71 citations · 291 across the 40 of their papers we have counts for
23 papers · 1 filter
Agentic Economies for Autonomous Scientific Discovery
Nenad Tomasev, Matija Franklin, Atoosa Kasirzadeh +4
Recent advances in agentic Artificial Intelligence (AI) systems have marked a shift in AI for Science: moving away from the use of individual AI systems for narrow task execution,…
The Case for Globally Beneficial Technology
Iason Gabriel, Atoosa Kasirzadeh
To whom do the fruits of advanced technological innovation belong? To their inventors, to the organizations and individuals involved in making such discoveries possible, or to stil…
Bridging the Gap in the Responsible AI Divides
Bálint Gyevnár, Atoosa Kasirzadeh
Tensions between AI Safety (AIS) and AI Ethics (AIE) have created what we term a "responsible AI divide." This divide has been persistent, and has dominated the public and policy d…
International AI Safety Report 2026
Yoshua Bengio, Stephen Clare, Carina Prunkl +89
The International AI Safety Report 2026 synthesises the current scientific evidence on the capabilities, emerging risks, and safety of general-purpose AI systems. The report series…
Legal Alignment for Safe and Ethical AI
Noam Kolt, Nicholas Caputo, Jack Boeglin +14
Alignment of artificial intelligence (AI) encompasses the normative problem of specifying how AI systems should act and the technical problem of ensuring AI systems comply with tho…
AI, Digital Platforms, and the New Systemic Risk
Philipp Hacker, Lilian Edwards, Atoosa Kasirzadeh
As artificial intelligence (AI) becomes increasingly embedded in digital, social, and institutional infrastructures, and AI and platforms are merged into hybrid structures, systemi…
Position: Beyond Sensitive Attributes, ML Fairness Should Quantify Structural Injustice via Social Determinants
Zeyu Tang, Alex John London, Atoosa Kasirzadeh +4
Algorithmic fairness research has largely framed unfairness as discrimination along sensitive attributes. However, this approach limits visibility into unfairness as structural inj…
Characterizing AI Agents for Alignment and Governance
Atoosa Kasirzadeh, Iason Gabriel
The creation of effective governance mechanisms for AI agents requires a deeper understanding of their core properties and how these properties relate to questions surrounding the…
AI Safety for Everyone
Balint Gyevnar, Atoosa Kasirzadeh
Recent discussions and research in AI safety have increasingly emphasized the deep connection between AI safety and existential risk from advanced AI systems, suggesting that work…
A Taxonomy of Systemic Risks from General-Purpose AI
Risto Uuk, Carlos Ignacio Gutierrez, Daniel Guppy +5
Through a systematic review of academic literature, we propose a taxonomy of systemic risks associated with artificial intelligence (AI), in particular general-purpose AI. Followin…
Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work
Aviv Ovadya, Kyle Redman, Luke Thorburn +11
This position paper argues that effectively "democratizing AI" requires democratic governance and alignment of AI, and that this is particularly valuable for decisions with systemi…
Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models
Eddie L. Ungless, Nikolas Vitsakis, Zeerak Talat +5
This whitepaper offers an overview of the ethical considerations surrounding research into or with large language models (LLMs). As LLMs become more integrated into widely used app…
Measurement challenges in AI catastrophic risk governance and safety frameworks
Atoosa Kasirzadeh
Safety frameworks represent a significant development in AI governance: they are the first type of publicly shared catastrophic risk management framework developed by major AI comp…
Explanation Hacking: The perils of algorithmic recourse
Emily Sullivan, Atoosa Kasirzadeh
We argue that the trend toward providing users with feasible and actionable explanations of AI decisions, known as recourse explanations, comes with ethical downsides. Specifically…
Two Types of AI Existential Risk: Decisive and Accumulative
Atoosa Kasirzadeh
The conventional discourse on existential risks (x-risks) from AI typically focuses on abrupt, dire events caused by advanced AI systems, particularly those that might achieve or s…
Typology of Risks of Generative Text-to-Image Models
Charlotte Bird, Eddie L. Ungless, Atoosa Kasirzadeh
This paper investigates the direct risks and harms associated with modern text-to-image generative models, such as DALL-E and Midjourney, through a comprehensive literature review.…
Reconciling Governmental Use of Online Targeting With Democracy
Katja Andric, Atoosa Kasirzadeh
The societal and epistemological implications of online targeted advertising have been scrutinized by AI ethicists, legal scholars, and policymakers alike. However, the government'…
ChatGPT, Large Language Technologies, and the Bumpy Road of Benefiting Humanity
Atoosa Kasirzadeh
The allure of emerging AI technologies is undoubtedly thrilling. However, the promise that AI technologies will benefit all of humanity is empty so long as we lack a nuanced unders…
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…
Algorithmic Fairness and Structural Injustice: Insights from Feminist Political Philosophy
Atoosa Kasirzadeh
Data-driven predictive algorithms are widely used to automate and guide high-stake decision making such as bail and parole recommendation, medical resource distribution, and mortga…
Fairness and Data Protection Impact Assessments
Atoosa Kasirzadeh, Damian Clifford
In this paper, we critically examine the effectiveness of the requirement to conduct a Data Protection Impact Assessment (DPIA) in Article 35 of the General Data Protection Regulat…
Reasons, Values, Stakeholders: A Philosophical Framework for Explainable Artificial Intelligence
Atoosa Kasirzadeh
The societal and ethical implications of the use of opaque artificial intelligence systems for consequential decisions, such as welfare allocation and criminal justice, have genera…
The Use and Misuse of Counterfactuals in Ethical Machine Learning
Atoosa Kasirzadeh, Andrew Smart
The use of counterfactuals for considerations of algorithmic fairness and explainability is gaining prominence within the machine learning community and industry. This paper argues…