From Animals to Algorithms: Comparative Psychology for the Study of Artificial Intelligence
type: CreativeWork
description: Artificial Intelligence (AI) systems are becoming increasingly sophisticated, capable of completing complex tasks such as playing games, recognising images, and producing human-like language. The problem is, we often cannot explain nor predict their behaviour. In this interdisciplinary dissertation, I argue that a comparative psychological approach can help. Comparative psychologists have created methodological tools for studying the behaviour of another class of complex system, non-human animals. While many have advocated for conducting behavioural experiments on AI systems, treating them as though they are participants in the laboratory, the value of a comparative psychological approach has been underappreciated (Chapter 1). In Chapter 2, I critique the common practice of developing general benchmarks for studying the capabilities of AI systems to complete certain kinds of task. Comparative psychology can help by offering carefully crafted experimental designs as well as methodological advice for the scientific study of non-human behaviour. In Chapter 3, I introduce the Animal-AI Environment, a platform for conducting behavioural tests inspired by comparative psychology with reinforcement learning agents. In Chapter 4, I present O-PIAAGETS, a benchmark built in the Animal-AI Environment for studying object permanence, the ability to track objects under occlusion. Then, in Chapter 5, I introduce the novel *measurement layout* approach to making more meaningful inferences about the capabilities of AI systems based on how they perform on tasks with different difficulties. In Chapter 6, I present results from the performances of human children and a range of artificial agents on a subset of O-PIAAGETS, including the first application of the measurement layout approach to real behavioural data. In the second part of this dissertation, I examine how alter- native hypotheses for explaining animal behaviour are generated in comparative psychology, drawing lessons for the …
abstract: Artificial Intelligence (AI) systems are becoming increasingly sophisticated, capable of completing complex tasks such as playing games, recognising images, and producing human-like language. The problem is, we often cannot explain nor predict their behaviour. In this interdisciplinary dissertation, I argue that a comparative psychological approach can help. Comparative psychologists have created methodological tools for studying the behaviour of another class of complex system, non-human animals. While many have advocated for conducting behavioural experiments on AI systems, treating them as though they are participants in the laboratory, the value of a comparative psychological approach has been underappreciated (Chapter 1). In Chapter 2, I critique the common practice of developing general benchmarks for studying the capabilities of AI systems to complete certain kinds of task. Comparative psychology can help by offering carefully crafted experimental designs as well as methodological advice for the scientific study of non-human behaviour. In Chapter 3, I introduce the Animal-AI Environment, a platform for conducting behavioural tests inspired by comparative psychology with reinforcement learning agents. In Chapter 4, I present O-PIAAGETS, a benchmark built in the Animal-AI Environment for studying object permanence, the ability to track objects under occlusion. Then, in Chapter 5, I introduce the novel *measurement layout* approach to making more meaningful inferences about the capabilities of AI systems based on how they perform on tasks with different difficulties. In Chapter 6, I present results from the performances of human children and a range of artificial agents on a subset of O-PIAAGETS, including the first application of the measurement layout approach to real behavioural data. In the second part of this dissertation, I examine how alter- native hypotheses for explaining animal behaviour are generated in comparative psychology, drawing lessons for the …
author: Voudouris, Konstantinos
language: eng
keywords: AI Evaluation, Artificial Intelligence, Capability Measurement, Comparative Psychology, Philosophy of Comparative Psychology
license: https://www.repository.cam.ac.uk/bitstreams/82aef309-8662-444e-9fdc-71855fb5673e/download
license: https://www.rioxx.net/licenses/all-rights-reserved/
date published: 2024-03-23
date modified: 2026-07-24T01:33:21Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.112213