Algorithm Debt: Challenges and Future Paths

Emmanuel Iko Ojo Simon; Melina Vidoni; Fatemeh H. Fard

doi:10.1109/CAIN58948.2023.00020

Algorithm Debt: Challenges and Future Paths

Emmanuel Iko Ojo Simon^*, Melina Vidoni, Fatemeh H. Fard

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Technical Debt (TD) is the implied cost of additional rework caused by choosing easier solutions in favour of shorter release time. It impacts software maintainability and evolvability, manifesting as different types (e.g., Code, Test, Architecture). Algorithm Debt (AD) is a new TD type recently identified as sub-optimal implementations of algorithm logic in scientific and Artificial Intelligence (AI) software. Given its newness, AD and its impact on AI-driven software remains a research gap. This poster aims to motivate reflective discussion on AD in AI software, by summarising findings, discussing its possible impact, and outlining future areas of work.

Original language	English
Title of host publication	Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	90-91
Number of pages	2
ISBN (Electronic)	9798350301137
DOIs	https://doi.org/10.1109/CAIN58948.2023.00020
Publication status	Published - 2023
Event	2nd IEEE/ACM International Conference on AI Engineering - Software Engineering for AI, CAIN 2023 - Melbourne, Australia Duration: 15 May 2023 → 16 May 2023

Publication series

Name	Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023

Conference

Conference	2nd IEEE/ACM International Conference on AI Engineering - Software Engineering for AI, CAIN 2023
Country/Territory	Australia
City	Melbourne
Period	15/05/23 → 16/05/23

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10.1109/CAIN58948.2023.00020

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Simon, E. I. O., Vidoni, M., & Fard, F. H. (2023). Algorithm Debt: Challenges and Future Paths. In Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023 (pp. 90-91). (Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CAIN58948.2023.00020

Simon, Emmanuel Iko Ojo ; Vidoni, Melina ; Fard, Fatemeh H. / Algorithm Debt : Challenges and Future Paths. Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. pp. 90-91 (Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023).

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title = "Algorithm Debt: Challenges and Future Paths",

abstract = "Technical Debt (TD) is the implied cost of additional rework caused by choosing easier solutions in favour of shorter release time. It impacts software maintainability and evolvability, manifesting as different types (e.g., Code, Test, Architecture). Algorithm Debt (AD) is a new TD type recently identified as sub-optimal implementations of algorithm logic in scientific and Artificial Intelligence (AI) software. Given its newness, AD and its impact on AI-driven software remains a research gap. This poster aims to motivate reflective discussion on AD in AI software, by summarising findings, discussing its possible impact, and outlining future areas of work.",

keywords = "Algorithm Debt, Artificial Intelligence, Code Debt, Scientific Software, Software Engineering, Technical Debt",

author = "Simon, {Emmanuel Iko Ojo} and Melina Vidoni and Fard, {Fatemeh H.}",

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year = "2023",

doi = "10.1109/CAIN58948.2023.00020",

language = "English",

series = "Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

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address = "United States",

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Simon, EIO, Vidoni, M & Fard, FH 2023, Algorithm Debt: Challenges and Future Paths. in Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023. Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023, Institute of Electrical and Electronics Engineers Inc., pp. 90-91, 2nd IEEE/ACM International Conference on AI Engineering - Software Engineering for AI, CAIN 2023, Melbourne, Australia, 15/05/23. https://doi.org/10.1109/CAIN58948.2023.00020

Algorithm Debt: Challenges and Future Paths. / Simon, Emmanuel Iko Ojo; Vidoni, Melina; Fard, Fatemeh H.
Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023. Institute of Electrical and Electronics Engineers Inc., 2023. p. 90-91 (Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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N2 - Technical Debt (TD) is the implied cost of additional rework caused by choosing easier solutions in favour of shorter release time. It impacts software maintainability and evolvability, manifesting as different types (e.g., Code, Test, Architecture). Algorithm Debt (AD) is a new TD type recently identified as sub-optimal implementations of algorithm logic in scientific and Artificial Intelligence (AI) software. Given its newness, AD and its impact on AI-driven software remains a research gap. This poster aims to motivate reflective discussion on AD in AI software, by summarising findings, discussing its possible impact, and outlining future areas of work.

AB - Technical Debt (TD) is the implied cost of additional rework caused by choosing easier solutions in favour of shorter release time. It impacts software maintainability and evolvability, manifesting as different types (e.g., Code, Test, Architecture). Algorithm Debt (AD) is a new TD type recently identified as sub-optimal implementations of algorithm logic in scientific and Artificial Intelligence (AI) software. Given its newness, AD and its impact on AI-driven software remains a research gap. This poster aims to motivate reflective discussion on AD in AI software, by summarising findings, discussing its possible impact, and outlining future areas of work.

KW - Algorithm Debt

KW - Artificial Intelligence

KW - Code Debt

KW - Scientific Software

KW - Software Engineering

KW - Technical Debt

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DO - 10.1109/CAIN58948.2023.00020

M3 - Conference contribution

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BT - Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023

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Simon EIO, Vidoni M, Fard FH. Algorithm Debt: Challenges and Future Paths. In Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023. Institute of Electrical and Electronics Engineers Inc. 2023. p. 90-91. (Proceedings - 2023 IEEE/ACM 2nd International Conference on AI Engineering - Software Engineering for AI, CAIN 2023). doi: 10.1109/CAIN58948.2023.00020

Algorithm Debt: Challenges and Future Paths

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