"Falsehood flies," wrote Jonathan Swift 300 years ago, "and truth comes limping after it, so that when men come to be undeceived, it is too late; the jest is over, and the tale hath had its effect." And the good Dean Swift was not even on Twitter.

Perhaps he would have been intrigued by the announcement of the latest hi-tech wheeze intended to counter the age-old problem of the rapid dissemination of falsehood, calumny and plausible gibberish: a social media lie detector. Researchers at the University of Sheffield have been given an EU grant to develop an automated system to grade the reliability of online assertions and rumours, so we all know what to believe.

On the internet, mendacious or just careless untruths have as much chance of going viral as perfectly respectable documentary images of kittens reclining on cushions – as those who alluded on Twitter to the false allegations about Lord McAlpine learned to their heavy cost. But surely, optimistic techno-utopians think, there must be a way to retain the good side of electronic media (the swift and global distribution of information and debate) while suppressing the dark side?

The ambition for a computerised system that will be able to sort truth from lies on Twitter and elsewhere is certainly in tune with our modern algorithm fetish, the curious assumption that software should replace human judgment wherever possible. But algorithms are designed by humans, and their workings depend on the human assumptions that were baked into them. So what are the assumptions governing the social media lie detector?

According to Sheffield's news release, the system will aim to "classify online rumours into four types: speculation, such as whether interest rates might rise; controversy, as over the MMR vaccine; misinformation, where something untrue is spread unwittingly; and disinformation, where it's done with malicious intent". Not content with that, it plans to "automatically categorise sources to assess their authority, such as news outlets, individual journalists, experts, potential eye witnesses, members of the public or automated bots. It will also look for a history and background, to help spot where Twitter accounts have been created purely to spread false information."

On the face of it, these look like good ideas. But one can immediately think of examples where they would have resulted in misleading judgments. Authoritative news outlets, for example, have sometimes been complicit in spreading state disinformation (see the New York Times' sorry record with the pre-Iraq war weapons of mass destruction claims). And sometimes, of course, despite what one lone rebel says is correct, institutional authorities may disagree (see Galileo). The risk, then, is that such systems will encourage their users to place more faith in mainstream sources simply because they are official. In the future, if such automated systems of truth grading are taken seriously by powerful institutions or the state itself, then the people designing the algorithms will essentially be an unelected cadre of cyber thought police.

Perhaps you think that's a small price to pay for being able to tell, from your browser's Truthiness Dashboard™, whether that person on your timeline really did just witness a dog skateboarding past his window wearing giant Beats headphones. Actually, the main problem as I see it is that the proposal doesn't go far enough, and that its categories of bad thoughts don't sufficiently thin-slice the tsunami of frankly undesirable communication on the internet. After all, factual claims are only one genre of social media post among many, which also include foodist oneupmanship, excruciating puns and expressions of desire for shiny objects.

I hope that when the academics have got their magical lie detection machine working properly, they will then extend its capabilities to warn users sternly against reading the face-meltingly banal pseudoinspirational effluvia of Paulo Coelho, the preeningly obsessive rantings of nu-atheists, and the passive aggressive narcissism of writers who only ever retweet praise for themselves. Eventually the system will be so perfect and foolproof that we'll be free to ignore almost everything on Twitter and go back to believing everything we read in the Guardian.