logo
How Companies Secretly Use Your Data to Charge You More : Surveillance Pricing Explained

How Companies Secretly Use Your Data to Charge You More : Surveillance Pricing Explained

Geeky Gadgets5 hours ago

What if the price you pay for everyday goods and services wasn't just about supply and demand, but about you—your income, your location, even how long you hesitated before clicking 'buy'? Welcome to the shady world of surveillance pricing, where companies use your personal data to decide how much to charge you, often without your knowledge. Imagine booking a flight and discovering that someone sitting next to you paid significantly less, simply because their browsing history or zip code made them appear less willing to splurge. This isn't science fiction—it's a growing reality in today's data-driven economy, and it raises unsettling questions about fairness, transparency, and who really holds the power in the marketplace.
In this breakdown, Robert Reich and Lina Khan uncover how businesses are using your personal data—from your geolocation to your online behavior—to manipulate prices and maximize profits. You'll learn about the hidden mechanisms behind these practices, from ride-sharing apps exploiting low phone batteries to test prep companies targeting specific demographics with inflated fees. But it's not just about the tactics; we'll also explore the ethical and legal battles surrounding this controversial pricing model, featuring insights from FTC Chair Lina Khan, a leading voice in consumer protection. By the end, you'll have a clearer picture of the stakes involved—and the steps you can take to protect yourself in this increasingly opaque digital landscape. Are we witnessing innovation, exploitation, or both? Let's examine the evidence. Understanding Surveillance Pricing How Companies Use Your Data
The foundation of surveillance pricing lies in the extensive collection of personal data. Companies gather this information through various channels, including your devices, online activity, and third-party data brokers. The data collected can include highly sensitive details, such as: Your physical location
Income level
Browsing history
Behavioral patterns, such as how long you linger on a webpage or your mouse movements
Geolocation technology plays a particularly pivotal role in this process. For instance, businesses can track your location to assess local economic conditions or demographic trends. A travel website might charge higher prices to users browsing from affluent neighborhoods, assuming they are willing to pay more. Similarly, ride-sharing apps have been known to increase fares for users with low phone battery levels, exploiting the assumption that they are less likely to delay their purchase. These tactics demonstrate how companies use personal circumstances to maximize profits, often at the expense of fairness. Real-World Examples of Discriminatory Pricing
Surveillance pricing has led to numerous examples of discriminatory practices, disproportionately affecting certain groups and communities. Consider the following real-world scenarios: Test preparation services charging higher fees in areas with larger Asian populations, based on assumptions about demand for academic success.
Internet service providers offering slower speeds at the same price in economically disadvantaged neighborhoods, perpetuating digital inequality.
In critical situations, the consequences of such practices can be even more severe. Imagine being charged inflated prices for essential items like medicine during a health emergency or for last-minute travel to attend a funeral. These examples highlight the darker side of surveillance pricing, where profit motives overshadow ethical considerations and consumer well-being. Such practices not only exploit vulnerable populations but also deepen existing inequalities. The Shady World of Surveillance Pricing
Watch this video on YouTube.
Dive deeper into AI business with other articles and guides we have written below. Ethical and Legal Challenges
The ethical implications of surveillance pricing are profound and far-reaching. By exploiting personal data, companies can manipulate prices in ways that disproportionately harm vulnerable populations, raising critical questions about fairness and accountability. Should businesses have the right to use your data in this way? And what safeguards should exist to protect consumers?
In response to these concerns, some governments and regulatory bodies are beginning to take action. Efforts to address the ethical and legal challenges of surveillance pricing include: Proposed legislation in several U.S. states to ban surveillance pricing outright.
Stronger privacy laws aimed at limiting data collection and usage.
Investigations by the Federal Trade Commission (FTC) into companies suspected of discriminatory pricing practices.
These measures aim to create a more equitable and transparent marketplace. However, progress remains uneven, with many companies continuing to operate in legal gray areas. The lack of universal regulations leaves consumers vulnerable to exploitation, underscoring the need for stronger enforcement and global cooperation. How You Can Protect Yourself
As a consumer, there are practical steps you can take to reduce your exposure to surveillance pricing and regain some control over your personal data. Consider implementing the following strategies: Use private browsing tools or virtual private networks (VPNs) to limit the data companies can collect about you.
Clear your search history and cookies regularly to minimize your digital footprint.
Install privacy-focused browser extensions to block online trackers and prevent companies from monitoring your browsing habits.
These measures can help you safeguard your privacy and reduce the likelihood of being targeted by discriminatory pricing practices. While these tools are not foolproof, they represent an important step toward protecting your rights in an increasingly data-driven marketplace. Balancing Innovation and Ethics
The practice of surveillance pricing highlights the ongoing tension between technological innovation and ethical responsibility. On one hand, this approach allows businesses to maximize profits by tailoring prices to individual consumers. On the other hand, it often does so at the expense of fairness, transparency, and consumer trust. The growing awareness of these issues has led to increased calls for stronger regulations, ethical data usage, and greater transparency in pricing practices.
Addressing the challenges of surveillance pricing requires a collaborative effort. Policymakers must enforce regulations that protect consumers from exploitation, while businesses should adopt ethical practices that prioritize fairness and transparency. As a consumer, staying informed and taking proactive steps to protect your privacy can help mitigate the impact of these practices. The ongoing debate underscores the need for a careful balance between technological advancement and the protection of consumer rights in the digital age. By fostering accountability and ethical standards, society can ensure that innovation serves the greater good rather than perpetuating inequality.
Media Credit: Robert Reich Filed Under: Technology News, Top News
Latest Geeky Gadgets Deals
Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.

Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

How I Learned to Stop Worrying and Love the Chaos: By Erica Andersen
How I Learned to Stop Worrying and Love the Chaos: By Erica Andersen

Finextra

time31 minutes ago

  • Finextra

How I Learned to Stop Worrying and Love the Chaos: By Erica Andersen

Or: AI Confessions from the Keynote Stage What a difference a year makes. Last week, I found myself on stage at the AI World Congress, delivering a keynote to a room full of people who, twelve months ago, were probably telling anyone who'd listen that AI was going to solve world hunger, cure cancer, and maybe even fix their corporate expense reporting system. Fast forward to today, and suddenly the same crowd is singing a very different tune. The other keynotes? Let's just say they weren't exactly radiating optimism. Microsoft, Oracle, IBM, McKinsey – the usual suspects – all took their turns at the podium to essentially deliver variations of the same message: "AI is hard. Our systems don't work. Where's our ROI? We're confused and slightly terrified." Welcome to reality, folks. Population: everyone who actually tried to implement AI. The Crybaby Chronicles Now, I don't want to sound unsympathetic. Actually, scratch that – I do want to sound a little unsympathetic, because here's the thing: we've been saying this for years. AI isn't just software with a fancy hat. It's a completely different beast that doesn't play by the rules you learned in your Computer Science 101 class. These organizations have been approaching AI with a software-only mentality, and then acting shocked – shocked! – when things don't work like a traditional database query. AI systems can fail silently, which is terrifying if you're used to error messages that actually tell you what went wrong. They can also appear to work perfectly while delivering completely suboptimal results, which is like having a GPS that confidently directs you to drive into a lake. You need an engineering mindset for this, not just a software background. Engineers understand that things break, that systems are unpredictable, and that you need multiple layers of protection. Software developers expect deterministic outcomes. AI gives you probabilistic chaos with a side of randomness. The Economics of Artificial Anxiety And then there's the money talk. Suddenly, everyone's discovered that running AI costs actual money. Who could have predicted this shocking development? Here's the part that's going to make you really popular at parties: I think the big providers – AWS, OpenAI, the whole gang – are actually undercharging right now. They're burning through investor cash to grab market share. At some point, someone's going to want to actually make money, and those token costs are going to climb faster than a venture capitalist chasing the next unicorn. But here's where it gets interesting. People are obsessing over ROI, but that's like asking what the ROI was on the first spreadsheet. Imagine trying to explain to someone in 1979 why they should pay for VisiCalc: "Well, it's like a calculator, but bigger, and it has boxes, and you can change one number and other numbers change too." Revolutionary? Absolutely. Easy to calculate ROI? Not so much. The smartR Approach: Embrace the Chaos When we work with our AI models in our company we've taken a different approach. We think of AI as Assistive Intelligence, not Artificial Intelligence. The difference isn't just semantic – it's philosophical. Instead of trying to replace humans entirely (which is where most people run into trouble), we augment what people can do. Think of it like having a really powerful, occasionally unpredictable intern. They can do things that are hard or impossible for humans, but you still want someone experienced reviewing their work. The magic happens when you combine AI's raw computational power with human judgment and oversight. You get something better than the sum of its parts, and you avoid the nightmare scenario of full automation gone wrong. The Great Data Myth Here's another sacred cow we love to slaughter: the obsession with perfect data. Everyone keeps saying, "Your data needs to be in order first." Well, guess what? Your data is never going to be in order. It's a beautiful, chaotic mess, and it always will be. But here's the plot twist: AI can actually help clean up your data. Instead of spending months (or years) trying to organize everything perfectly, you can curate good datasets from your