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You never needed to log in to simply view content on Reddit before, but now the CEO is seemingly looking to change that.
Unsurprisingly, part of the reason cited for making the change is their ad business:
We’re making the change because it’s better for user experience, better for our ads business, is more in line with safety regulations, and more protective of Reddit data. And we can do this while continuing to ensure user privacy.
According to him, "Reddit is so big now that without some personalization, it's just not relevant. Or even worse, it just doesn't work."
The fact that every user previously saw the same thing is cited as a drawback. Personally, having the option to view Reddit neutrally and then log in for more personalization seems like the more logical option.
He also cites data scraping as a reason for the change.
Reddit had previously restricted access to unknown bots and crawlers in order to curb the onslaught of AI training scrapers, but with some exceptions like the Internet Archive.
Later, they decided to block the Internet Archive anyway because AI bots were scraping from the Wayback machine instead of directly from Reddit.
Then, they announced they would be closing public access to their API and RSS feeds.
They restricted access to old.reddit.com to only logged-in users in the same announcement.
You also may have noticed an increase in annoying popups asking you to download the Reddit app on mobile, something they've been doing for years at this point.
This announcement now brings that restriction to the main site. It's almost refreshing to see a CEO being so forthright that they want to be able to use your data to serve you personalized ads:
It will make it easier to adapt to emerging regulations around the world, and of course, more users being logged in allows us to deliver more relevant ads. This is better for business outcomes, but it's also better for users. A non-targeted ad is just a waste of space for everybody.
It's unclear what effect this will have on alternate Reddit frontends like Redlib.
"Our search referral traffic was down meaningfully in Q3, with the decline accelerating later in the quarter. The biggest impact was on logged-out and web traffic...".
In the most recent update to Apple’s devices, iOS 27.2, the company has introduced a new setting to “Exclude Apps” from Siri AI, addressing a privacy concern raised by digital rights advocates including EFF.
One major concern with new AI features on devices is how those features interact with end-to-end encrypted content, particularly with secure messaging apps. Many AI features require cloud processing, and despite privacy protections engineered into these systems, the content of secure messaging apps may leave a user’s device without their knowledge. That changes the privacy concerns around using those tools. In a perfect world, users would be able to put a barrier up to ensure data from certain apps doesn’t leave the device. A key recommendation was:
You should be able to tell the operating system’s AI to not access an app, even if that comes at the “cost” of missing out on some features. The setting should be straightforward and easy to understand in ways the Gemini and Apple Intelligence controls currently are not.
At launch, the settings to control Siri AI’s app access behavior were pretty confusing. You had to toggle several options to block Siri AI off from accessing an app, or disable Siri AI entirely. Turning off Siri AI and reverting to Siri Classic is, for now, still a good option if you’d prefer to use the older version.
The most recent update is far more clear and does more to protect your data. And, just as expected, it comes at the cost of some features. That’s a good thing, actually. The features not working shows that the new setting is effective.
Here’s how to add apps to the exclusion list, once you’ve updated to 27.2:
Open Settings > Siri > Excluded Apps
Tap “Add Apps” and select any apps you’d like to add to the exclusion list
Now Siri AI cannot access the contents of the app. Excluding an app also means you may lose some features. For example, if you exclude the Apple Messages app, you will no longer be able to have Siri AI read or respond to messages for you. Even the “onscreen awareness” feature, where you invoke Siri and ask it for information about what you’re currently looking at, will not work anymore. For example, if you exclude Signal, you cannot invoke Siri and ask it to discern any information in the Signal app. You’ll just get these messages:
What’s the State of This on Android?
This update from Apple is also a good excuse to check in on the process on Android. It has improved a little, but is not as straightforward as Apple’s new settings, and lacks the ability to set the screen context feature per-app. But you do have some control over what Google's Gemini can access:
Tap your user photo, then Settings > Personal Intelligence > Connected Apps (or visit this link https://gemini.google.com/apps)
Revoke access to any apps you do not want Gemini to have access to
Image: DIW. CC BY
This process seems to work well enough for some data and we like that it’s opt in, but it’s not exactly intuitive. For example, Signal doesn’t appear there because Signal doesn’t support Gemini’s app access feature at all. That means Gemini can’t access the content of Signal directly, which is good.
