Reaching critical mass: does being the first to implement a big data solution guarantee a monopoly?

We hear it all the time: break up Facebook, Google, Twitter, et al. because they have an information “monopoly”. Add the manipulation of their algorithms to serve the ideological agenda of their management, shadowbanning and censoring search results for example, the more reason to break them up for abusing their “monopoly”.

In my prior post, Social media and software are NOT utilities — don’t ask for it to be regulated, I pointed out how unnecessary these services are and should suffer the consequences of a free market. The market just hasn’t waken up.

This article dips a toe into the pool of market psychology metaphysics, and asks whether there is such thing as critical mass for big data (or social media) — a point where the group-think driven algorithms spur group-think in the public psychology, making the users wholly dependent on these algorithms for day-to-day living. A point where the public is unable to use alternative sources because the alternatives don’t have the necessary magnitude of big data backing them up. Besides, why do so many users feel as though Facebook has a monopoly over information when stepping back and looking at the scenario objectively, Facebook clearly does not have any information vital for day-to-day living?

If Facebook users stopped using Facebook, its power to influence others would simply stop. There isn’t a social media platform at the moment with the same amount of users and personal data than Facebook. But would people be unable to live without Facebook or a Facebook clone? No, but like many drug habits, it certainly would feel that way for users if they go cold turkey.

If Google users stopped using Google, would people be unable to live? No, but because many people use several (non-essential) services tied to Google, it would feel like an awful lot of work for them to switch to alternative platforms to keep the same niceties.

Like the over-inflated debt-ridden stock market bubble and Keynesian driven policies, it will take pain and undone extravagance in the interim to go back to a healthy lifestyle away from these “drugs”. Google and Facebook may make a few things more convenient, like finding the most relevant search result and being easily distracted on your phone, but just knowing that the bulk of these social media and search engine algorithms are based on group-think — that is, crowdsourced opinions giving you the most popular opinion of the time, or perhaps a handpicked opinion based on the management’s ideology — users should realize they are not getting the most objective results. They are getting a result that has a significant likelihood of being an argument ad populum: a fallacy derived from group-think that leads to more group-think. They are being fed a result that is psychologically satisfying in the short term but possibly detrimental in the long.

Very few big data solutions are built on top of first principles, that is, solutions where mined data are backed by science, facts and truth, rather than opinions, agendas, human misinterpretations and bad extrapolations. A brilliant chess engine that can learn from millions of grandmaster games and weed out the best moves from the poor moves based on first principles, which is easier to do in chess since there are immediate, measurable, objective results to analyze against, is an example of big data used well. A social media engine like Twitter that weeds out opinions based on popularity and the biases of Jack Dorsey and management (Twitter Moments, e.g.) is big data used poorly.

Until big data solutions built upon first principles and not popularity are primarily employed by the current tech giants, it’s probably safe to say that they do not yet have information monopolies. In reality, they have misinformation monopolies, and to a greater extent after reaching a critical mass of gullible users, they have mind-control monopolies on the public majority trapped in the group-think bubble fueled by biased data.

*     *     *

For a further explanation on why many current big data solutions are subject to heavy bias, see the article: Exploiting the big data monopoly: YouTube, Google and Facebook are vulnerable in ways small startups are not.

If you liked this article, be sure to share, leave a comment and subscribe to the RSS feed. Consider a donation or support my other work.

0 thoughts on “Reaching critical mass: does being the first to implement a big data solution guarantee a monopoly?”

Leave a Reply

Your email address will not be published. Required fields are marked *