The RE4AI Workshop is part of REFSQ 2020 (The 26th International Working Conference on Requirements Engineering).
Nowadays AI is embedded in software and hardware systems, from everyday objects, such as cars, household appliances, wearable devices, to unmanned military vehicles and arms. Moreover, AI techniques such as Machine Learning are used since several years by big tech players, as well as by startups that, for instance, provide business intelligence services to insurance companies.
Since several years ago (e.g. 2015 open letter and a document about research priorities), AI researchers have manifested their worries and recommendations for the responsible use of data, employment of discrimination-free algorithms, alignment of AI-based systems and technologies with human values and transparency. However, it is hard to imagine that AI systems will achieve these attributes without accounting for a strong emphasis on capturing and maintaining “the right” requirements, and making sure that the system is validated to properly meet such requirements. As the RE community is aware, this entails a myriad of methods and tools covering all RE activities, including requirements analysis, documentation and evolution. Nevertheless, many AI systems are today developed without much focus on the early development stages. In other words, much focus is put on combining different algorithms and heuristics, without however a more abstract view on what the system should deliver. As a result of the lack of RE support, the resulting system may be far from what is intended, leading to failing projects and systems that go rogue, which may ultimately cause harm to human individuals and society.
The main goals of the RE4AI Workshop may be summarized as follows:
- raising awareness in the RE community about the importance of RE in realizing Trustworthy AI systems;
- bringing in the same room people from AI and RE industry and academia to discuss pressing issues, such as how RE can contribute to prevent AI systems to fail or to go rogue;
- setting up the basis for collaboratively producing a report on the challenges, candidate solution paths, and research priorities regarding RE4AI;
- motivating cross fertilization between AI and RE works.
To achieve these goals, we plan a workshop which mixes paper presentations (please see the CFP) and interactive sessions.