No. 114/2022

algorithms’ decisions. “Imagine you are applying for a job. An algorithm rejects your application. Then you’re not really interested in how the algorithm works, instead you ask yourself what would have to be different about you for you to get the job.” AI LEARNS DISCRIMINATION This example was not plucked out of thin air. A major global corporation really did develop AI that was supposed to help select job applicants. Professor Aimee van Wynsberghe of the University of Bonn describes this as a case of discrimination by AI: “They used ten years of historical data to create a recruiting tool. When those responsible were then going through the CVs to choose candidates for the positions, they found that the machine was only recommending men for the managerial positions, never women.” The explanation is that existing inequalities had found their way into the training data which the AI had then adopted. Aimee van Wynsberghe suggests using this downside of AI to advantage: “If you use this recruitment tool to investigate discrimination in corporate culture instead of as a basis for recruiting new staff, it’s a fascinating tool. That is how the technology sheds light on certain forms of inequality. And then we have a choice: do we perpetuate these systems of inequality, or do we stop and make a difference right now? AI has enormous potential for our society, but it’s up to us how we decide to use it.” The huge advantage of AI models in medical imaging is that they always give you an answer, irrespective of the number of images you show them. Daniel Rückert, Alexander von Humboldt Professor for AI at the Technical University of Munich FOCUS 20 HUMBOLDT KOSMOS 114/2022