THE AUTOMATED SPEECH POLICE: Teaching computers to weed out thought crimes

From Front Page Magazine:

There are plenty of reasons to worry about the concept of ‘hate speech’. There are also specific concerns about the notion of Islamophobia, especially in light of controversial recent moves by the All Party Parliamentary Group (APPG) on British Muslims to produce a definition. 

Both concepts are subjective and hard to pin down. But it gets worse. For around the globe, a cottage industry is springing up, attempting to devise ways to automate the detection of online ‘hate speech’ in general, and of ‘Islamophobia’ in particular. 

The aura of scientific objectivity that goes along with the computerised detection of ‘hate’ online is very dangerous. 

You can’t make a loose and fuzzy idea rigorous by getting complicated algorithms and sophisticated statistical analysis to do your dirty work for you. But you can make it look that way. 

And worryingly, many of those working to automate ‘hate speech’ detection have direct influence on governments and tech firms. 

Those working on such tools often see ‘hate speech’ as a problem worsened by technology. Hence they assume that the solution is more technology. For example, the Anti-Defamation League (ADL) is ‘teaching machines to recognise hate’ by working to produce an Online Hate Index. 

The ADL argues that a combination of a team of human assessors and a ‘constantly evolving process of machine learning’ can help us learn more about ‘hate’ online and ‘push for the changes necessary to ensure that online communities are safe and inclusive spaces’. 

But in truth projects like this will only fuel attempts by social-media platforms and governments to chill debate. 

The APPG on British Muslims at least recognised that any definition of Islamophobia must not rule out genuine criticism of religion. But it is not at all clear that those working on the automated detection of Islamophobia and other ‘hate speech’ are taking steps to protect legitimate criticism and opinion.