Is Facebook Using Public Confusion Over Its Scandal To Monetize User Data Even More?
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The Cambridge Analytica scandal first revealed several weeks ago since has continued to avalanche, with Facebook stock taking a beating, numerous organizations, personalities, and users abandoning the platform, and Mark Zuckerberg himself testifying before Congress for the first time.

Even Steve Wozniak, co-founder of Apple, recently publicly left Facebook, criticizing the company’s business practices as even fellow major technology companies are denouncing Facebook’s actions.

Amid the increasing public outrage, policymaker scrutiny, market reaction, and regulatory threats, Facebook has announced it is implementing a multitude of changes to its data sharing policies with the public intention to purportedly strengthen user privacy and data protections.

Many of these are moves in the right direction and it is clear that Facebook should be making amends for the data policies that led to the Cambridge Analytica events. However some of the changes seem to be in fact continuing Facebook’s aggressive monetization of user data that contributed to the initial scandal, particularly by seeming to exploit general confusion over Facebook’s data mechanisms.

One major change Facebook has recently announced is that it will be changing the way third parties are allowed to use their own data in advertising on Facebook. Specifically, Facebook will be shutting down “Partner Categories” over the next 6 months, thereby no longer allowing third party data suppliers to offer their data to assist with targeting advertising on Facebook.

Facebook made over $40 billion in revenue in 2017, with nearly the entirety coming from advertising. Advertisers are interested in spending money on Facebook because of the micro targeting from user data that gets better results.

Third parties have over the years used other sources of data that they have access to, such as databases for consumers and credit, to then micro-target advertising on Facebook. Facebook allowed these advertisers to interface that data, which may contain attributes proprietary or particularly relevant to that company, with the platform.

While Facebook’s changes on third party data upload policies initially seem like it is a data privacy move, it is easy to see how this fact allows Facebook to increasingly become the sole arbiter of data for use on its platform and therefore increase monetization even more.

Furthermore, Facebook’s data reforms are generally with the seeming intent to restrict other organizations from supplying an alternative to Facebook’s own data. To prevent third parties from providing their own data into Facebook seems to be a restriction in precisely the opposite direction of where the necessary increased protections should be, which is for Facebook’s data on its users flowing outside the company rather than other companies’ information flowing in.

The Cambridge Analytica scandal was primarily a result of Facebook’s own aggressive monetization of its users, its inability to control that data, and the actions of an app developer that took advantage of those vulnerabilities.

The third parties that Facebook is now seeking to punish do not seem to have any fault in the Cambridge Analytica scandal nor cause any clear threats to the Facebook users’ data privacy. Many organizations legally and ethically collect user information from market research and other means and advertisers have in the past used it to supplement their advertising on Facebook, seemingly without incident.

It is ironic that Facebook would consider a “data fix” in the wake of this scandal to be decreasing non-Facebook institutions’ ability to use their own information on the platform, with what appears to be little benefit to user privacy. The only party that stands to gain here is Facebook itself, which would dramatically increase advertiser reliance on Facebook’s own user data.

If this is any indication of Facebook’s overall “data fixes,” it would appear Facebook is simply trying to find ways to extract even more profits off of user data by taking advantage of public confusion regarding data science. Undoubtedly it is an attitude only likely to continue to aggravate policymakers, investors, and users.

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