Li, Huao and Milani, Stephanie and Krishnamoorthy, Vigneshram and Lewis, Michael and Sycara, Katia
(2019)
Perceptions of Domestic Robots’ Normative Behavior Across Cultures.
In: AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society, 27-28 Jan 2019, Honolulu, HI, United States of America.
Abstract
As domestic service robots become more common and widespread, they must be programmed to efficiently accomplish tasks while aligning their actions with relevant norms. The first step to equip domestic robots with normative reasoning competence is understanding the norms that people apply to the behavior of robots in specific social contexts. To that end, we conducted an online survey of Chinese and United States participants in which we asked them to select the preferred normative action a domestic service robot should take in a number of scenarios. The paper makes multiple contributions. Our extensive survey is the first to: (a) collect data on attitudes of people on normative behavior of domestic robots, (b) across cultures and (c) study relative priorities among norms for this domain. We present our findings and discuss their implications for building computational models for robot normative reasoning.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
Conference or Workshop Item
(Paper)
|
| Status: |
Published |
| Creators/Authors: |
|
| Date: |
2019 |
| Date Type: |
Publication |
| Journal or Publication Title: |
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society |
| Event Title: |
AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society |
| Event Dates: |
27-28 Jan 2019 |
| Event Type: |
Conference |
| Schools and Programs: |
School of Computing and Information > Information Science |
| Refereed: |
Yes |
| Date Deposited: |
31 May 2019 16:10 |
| Last Modified: |
31 May 2019 16:10 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/36820 |
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}