Incognito Mode Isn’t Doing What You Think It’s Doing
Private browsing, for one thing, may be giving holiday shoppers a false sense of privacy
3 min
There is an urban myth that says online shoppers who doggedly search for certain items on the web get tagged by algorithms that then cause them to see higher prices than others shopping for those same items.
The solution for many people: They choose private mode on their web browsers, believing that cloaking their identity can help them get better prices.
But while such “private” settings as Google Chrome’s Incognito mode or Apple’s Safari private browsing mode do offer some benefits, getting a better price isn’t one of them.
“All these private modes do for shoppers is basically erase your search history from the device you’re on and prevent the browser from using your cookies to see your browsing activity across different sites,” says Benjamin Barrontine, vice president of executive services at 360 Privacy, a company that specialises in protecting clients’ digital identity. This is a great feature if you share a laptop with your children and you want to hide the presents you’re purchasing for them, but companies’ pricing is typically based on a number of factors—timing, location, how much an item in that category’s company paid to rise to the top of your search results—that don’t have to do with you personally or how often you search for a product.
A Google spokesperson confirms that cookies, or information stored on your device, are remembered in the current Chrome browsing session while in Incognito mode but then deleted immediately after closing out the session. If you return in Incognito mode to make the purchase, the websites will see you as a new user and won’t remember what you left in your cart. You essentially have to start your search anew, but with the benefit of blocking anyone who shares that device from seeing what you were researching.
Ultimately, experts say, private modes give shoppers a false sense of anonymity and a feeling that they are gaming the system, when all they are doing is hiding past searches. “You should know that your internet-service provider and even your network administrator at work, if you’re searching on a work device or network, may still see what you’re searching,” says Barrontine. “Private mode is not so private, after all.”
In fact, the big tech companies most likely know with near certainty who it is that is doing this supposedly secret searching, even in private mode.
“When you go on to Amazon.com in private mode and search for a bathrobe, even if you’re not logged into the site, Amazon is 99.9% sure of who you are because of the digital fingerprint they’ve developed for you over time,” says Ken Carnesi, chief executive and co-founder of DNSFilter, a software firm that protects companies from attacks at the domain name system level. That’s because Amazon would still know how you arrived at its site based on the link you clicked, your IP address, your ZIP Code, many of your preference settings and loads of other device-specific attributes. A company spokesman declined to comment.
The tech firms may not know that it is specifically you scouring their sites, but they’d know the search came from your home, which operating system you’re using, which language is your default and other details that point to you.
“That’s why, even when you’re not in private mode later on, if you didn’t close out that private window, you may still see bathrobes being pitched to you,” Carnesi says. “All the tracking is likely still passed through to the company who paid for the ad you clicked on.”
Contrary to popular belief, pricing for highly fluctuating, big-ticket items isn’t impacted by private searches, says Kevin Williams, an associate professor at the Yale School of Management who recently published a paper looking at airlines’ methods of dynamic pricing. Williams says in the case of plane tickets, “Airline pricing doesn’t take into account any of your personal information except location,” as in the country of origin. Using a virtual private network (VPN) can obfuscate your device’s physical location, and may turn up a better fare, but might require some trial and error, Williams says.
There are some additional benefits for shoppers to using private mode, beyond hiding your searches from prying eyes. The search bar won’t auto-fill with prior searches, so you can start anew every time you open a new private window and not fall down an old rabbit hole. You can keep your searches private on a public device or borrowed computer. And you can use a credit card that will later be wiped so your children won’t have access to funds without permission.
For true privacy, consider shopping through a search engine like Brave.com, which doesn’t ever track your searches or your clicks. “Unlike with other search engines, you and your data are not the product here,” Carnesi says. And your partner will never know about that bathrobe you forgot to actually purchase.
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Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
Technology and semiconductor shares fell sharply as investors questioned the debt financing the AI infrastructure boom and confronted higher rates and Chinese competition.
4 minA sharp technology sell-off has exposed a new anxiety on global markets: whether the enormous borrowing behind the artificial-intelligence infrastructure boom can generate sufficient returns as interest rates rise and Chinese competition intensifies.
The artificial-intelligence investment boom has powered technology shares, semiconductor manufacturers and data-centre operators to extraordinary heights. Last week, investors were given a reminder that much of this expansion is being built with borrowed money.
The technology-heavy Nasdaq Composite fell 4.5 per cent over the week ended October 16, its weakest performance since late June. Semiconductor shares suffered an even deeper correction, with the Philadelphia Semiconductor Index losing about 11.4 per cent.
The selling spread quickly through global markets. Micron Technology fell 14.6 per cent over the week, while South Korea’s Samsung Electronics and SK Hynix dropped approximately 18 per cent and 24 per cent respectively.
