Detecting Feature Eligibility Illusions in Enterprise AI Autopilots

Authors: 

Fabio Casati, Veeru Metha, Gopal Sarda, Sagar Davasam, and Kannan Govindarajan, Servicenow

Abstract: 

SaaS Enterprise workflow companies, such as Salesforce and Servicenow, facilitate AI adoption by making it easy for customers to train AI models on top of workflow data, once they know the problem they want to solve and how to formulate it. However, as we experience over and over, it is very hard for customers to have this kind of knowledge for their processes, as it requires an awareness of the business and operational side of the process as well as of what AI could do on each with the specific data. The challenge we address is how to take customers to that stage, and in this paper we focus on a specific aspect of such challenge: the identification of which "useful inferences" AI could make and which process attributes can be leveraged as predictors, based on the data available for that customer.

OpML '20 Open Access Sponsored by NetApp

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BibTeX
@inproceedings {256628,
author = {Fabio Casati and Veeru Metha and Gopal Sarda and Sagar Davasam and Kannan Govindarajan},
title = {Detecting Feature Eligibility Illusions in Enterprise {AI} Autopilots},
booktitle = {2020 {USENIX} Conference on Operational Machine Learning (OpML 20)},
year = {2020},
url = {https://www.usenix.org/conference/opml20/presentation/casati},
publisher = {{USENIX} Association},
month = jul,
}

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