Search Results for author: Emma Bluemke

Found 7 papers, 1 papers with code

Visibility into AI Agents

no code implementations23 Jan 2024 Alan Chan, Carson Ezell, Max Kaufmann, Kevin Wei, Lewis Hammond, Herbie Bradley, Emma Bluemke, Nitarshan Rajkumar, David Krueger, Noam Kolt, Lennart Heim, Markus Anderljung

Increased delegation of commercial, scientific, governmental, and personal activities to AI agents -- systems capable of pursuing complex goals with limited supervision -- may exacerbate existing societal risks and introduce new risks.


Towards Publicly Accountable Frontier LLMs: Building an External Scrutiny Ecosystem under the ASPIRE Framework

no code implementations15 Nov 2023 Markus Anderljung, Everett Thornton Smith, Joe O'Brien, Lisa Soder, Benjamin Bucknall, Emma Bluemke, Jonas Schuett, Robert Trager, Lacey Strahm, Rumman Chowdhury

With the increasing integration of frontier large language models (LLMs) into society and the economy, decisions related to their training, deployment, and use have far-reaching implications.

Exploring the Relevance of Data Privacy-Enhancing Technologies for AI Governance Use Cases

no code implementations15 Mar 2023 Emma Bluemke, Tantum Collins, Ben Garfinkel, Andrew Trask

The development of privacy-enhancing technologies has made immense progress in reducing trade-offs between privacy and performance in data exchange and analysis.

Challenges for machine learning in clinical translation of big data imaging studies

1 code implementation7 Jul 2021 Nicola K Dinsdale, Emma Bluemke, Vaanathi Sundaresan, Mark Jenkinson, Stephen Smith, Ana IL Namburete

The combination of deep learning image analysis methods and large-scale imaging datasets offers many opportunities to imaging neuroscience and epidemiology.

BIG-bench Machine Learning Epidemiology +1

Beyond Privacy Trade-offs with Structured Transparency

no code implementations15 Dec 2020 Andrew Trask, Emma Bluemke, Ben Garfinkel, Claudia Ghezzou Cuervas-Mons, Allan Dafoe

The copy problem is often amplified by three related problems which we term the bundling, edit, and recursive enforcement problems.

Federated Learning Cryptography and Security Computers and Society

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