But Gemini can read notifications if you’ve enabled the “Device Assistance” Connected App (which you likely have, since that also enables basic features, like setting a timer—check under Settings > Personal Intelligence > Connected Apps), and it can use screen context unless you’ve disabled the “Use screen and app data” or “Analyze on-screen text” option in the Gemini/Android Settings which can be accessed via Device controls > Screen context (see screenshot).
Image: DIW. CC BY.
These two features may access the contents of the Signal app or notifications, if you choose to use them. We’d prefer a more hard-lined approach that reduces the chances of user error here: Google should give users the ability to turn these features off per app.
Apple clearly understands that some users want stronger controls over what Siri AI can and cannot access. However, operating systems could go further by offering the option to only use “on device” AI features, similar to what Samsung offered with its Galaxy AI. We’re happy to see this change and think all operating systems need to consider similar controls moving forward.
Image: Andy Wang - UnsplashWith the release of iOS 27.2, Apple has introduced the option to submit a selfie for age estimation as an option to comply with age verification laws in certain regions.
The feature uses an age estimation AI model to determine if you're an adult or not. Apple says the age model runs locally on your device or with Apple's Private Cloud Compute, so theoretically neither Apple nor any third party should have access to your selfie.
To confirm that you're an adult, your selfie is analyzed using age-estimation models that run both on-device and on Private Cloud Compute, which extends the security and privacy of your Apple device into the cloud. The results are combined on your device. When your selfie is analyzed on your device and on Private Cloud Compute, it isn't accessible to anyone, not even Apple. Once your age is confirmed, your selfie is deleted and isn't retained in any form.
Previously, you could verify your age if your Apple account was old enough to meet the age requirements, by having a credit card attached to your account (debit cards don't work), or by scanning your passport, driver's license, or government ID.
All but the first method have their privacy problems: providing credit card details means giving identifiable information (although Apple already requires you to give payment information in order to download even free apps, so it's not much different than what most people already have to do).
Scanning your ID can expose sensitive personal documents to third parties. The online messaging platform Discord famously had a data leak of around 70,000 IDs from a third party they used to verify ages from ID photos.
Selfies can suffer from wildly differing effectiveness and security. The age verification in Discord was hilariously defeated using the in-game photo mode in Death Stranding.
The effectiveness depends entirely on how good the age estimation algorithm is, and there will always be a false-positive and false-negative rate.
Poorly-implemented selfie verification can have disastrous privacy consequences as well. A firm that handles age verification for companies like Roblox and ChatGPT, Persona, leaked their database of selfies and it was discovered over 269 checks were performed on faces, including if they look "suspicious."
It seems like Apple's version is much better in that regard, definitely better than having to send sensitive documents off to a third party.
If you live in Australia, Brazil, Singapore, South Korea, the UK, or Texas (United States), you'll have to verify your age, but if you're not from one of these regions you won't have to worry about it for now.
For many, the internet is feeling less secure these days, thanks to generative artificial intelligence (AI) tools making it easier than ever to exploit hidden security flaws.
Last week’s PHP incident is a great example. PHP is one of the main technologies that run in the background, supporting more than 70% of the websites we use every day. A critical vulnerability prompted many organisations to take their websites offline to secure them.
The national cyber security agency, Australian Signals Directorate, is also warning of rapidly evolving cyber threats. It issued more than 4,400 notifications about potentially malicious cyber activity in 2025–26, almost 80% more than the previous year.
In the wrong hands, AI tools can threaten the underlying systems the internet relies on, outpacing many organisations’ capability to patch them.
With all this on the horizon, it’s reasonable to ask: could failures similar to the PHP issue become widespread? Worse, could the internet itself be brought down?
Is there an off switch for the internet?
First, let’s establish there’s no big switch that turns the internet off. Why? Because the internet is not just one big box of technology. It’s not like your smartphone or TV that you can power on and off.
Instead, the internet is a global network of computers and other devices connected to each other, and it supports a collection of services.
