2019/06/17 by Alex Cummaudo, Cummaudo, Alex, Rajesh Vasa +7 · 1 voice · 1 citation
Business, Management and Accounting · Decision Sciences · #Big Data and Business Intelligence #Data Quality and Management #cs.AI #cs.SE
paper · pdf · doi:10.48550/arxiv.1906.07328
openalex publication_date 2019/06/17 · openalex created_date 2022/07/28 · openalex updated_date 2026/07/28
Recent advances in artificial intelligence (AI) and machine learning (ML),\nsuch as computer vision, are now available as intelligent services and their\naccessibility and simplicity is compelling. Multiple vendors now offer this\ntechnology as cloud services and developers want to leverage these advances to\nprovide value to end-users. However, there is no firm investigation into the\nmaintenance and evolution risks arising from use of these intelligent services;\nin particular, their behavioural consistency and transparency of their\nfunctionality. We evaluated the responses of three different intelligent\nservices (specifically computer vision) over 11 months using 3 different data\nsets, verifying responses against the respective documentation and assessing\nevolution risk. We found that there are: (1) inconsistencies in how these\nservices behave; (2) evolution risk in the responses; and (3) a lack of clear\ncommunication that documents these risks and inconsistencies. We propose a set\nof recommendations to both developers and intelligent service providers to\ninform risk and assist maintainability.\n