|
The Best Way to Instil Confidence is by Being Right An Evaluation of the Effectiveness of Case-Based Explanations in providing User Confidence |
Nugent, Conor; Cunningham, Padraig; Doyle, Donal
|
|
|
|
TCD-CS-2005-21 Instilling confidence in the abilities of machine learning systems in end-users is seen as critical to their success in real world problems. One way in which this can be achieved is by providing users with
interpretable explanations of the system's predictions. CBR systems have
long been understood to have an inherent transparency that has particular advantages for explanations compared with other machine learning
techniques. However simply suppling the most similar case is often not
enough. In this paper we present a framework for providing interpretable
explanations of CBR systems which includes dynamically created discursive texts explaining the feature-value relationships and a measure of
confidence of the CBR systems prediction being correct. We also present
the results of a preliminary user evaluation we have carried out on the
framework.It is clear from this evaluation that being right is important.
It appears that caveats and notes of caution when the system is uncertain
damage user confidence.
|
|
Keyword(s):
|
Computer Science |
Publication Date:
|
2005 |
|
Type:
|
Report |
|
Peer-Reviewed:
|
Unknown |
|
Language(s):
|
English |
|
Institution:
|
Trinity College Dublin |
|
Citation(s):
|
Nugent, Conor; Cunningham, Padraig; Doyle, Donal. 'The Best Way to Instil Confidence is by Being Right An Evaluation of the Effectiveness of Case-Based Explanations in providing User Confidence'. - Dublin, Trinity College Dublin, Department of Computer Science, TCD-CS-2005-21, 2005, pp15 |
|
Publisher(s):
|
Trinity College Dublin, Department of Computer Science |
|
File Format(s):
|
application/pdf |
|
First Indexed:
2014-05-13 05:31:06 Last Updated:
2015-04-10 05:13:47 |