Think of the applications you use every day, from browsing social media to sending emails or banking. For these services to run, computers use network infrastructure to exchange data. For example, when you look at a website hosted on a server in the United States, data travels between your computer or smartphone and that server through network connections.
These connections may use physical cables that run between continents to connect networks together, as well as wireless links (such as wifi) and satellites.
This network is like the roads between Melbourne and Brisbane. One road may be blocked, but there will usually be alternative routes, although there may be some travel interruptions or delays.
Australia’s submarine cable connections. Includes active cables and cables under construction. Cropped from TeleGeography’s 2026 map.CC BY-SA
Losing access to one internet system doesn’t necessarily mean losing access to others. But what happens when many of these systems depend on the same underlying technology?
These are known as shared dependencies. Think, for instance, of how we use Google or Microsoft accounts to access school, university or workplace services. A failure in the shared sign-in system could prevent us from accessing email, Word documents and online learning platforms at the same time.
What an internet outage would really look like
A complete internet blackout is highly unlikely, given its underlying infrastructure.
Interruptions to specific services, on the other hand, are both plausible and likely to continue to increase. If there was a cyber attack on healthcare systems, for example, a clinic might continue consultations but Medicare claims might be delayed.
A transport or banking app might be unavailable due to security risks, while trains could still run and card payments continue to work, assuming these services were not affected, as well.
Patching or recovery from cyber incidents can range from routine repairs to systems or equipment, to investigating compromised systems, which may involve complex digital forensic work.
The reach of an outage depends on which shared systems fail and whether alternatives are available. The examples below show how widely some digital services and technologies are used, and how a failure could affect our lives.
Selected services that rely on widely used shared technology. Sources checked October 2026.CC BY-ND
Preparing before something goes wrong
All this shows that the better we plan for interruptions to online services, the more resilient we can be.
For organisations and businesses, that means having a well-prepared and tested incident response plan. This plan would include clear criteria for when a system must be isolated or a service taken offline, alongside arrangements for maintaining essential operations, and a recovery plan.
The key is preparation, so that any service outage follows a pre-planned response rather than having to act in the moment. This can reduce the risk of a single vulnerability turning into a disaster.
How can I prepare for online service outages?
For users, the same principle applies. Preparedness is essential, and it starts now by identifying the services, apps or tools that would disrupt our lives or businesses if they became unavailable.
1. Keep essentials offline
Store important contact numbers, photos, receipts, booking details and essential documents such as medical prescriptions securely so you can access them even without an internet connection.
2. Identify alternatives
Find other ways to communicate, access your data, make a payment or complete an essential task if your usual service is unavailable. For example, if you normally sign in to a website through Google or Microsoft, check whether it offers another sign-in method and set it up, too. For payments, keep a physical card and a small cash reserve rather than relying entirely on your smartphone wallet.
3. Set up and test
Prepare backup arrangements and check that they work. For example, switch off your internet connection and open your saved documents to confirm they’re available locally, not just when you’re connected to the cloud. Many services rely on multi-factor authentication. Where available, generate backup sign-in codes and store them securely offline.
The internet itself is very unlikely to fail completely. But the individual services we all depend on are far more vulnerable. Whether an interruption becomes a brief inconvenience or a prolonged crisis depends on how well we prepare in advance – before anything goes wrong.
As online retailers and delivery networks race to shorten transit times, investing heavily in micro-fulfillment centers and gig-economy courier fleets, speed remains a key battleground in e-commerce. Yet, despite the industry's push toward near-instant fulfillment, consumer demand for same-day delivery varies considerably and remains a minority preference in most major markets.
According to data from Statista Consumer Insights*, the United States leads other major markets in terms of consumer appetite for ultra-fast delivery, with 36 percent of online shoppers stating they want to receive their orders on the same day. Brazil, Australia, Canada and the UK follow closely behind, while urgency is notably lower in continental Europe and parts of Asia. Only 27 percent of shoppers in France, 22 percent in Germany and 15 percent in Japan consider same-day delivery an important factor when shopping online. While free and fast delivery remains a key priority for online shoppers, same-day turnarounds go beyond most consumers’ expectations.
*Note: Country samples ranged from 1,700 to 8,600 respondents aged 18–64, surveyed between October 2025 and September 2026.
