AI governance frameworks are designed to address the tangible characteristics and risks of current and near-term AI systems. Autonomy (acting without direct human control), automation (of cognitive tasks), adaptability (learning from new data), and the ability to operate at immense speed and scale are all fundamental, existing characteristics of AI. These attributes create unique challenges for accountability, safety, and fairness, necessitating comprehensive governance. Superintelligence, a hypothetical future state where AI surpasses human intelligence across all domains, is a speculative concept. While it is a topic of long-term ethical and safety research, it is not a characteristic of present-day AI that practical, contemporary governance structures are built to manage.

A. Autonomy: AI's capacity to operate independently is a core reason for governance, as it raises critical questions about control, liability, and decision-making accountability.

B. Automation: The automation of complex tasks by AI systems introduces risks like algorithmic bias and workforce displacement, which are central concerns for AI governance.

C. Adaptability: The ability of AI models to change over time (e.g., model drift) requires continuous monitoring and management, a key function of a robust governance program.

D. Speed and scale: AI operates at a velocity and scale that can amplify errors and biases rapidly, making human oversight difficult and robust governance frameworks essential.

1. National Institute of Standards and Technology (NIST). (2023). Artificial Intelligence Risk Management Framework (AI RMF 1.0). NIST AI 100-1. In Section 3.1

"AI systems have a unique set of characteristics

" the framework highlights that AI systems are "dynamic" (Adaptability) and can "operate at a speed and scale that makes human oversight challenging" (Speed and scale)

which are core drivers for the RMF's governance guidance.

2. OECD. (2019). Recommendation of the Council on Artificial Intelligence. OECD/LEGAL/0449. The commentary accompanying the principles

particularly for "Robustness

Security and Safety

" notes that AI systems can "act with a certain degree of autonomy

" which necessitates specific safeguards and governance mechanisms.

3. Floridi

L.

& Cowls

J. (2019). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review

1(1). https://doi.org/10.1162/99608f92.8cd550d1. The article identifies AI's autonomy and its learning capacity (Adaptability) as key features that distinguish it and require a specific ethical and governance approach.

4. Bostrom

N. (2014). Superintelligence: Paths

Dangers

Strategies. Oxford University Press. This foundational text defines and analyzes superintelligence as a potential

future development

distinguishing it from the capabilities of contemporary AI systems that are the subject of current governance frameworks.