gain similar capabilities, allowing people to build and personalise their own AI experiences without leaving the messaging app. A small number of beta testers using Android and iOS have already started to see a new section called “AI Studio,” where the feature is being tested quietly ahead of a wider rollout.

Instead of overwhelming users with technical terms, the chatbot creation process is designed to be simple and intuitive. It begins by asking the user to pick a role for their AI—whether it’s a helpful tutor, a travel planner, or even a virtual companion for motivation. After choosing the type of assistant they want, users then select a personality style, ranging from calm and thoughtful to lively and humorous or even formal and informative. Based on those choices, WhatsApp then provides intelligent suggestions to help fine-tune the assistant’s tone and behaviour during conversations.

While each AI chatbot will start out as private, WhatsApp will also give users the option to share them with others using a unique link. This approach is similar to what platforms like OpenAI and Google have already done, where users can browse and interact with bots created by others. Although features like the GPT Store haven’t become hugely popular, they still offer useful inspiration for building creative assistants, and Meta could be hoping to take a simpler and more user-friendly approach through WhatsApp.

At this stage, the feature is still in development and not available to most users, but signs of its arrival have already appeared in recent beta versions of the app. This adds to a busy period for WhatsApp, which has just launched an official app for iPad and started testing usernames, pointing to a broader push to expand what the platform can offer beyond traditional messaging.

Read next: Breaking Down Billion-Dollar Revenues: How Much Top Tech Companies Earn Per Employee
by Irfan Ahmad via Digital Information World