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Ms Crawford the social debate about AI ranges from the great opportunities AI brings for all of us to concerns about surveillance or loss of privacy How do you perceive the debate In my view it is not a single debate but many debates on various aspects These new technologies affect our daily lives in many different places They affect everything from how we work to our health systems to education and even to criminal justice Artificial intelligence already has an impact on our work for example through surveillance at the workplace or so called nudging which influ ences the motivation or attitude of employees All these phenomena are having an influence before many people notice To what extent does the technology of AI reinforce asymmetrical power structures In our daily working life technologies are increasingly introduced to track what employees are doing such as counting the productive hours and breaks This is incredibly invasive and it creates an asymmetry of power between employers and employees So we need to have a debate on how we structure power and how we can The Machine Discriminates A conversation with sociologist Kate Crawford about the downside of algorithms and learning machines ensure that artificial intelligence does not strengthen the power of those already powerful When you say that the ownership of data and algorithms creates power what does that mean for the global distribution of power and which countries have it in your view The geopolitical scenario of AI is very important right now Currently there is this strong narrative according to which there is a battle between two superpowers the USA on the one hand and China on the other But I am concerned about the war rhetoric that emerges from different cultures China has a very different AI culture than the USA and Europe has yet another very different culture What could be the role of Germany and Europe Here in Germany there is a great op portunity to hold the debate in such a way that a technology is created that is accountable fair and transparent and in which the responsibility is also clear People should know when they are judged by an AI system and How do machines learn When computer systems learn independent ly we re generally talking about artificial intelligence But the terms are confusing machines learn less independently than it sounds and it still has little to do with how people learn Machines learn from training data and corresponding feedback In image recognition for instance they learn by people showing them several images with a note of what can be seen cats for exam ple This way the programs learn criteria for recognizing cats on their own In another type of machine learning unsuper vised learning the machine automatically searches for patterns in large amounts of data and forms groups of similar data This is how Amazon s recommendation system and others operate the idea is that people interested in X are usually also interested in Y In the case of the Google software of DeepMind which won against the world s best go player the system practically gener ated the training data itself it was simply fed with the rules of the game The system then began to play against itself and thus with every victory learned which strategies are successful It even discovered strategies that human beings had never thought of before But that doesn t mean that AI is on the verge of beating human intelligence There are many things that are incredibly difficult for machines to do even though they are simple for humans Interview 35THE MAGAZINE 3 18 INTERVIEW Jannik Rust Eva Wolfangel PHOTOS Studio I like Birds

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