by Lisa Herzog, Stephan Jonas, Philipp Kellmeyer, Karola Kreitmair, Michael Klenk, Eva Kuhn, and Kai Spiekermann
Facebook, Amazon, Apple, Microsoft, and Google, often referred to as Big Tech, know more about you than your closest friends and family. They know who you are talking to and what you are talking about, what you are buying or are thinking of buying, how much money you have, and what your fears and desires are. What a few years ago may have sounded like a dystopic vision, is today a reality of our online life (our ‘onlife’). In this setting, even Facebook’s plans of introducing their own currency, Libra, does not seem out of the ordinary.
While users of digital technology operate on an implicit assumption of trust this trust is misguided. The trouble is not merely that a given company records user behaviour within its own digital ecosystem but that companies integrate virtually all of our online activities from a plethora of sources, thereby making us transparent and vulnerable to observation, manipulation, and exploitation.
Tracking personal data streams has become the dominant business model of the web. What this means is that when a service is ‘free’ on the web, your data is the payment that sustains the business model. In this internet of humans, in which personal data have become the most valuable commodity, we have no meaningful control over who has access to such information and no power to amend, correct, or withdraw it. In light of recent push-back against online privacy violations, e.g. Facebook losing users and facing a $5bn fine after the Cambridge Analytica scandal, as well as a growing public animosity towards big tech (so-called tech-lash), companies have learned that user privacy concerns could hurt their revenue streams and thus should not be ignored. Unsurprisingly, most proposals by tech representatives intended to address these issues involve a thorough revision of privacy laws and some form of making money by selling privacy privileges, such as subscription models that permit the use of apps without providing data or enduring ads.
One could argue that people concerned with their privacy should just stop using online services altogether. But given the pervasiveness of interconnected digital technology, this is unrealistic.
Recent proposals referred to as rebel tech promote the use of alternatives for many of our online activities, such as messaging, browsing, blogging, and social media. But with the immense user base of big tech services, simply switching to an app that prioritizes privacy may be impractical for most individuals if most of their online contacts remain with big tech. Fortunately, rebel tech also comprises effective open-source and cost-free tools that would allow users to use big tech services while protecting online privacy. For instance, Virtual Private Networks (VPN) allow users to hide their location and unique IP address, preventing tech companies from linking different interactions to one identity. What’s more, it is no longer the case that only tech-savvy hackers can employ such rebel tech. Some measures that allow users to protect privacy are already widely in place. For example, most browsers allow private modes which block some tracking techniques. Other initiatives envision a more radical reconfiguration. Tim Berners-Lee’s SOLID project, for instance, intends to decentralize the web, and blockchain technology is explicitly designed to enable privacy. However, tech companies have a strong interest in preventing rebel tech from working well, making these tools harder to use than necessary. For instance, Netflix, Hulu, and Amazon block access to VPN users.
Given big tech’s position of power and control over our online activities, effective governance and regulation is required to make rebel tech an accessible and viable alternative for all users. For example, blocking of VPNs should only be permitted if identification is required for security purposes, such as in online voting or to prevent crime. Furthermore, companies should only be permitted to collect as much data— both with respect to the extent and the granularity—as is necessary in order to provide the marketed service. For instance, a navigation app needs to know your intended destination, but not your shoe size or the content of your private conversations. The default should be data sparsity, i.e. that only the minimum amount of data required for a service should be aggregated. One way to ensure this principle at the regulatory level would be to shift the onus of justification onto the companies. Companies must show that detailed data profiling of individual users—rather than, for example, representative samples for group level analyses—are required for the company’s product.
State support for rebel tech initiatives would enhance their legal, public, and economic clout. It would allow them to become a serious option to keep the data collection of big tech in check. The goal is not total anonymity on the web, it is to strike a balance between privacy and security. One legitimate way to strike this balance is by empowering users so that their interests can compete with the business interests of big tech. One of the most effective tools for empowerment is education. Simply promoting the use of rebel tech tools may have the benefit of educating users on how their data is used and the value it has for companies. Understanding how much companies gain from individually targeted advertising may have an enlightening effect on internet users and make them question the trust they have in big tech.
Ultimately, however, a progressive and sustainable remodelling of the current incentive structure of the web should aim at upending the power asymmetry between those companies that control the web and the (often vulnerable) users who participate in perpetuating this status quo by paying with their personal data (as well as their time and attention). Rebel tech will not be sufficient however, to free users from digital serfdom. With state support and a promotion to the public, however, it could pose a real challenge to the dominant business model of big tech.