Causal Learning for Socially Responsible AI
Cheng, Lu, Mosallanezhad, Ahmadreza, Sheth, Paras, Liu, Huan
–arXiv.org Artificial Intelligence
There have been increasing concerns about Artificial Causal inference is the key to uncovering the real-world Intelligence (AI) due to its unfathomable DGPs [Pearl, 2009]. In the era of big data, especially, it is potential power. To make AI address ethical possible to learn causality by leveraging both causal knowledge challenges and shun undesirable outcomes, researchers and the copious real-world data, i.e., causal learning proposed to develop socially responsible (CL) [Guo et al., 2020a]. There have been growing interests AI (SRAI). One of these approaches is causal learning seeking to improve AI's social responsibility from a CL perspective, (CL).
arXiv.org Artificial Intelligence
Apr-25-2021
- Country:
- North America > United States (0.14)
- Genre:
- Overview (1.00)
- Public Relations > Community Relations (0.61)
- Research Report (1.00)
- Industry:
- Education (0.46)
- Health & Medicine (0.47)
- Social Sector (0.69)
- Technology:
- Information Technology
- Artificial Intelligence
- Issues > Social & Ethical Issues (1.00)
- Machine Learning > Neural Networks (1.00)
- Natural Language (1.00)
- Representation & Reasoning (1.00)
- Data Science > Data Mining (1.00)
- Artificial Intelligence
- Information Technology