This was more than a routine bout of profit-taking. Investors were reassessing three interconnected risks: higher interest rates, the rapidly expanding debt burden attached to AI infrastructure and the prospect of stronger competition from Chinese memory-chip manufacturers.
The debt behind the AI build-out
Artificial intelligence requires a physical infrastructure network of enormous scale. Data centres must be built, advanced processors purchased, power supplies secured and cooling systems installed before customers begin generating meaningful revenue from them.
Technology companies are increasingly supplementing their own cash with corporate bonds, syndicated loans, equipment leases, private credit and project-level financing.
JPMorgan describes the emerging funding model as a combination of conventional corporate borrowing and project finance tied to individual data-centre assets. In Australia, the Reserve Bank estimates that syndicated loans accounted for approximately three-quarters of data-centre financing during 2025 and 2026 to date.
The numbers are becoming large enough to affect broader credit markets. The Federal Reserve Bank of Dallas has cited Wall Street estimates suggesting AI-related investment-grade bond issuance could approach US$300 billion in 2026 alone.
That borrowing is not automatically problematic. Debt can be an efficient way to finance long-lived infrastructure when future revenue is sufficiently predictable. The concern is that AI technology, customer demand and computing economics are changing much faster than the repayment schedules attached to the assets.
A data centre financed today may carry debt for years. Investors must therefore make assumptions about future utilisation rates, electricity prices, chip performance, customer concentration and the amount businesses will ultimately pay for AI computing.
When interest rates rise, those assumptions become less forgiving.
Inflation changes the calculation
September’s US inflation data intensified the pressure. Consumer prices increased 3.7 per cent over the year, ahead of market expectations and up from 3.4 per cent in August.
The hotter reading reduced confidence that interest rates would fall quickly and pushed bond yields higher. That matters particularly for companies whose valuations depend on profits expected well into the future, as well as highly leveraged infrastructure operators that may need to refinance.
CoreWeave has emerged as a closely watched test case. The specialist cloud-computing company has accumulated substantial debt and lease obligations to build AI capacity, while relying on a concentrated group of large technology customers.
Its shares fell sharply during the sell-off, while the cost of insuring its debt against default climbed. CoreWeave has argued that its contracted backlog more than covers its obligations and that financial markets do not always understand its business model. Nevertheless, its securities have become a proxy for investor confidence in debt-funded AI infrastructure.
Oracle, another major investor in AI computing capacity, fell 8.8 per cent in Friday trading, while CoreWeave dropped 15.5 per cent.
The question is shifting from how much AI infrastructure can be built to how profitably it can be operated.
China adds another source of pressure
Interest rates were not the only catalyst. Reports of advances by Chinese memory-chip producer ChangXin Memory Technologies raised concerns that lower-cost Chinese products could increase competition across the global semiconductor industry.
Memory chips are essential to AI systems, but the industry is historically cyclical. Periods of tight supply and high pricing can encourage rapid investment, eventually producing oversupply and falling margins.
The prospect of a well-funded Chinese competitor expanding its technological capabilities unsettled investors in Samsung, SK Hynix and Micron. It also demonstrated that AI-related demand does not insulate chipmakers from conventional competitive pressures.
That combination—slower rate cuts, more expensive financing and potentially cheaper supply—challenged the assumption that every company exposed to AI would enjoy continually expanding margins.
A reset rather than the end of the boom
The sell-off does not establish that the AI boom is ending. Demand for computing power remains strong, the largest technology companies continue to generate formidable cash flows and many infrastructure projects are backed by long-term customer contracts.
What has changed is the market’s willingness to overlook the price and financing structure of that growth.
The most resilient companies are likely to be those able to fund investment from operating cash flow, secure long-duration customers and demonstrate that new capacity will earn returns comfortably above its financing costs.
More speculative operators may face greater scrutiny, particularly where debt is expensive, customers are concentrated or expected revenue depends on demand that has not yet materialised.
For Australian investors, the lesson extends beyond US technology shares. Local data-centre operators, infrastructure funds, electricity suppliers and property groups are increasingly exposed to the same investment cycle.
Artificial intelligence may remain one of the defining growth themes of the decade. But last week’s correction showed that enthusiasm for the technology does not eliminate financial discipline.
The next stage of the AI boom will be judged not only by computing power, model performance or demand for chips, but by something more traditional: whether the assets being financed can generate enough cash to repay the money borrowed to build them.
Fact box
Nasdaq Composite: Down 4.5 per cent for the week ended October 16, 2026
Philadelphia Semiconductor Index: Down approximately 11.4 per cent
Micron Technology: Down approximately 14.6 per cent
Samsung Electronics: Down approximately 18 per cent
SK Hynix: Down approximately 24 per cent
US September inflation: 3.7 per cent annually
Estimated 2026 AI-related investment-grade issuance: Approximately US$300 billion
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