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Requirements Elicitation Techniques and Tools in the Context of Artificial Intelligence

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Intelligent Systems (BRACIS 2022)

Abstract

Context: During software development in the context of Artificial Intelligence (AI), just like any other software, there is the requirements elicitation phase. In this phase, developers alongside stakeholders make use of various techniques, methodologies, and tools available to elicit software requirements. Problem: The need of understanding which techniques, methodologies, and tools are suitable in requirements elicitation in the context of AI, taking into consideration ethical issues. Solution: Investigation of the ICT practitioners’ perception about their approaches regarding the requirements elicitation process for AI systems. Method: We have conducted a survey with ICT practitioners and reviewed the literature to identify requirements elicitation practices in the context of AI. Summary of Results: Most ICT practitioners work with the techniques and methodologies found in the literature. Regarding tools, our findings were inconclusive, as most practitioners do not use the tools identified in the literature, or even do not use any tools. As for ethical requirements, some were well consolidated with practitioners but others were not, such as the principle of equity and inclusion. Contributions and Impact in the IS area: An overview of how AI systems are being developed across organizations and the treatment that is given to ethical requirements. Our findings reveal that there is a need for organizations to consolidate ethical and legal notions with developers so that they can be applied during the requirements elicitation phase.

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Correspondence to Edna Dias Canedo .

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de Sousa Silva, A.F., Silva, G.R.S., Canedo, E.D. (2022). Requirements Elicitation Techniques and Tools in the Context of Artificial Intelligence. In: Xavier-Junior, J.C., Rios, R.A. (eds) Intelligent Systems. BRACIS 2022. Lecture Notes in Computer Science(), vol 13653. Springer, Cham. https://doi.org/10.1007/978-3-031-21686-2_2

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  • DOI: https://doi.org/10.1007/978-3-031-21686-2_2

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