underlying messy data. The AI helps with the cleanup process. It's like having a really good research assistant who can find the good stuff buried in your filing cabinet of chaos. People telling you that you must clean all your data first are essentially creating expensive busy work. They're making money off your preparation anxiety while you could be getting actual results. The VC Reality Check We also love talking about how the AI engine companies probably aren't going to make the ridiculous money that had VCs practically hyperventilating with excitement. This technology is going to become commoditized and open source. The real money – the sustainable, long-term money – is going to be made by people who figure out how to actually apply AI to solve real business problems. That doesn't mean these foundational tools aren't important. They're absolutely crucial. But making venture capitalist levels of money from them? That's going to be tough when you're competing against open source alternatives and every tech giant on the planet. Privacy: The Chickens Come Home to Roost And speaking of uncomfortable truths, let's talk about privacy. We've been banging this drum for years, pushing private and secure models while everyone else was happily shipping their data off to the big cloud providers. Well, surprise! A US court just told OpenAI they can't delete anything – including conversations people specifically asked to be deleted. Your private messages might become public evidence. But surely GDPR will save us, right? Wrong. America doesn't care about your data protection laws. The worst that will happen is some European official will impose a token fine, give a stern speech about showing those big bad tech companies who's boss, and then everything will continue exactly as before – except now your private information is scattered across the web like digital confetti. If you want your data to stay private, don't send it outside your ecosystem. It's that simple. The Swiss Cheese Philosophy Here's the thing about AI mistakes: they're inevitable. Sometimes what looks like a mistake to one person is actually a reasonable answer to someone else. That's just the nature of the beast. I like to think of AI implementation using the Swiss cheese model. Imagine multiple layers of cheese stacked on top of each other, each representing a different safety barrier. The holes represent vulnerabilities. No single layer is perfect, but together they provide protection. AI should be another layer or two of cheese in your stack. It adds protection and capability, but it shouldn't be the only layer. If you're going to remove human oversight, you better be absolutely confident that the AI can't break your entire system. The Bottom Line We're constantly upgrading our proprietary platform, based on real-world implementation experience. We've learned that AI works best when you stop trying to make it behave like traditional software and start treating it like the powerful, unpredictable tool it actually is. The companies crying about AI being hard aren't wrong – it is hard. But it's hard in an interesting way, like switching from building model airplanes to building rockets. Sure, they both fly, but rockets require understanding thrust vectors, fuel chemistry, and the uncomfortable reality that sometimes they explode spectacularly on the launch pad. The physics are different, the margin for error is smaller, but when you get it right, you're not just flying – you're reaching orbit.. The key is approaching it with the right expectations, the right safeguards, and maybe a sense of humor about the whole thing. Because if you can't laugh at the absurdity of trying to teach machines to think while we're still figuring out how human thinking works, you're probably taking this whole AI revolution thing a bit too seriously. And trust me, after listening to those other keynotes, we could all use a little less seriousness and a lot more practical wisdom about what AI can actually do – and what it definitely can't. Written by Oliver King-Smith, founder and CEO, smartR AI

Trump says he has group of ‘very wealthy people' lined up to buy TikTok after pushing back ban of social media app
Trump says he has group of ‘very wealthy people' lined up to buy TikTok after pushing back ban of social media app

The Sun

time36 minutes ago

  • The Sun

Trump says he has group of ‘very wealthy people' lined up to buy TikTok after pushing back ban of social media app

