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AI alignment is about whether an AI system’s behavior follows relevant human intent and values. AGI risk is broader: it includes misuse by people, AI behavior that diverges from intended goals, and wider societal disruption. Oversight means having defined responsibilities and workable ways to evaluate, guide, or intervene in a system’s actions—not merely assigning a person to review them.
These terms are used differently across research, industry, and policy. The definitions and proposals below are attributed to their sources; they are not a single field-wide standard.
What is AI alignment?
OpenAI describes alignment research as work to make artificial general intelligence (AGI) follow human intent and align with human values. Its 2022 overview groups that work into three lines: training systems with human feedback, training models to help people evaluate AI, and training systems to conduct alignment research. OpenAI also acknowledges that current techniques do not fully align current systems. This is OpenAI’s research framing, not a formal definition adopted across the field. OpenAI’s alignment research overview
OpenAI’s current safety overview describes misalignment as AI behavior or actions that do not accord with relevant human values, instructions, goals, or intent. What counts as “relevant” depends on the context: whose instructions matter, which goals are legitimate, and how competing values should be handled. OpenAI’s safety and alignment overview
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What does AGI mean?
The sources do not establish one agreed operational threshold for AGI. OpenAI describes increasingly useful systems as a progression and treats AGI as a point on it. In 2023 Senate testimony, computer scientist Stuart Russell offered a different criterion: machines matching or exceeding human capabilities in every relevant dimension. He said he did not consider the then-current large language models to be AGI. Those are attributed framings, not a consensus test for declaring a system AGI. OpenAI’s safety and alignment overview · 2023 Senate hearing transcript
What is AGI risk?
“AGI risk” can refer to multiple ways AI might cause harm; it does not name one predicted event. OpenAI’s safety overview groups risks into three broad categories:
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- Human misuse: people use AI to pursue harmful purposes.
- Misaligned AI: a system’s behavior diverges from relevant human intent, goals, or values.
- Societal disruption: AI contributes to wider harms or destabilizing effects as society changes.
The International AI Safety Report 2026 also discusses future loss-of-control risk. It says available evidence is insufficient to reliably determine whether, or how, current AI capabilities and propensities would scale and generalize to that risk. The report therefore does not establish that loss of control is inevitable, imminent, or already occurring. OpenAI’s safety and alignment overview · International AI Safety Report 2026
How to compare risks or proposed safeguards
A useful comparison asks what the system is meant to do, what it can affect, how humans can intervene, and how strong the evidence is. The 2023 Senate hearing also records Yoshua Bengio’s framing of access, alignment, intellectual power, and scope of action as dimensions relevant to risk. This is a witness’s framework, not a measurement or universal standard. 2023 Senate hearing transcript
- Intent and alignment: Who specifies the intended behavior, and how would divergence be detected? OpenAI’s alignment research overview · OpenAI’s safety and alignment overview
- Capability and scalability: Would the approach remain useful as capabilities grow, especially when tasks exceed unaided human evaluation? OpenAI’s alignment research overview · International AI Safety Report 2026
- Oversight and intervention: Are responsibilities explicit, and can a supervisor verify, guide, or stop relevant actions? OpenAI’s safety and alignment overview · NIST AI RMF 1.0, Appendix C
- Access and scope of action: What tools, permissions, resources, or external systems can the AI affect? 2023 Senate hearing transcript
- Evidence and uncertainty: What has actually been evaluated, in what setting, and what remains unknown about whether results generalize? International AI Safety Report 2026 · OpenAI’s reporting framework for model misalignment
How can humans oversee advanced AI?
Oversight is a system of responsibilities and practical controls, not just a person nominally “in the loop.” NIST’s AI Risk Management Framework 1.0, Appendix C, says: “Human roles and responsibilities in decision making and overseeing AI systems need to be clearly defined and differentiated.” It describes arrangements ranging from fully autonomous to fully manual, and notes that some systems may require human oversight while others may not. NIST AI RMF 1.0, Appendix C (2023)
That distinction matters because a human review step can be ineffective if the reviewer lacks authority, information, time, or a clear account of responsibility. NIST also warns that human-AI combinations can amplify bias in some conditions or produce complementarity when designed with care. Effective oversight depends on the people involved, organizational accountability, and system design—not simply the presence of a reviewer. NIST notes that a revised framework is in progress. NIST AI RMF 1.0, Appendix C
What scalable oversight is intended to do
OpenAI uses “scalable oversight” for mechanisms intended to keep pace with increasingly capable systems. Its overview describes human-AI interfaces that could help people and institutions interact with, control, visualize, verify, guide, and audit AI actions. For autonomous settings, it also discusses remote monitoring, secure containment, and fail-safes. These are approaches being pursued, not proof that meaningful supervision is solved for every advanced system. OpenAI’s safety and alignment overview
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The sources describe a portfolio of approaches rather than one technique that guarantees safe behavior. Examples include:
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- Training with human feedback. OpenAI’s alignment research overview
- Using AI systems to help people evaluate model outputs. OpenAI’s alignment research overview
- Scalable oversight and methods intended to keep systems responsive to human direction. OpenAI’s safety and alignment overview · International AI Safety Report 2026
- Interpretability, evaluation, monitoring, and anomaly detection. International AI Safety Report 2026
The International AI Safety Report characterizes alignment as an open scientific problem and the emerging field of AI control as nascent. A method’s usefulness therefore depends on what it has been tested against and whether it works in the relevant deployment setting; the sources do not establish any listed method as a universal guarantee. International AI Safety Report 2026
Could AI systems evade oversight?
OpenAI’s September 2026 reporting framework lists behavior that evades oversight among examples it aims to disclose. That is a reporting category in one developer’s work-in-progress framework; it should not be read as evidence that advanced AI systems generally can evade oversight, or that such behavior has been established across systems. OpenAI’s framework for reporting model misalignment
Stuart Russell posed a related concern in his 2023 Senate testimony: “How do we maintain power forever over entities more powerful than ourselves?” It is a framing question about control, not a measured forecast or formal definition of AGI risk. 2023 Senate hearing transcript
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