"The lie flies," wrote Jonathan Swift 300 years ago, "and the truth comes slowly after it," and he means the speed with which a lie spreads. Imagine that at the time Dean Swift wrote it, it didn't exist Twitter.
Researchers from his University Sheffield have managed to get an EU grant to develop an automated system that will control the degree of credibility of online publications in social media.
The internet, we probably know it all, is an environment that thrives everything. From the cruel truth, to fraud and innocent lie. We have seen several times failures to spread like a wave on Twitter. Optimistic researchers probably think there should be a way to maintain the good side of social media, such as the direct and global distribution of information, while at the same time suppressing the dark side.
The ambition for a computer system that will be able to classify truth from the lie on Twitter or elsewhere should definitely have our fetish algorithm, and the strangest thing is that software is going to replace the human crisis. Possible; We know that algorithms are designed by man, and their function depends on the person who made them. So, what are the assumptions that will govern the social media lie detector?
Σύμφωνα με το δελτίο τύπου του Sheffield, το σύστημα θα έχει σαν στόχο να “κατατάξει τις online φήμες σε τέσσερις τύπους: φήμες κερδοσκοπίας, όπως πχ. η αύξηση των επιτοκίων. Διαμάχη, πχ είναι ωφέλιμο το εμβόλιο MMR; Παραπληροφόρηση, όπου κάτι αναληθές αρχίζει να εξαπλώνεται, και παραπληροφόρηση, που γίνεται με κακόβουλη πρόθεση.” Αν κάτι δεν μπορεί να ενταχθεί σε αυτές τις κατηγορίες, σχεδιάζουν μια “automatic κατηγοριοποίηση των πηγών για την εκτίμηση τους.” Πηγές μπορεί να είναι τα ειδησεογραφικά πρακτορεία, μεμονωμένοι δημοσιογράφοι, εμπειρογνώμονες, αυτόπτες μάρτυρες, το ίδιο το κοινό ή αυτοματοποιημένα bots. Θα εξετάσει επίσης την ιστορία και το υπόβαθρο, γνωρίζουμε ότι υπάρχουν λογαριασμοί στο Twitter που έχουν δημιουργηθεί αποκλειστικά για τη διάδοση ψευδών πληροφοριών.”
At first glance, these all seem like very good ideas. But there are immediate examples that would have led to misleading judgments. Authentic agencies news, for example, are sometimes complicit in spreading misinformation (see New York Times with Iraq's alleged nuclear weapons). Sometimes there is also the lone rebel who says the right thing, but the institutional authorities may disagree (see Galileo). So you understand the dangers of the argument. There is of course the other side which is also dangerous. In an optimistic scenario, academics eventually manage to create magical lie detector software. Who will protect us from those who manipulate it?
Publishing was at TheGuardian Believe it or not, a social media lie detector is being developed.
