To be honest, I can’t even remember when I started completely “giving up” on protecting my privacy.

Every time I download a new app and a dozens-of-pages-long “Privacy Policy and User Agreement”—with font so small it looks like a line of ants—pops up on my screen, my brain refuses to even read it. Instead, I rely on muscle memory to tap “Agree and Continue” with pinpoint accuracy. It’s not that I haven’t thought about resisting; it’s just that I’m fully aware of the reality: as long as I’m using a smartphone, my commute routes, the bizarre questions I search for during late-night emo sessions, how long I hesitate on a product page before swiping away… all of this has already turned into lines of code, sitting quietly in the databases of internet giants.

Academia has given this state of mind a pretty apt name: “Privacy Fatigue,” or “Digital Resignation.” It’s not that we don’t care anymore; it’s just that in an era where you’re forced to provide your location just to scan a QR code and order food at a restaurant, chasing “absolute privacy” for an ordinary person is too exhausting—and frankly, unrealistic. Andrejevic (2019) argues that contemporary automated media environments embed users within systems of pervasive data collection and monitoring, making participation in these processes a condition of everyday life.

The reason we click “Agree” over and over again is actually because we’ve tacitly accepted an exchange: I’ll generously hand over my personal data, and you’ll use it to analyze and understand me. In return, you have to make your service smoother, more intuitive, and more considerate.

Sounds like a fair trade, right?

But reality has slapped us hard in the face. Lately, I’ve become increasingly aware that platforms holding massive amounts of data tore up this invisible contract a long time ago. They took our privacy, but instead of upgrading their services to be “smarter for you,” they turned that “smartness” into a tool to “exploit you.”

In this post, I don’t want to talk about high-brow academic theories. I want to talk to you about the most hidden and infuriating form of exploitation in the digital age: “Big Data Price Discrimination,” also known as algorithmic price discrimination. I also want to talk about why, in the face of this systemic calculation, fighting alone as an individual is almost useless—and why we must call for the state to step in.

Everything is “Datafied”: A Soured Deal

To understand how we’re being exploited, we first need to know what we look like in the eyes of the giants. To them, we aren’t living, breathing individuals; we are “digital labels” pieced together from countless data points. In the context of digital governance, this process is called “Datafication.”

Datafication is more than just typing paper documents into a computer. It refers to tech companies using a vast array of sensors and code to turn behaviors in our lives—things that were originally invisible, intangible, or even seemingly worthless at first glance—into assets that can be tracked, analyzed, and even sold. Crawford (2021) argues that AI systems are fundamentally dependent on extractive processes, including the large-scale collection of human behavioral data, which are deeply tied to existing structures of power.

Here’s a somewhat scary but absolutely true example: you think the platform only knows your name and phone number? Think again. They know you’re a worker who habitually orders takeout on Friday nights; they know you almost never compare prices for flights and always pick the most convenient time; they even know your phone battery is at 5%—meaning you’re panicking and want to get in a car as soon as possible, making you far less sensitive to price.

We traded our privacy for convenience, but platforms turned that ‘smartness’ into a tool to ‘exploit’ us.

Initially, this deep datafication did give us a taste of convenience. Music apps could accurately guess that song you were thinking of, and the homepages of shopping apps were filled with the very items you were planning to buy. We were once immersed in this “Cyber-Utopian” illusion, thinking it was only natural to trade privacy for convenience. Nissenbaum (2018) argues that privacy is grounded in “contextual integrity,” meaning that information should flow according to context-specific norms. However, digital platforms often repurpose user data beyond its original context—for example, for commercial purposes—thereby violating these norms and undermining trust.

But the calculus of capital is always about profit maximization. Once platforms monopolized our data, they discovered that the greatest commercial value of this data wasn’t in “keeping you happy,” but in calculating your breaking point. Thus, the most disgusting byproduct of the internet age was born: big data price discrimination.

