Requirements engineering for artificial intelligence systems: A systematic mapping study

In traditional software systems, Requirements Engineering (RE) activities are well-established and researched. However, building Artificial Intelligence (AI) based software with limited or no insight into the system’s inner workings poses significant new challenges to RE. Existing literature has foc...

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Vydané v:Information and software technology Ročník 158; s. 107176
Hlavní autori: Ahmad, Khlood, Abdelrazek, Mohamed, Arora, Chetan, Bano, Muneera, Grundy, John
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Elsevier B.V 01.06.2023
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ISSN:0950-5849, 1873-6025
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Abstract In traditional software systems, Requirements Engineering (RE) activities are well-established and researched. However, building Artificial Intelligence (AI) based software with limited or no insight into the system’s inner workings poses significant new challenges to RE. Existing literature has focused on using AI to manage RE activities, with limited research on RE for AI (RE4AI). This paper investigates current approaches for specifying requirements for AI systems, identifies available frameworks, methodologies, tools, and techniques used to model requirements, and finds existing challenges and limitations. We performed a systematic mapping study to find papers on current RE4AI approaches. We identified 43 primary studies and analyzed the existing methodologies, models, tools, and techniques used to specify and model requirements in real-world scenarios. We found several challenges and limitations of existing RE4AI practices. The findings highlighted that current RE applications were not adequately adaptable for building AI systems and emphasized the need to provide new techniques and tools to support RE4AI. Our results showed that most of the empirical studies on RE4AI focused on autonomous, self-driving vehicles and managing data requirements, and areas such as ethics, trust, and explainability need further research. •New requirements are emerging in engineering AI software such as data and ethics.•Requirements Specifications for AI systems presents new issues.•Existing RE tools need to be re-evaluated when building AI Software.•Trade-offs need to be calculated carefully when writing requirements for AI.•There is limited empirical evaluation on ethics, explainability and trust.
AbstractList In traditional software systems, Requirements Engineering (RE) activities are well-established and researched. However, building Artificial Intelligence (AI) based software with limited or no insight into the system’s inner workings poses significant new challenges to RE. Existing literature has focused on using AI to manage RE activities, with limited research on RE for AI (RE4AI). This paper investigates current approaches for specifying requirements for AI systems, identifies available frameworks, methodologies, tools, and techniques used to model requirements, and finds existing challenges and limitations. We performed a systematic mapping study to find papers on current RE4AI approaches. We identified 43 primary studies and analyzed the existing methodologies, models, tools, and techniques used to specify and model requirements in real-world scenarios. We found several challenges and limitations of existing RE4AI practices. The findings highlighted that current RE applications were not adequately adaptable for building AI systems and emphasized the need to provide new techniques and tools to support RE4AI. Our results showed that most of the empirical studies on RE4AI focused on autonomous, self-driving vehicles and managing data requirements, and areas such as ethics, trust, and explainability need further research. •New requirements are emerging in engineering AI software such as data and ethics.•Requirements Specifications for AI systems presents new issues.•Existing RE tools need to be re-evaluated when building AI Software.•Trade-offs need to be calculated carefully when writing requirements for AI.•There is limited empirical evaluation on ethics, explainability and trust.
ArticleNumber 107176
Author Ahmad, Khlood
Bano, Muneera
Abdelrazek, Mohamed
Arora, Chetan
Grundy, John
Author_xml – sequence: 1
  givenname: Khlood
  orcidid: 0000-0002-7148-380X
  surname: Ahmad
  fullname: Ahmad, Khlood
  email: ahmadkhl@deakin.edu.au
  organization: Deakin University, Geelong, VIC, Australia
– sequence: 2
  givenname: Mohamed
  surname: Abdelrazek
  fullname: Abdelrazek, Mohamed
  email: mohamed.abdelrazek@deakin.edu.au
  organization: Deakin University, Geelong, VIC, Australia
– sequence: 3
  givenname: Chetan
  surname: Arora
  fullname: Arora, Chetan
  email: chetan.arora@monash.edu
  organization: Monash University, Clayton, VIC, Australia
– sequence: 4
  givenname: Muneera
  surname: Bano
  fullname: Bano, Muneera
  email: muneera.bano@csiro.au
  organization: CSIRO’s Data61, Clayton, VIC, Australia
– sequence: 5
  givenname: John
  surname: Grundy
  fullname: Grundy, John
  email: john.grundy@monash.edu
  organization: Monash University, Clayton, VIC, Australia
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Keywords Requirements engineering
Artificial intelligence
Machine learning
Systematic mapping study
Software engineering
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  start-page: 61
  issue: 1
  year: 2012
  ident: 10.1016/j.infsof.2023.107176_b50
  article-title: Robots: ethical by design
  publication-title: Ethics Inform. Technol.
  doi: 10.1007/s10676-011-9278-2
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Snippet In traditional software systems, Requirements Engineering (RE) activities are well-established and researched. However, building Artificial Intelligence (AI)...
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StartPage 107176
SubjectTerms Artificial intelligence
Machine learning
Requirements engineering
Software engineering
Systematic mapping study
Title Requirements engineering for artificial intelligence systems: A systematic mapping study
URI https://dx.doi.org/10.1016/j.infsof.2023.107176
Volume 158
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