Paper Reading #32

Taking advice from intelligent systems: the double-edged sword of explanations

Authors:	Kate Ehrlich	IBM, Cambridge, MA, USA
	Susanna E. Kirk	IBM, Cambridge, MA, USA
	John Patterson	IBM, Cambridge, MA, USA
	Jamie C. Rasmussen	IBM, Cambridge, MA, USA
	Steven I. Ross	IBM, Cambridge, MA, USA
	Daniel M. Gruen	IBM, Cambridge, MA, USA

Proceeding 

CHI '11 Proceedings of the 2011 annual conference on Human factors in computing systems 

 

Summary

• Hypothesis - The researchers point out that intelligent systems can both help and hurt users by giving explanations. The explanations were hypothesized to help users when a correct answer is available, but harm when one is not available. Their goal was to determine the extent of this situation.

• Content - Intelligent systems have the capability of giving suggestions and explanations on problems. If the situation is critical, users must be able to trust the system for correct responses and understand that the explanations are correct. However, even if the system is correct, the researchers claim that correct explanations can lead to incorrect results from ambiguity.
• Methods - The researchers designed a prototype machine learning program (NIMBLE) that give recommendations and explanations in regard to network security issues. 19 participants were selected to perform a 2 hour session consisting of 24 timed trials of network security tasks. The task was to rank a set of 11 threats by importance, either low or medium. To help the users, the system gave recommendations in 3 levels: no recommendation, recommendation only, and recommendation along with a justification. The recommendations also could either have only one or no correct choices with the 3 given recommendation conditions. The helpfulness of the system was then rated in a Likert scale.
• Results - Suggestions and justifications were found to significantly help accuracy when a correct choice was available. However, when it is not available, there was an insignificant drop in accuracy. In all, the researchers found that the participants used the suggestions widely, depending on the level of skill they have.  

Discussion
The closest I can relate to this system is back when I used the spelling and grammar check of earlier Microsoft Word products. Back then, the explanations for some grammar corrections were vague, and some didn't even bother giving explanations. Granted, rationally parsing all of incorrect English is not an easy task, but I remember being unsatisfied with some of the results. For future work, these principles should be applied in areas where fault tolerance is necessary.