The Algorithmic Black Box: From “Customized for You” to “Precision Harvesting”

You’ve surely had one of those “what on earth?” moments: you and a friend are sitting at the same table, opening the same takeout app at the same time, ordering the same meal from the same shop to the same address. The result? You, the “prestigious veteran member” of the platform, are actually charged several dollars more than your friend who rarely uses the app. Calling rides, booking hotels, and buying flights are the worst-hit areas.

This isn’t a system bug; it’s carefully designed “Algorithmic Price Discrimination.”

In the world of traditional economics, the cost for a merchant to sell the same item to different people at different prices was sky-high because it was difficult to know each customer’s bottom line. But in the digital age, “Algorithms” have taken over pricing power. Pasquale (2015) highlights how opaque algorithmic systems concentrate power in the hands of those who control data, while leaving individuals with little insight into how decisions about them are made, thereby reinforcing structural imbalances.

Based on that dense web of “datafication” I mentioned earlier, algorithm completes a precise “worth assessment” of you in the blink of an eye. It calculates how much you crave this item, knows you’re too lazy to check other platforms for prices, and finally, firmly sets a “highest price that you’ll begrudgingly accept while the platform earns the most.”

Algorithms act as cold, heartless, and tireless harvesters.

This is what’s truly chilling. Because of our loyalty and frequent use, we contribute the most daily data to the platform; and the platform, in turn, uses the data we handed over to forge a sickle specifically to harvest us.

Faced with this blatant exploitation, those “scam-prevention guides” online are always teaching us: “Clear your phone cookies frequently!” “Remember to use incognito mode!” “Better yet, use several phones and switch between accounts!”…

Honestly, this is a ridiculous form of “victim-blaming”.

In the face of today’s billion-level computing power and “Algorithmic Black Boxes” as complex as a maze, asking ordinary people to protect themselves with these minor tricks is like asking us to fight an alien mothership with spears and swords. Algorithms are extremely opaque; you can never know exactly which hundreds of hidden data dimensions are being used to price you. When you, as a mere consumer, try to fight a massive system composed of top engineers and supercomputers, the information gap and power imbalance between you have already destined you to lose. Suzor (2019) argues that major digital platforms establish and enforce their own rules, often with limited transparency, leaving ordinary users with little power to challenge these systems.

If individuals can’t protect themselves, what should be done? This is where “Digital Governance” must be brought into the conversation.

The State’s Heavy Blow: A “Dimensional Strike” Against Algorithmic Exploitation

When technological wrongdoing has become a systemic structural problem, expecting tech giants to find their “conscience” and stop through industry self-regulation is like “asking a tiger for its hide.” At this stage, the only entity qualified to go toe-to-toe with these giants is the state apparatus and public policy. Flew (2021) suggests that the expanding societal role of digital platforms necessitates stronger public policy intervention, as these systems can no longer be governed solely through private or self-regulatory mechanisms.

This is the heartening news I especially want to share with you today. On April 10, 2026, a major new regulation jointly formulated by several Chinese government departments—“the Rules on Pricing Practices of Internet Platforms“—officially came into effect (Issued in December last year).

It is no exaggeration to say that this is an absolute bellwether in the field of global Digital Governance. Faced with increasingly brazen big data price discrimination, this policy didn’t play games or beat around the bush; it went straight for the algorithm’s power plug and drew a clear red line.

Several points in the new regulation hit right where it hurts:

1. Trictly Prohibiting “Targeted Pricing”: It is written in black and white that platforms are not allowed to use technical means like algorithms and data to implement unreasonable differential treatment in transaction conditions and prices based on consumers’ preferences and transaction habits.

2. Breaking the “Scamming Veterans” Rule: It specifically emphasizes that platforms cannot use a consumer’s new or old status or frequency of consumption as an excuse to set unfair prices. The phrase “old customers should receive better treatment” has finally moved from a moral appeal to a hard legal requirement.

3. Restricting “Forced Financial Exploitation” Data Collection: The policy strikes at the source, further restricting platforms from excessively soliciting unnecessary privacy data just to implement price discrimination.

