736 citations · 1.8k across the 23 of their papers we have counts for
24 papers
Virtual Agent Economies
Nenad Tomasev, Matija Franklin, Joel Z. Leibo +4
The rapid adoption of autonomous AI agents is giving rise to a new economic layer where agents transact and coordinate at scales and speeds beyond direct human oversight. We propos…
Value Profiles for Encoding Human Variation
Taylor Sorensen, Pushkar Mishra, Roma Patel +6
Modelling human variation in rating tasks is crucial for personalization, pluralistic model alignment, and computational social science. We propose representing individuals using n…
Multi-Agent Risks from Advanced AI
Lewis Hammond, Alan Chan, Jesse Clifton +41
The rapid development of advanced AI agents and the imminent deployment of many instances of these agents will give rise to multi-agent systems of unprecedented complexity. These s…
Hedging and Non-Affirmation: Quantifying LLM Alignment on Questions of Human Rights
Rafiya Javed, Cassandra Parent, Jackie Kay +9
Hedging and non-affirmation are behaviors exhibited by large language models (LLMs) that limit the clear endorsement of specific statements. While these behaviors are desirable in…
How will advanced AI systems impact democracy?
Christopher Summerfield, Lisa Argyle, Michiel Bakker +20
Advanced AI systems capable of generating humanlike text and multimodal content are now widely available. In this paper, we discuss the impacts that generative artificial intellige…
Generative AI Misuse: A Taxonomy of Tactics and Insights from Real-World Data
Nahema Marchal, Rachel Xu, Rasmi Elasmar +3
Generative, multimodal artificial intelligence (GenAI) offers transformative potential across industries, but its misuse poses significant risks. Prior research has shed light on t…
The Ethics of Advanced AI Assistants
Iason Gabriel, Arianna Manzini, Geoff Keeling +54
This paper focuses on the opportunities and the ethical and societal risks posed by advanced AI assistants. We define advanced AI assistants as artificial agents with natural langu…
Holistic Safety and Responsibility Evaluations of Advanced AI Models
Laura Weidinger, Joslyn Barnhart, Jenny Brennan +16
Safety and responsibility evaluations of advanced AI models are a critical but developing field of research and practice. In the development of Google DeepMind's advanced AI models…
Sociotechnical Safety Evaluation of Generative AI Systems
Laura Weidinger, Maribeth Rauh, Nahema Marchal +10
Generative AI systems produce a range of risks. To ensure the safety of generative AI systems, these risks must be evaluated. In this paper, we make two main contributions toward e…
Model evaluation for extreme risks
Toby Shevlane, Sebastian Farquhar, Ben Garfinkel +18
Current approaches to building general-purpose AI systems tend to produce systems with both beneficial and harmful capabilities. Further progress in AI development could lead to ca…
Manifestations of Xenophobia in AI Systems
Nenad Tomasev, Jonathan Leader Maynard, Iason Gabriel
Xenophobia is one of the key drivers of marginalisation, discrimination, and conflict, yet many prominent machine learning (ML) fairness frameworks fail to comprehensively measure…
A Human Rights-Based Approach to Responsible AI
Vinodkumar Prabhakaran, Margaret Mitchell, Timnit Gebru +1
Research on fairness, accountability, transparency and ethics of AI-based interventions in society has gained much-needed momentum in recent years. However it lacks an explicit ali…
Improving alignment of dialogue agents via targeted human judgements
Amelia Glaese, Nat McAleese, Maja Trębacz +31
We present Sparrow, an information-seeking dialogue agent trained to be more helpful, correct, and harmless compared to prompted language model baselines. We use reinforcement lear…
Power to the People? Opportunities and Challenges for Participatory AI
Abeba Birhane, William Isaac, Vinodkumar Prabhakaran +4
Participatory approaches to artificial intelligence (AI) and machine learning (ML) are gaining momentum: the increased attention comes partly with the view that participation opens…
In conversation with Artificial Intelligence: aligning language models with human values
Atoosa Kasirzadeh, Iason Gabriel
Large-scale language technologies are increasingly used in various forms of communication with humans across different contexts. One particular use case for these technologies is c…
Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models
Maribeth Rauh, John Mellor, Jonathan Uesato +9
Large language models produce human-like text that drive a growing number of applications. However, recent literature and, increasingly, real world observations, have demonstrated…
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Jack W. Rae, Sebastian Borgeaud, Trevor Cai +77
Language modelling provides a step towards intelligent communication systems by harnessing large repositories of written human knowledge to better predict and understand the world.…
Ethical and social risks of harm from Language Models
Laura Weidinger, John Mellor, Maribeth Rauh +20
This paper aims to help structure the risk landscape associated with large-scale Language Models (LMs). In order to foster advances in responsible innovation, an in-depth understan…
Toward a Theory of Justice for Artificial Intelligence
Iason Gabriel
This paper explores the relationship between artificial intelligence and principles of distributive justice. Drawing upon the political philosophy of John Rawls, it holds that the…
Alignment of Language Agents
Zachary Kenton, Tom Everitt, Laura Weidinger +3
For artificial intelligence to be beneficial to humans the behaviour of AI agents needs to be aligned with what humans want. In this paper we discuss some behavioural issues for la…
Modelling Cooperation in Network Games with Spatio-Temporal Complexity
Michiel A. Bakker, Richard Everett, Laura Weidinger +4
The real world is awash with multi-agent problems that require collective action by self-interested agents, from the routing of packets across a computer network to the management…
The Challenge of Value Alignment: from Fairer Algorithms to AI Safety
Iason Gabriel, Vafa Ghazavi
This paper addresses the question of how to align AI systems with human values and situates it within a wider body of thought regarding technology and value. Far from existing in a…
Beyond Privacy Trade-offs with Structured Transparency
Andrew Trask, Emma Bluemke, Teddy Collins +5
Successful collaboration involves sharing information. However, parties may disagree on how the information they need to share should be used. We argue that many of these concerns…
Artificial Intelligence, Values and Alignment
Iason Gabriel
This paper looks at philosophical questions that arise in the context of AI alignment. It defends three propositions. First, normative and technical aspects of the AI alignment pro…