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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.
You search for a hotel, explore an idea for a mobile app or ask ChatGPTa question. You might even save the idea in Gmail to share with your partner later. And then, you see a related ad on Facebook or YouTube. It can feel like digital companies are listening to your conversations.
But you are not the only one. Many consumers experience this too. A 2024 eMarketer survey found that nearly 80% of US consumers had noticed ads based on their previous internet searches. A 2019 Pew Research Center survey also found that 64% of US adults had seen ads they believed were based on their personal data.
Websites and apps can share your activity with advertising companies, which use this data to predict your interests. But the data they collect can have consequences beyond advertising. In some cases, companies may also have to hand over user information in response to legal requests.
Here's how companies collect and use your data and what you can do to protect your privacy.
Companies can combine these signals to build profiles of people's interests and likely behavior. Someone who searches for flights and visits hotel websites may be classified as a potential traveler. Advertisers can use that profile to reach people who are more likely to buy their products.
Data brokers gather information from different sources and compile profiles for sale or sharing. In a 2024 enforcement case, the FTC alleged that a data broker used location histories to classify people into groups such as “parents of preschoolers” and “wealthy and not healthy”. This shows how location data collected through apps can reveal sensitive details about people's lives.
How Big Tech Uses the Data
For companies such as Google and Meta, personal data helps power targeted advertising. Advertisers pay to reach selected audiences, and platforms use their advertising systems to decide which ads to show. The platforms can earn revenue from this process without selling advertisers a person's name or complete personal profile.
Information can also move between services. A retailer using Meta Pixel, for example, may send website activity to Meta for advertising. Meta announced in June 2026 that it would also use activity businesses already shared with it to personalize Facebook and Instagram feeds and AI responses, extending its use beyond ads. Meta said the change involved using existing data for additional purposes, not collecting new data.
Google's privacy policy, effective October 16, 2026, offers another example. Users may allow services such as Search or Gemini to access information from Gmail, Drive and Google Photos to personalize their experience. Search may use permitted data to personalize content, including ads.
Google says it does not show personalized ads based on content from Gmail, Drive or Photos unless users choose to make data from those services available to other Google services that support personalized ads. Its Gmail help page also says Gmail does not scan or read messages to select ads shown inside Gmail.
These examples show how data shared across services can be used for purposes beyond the one for which people originally provided it.
What AI Adds to the Picture
People share more than browsing activity with AI tools. Depending on the product and its terms, companies may use submitted content to provide answers, improve services or train models.
Advertising is a separate use. OpenAI's privacy policy, updated in 2026, describes sharing limited information with selected marketing partners to promote its products on third-party websites and apps. Its explanation of this practice says partners may receive identifiers linked to a browser or device, an IP address or a hashed email or phone number, along with basic commercial or browsing information. OpenAI says it does not share conversations or uploaded content with those partners for this advertising purpose.
As AI becomes part of everyday life, users may need to consider not only what they share with these tools, but also how the companies behind them use data to reach and influence them.
What Can Users Do?
Read a service's privacy policy and terms before signing up, especially if you plan to share private conversations, documents, photos or location data. Check them again when the company changes its policy or introduces a new AI feature.
Look for sections on data collection, advertising, sharing, retention, AI training and account deletion. Ask practical questions: What information does the service collect? Why does it need it? Can it share that information with advertisers or other businesses? How long does it keep the data? Can you delete it?
Then compare the answers with your own expectations. If an app requests access to contacts, photos or location that it does not need for its main function, deny that permission where possible. If a company's data practices go beyond what you accept, consider limiting what you share, disconnecting linked services or switching to an alternative with clearer privacy practices. Before deleting an account, check what happens to stored content and retained data.
You can also reduce some forms of tracking with Privacy Badger which is a free browser extension that blocks many third-party trackers.
These measures have limits. Tracker blockers cannot prevent all data collection inside apps or accounts, and private browsing does not make you invisible to websites. Data brokers may also retain information gathered from other sources. Treat these tools as ways to reduce exposure, not erase your digital footprint.
Why This Is a Public Issue
Concern about these practices is widespread. In the US, a March 2026 Verasight survey found that 75% of 1,000 adults were concerned about their online activities being tracked, while a separate Pew Research Center survey found that 71% said increased AI use would make their personal information less secure. Similarly, in a survey of 2,074 UK adults conducted in May 2026, consumer group Which? found that 72% were worried about the security of their data, 71% about how businesses collect and use it, and 69% about how businesses use AI in ways that affect them.
Individual choices can reduce exposure, but they cannot solve every problem. People can share reliable privacy guidance, ask companies to explain unclear practices and raise concerns with consumer groups, regulators and policymakers. When a company's data practices affect large numbers of people, public pressure can help push for clearer rules and meaningful choices.
Personal data helps fund online services and can make products more useful. But people need to know what they are sharing, how companies use it and who else can access it. Without clear answers, they cannot make an informed choice about the services they use.
