Disputas - Master of Science Srishti Gautam

Master of Science Srishti Gautam will Friday March 15th, 2024, at 12:15 hold herdisputas for the PhD degree in Science. The title of her thesis is:

"Towards Interpretable, Trustworthy and Reliable AI"

Summary:

The field of artificial intelligence recently witnessed remarkable growth, leading
to the development of complex deep learning models that perform exceptionally
across various domains. However, these developments bring forth critical issues.
Deep learning models are vulnerable to inheriting and potentially exacerbating
biases present in their training data. Moreover, the complexity of these models
leads to a lack of transparency, which can allow biases to go undetected. This
can lead to ultimately hindering the adoption of these models due to a lack
of trust. It is therefore crucial to foster the creation of artificial intelligence
systems that are inherently transparent, trustworthy, and fair.
This thesis contributes to this line of research by exploring the interpretability of
deep learning through self-explainable models. These models represent a shift
towards more transparent systems, offering explanations that are integral to
the model’s architecture, yielding insights into their decision-making processes.
Consequently, this inherent transparency enhances our understanding, thereby
providing a mechanism to address the inadvertent learning of biases.

Evaluation committee:

• Professor Georgios Leontidis, Chair of Machine Learning, lnterdisciplinary Director of Data and Al, Turing Academic Liaison, Vice-Principals' Office, University of Aberdeen, UK (1. Opponent)
• Professor Lilja Øvrelid, Language Technology Group, Section for Machine Learning, Department of lnformatics, University of Oslo, Oslo, Norway (2. Opponent)
• Associate Professor Elisabeth Wetzer, Machine Learning Group, Department of Physics and Technology, UiT (intern member and leader of the committee)

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