The blurry line between narrow, general and superintelligent AI

In the field of artificial intelligence there is often much confusion and misuse of terminology, particularly around the distinctions between narrow AI, artificial general intelligence (AGI), and artificial superintelligence (ASI).

The definitional challenge: Clear definitions are essential for meaningful discussion and understanding of artificial intelligence technologies and capabilities.

• Precise terminology helps avoid miscommunication and ensures people are discussing the same concepts when debating AI developments
• Without agreed-upon definitions, there is a risk of people talking past each other or making inaccurate comparisons
• Technical and legal definitions often differ from casual societal usage of AI-related terms

Key distinctions matter: The differences between AI, AGI, and ASI represent fundamental technological and capability gaps that should not be conflated.

• AI refers to narrow artificial intelligence systems designed for specific tasks
• AGI describes hypothetical future systems with human-level intelligence across all domains
• ASI represents a theoretical superintelligent AI that would far exceed human cognitive capabilities
• Each term represents a distinct level of technological achievement and capability

Current state of confusion: There is growing concern about the intentional blurring of lines between these distinct concepts.

• Some companies and individuals are deliberately obscuring the boundaries between current AI capabilities and future possibilities
• Marketing materials and public statements often fail to distinguish between narrow AI and more advanced concepts like AGI
• This confusion can lead to unrealistic expectations and misunderstanding of current technological capabilities

Timeline predictions: Claims about the imminent arrival of AGI or ASI deserve careful scrutiny.

• Many predictions about AGI and ASI development timelines lack scientific rigor
• Historical predictions about advanced AI capabilities have consistently proven premature
• The complexity of developing human-level or superhuman AI is often underestimated

Critical analysis needed: The technology sector would benefit from increased precision in how it discusses and defines different levels of artificial intelligence capability.