31 citations · 85 across the 12 of their papers we have counts for
12 papers
Concept Extrapolation: A Conceptual Primer
Matija Franklin, Rebecca Gorman, Hal Ashton +1
This article is a primer on concept extrapolation - the ability to take a concept, a feature, or a goal that is defined in one context and extrapolate it safely to a more general c…
Recognising the importance of preference change: A call for a coordinated multidisciplinary research effort in the age of AI
Matija Franklin, Hal Ashton, Rebecca Gorman +1
As artificial intelligence becomes more powerful and a ubiquitous presence in daily life, it is imperative to understand and manage the impact of AI systems on our lives and decisi…
The dangers in algorithms learning humans' values and irrationalities
Rebecca Gorman, Stuart Armstrong
For an artificial intelligence (AI) to be aligned with human values (or human preferences), it must first learn those values. AI systems that are trained on human behavior, risk mi…
Sigmoids behaving badly: why they usually cannot predict the future as well as they seem to promise
Anders Sandberg, Stuart Armstrong, Rebecca Gorman +1
Sigmoids (AKA s-curves or logistic curves) are commonly used in a diverse spectrum of disciplines as models for time-varying phenomena showing initial acceleration followed by slow…
Chess as a Testing Grounds for the Oracle Approach to AI Safety
James D. Miller, Roman Yampolskiy, Olle Haggstrom +1
To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical m…
Counterfactual equivalence for POMDPs, and underlying deterministic environments
Stuart Armstrong
Partially Observable Markov Decision Processes (POMDPs) are rich environments often used in machine learning. But the issue of information and causal structures in POMDPs has been…