Explain to whom? Putting the User in the Center of Explainable AI
Overview & Synopsis
The ability to explain actions and decisions is often regarded as a basic ingredient of cognitive systems. But when researchers propose methods for making AI systems understandable, users are usually not involved or even mentioned. However, the purpose is to make people willing to accept the decision of a machine or to be better able to interact with it. Therefore, I argue that the evaluation of explanations must involve some form of user testing.
Indexed from repository: HAL Open Science
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hal.science)
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Document Information
| Document Title | Explain to whom? Putting the User in the Center of Explainable AI |
|---|---|
| Author / Organization | Alexandra Kirsch |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2017 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-18885 |
| Original Source Link | Visit Source Page on hal.science » |