Big tech companies make the devices we use and the operating systems that come on them. They also make the bulk of the default software that comes packed into those operating systems. But spend even just a few moments of your time looking, and you’ll find a variety of other options out there.
Using software made by big tech companies means having to accept their decisions about subscription prices, features, and which apps they keep available. Subscription prices always seem to rise, new features often fail to solve the problems real users face, and companies may abandon your favorite small app/feature if it does not make enough money to justify keeping it. But you are not stuck with the default options: you can find and choose replacements that are more (or less) feature-rich, more privacy preserving, and developed by passionate individuals concerned with making good software, rather than just making money.
Here are some alternatives to consider, covering web browsers, search engines, email, office software, and design tools.
Browsers
Have you been using the default browser that came with your phone or laptop since you got it? Chrome, Safari, or Edge? There are plenty of alternatives, and many of them are just as good as the defaults, if not significantly better. Switching to a better, more trustworthy browser can give you improved privacy and usability settings right out of the box, without having to reconfigure everything yourself. The only thing you might need to do is transfer your bookmarks to the new browser. Most browsers make this easy with export and import options.
For a starting point, some browsers that focus on preserving privacy, to various degrees, include: Brave, DuckDuckGo, Firefox, and Vivaldi. And of course, the Tor Browser, which might not be an everyday browser for many people, but is always good to keep around. Remember, you can have multiple browsers installed! It can be helpful to use one browser for work and another for personal matters.
Image: DIW
You can also consider browser extensions such as Privacy Badger, which helps block trackers that follow your activity across websites.
Web Search
Google might be a verb for some age groups, but not for everyone. To further decouple the term from searching the web, you can start using another search engine. Yes, there are other ways to search the web beyond Google, and many of them are more privacy preserving, more customizable, and less ad-ridden. Many also give you more power over how AI features work or whether you use them at all.
DuckDuckGo is the most popular privacy-preserving alternative, but others, like Brave Search and Startpage may be worth checking out. If you’re willing to pay a subscription fee, Kagi is another option. Whichever you choose, be sure to take the time to change the default search option in the browser you just installed so it always uses your new choice.
Email
While it dominates the email landscape nearly as much as its search engine, Google’s Gmail is not the only email provider out there. In fact, there are tons of options to choose from, many that’ll have special feature sets that better suit your needs. Leaving Gmail can be a tall order if you’ve had your account for decades, but other platforms might offer stronger privacy, fewer (or truly optional) AI features, and more powerful automation.
Proton Mail, Tuta, and Mailbox all offer some level of end-to-end encryption for your emails, at least with email sent between users of the service (like a Proton Mail user emailing another). They all also claim to provide additional privacy in one way or another, like blocking trackers and not including ads. If the security features aren’t interesting to you, other options, like Fastmail, provide powerful email tools outside of the big tech ecosystem.
Office Suites
Microsoft Office is a massive and expensive suite of software. Regardless of whether you pay for a subscription or just a one-time fee for one specific application, there may be free or cheaper one-time payment options that better suit your needs without draining your pocketbook.
If you’re looking for direct alternatives to Microsoft Office that work similarly, two of the more popular choices are both free and open-source: LibreOffice and OnlyOffice.
If you need something with more collaborative features, alternatives like Proton and CryptPad offer more private document collaboration across a series of different file types and formats. If it’s just text documents you collaborate on, others, like Ellipsus, try to replicate the feeling of Google Docs without the AI features and Big Tech surveillance apparatus.
If you just need a word processor, there’s a zillion to choose from, typically designed around different philosophies or use-cases. There are paid apps like Scrivener and Ulysses for authors, and iA writer or Calmly for those looking for something minimal without going fully over to a plain bones text editor.
As for notetaking, Obsidian is one of the most comprehensive apps out there and often suggested as a replacement for apps like OneNote. But if it doesn’t suit your needs, you have tons of alternatives, including end-to-end encrypted options like Standard Notes, NotesNook, and Joplin, and minimalist apps like Simplenote and Bear.
Design Software
Adobe’s Creative Suite is an expensive subscription, and one that not everyone really needs. Replacing Adobe’s suite of software can be difficult, but it’s not impossible. Some of the alternatives can be a little rough around the edges, but they can get the job done, and perhaps most importantly, they are often free to use.
Some free and open-source alternatives to various parts of Adobe’s suite include:
While not open-source, other free options include Davinci Resolve (Premier) and Fusion (After Effects). If you’re looking to replace a large chunk of software collection in one go, Affinity Suite (Canva) may also be worth a look. It’s not open-source, but it is free.
This is by no means an exhaustive list of every type of software that exists. There are many, many other available options. But this will hopefully be useful to start your journey. For more ideas, check out sites like Privacy Guides, The Verge, Wired, and just aboutevery techsiteout there. AlternativeTo can also be a useful place to start your search.
Note: Based on an article originally published by the Electronic Frontier Foundation (EFF)and republished under the Creative Commons Attribution (CC BY) license, with edits for clarity and readability.
