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The UNESCO Recommendation on AI Ethics is an international framework adopted to guide the ethical development and deployment of artificial intelligence technologies. It emphasizes human rights, transparency, fairness, and accountability in AI systems.
The Montreal Declaration for Responsible AI is a set of ethical guidelines aimed at promoting the development and deployment of artificial intelligence technologies in a manner that respects human rights, social justice, and democratic values. Initiated in 2017, it represents a collaborative effort to address the societal impacts of AI and encourage responsible innovation.
Explainable artificial intelligence (XAI) refers to methods and techniques in AI that make the outcomes of machine learning models understandable to humans. XAI aims to provide transparency, interpretability, and trustworthiness in AI systems, especially in critical applications.
Code as policies in robot control refers to the practice of embedding rules and regulations into the programming of robots to ensure compliance with ethical and operational standards.
Greg Brockman is a prominent figure in the field of artificial intelligence, known for his role as co-founder and CTO of OpenAI, where he focuses on developing advanced AI technologies.
In-processing bias mitigation refers to methods employed during data processing to reduce bias in machine learning and AI systems.
Artificial intelligence in fiction explores the portrayal of AI in literature, film, and other media, reflecting societal hopes and fears about technology.
Concept activation vectors (CAV) are a method used in machine learning to interpret neural networks by associating specific directions in the latent space with human-understandable concepts.
The Asilomar AI Principles are a set of guidelines designed to promote the safe, ethical, and beneficial development of artificial intelligence. Created in 2017, they address issues such as research transparency, value alignment, and long-term safety.