Towards an Interface Description Template for AI-enabled Systems
- URL: http://arxiv.org/abs/2007.07250v1
- Date: Mon, 13 Jul 2020 20:30:26 GMT
- Title: Towards an Interface Description Template for AI-enabled Systems
- Authors: Niloofar Shadab, Alejandro Salado
- Abstract summary: Reuse is a common system architecture approach that seeks to instantiate a system architecture with existing components.
There is currently no framework that guides the selection of necessary information to assess their portability to operate in a system different than the one for which the component was originally purposed.
We present ongoing work on establishing an interface description template that captures the main information of an AI-enabled component.
- Score: 77.34726150561087
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Reuse is a common system architecture approach that seeks to instantiate a
system architecture with existing components. However, reusing components with
AI capabilities might introduce new risks as there is currently no framework
that guides the selection of necessary information to assess their portability
to operate in a system different than the one for which the component was
originally purposed. We know from SW-intensive systems that AI algorithms are
generally fragile and behave unexpectedly to changes in context and boundary
conditions. The question we address in this paper is, what type of information
should be captured in the Interface Control Document (ICD) of an AI-enabled
system or component to assess its compatibility with a system for which it was
not designed originally. We present ongoing work on establishing an interface
description template that captures the main information of an AI-enabled
component to facilitate its adequate reuse across different systems and
operational contexts. Our work is inspired by Google's Model Card concept,
which was developed with the same goal but focused on the reusability of AI
algorithms. We extend that concept to address system-level autonomy
capabilities of AI-enabled cyber-physical systems.
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