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Losing confidence in quality: unspoken evolution of computer vision services

conference contribution
posted on 01.01.2019, 00:00 authored by Alex CummaudoAlex Cummaudo, Rajesh VasaRajesh Vasa, John Grundy, Mohamed AbdelrazekMohamed Abdelrazek, Andrew CainAndrew Cain
Recent 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 Conference

Pagination

333 - 342

Publisher

Institute of Electrical and Electronics Engineers

Location

Cleveland, Oh.

Place of publication

Piscataway, N.J.

Start date

29/09/2019

End date

04/10/2019

ISBN-13

9781728130941

Language

eng

Publication classification

E1 Full written paper - refereed

Editor/Contributor(s)

[Unknown]

Title of proceedings

ICSME 2019 : Proceedings of the 2019 IEEE International Conference on Software Maintenance and Evolution