Privacy on Facebook: A Real Solution or a Hyped Trend?

“The Future is Private”

This isn’t the first time we’ve heard hype-inducing language at a tech conference — whether it’s about artificial intelligence or the newest mobile camera. Usually, I try to disregard this fluff when I watch the 5-minute summary videos. But when I heard Mark Zuckerberg prophesize this forthcoming trend about privacy at the most recent F8 conference, it didn’t sit well in my stomach.

Does our society suddenly care more about privacy now than it did before? Should we put privacy in the same basket as other technology trends?

Source: Engadget

Later in the conference, Zuckerberg announced that Facebook would focus more on “private” features such as groups, events, messaging, and stories — emphasizing security features like end-to-end encryption. Beyond Facebook, other tech companies such as Google are presenting new privacy tools in their applications¹. I’ve always considered privacy an essential ingredient in technology — so much so that it should be embedded without any tech conference bragging. And for a while, no one did brag about it. So why is it currently being treated as an upcoming trend?

The Privacy Paradox

While people say they want privacy, they usually don’t act accordingly. The Privacy Paradox describes the discrepancy between a consumer’s attitude towards privacy and their actual behavior. As indicated in Barth et. al.’s literature review², “While users claim to be very concerned about their privacy, they nevertheless undertake very little to protect their personal data.” There are several theories that attempt to explain this phenomenon. Some researchers claim that consumers make rational decisions on a case-by-case basis — the benefits of (free) personalized online experiences outweigh the risks of information disclosure. Others believe that consumers have incomplete information and simply don’t know the risks.

One experiment³ done at the University of Chicago explored how behavioral biases are involved in the Privacy Paradox. In the experiment, subjects at a mall were given the choice between a free $10 gift card or a $12 gift card. If subjects chose the $12 gift card, their card number and name were recorded by the researchers. Although all subjects had the same choices, they were presented the choices in one of four ways. Some subjects were given the $10 card first and then were offered the $12 card — or vice versa. Other subjects saw both cards, but the researchers switched the ordering of the $10 and $12 card.

Source: Acquisti, Alessandro et. al. ³

The results are very surprising. Although all participants had had the same two options, their decisions varied greatly based on the way the choices were presented. Evidently, the Privacy Paradox is a result of more than rational cost-benefit analyses.

What does this behavioral paradox say about the current hype around privacy? Clearly, the typical consumer’s actions regarding privacy are dependent on the environment in which this action takes place — even when the consequences of that action are held constant. While privacy has generally been a concern for technology companies, these efforts are seemingly more valued by the consumer in situations where the risks are more apparent. This may explain why, after incidents like the Cambridge Analytica scandal and Tim Cook’s privacy letter, many companies are now jumping on the privacy hype train.

Beyond the Individual

Although our actions regarding privacy are extremely dependent on behavioral influences, there are real systemic threats of mass personal information disclosure beyond just individual identity theft. In this section, I will focus on the systemic threats of price discrimination and network polarization.

Price Discrimination

Price discrimination (or personalized pricing) is a differential pricing scheme where the producer changes the price of a product for each consumer based on their willingness to pay. With more personal information being disclosed on the internet, producers are able to access a profile attached to an individual’s identity, including age, gender identity, browser history, and even personal interests. As a result, producers can predict the price each individual is willing to pay for their product and personalize the price accordingly. According to the Chicago Booth⁴, companies like ZipRecruiter are already using this scheme to increase profits.

A diagram I created using images from Miller and John Chuang

The diagram above illustrates how personalized pricing allows producers to maximize their surplus while removing all consumer surplus. Evidently, customers can be paying more than they think when they are disclosing their information.

Network Polarization

Right now we are experiencing one of the most politically polarized moments in history. Much of this can be attributed to personal information disclosure and the dissemination of viral misinformation on social networks. With access to personal information, agents in a network can make their content viral my targetting the most susceptible individuals. A study⁵ published in PLOS One simulated social networks exposed to viral misinformation. In the simulation, each node (user) was randomly assigned a point on a 1-dimensional political spectrum. They measured “polarization” as the standard deviation of all the user’s political opinion from the average. At each time step, a group of users was exposed to some “biased” information, which would more likely spread if a connected user shared the same bias. Also, each user’s political views would update based on the new misinformation. They measured the “virality” as the percent of nodes this misinformation reached on the network.

Source: Törnberg, Petter et. al. ⁵

As shown in the results, network polarization was positively correlated with misinformation virality — until the network was so polarized that information stopped spreading across the network. Also, polarization and virality were both increased when the misinformation was seeded at nodes with the same bias.

Evidently, as misinformation is targeted towards people with the same biases, we see increased virality along with increased network polarization. This exposes a conflict of incentives. While the advertiser wants to maximize virality, this can ultimately lead to a polarized network — and we’ve seen the risks of those.

Conclusion

I am unsettled by the privacy hype train that Facebook is currently promoting. On the surface, it appears like Zuckerberg is overhauling the company’s business model to prioritize the privacy of the individual. At the very least, their promotion of privacy can lead to a heightened awareness amongst users, which can help close the discrepancy of the privacy paradox. But is this heightened awareness just a tactic to win back the trust of consumers?

It is currently unclear whether Zuckerberg’s plan really tackles deep systemic issues, such as price discrimination and polarization, which can arise from information disclosure on social networks. For instance, while the new focus on groups may seem beneficial, more clustered social networks are shown to increase polarization⁵. In general, given the conflict of incentives between producers and consumers around these issues, government regulation is likely the best route to promote true privacy.

[1] Dave, Paresh; Google plans new browser tools on privacy, ad transparency. https://in.reuters.com/article/us-alphabet-google-browser/google-plans-new-browser-tools-on-privacy-ad-transparency-idINKCN1SD2PU

[2] Barth, Susan et. al.; The privacy paradox — Investigating discrepancies between expressed privacy concerns and actual online behavior — A systematic literature review. https://www.sciencedirect.com/science/article/pii/S0736585317302022

[3]Acquisti, Alessandro et. al.; What Is Privacy Worth?https://www.cmu.edu/dietrich/sds/docs/loewenstein/WhatPrivacyWorth.pdf

[4] Wallheimer, Brian; Are you ready for personalized pricing? http://review.chicagobooth.edu/marketing/2018/article/are-you-ready-personalized-pricing

[5] Törnberg, Petter et. al.; Echo chambers and viral misinformation: Modeling fake news as complex contagion. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6147442/

I’m an optimistic human who enjoys writing, adventures, and other optimistic humans. johnleyden.com

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