Nearly two-thirds (64%) of AI users have bought from a brand they’d never heard of until an AI tool mentioned it, according to new research.
The findings emerged in a survey of 2,000 Americans who have used an AI tool or assistant for a personal task in the last three months, according to the data by We are Talker.
Seven in 10 (70%) said they have discovered a brand, product or service for the first time because an AI tool recommended or mentioned it. Of those, the majority (91%) went on to buy or use something from one of those brands.
That results in nearly two-thirds of all AI users (64%) having made a purchase from a brand AI first put on their radar, rising to 83% of Gen Z.
Those recommendations also stick. Two-thirds (66%) feel confident that they remember the brands AI recommends to them well afterwards.
Half (51%) would consider a brand they’d never heard of if AI strongly recommended it over one they already knew, rising to 64% for millennials. The results also suggest AI enters the buying journey early.
Asked when they first used AI during their most recent AI-assisted purchase, respondents most commonly said “learning about the topic” (19%), ahead of researching specific options (17%) and getting ideas or inspiration (16%).
Tim Haslam, CEO of We Are Talker, said: “AI isn’t just helping people find information. It’s starting to shape decisions and it’s doing that earlier than many brands recognize.
People are turning to it while they’re very much still learning about a topic and working out their options. That means AI can influence which brands make the cut before someone has even visited a website, read a review or even formed a shortlist.”
AI can just as easily de-influence or take a brand off the list. More than two-thirds (68%) said something they learned through AI caused them to rule out a brand or product they were considering, including 87% of Gen Z.
And more than two in five (44%) said information or a recommendation from AI had changed a decision they were originally planning to make, including 59% of Gen Z and 57% of millennials, compared with 25% of boomers.
Among those whose decisions changed, shopping and retail purchases topped the list (27%), followed by food and restaurant choices (24%), health and wellness decisions (24%) and financial choices (22%).
The effects can really show up at the checkout too. Because of AI, 18% said they spent less than they’d planned, and a similar number (17%) switched from one brand or product to another, while 14% decided not to buy anything at all. Meanwhile, 13% said they spent more, a figure that rises to 20% among Gen Z, compared with just 4% of boomers.
When AI does make a specific recommendation, most shoppers seem to end up going with it. Among those who had received one, 81% followed the recommended option at least in part.
Some took it outright (29%), while others partly followed it (24%). Three in 10 researched it further before choosing it anyway (28%) and just 6% ignored it entirely.
AI now sits alongside long-established influences on what people buy. Among respondents open to using AI in purchase decisions, 73% rated AI recommendations as very or somewhat influential. That’s close behind friends and family (76%) and customer reviews (78%), and ahead of social media influencers (63%) and Reddit or online forums (60%).
Influence on purchase decisions
All
Gen Z
Google or search results
81%
74%
Customer reviews
79%
80%
Professional reviews
78%
78%
Recognized experts
76%
79%
Friends and family
76%
77%
Brand websites
75%
79%
AI recommendations
73%
80%
News and media
69%
80%
Social media influencers
63%
73%
Reddit or online forums
60%
74%
When asked how often AI had played a role in their purchasing decisions in the last three months, 21% of AI users said every day, rising to nearly a third of millennials (32%) and 27% of Gen Z.
Nearly half of AI users (48%) turn to it several times a week or more when deciding what to buy, rising to almost two-thirds of Gen Z and millennial users (64% each). Just 17% said AI had played no part in their purchasing in the past three months.
The results form part of We are Talker’s ‘Consideration, Trust, Choice’ report examining how AI is impacting consumer decisions.
Tim Haslam, CEO of We Are Talker, added: “AI can introduce a brand someone has never heard of, move another out of consideration and influence which one gets chosen.
“That makes the challenge for businesses very different. It’s no longer enough simply to be visible. You need enough credible, independent evidence for AI to understand why your brand deserves to be considered and recommended. Brands that build that authority can win customers they may never previously have reached. The ones that don’t may never even know they were excluded from the decision.”
