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A Framework for Risk Management in AI System Development Projects
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Author(s): Kitti Photikitti (Assumption University of Thailand, Thailand), Kitikorn Dowpiset (Assumption University of Thailand, Thailand)and Jirapun Daengdej (Assumption University of Thailand, Thailand)
Copyright: 2019
Pages: 20
Source title:
Forecasting and Managing Risk in the Health and Safety Sectors
Source Author(s)/Editor(s): Luisa Dall’Acqua (Scientific Lyceum TCO, Italy & University of Bologna, Italy)
DOI: 10.4018/978-1-5225-7903-8.ch001
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Abstract
It has been well-known that the chance of successfully delivering a software project within an allocated time and budget is very low. Most of the researches in this area have concluded that “user's requirements” of the systems is one of the most difficult risks to deal with in this case. Interestingly, until today, regardless of amount of effort put into this area, the possibility of project failure is still very high. The issue with requirement can be significantly increased when developing an artificial intelligence (AI) system, where one would like the systems to autonomously behave. This is because we are not only dealing with user's requirements, but we must also be able to deal with “system's behavior” that, in many cases, do not even exist during software development. This chapter discusses a preliminary work on a framework for risk management for AI systems development projects. The goal of this framework is to help project management in minimizing risk that can lead AI software projects to fail due to the inability to finish the projects on time and within budget.
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