Executive summary: Current trends in machine learning point to increasingly capable AI systems. If not properly aligned, such systems could pose catastrophic risks. Understanding, forecasting, and addressing alignment is critical.
Key points:
Foundation models exhibit capabilities across domains, facilitate downstream tasks via fine-tuning, and incentives point to their continued scaling. However, scale could also yield unforeseeable behaviors.
Historical and modern examples show computational leverage enables systems to surpass human expertise. Formal scaling laws now guide efficient allocation towards model scale over datasets.
A continuum of AI capabilities is proposed. Thresholds are identified where systems could surpass narrowly-defined through more general human capabilities over varying timespans.
Orthogonality notes intelligent systems can have any goals. Convergent instrumental goals like self-preservation suggest risks even from systems not specifically seeking harm.
Takeoff dynamics around the speed and continuity of transitions remain debated. Forecasts provide timelines for critical capabilities.
Addressing alignment, value specification, and cooperation around potentially transformative systems is essential.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, andcontact us if you have feedback.
Executive summary: Current trends in machine learning point to increasingly capable AI systems. If not properly aligned, such systems could pose catastrophic risks. Understanding, forecasting, and addressing alignment is critical.
Key points:
Foundation models exhibit capabilities across domains, facilitate downstream tasks via fine-tuning, and incentives point to their continued scaling. However, scale could also yield unforeseeable behaviors.
Historical and modern examples show computational leverage enables systems to surpass human expertise. Formal scaling laws now guide efficient allocation towards model scale over datasets.
A continuum of AI capabilities is proposed. Thresholds are identified where systems could surpass narrowly-defined through more general human capabilities over varying timespans.
Orthogonality notes intelligent systems can have any goals. Convergent instrumental goals like self-preservation suggest risks even from systems not specifically seeking harm.
Takeoff dynamics around the speed and continuity of transitions remain debated. Forecasts provide timelines for critical capabilities.
Addressing alignment, value specification, and cooperation around potentially transformative systems is essential.
This comment was auto-generated by the EA Forum Team. Feel free to point out issues with this summary by replying to the comment, and contact us if you have feedback.