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Historically, concerns about over-zealous censorship have focused on repressive governments. In the United States, free speech has been a pillar of our society since its founding. For the most part, government attempts at censorship or speech restrictions receive swift and successful push back. In recent times, however, a new path to censorship has arisen in the form of search engine and social media companies that are building analytically-based censorship algorithms.

These organizations are using analytics to censor speech more aggressively than any past United States governmental effort and are somehow convincing a sizable portion of the population that it is a good thing. This post will outline why using analytics for centralized censorship is a steep and slippery slope and also lay out an alternative that will enable those same censorship analytics to provide people with a choice rather than a dictate.

Where is the Line?

Let’s assume for the sake of argument that we all agreed that censorship was ethical and desired (of course, we don’t all agree on that, but assume we do). Under those terms then we still have to agree on exactly where to draw the line that delineates what should be censored from what should not. Reaching such …

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