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The application of Artificial Intelligence (AI) tools in different domainsare becoming mandatory for all companies wishing to excel in their industries.One major challenge for a successful application of AI is to combine themachine learning (ML) expertise with the domain knowledge to have the bestresults applying AI tools. Domain specialists have an understanding of the dataand how it can impact their decisions. ML experts have the ability to useAI-based tools dealing with large amounts of data and generating insights fordomain experts. But without a deep understanding of the data, ML experts arenot able to tune their models to get optimal results for a specific domain.Therefore, domain experts are key users for ML tools and the explainability ofthose AI tools become an essential feature in that context. There are a lot ofefforts to research AI explainability for different contexts, users and goals.In this position paper, we discuss interesting findings about how ML expertscan express concerns about AI explainability while defining features of an MLtool to be developed for a specific domain. We analyze data from two brainstormsessions done to discuss the functionalities of an ML tool to supportgeoscientists (domain experts) on analyzing seismic data (domain-specific data)with ML resources.

Do ML Experts Discuss Explainability for AI Systems? A discussion case in the industry for a domain-specific solution