Recruiting teams can spend hours copying profile details, searching for contact information, and repeating follow-ups. Automation can reduce that repetitive work, but a faster list is not necessarily a better shortlist. Outdated profiles, narrow search criteria, and unreviewed messages can spread through the workflow just as quickly as accurate information.
The practical challenge is deciding where software helps and where a recruiter needs to check the evidence. Start with one vacancy, a small test group, and clear rules for what happens before a candidate receives a message. The following steps make that division easier to manage.
Separate discovery, contact research, screening, and communication. Each task has a different success measure. Finding more profiles may help discovery; it says little about whether those people meet the vacancy's requirements. Agree with the hiring manager on the experience the role needs and the evidence that would support it.
A platform for automated talent sourcing can help recruiters search professional profiles, find contact details, and organize candidate records. Those functions are useful inputs to a hiring workflow. They do not establish that someone is qualified, available, or interested. Write down which outputs require a person to check them before the next step starts.
2. Test the search on a small sample
Start with twenty or thirty results and read them before saving hundreds more. Check whether titles, skills, locations, and seniority match the brief. If a search for a security engineer mainly returns physical-security roles, revise the query. If relevant people use several different titles, add those alternatives rather than relying on one familiar label.
Also examine who the search may overlook. A degree requirement, exact employer list, or rigid tenure filter can exclude people with comparable experience. Ask the hiring manager which filters reflect actual job needs and which are convenient shortcuts. Keep a record of changes so another recruiter can understand why the pool widened or narrowed.
Compare each result with the same written role criteria.
Use job-title alternatives and adjacent experience where relevant.
Remove duplicates before counting the size of the pool.
Record unresolved questions instead of converting missing information into a rejection.
3. Check identity and employment before contact details
A profile database may contain a previous title or employer. Cross-check the person's current professional profile, company biography, or recent work history before contacting them. When sources disagree, mark the record for review. Do not assume the newest-looking interface contains the newest information.
A usable email address answers a different question from a relevant work history. One concerns the contact channel; the other concerns the person and role. Record the source and date for both. This distinction becomes particularly useful when data moves into an applicant tracking system, where an imported record can otherwise look more certain than the evidence supports.
4. Put review gates into the workflow
The Recruitment process covers more than discovering people: it also includes assessing applications, interviews, and hiring decisions. Define how sourced profiles enter that wider process. For example, require a recruiter to confirm role relevance before adding someone to an outreach list, then require a response or completed application before moving them into screening.
Use simple statuses such as Needs Review, Ready for Contact, Replied, and Closed. Give each record an owner and a next action. Avoid a rule that moves every new profile directly into a message sequence. A mistaken job match or stale employer reference is easier to correct before the candidate sees it.
Review a small set of profiles against the vacancy criteria.
Verify identity, current employment, and the intended professional contact channel.
Approve the message and the reason for approaching each person.
Assign replies to a recruiter who can answer questions.
Close the thread when someone declines or asks for no further contact.
Stage
Software contribution
Human check
Discovery
Search and organize profiles
Relevance to the role
Contact research
Find available channels
Identity and current employment
Outreach
Schedule approved messages
Accuracy and replies
5. Keep automated messages specific and restrained
Draft the first message around the actual opportunity: responsibilities, location, working arrangement, and a brief reason the person's experience appears relevant. Check any statement about their work before sending it. An automatically generated compliment that misstates a project can damage trust before the role is even discussed.
For example, a recruiter hiring a logistics analyst could refer to verified experience in inventory reporting, share the role's scope, and ask whether the person wants the full brief. Avoid suggesting that software has already determined they are a perfect fit. Use a limited follow-up plan, and make sure replies pause further scheduled messages and reach a person.
6. Measure quality and correct the weak step
Track relevant profiles, qualified conversations, and progression to assessment alongside the time spent on research. A larger contact list or higher send count can hide weak targeting. Sample records regularly to check for stale employment details, duplicate messages, unsupported screening notes, and unresolved candidate questions.
Review problems at their source. Poor matches call for better search criteria; incorrect contact details call for fresh verification; unanswered replies call for clearer ownership. Change one part of the workflow at a time so the team can tell whether the adjustment helped. Automation earns its place when the resulting records and conversations are easier to trust, not simply when more steps run without a click.