DONALD Trump said he has a group of "very wealthy people" lined up to buy TikTok. The President has repeatedly delayed a ban blocking the app to allow more time for negotiations with the Chinese owners - who have consistently refused to sell. 4 4 4 Trump has fought to force TikTok's owners to sell to an American party since his first term. A bill signed last year makes it illegal to operate under the current Chinese owners, but the ban has been delayed three times and the company has always refused to sell. However, on Sunday, Trump told Fox News a "group of very wealthy people" wanted to purchase the app from ByteDance. He said: 'I think I will need China['s] approval, and I think President Xi will probably do it." Without revealing any details, he added: 'I'll tell you in about two weeks.' The closest to Trump has come to barring American users from TikTok was at the time of his inauguration in January this year. A ban took effect on January 19, and TikTok shut itself down an hour before that, telling users "you can't use TikTok for now" due to a "law banning TikTok". But around 12 hours later it came back online after conversations between the US and China behind the scenes - and was available for download again three weeks later. Since then, Trump has delayed the ban three times - twice for 75 days and most recently by 90 days on June 17. The eventual ban or sale is required by a "foreign adversary" bill signed in March 2024. ByteDance challenged the Act, but it was upheld by the Supreme Court in January. It's not clear how much TikTok would sell for, with valuations ranging from $30billion to $300billion. Rumoured new American owners have included major tech companies like Microsoft and Oracle. The wildly popular YouTuber Mr Beast, real name Jimmy Donaldson, said in January he would submit an official offer for TikTok through and investment group led by Jesse Tinsley. Steve Mnuchin, Trump's treasury secretary during his first term in office, also floated the idea of purchasing the app with a group of billionaire investors when the ban was first passed. Amazon reportedly made a last-minute bid to purchase TikTok three days before the second recent extension in April. The bill banning continued Chinese ownership of TikTok cites concerns about national security risks. ByteDance was initially given nine months to sell-up - and that expired in January. However, the company has repeatedly insisted it will not give-up the app. It said in April: "ByteDance doesn't have any plans to sell TikTok." Reports circulated that it was considering a sale of the app without the key algorithm, but these were denied. The owners insisted: "Foreign media reports of ByteDance selling TikTok are not true." 4

Donald Trump says 'very wealthy group' has agreed to buy TikTok in the US
Donald Trump says 'very wealthy group' has agreed to buy TikTok in the US

Sky News

time37 minutes ago

  • Sky News

Donald Trump says 'very wealthy group' has agreed to buy TikTok in the US

Donald Trump has said the US government has found a buyer for TikTok that he will reveal "in about two weeks". The president told Fox News "it's a group of very wealthy people", adding: "I think I'll probably need China approval, I think President Xi will probably do it." TikTok was ordered last year to find a new owner for its US operation - or face a ban - after politicians said they feared sensitive data about Americans could be passed to the Chinese government. The video app's owner, Bytedance, has repeatedly denied such claims. It originally had a deadline of 19 January to find a buyer - and many users were shocked when it "went dark" for a number of hours when that date came round, before later being restored. However, President Trump has now extended the deadline several times. The last extension was on 19 June, when the president signed another executive order pushing it back to 17 September. Mr Trump's latest comments suggest multiple people coming together to take control of the app in the US. Among those rumoured to be potential buyers include YouTube superstar Mr Beast, US search engine startup Perplexity AI, and Kevin O'Leary - an investor from Shark Tank (the US version of Dragons' Den). Bytedance said in April that it was still talking to the US government, but there were "differences on many key issues". It's believed the Chinese government will have to approve any agreement. President Trump's interview with Fox News also touched on the upcoming end of the pause in US tariffs on imported goods. On April 9, he granted a 90-day reprieve for countries threatened with a tariff of more than 10% in order to give them time to negotiate. Deals have already been struck with some countries, including the UK. The president said he didn't think he would need to push back the 9 July deadline and that letters would be sent out imminently stating what tariff each country would face. "We'll look at the deficit we have - or whatever it is with the country; we'll look at how the country treats us - are they good, are they not so good. Some countries, we don't care - we'll just send a high number out," he said. "But we're going to be sending letters out starting pretty soon. We don't have to meet, we have all the numbers." The president announced the tariffs in April, arguing they were correcting an unfair trade relationship and would return lost prosperity to US industries such as car-making.

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store