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Conference proceeding
Embedding Ethical Principles in Collective Decision Support Systems
Proceedings of the ... AAAI Conference on Artificial Intelligence, Vol.30(1), pp.4147-4151
AAAI Conference on Artificial Intelligence
AAAI Conference on Artificial Intelligence, 30th (Phoenix, Arizona USA, 02/12/2016–02/17/2016)
03/05/2016
Web of Science ID: WOS:000485474204034
Abstract
The future will see autonomous machines acting in the same environment as humans, in areas as diverse as driving, assistive technology, and health care. Think of self-driving cars, companion robots, and medical diagnosis support systems. We also believe that humans and machines will often need to work together and agree on common decisions. Thus hybrid collective decision making systems will be in great need.
In this scenario, both machines and collective decision making systems should follow some form of moral values and ethical principles (appropriate to where they will act but always aligned to humans'), as well as safety constraints. In fact, humans would accept and trust more machines that behave as ethically as other humans in the same environment. Also, these principles would make it easier for machines to determine their actions and explain their behavior in terms understandable by humans. Moreover, often machines and humans will need to make decisions together, either through consensus or by reaching a compromise. This would be facilitated by shared moral values and ethical principles.
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Details
- Title
- Embedding Ethical Principles in Collective Decision Support Systems
- Publication Details
- Proceedings of the ... AAAI Conference on Artificial Intelligence, Vol.30(1), pp.4147-4151
- Resource Type
- Conference proceeding
- Conference
- AAAI Conference on Artificial Intelligence, 30th (Phoenix, Arizona USA, 02/12/2016–02/17/2016)
- Publisher
- Assoc Advancement Artificial Intelligence
- Series
- AAAI Conference on Artificial Intelligence
- Number of pages
- 5
- Copyright
- © 2016, Association for the Advancement of Artificial Intelligence
- Identifiers
- WOS:000485474204034; 99380590597106600
- Academic Unit
- Hal Marcus College of Science and Engineering ; Intelligent Systems and Robotics; Institute for Human and Machine Cognition
- Language
- English