Making AI More Transparent
When artificial intelligence (AI) analyzes images, it is often difficult for humans to understand how specific decisions are made – for example, in medical diagnostics. Zeynep Akata, Director of the Institute for Explainable Machine Learning at Helmholtz Munich and Professor of Computer Science at the Technical University of Munich, develops AI systems that explain their reasoning by integrating visual, linguistic, and conceptual information.
A core focus of her research is image classification. Her AI models learn to recognize objects using a combination of visual and textual data – even from very limited examples (a technique known as low-shot learning). In 2013, Akata introduced Attribute Label Embedding (ALE), a model for zero-shot learning that enables AI to identify new categories without prior image data – based solely on descriptive language. Her current work enhances explainability by highlighting the image features that influenced the AI’s decision, thereby increasing transparency and user trust. In the field of generative AI, she has also developed innovative methods for automatically generating realistic images from text.
About Zeynep Akata
Zeynep Akata studied computer engineering and media informatics in Turkey and Germany, earned her PhD in France, and conducted research in Saarbrücken, Berkeley, and Amsterdam. From 2019 to 2023, she was Professor of Computer Science at the University of Tübingen and Senior Group Leader at the Max Planck Institute for Informatics. Since 2024, she has held the Liesel Beckmann Distinguished Professorship at the Technical University of Munich and leads the Institute for Explainable Machine Learning at Helmholtz Munich. Akata has received numerous honors for her research, including the Lise Meitner Award (2014), the Alfried Krupp Prize for Young University Teachers (2023), and a European Research Council (ERC) Starting Grant (2019). In 2024, Capital magazine named her one of Germany’s “Top 40 under 40.”
About the Award
The ZukunftsWissen – Early Career Award of the Leopoldina and the Commerzbank Foundation recognizes early-career researchers whose work addresses major future challenges and aligns with the theme of the respective Leopoldina Annual Assembly. The €50,000 prize includes a public lecture by the award recipient.
More information: https://www.leopoldina.org/ueber-uns/auszeichnungen/preise-und-ehrungen/zukunftswissen/
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