Uploaded December 2021 | Updated September 2026, 1 hour ago
Online communication channels are popular, to say the least. For instance, there are 187 million active Twitter users per day alone. Sadly, these open channels of communication also open up the potential for harm, through online hate speech. The problem is so large that we require AI to help detect it. But what about when it comes to emoji? According to some reports, ten billion emoji are sent in messages around the world every day. When the same emoji can have vastly different meanings depending on the context, how can we use AI to detect their use as hate speech? We speak to Oxford AI researcher Hannah Rose Kirk to find out.
Online communication channels are popular, to say the least. For instance, there are 187 million active Twitter users per day alone. Sadly, these open channels of communication also open up the potential for harm, through online hate speech. The problem is so large that we require AI to help detect it. But what about when it comes to emoji? According to some reports, ten billion emoji are sent in messages around the world every day. When the same emoji can have vastly different meanings depending on the context, how can we use AI to detect their use as hate speech? We speak to Oxford AI researcher Hannah Rose Kirk to find out.
