AI to Profile Gang Members on Twitter
November 16, 2016
Researchers from Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis) are claiming that an algorithm developed by them is capable of identifying gang members on Twitter.
Vice.com recently published an article titled Researchers Claim AI Can Identify Gang Members on Twitter, which claims that:
A deep learning AI algorithm that can identify street gang members based solely on their Twitter posts, and with 77 percent accuracy.
The article then points out the shortcomings of the algorithm or AI by saying this:
According to one expert contacted by Motherboard, this technology has serious shortcomings that might end up doing more harm than good, especially if a computer pegs someone as a gang member just because they use certain words, enjoy rap, or frequently use certain emojis—all criteria employed by this experimental AI.
The shortcomings do not end here. The data on Twitter is being analyzed in a silo. For example, let us assume that few gang members are identified using the algorithm (remember, no location information is taken into consideration by the AI), what next?
Is it not necessary then to also identify other social media profiles of the supposed gang members, look at Big Data generated by them, analyze their communication patterns and then form some conclusion? Unfortunately, none of this is done by the AI. It, in fact, would be a mammoth task to extrapolate data from multiple sources just to identify people with certain traits.
And most importantly, what if the AI is put in place, and someone just for the sake of fun projects an innocent person as a gang member? As rightly pointed out in the article – machines trained on prejudiced data tend to reproduce those same, very human, prejudices.
Vishal Ingole, November 16, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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