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Losing confidence in quality: unspoken evolution of computer vision services
conference contribution
posted on 2019-01-01, 00:00 authored by Alex CummaudoAlex Cummaudo, Rajesh VasaRajesh Vasa, John Grundy, Mohamed AbdelrazekMohamed Abdelrazek, Andrew CainAndrew CainRecent advances in artificial intelligence (AI) and machine learning (ML), such as computer vision, are now available as intelligent services and their accessibility and simplicity is compelling. Multiple vendors now offer this technology as cloud services and developers want to leverage these advances to provide value to end-users. However, there is no firm investigation into the maintenance and evolution risks arising from use of these intelligent services; in particular, their behavioural consistency and transparency of their functionality. We evaluated the responses of three different intelligent services (specifically computer vision) over 11 months using 3 different data sets, verifying responses against the respective documentation and assessing evolution risk. We found that there are: (1) inconsistencies in how these services behave; (2) evolution risk in the responses; and (3) a lack of clear communication that documents these risks and inconsistencies.We propose a set of recommendations to both developers and intelligent service providers to inform risk and assist maintainability.
History
Event
IEEE Computer Society. International Conference (35th : 2019 : Cleveland, Oh.)Series
IEEE Computer Society International ConferencePagination
333 - 342Publisher
Institute of Electrical and Electronics EngineersLocation
Cleveland, Oh.Place of publication
Piscataway, N.J.Publisher DOI
Start date
2019-09-29End date
2019-10-04ISBN-13
9781728130941Language
engPublication classification
E1 Full written paper - refereedEditor/Contributor(s)
[Unknown]Title of proceedings
ICSME 2019 : Proceedings of the 2019 IEEE International Conference on Software Maintenance and EvolutionUsage metrics
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