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a single Californian company making decisions over what counts as hate speech and profanity for some of the world's most popular sites without anyone ever examining whether its own algorithms might be biased or excessively conservative

It's the proliferation—not elimination—of intermediaries that has made blogging so widespread.  The right term here is “hyperintermediation,” not “disintermediation.”

this marriage of big data and automated content moderation might also have a darker side, particularly in undemocratic regimes, for whom a war on spam and hate speech—waged with the help of domestic spam-fighting champions—is just a pretense to suppress dissenting opinions. In their hands, solutions like Impermium's might make censorship more fine-grained and customized, eliminating the gaps that plague “dumb” systems that censor in bulk

Just imagine what kind of new censorship possibilities open up once moderation decisions can incorporate geolocational information (what some researchers already call7 “spatial big data”): Why not block comments, videos, or photos uploaded by anyone located in, say, Tahrir Square or some other politically explosive location?

For governments and corporations alike, the next frontier is to learn how to identify, pre-empt, and disrupt emerging memes before they coalesce behind a catchy hashtag—this is where “big data” analytics would be most helpful. Thus, one of the Russian security agencies has recently awarded a tender12 to create bots that can both spot the formation of memes and to disrupt and counter them in real-time through ”mass distribution of messages in social networks with a view to the formation of public opinion.” Moscow is learning from Washington here: Last year the Pentagon  awarded a $2.7 million contract to the San Diego-based firm Ntrepid in order to build software to create fake multiple online identities13 and “counter violent extremist and enemy propaganda outside the US.” “Big data”-powered analytics would make spotting such “enemy propaganda” much easier.