The right to obtain an explanation of the decision reached by an Artificial Intelligence (AI) model is now an EU regulation. Different stakeholders of an AI system (e.g. managers, developers, auditors, etc.) may have different background knowledge, competencies and goals, thus requiring different kinds of interpretations and explanations. Fortunately, there is a growing armoury of tools to interpret ML models and explain their predictions, recommendations and diagnoses which we will refer to collectively as explanation strategies. As these explanation strategies mature, practitioners will gain experience that helps them know which strategies to deploy in different circumstances. What is lacking, and is addressed by iSee, is capturing, sharing and re-using explanation strategies based on past positive experiences. The goal of the iSee platform is to improve every user's experience of AI, by harnessing experiences and best practices in Explainable AI.
WIJEKOON, A., WIRATUNGA, N., PALIHAWADANA, C., NKISI-ORJI, I., CORSAR, D. and MARTIN, K. 2023. iSee: intelligent sharing of explanation experience of users for users. In IUI '23 companion: companion proceedings of the 28th Intelligent user interfaces international conference 2023 (IUI 2023), 27-31 March 2023, Sydney, Australia. New York: ACM [online], pages 79-82. Available from: https://doi.org/10.1145/3581754.3584137