Understanding and Modeling AI-Intensive System Development

TL;DR

This paper discusses the unique challenges of developing AI-Intensive Systems and proposes a notation based on Software Engineering concepts to better model and understand their development processes.

Contribution

It introduces a notation framework for AI-Intensive Systems, adapting SE concepts to address their specific development challenges.

Findings

Proposed a notation for modeling AIIS development

Demonstrated the notation on AIIS characteristics

Highlighted the need for adapted SE methods for AIIS

Abstract

Developers of AI-Intensive Systems--i.e., systems that involve both "traditional" software and Artificial Intelligence"are recognizing the need to organize development systematically and use engineered methods and tools. Since an AI-Intensive System (AIIS) relies heavily on software, it is expected that Software Engineering (SE) methods and tools can help. However, AIIS development differs from the development of "traditional" software systems in a few substantial aspects. Hence, traditional SE methods and tools are not suitable or sufficient by themselves and need to be adapted and extended. A quest for "SE for AI" methods and tools has started. We believe that, in this effort, we should learn from experience and avoid repeating some of the mistakes made in the quest for SE in past years. To this end, a fundamental instrument is a set of concepts and a notation to deal with AIIS and the problems that characterize their development processes. In this paper, we propose to describe AIIS via a notation that was proposed for SE and embeds a set of concepts that are suitable to represent AIIS as well. We demonstrate the usage of the notation by modeling some characteristics that are particularly relevant for AIIS.