There is a key topic that banks spanning the world are asking right now: how are they able to make AI explainable? This was the opinion of Wolfgang Berner, the CTO of RegTech firm Hawk: AI, who recently presented a keynote speech on the above topic. Berner remarked, "In heavily regulated areas such as combating money laundering, considerations as to how transparent and comprehensible the use of artificial intelligence is are entirely appropriate. Classic concerns about such a "black box AI" arise in particular when the decisions of the AI are too disconnected from the original data and when there is no transparency about the way the algorithms work." Hawk AI sees the key to trust and acceptance in the compliance industry in the high level of transparency.

Artificial intelligence is growing ever more powerful and entering people's daily lives, yet often we don't know what goes on inside these systems. Their non-transparency could fuel practical problems, or even racism, which is why researchers increasingly want to open this'black box' and make AI explainable. When decisions are made by artificial intelligence, it can be difficult for the end user to understand the reasoning behind them. In February of 2013, Eric Loomis was driving around in the small town of La Crosse in Wisconsin, US, when he was stopped by the police. The car he was driving turned out to have been involved in a shooting, and he was arrested.

Artificial intelligence is growing ever more powerful and entering people's daily lives, yet often we don't know what goes on inside these systems. Their non-transparency could fuel practical problems, or even racism, which is why researchers increasingly want to open this'black box' and make AI explainable. In February of 2013, Eric Loomis was driving around in the small town of La Crosse in Wisconsin, US, when he was stopped by the police. The car he was driving turned out to have been involved in a shooting, and he was arrested. Eventually a court sentenced him to six years in prison.