Explainable & Trustworthy Artificial Intelligence

spring 2024

Artificial Intelligence (AI) has come a long way since its first use and application many decades ago. The use of AI and Machine Learning have seen an immense uptake in the 21st century. The techniques developed in the domain were and are successfully applied to a wide variety of problems, both in academia, private and public industry. As this domain became more and more established in recent years, new challenges arose.

Artificial Intelligence nowadays are complex and sophisticated algorithms that sometimes make it difficult for the humans to understand and interpret the decisions or suggestions of the AI system. Explainable AI puts the following properties on the foreground to deliver trust:

• Gaining trust by explaining for example the characteristics of AI output.
• By explaining an AI technique understanding will increase, allowing to investigate if the technique can be transferred to another domain or problem.
• Informing a user about the workings of an AI model so that there is no misinterpretation.
• Confidence of users can be established by using AI models that are explainable, stable but also robust.
• When explaining AI models issues concerning privacy awareness come into play. Private data should not be exposed by the models.
• It is important that actions can be explained. How have we come to specific outcomes and how could we change them?
• Nowadays, a wide variety of people from different background come into contact AI, it is important that they all understand why the system is behaving in such a manner and offer explanations tailored to their needs.

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