Why should we applaud this policy so vigorously? Because it has completed a crucial reversal of the burden of proof and power.

In the past, if you felt you were being overcharged for a ride, you were extremely weak as a consumer. You had to painstakingly take screenshots, find a friend’s phone to record screens simultaneously for comparison, and talk your head off trying to “prove” to customer service that you were being scammed. And the platform? A flippant “prices vary due to real-time supply and demand” was enough to brush you off.

But now, the logic of Digital Policy has fundamentally changed. The state has stepped in and told those tech giants in no uncertain terms: “You are not allowed to do this.” With the compulsory force of law, the policy has closed the massive power gap that every ordinary person faces when confronting algorithmic beasts. It announces a new consensus to the entire digital age—that a consumer’s surrender of privacy must never become a permit for a company to practice price discrimination.

Guarding Our Digital Bottom Line

Let’s go back to where we started at the beginning of this post.

It’s foreseeable that for a long time to come, we will still live in a highly datafied society. We probably still won’t be able to completely avoid the loss of some privacy, and we’ll likely continue to click “Agree” just for the sake of convenience. However, in terms of mindset, it’s truly time for us to wake up from the numbness of “Digital Resignation.”

The next time you find that the price for the same hotel, the same takeout, or the same flight is inexplicably more expensive for you than for others, please realize: this isn’t back luck, nor is it some damn “routine business strategy”—it is a direct violation of your legitimate digital rights. Goggin et al. (2017) argue that digital rights are central to ensuring that individuals can participate in digital society in ways that are fair, inclusive, and respectful of fundamental human rights.

As ordinary people enjoying digital life every day, we need to pay attention and call for more good policies like the Internet Platform Price Behavior Rules to be implemented in various countries and regions. In the vast hacker empire of algorithms, the power of an individual is simply too small. Only sound laws and strong state governance are our final shield against being “precisely harvested” in the cyber world.

Data can be used to serve us better, but it must never be used to exploit us. This is the bottom line that every one of us in the digital age must hold onto.

References

Andrejevic, M. (2019). Automated culture. In Automated media (pp. 44–72). Routledge.

Crawford, K. (2021). The atlas of AI: Power, politics, and the planetary costs of artificial intelligence. Yale University Press.

Flew, T. (2021). Regulating platforms. Polity.

Goggin, G., Vromen, A., Weatherall, K., Martin, F., Webb, A., Sunman, L., & Bailo, F. (2017). Executive summary and digital rights: What are they and why do they matter now? In Digital rights in Australia. University of Sydney. https://ses.library.usyd.edu.au/handle/2123/17587

National Development and Reform Commission [国家发展和改革委员会]. (2025, December 17). 互联网平台价格行为规则 [the Rules on Pricing Practices of Internet Platforms]. https://www.ndrc.gov.cn/xxgk/zcfb/ghxwj/202512/t20251217_1402474.html

Nissenbaum, H. (2018). Respecting context to protect privacy: Why meaning matters. Science and Engineering Ethics, 24(3), 831–852. https://doi.org/10.1007/s11948-015-9674-9

Pasquale, F. (2015). The need to know. In The black box society: The secret algorithms that control money and information (pp. 1–18). Harvard University Press.

Suzor, N. P. (2019). Who makes the rules? In Lawless: The secret rules that govern our digital lives (pp. 10–24). Cambridge University Press.

The Wall Street Journal. (2022, April 21). Dynamic pricing, explained: Why prices are changing more often | WSJ Price Index [Video]. YouTube. https://www.youtube.com/watch?v=vTWhsgs3ZRA

Unsplash. (n.d.). A brain over CPU represents artificial intelligence [Photograph]. https://unsplash.com/photos/a-brain-over-cpu-represents-artificial-intelligence-sv2SuTA-9ug

Unsplash. (n.d.). LinkedIn login screen with “Join now” option [Photograph]. https://unsplash.com/photos/linkedin-login-screen-with-join-now-option-RIXGU0veAps