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Conference Paper
Ethical Chatbot Design for Reducing Negative Effects of Biased Data and Unethical Conversations
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- Authors
- Junseong Bang, Sineae Kim, Jang Won Nam, Dong-geun Yang
- Issue Date
- 2021-08
- Citation
- International Conference on Platform Technology and Service (PlatCon) 2021, pp.47-51
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- Abstract
- AI technology is being introduced into various public and private service domains, transforming existing computing systems or creating new ones. While AI technologies can provide benefits to humans and society, the unexpected consequences (e.g., malfunctions) of AI systems can cause social losses. For this reason, research on ethical design for the development of AI-based systems is becoming important. In this paper, from existing studies on AI ethics, general guidelines such as transparency, explainability, predictability, accountability, fairness, privacy, and control for the ethical design of AI systems are reviewed. And, based on the ethical design guidelines, we discuss ethical design to reduce the negative effects of biased data and unethical dialogues in AI-based conversational chatbots.
- KSP Keywords
- Negative effects, Public and private, based system, computing systems, design guidelines