Super Alignment
Theoretical concept in AI, primarily focusing on ensuring that advanced AI systems or AGI align closely with human values and ethics to prevent negative outcomes.
Super Alignment involves the development of methodologies and frameworks to ensure that AGI's actions and decisions are deeply aligned with human ethical standards, values, and goals. The concept underscores the importance of creating AGI systems that not only understand human instructions but also the underlying intentions and moral considerations, ensuring these systems act in ways that are beneficial to humanity. This involves complex challenges, including defining human values in computable terms, ensuring the AI's ability to learn and adapt these values, and safeguarding against misinterpretation or manipulation.
The historical context and emergence of the term "Super Alignment" are not well-defined in mainstream AI literature and may vary depending on the source. The concept has gained attention as discussions around the potential risks and ethical considerations of AGI have become more prevalent, especially in the 21st century. The exact year of first use is difficult to pinpoint without specific references, as the concept has evolved gradually through discussions in the AI safety and ethics communities.
Key contributors to the development of the concept of AI alignment, which includes Super Alignment, are a diverse group of researchers, ethicists, and organizations focused on AI safety and ethics. Prominent figures include Nick Bostrom and Eliezer Yudkowsky, among others, who have extensively written on the risks of advanced AI and the importance of alignment. Organizations such as the Future of Humanity Institute (FHI) and the Machine Intelligence Research Institute (MIRI) have also played significant roles in advancing research and dialogue around this topic.