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Markus Anderljung
Markus Anderljung
Centre for the Governance of AI
Verified email at governance.ai - Homepage
Title
Cited by
Cited by
Year
Toward trustworthy AI development: mechanisms for supporting verifiable claims
M Brundage, S Avin, J Wang, H Belfield, G Krueger, G Hadfield, H Khlaaf, ...
arXiv preprint arXiv:2004.07213, 2020
4752020
Model evaluation for extreme risks
T Shevlane, S Farquhar, B Garfinkel, M Phuong, J Whittlestone, J Leung, ...
arXiv preprint arXiv:2305.15324, 2023
1632023
Frontier AI regulation: Managing emerging risks to public safety
M Anderljung, J Barnhart, A Korinek, J Leung, C O'Keefe, J Whittlestone, ...
arXiv preprint arXiv:2307.03718, 2023
1452023
Foundational challenges in assuring alignment and safety of large language models
U Anwar, A Saparov, J Rando, D Paleka, M Turpin, P Hase, ES Lubana, ...
arXiv preprint arXiv:2404.09932, 2024
1242024
Ethics and governance of artificial intelligence: Evidence from a survey of machine learning researchers
B Zhang, M Anderljung, L Kahn, N Dreksler, MC Horowitz, A Dafoe
Journal of Artificial Intelligence Research 71, 591–666-591–666, 2021
892021
Institutionalizing ethics in AI through broader impact requirements
CEA Prunkl, C Ashurst, M Anderljung, H Webb, J Leike, A Dafoe
Nature Machine Intelligence 3 (2), 104-110, 2021
782021
The Brussels effect and artificial intelligence: How EU regulation will impact the global AI market
C Siegmann, M Anderljung
arXiv preprint arXiv:2208.12645, 2022
732022
Filling gaps in trustworthy development of AI
NZ Shahar Avin, Haydn Belfield, Miles Brundage, Gretchen Krueger, Jasmine ...
Science 374 (6573), pp. 1327-1329, 2021
512021
Towards best practices in AGI safety and governance: A survey of expert opinion
J Schuett, N Dreksler, M Anderljung, D McCaffary, L Heim, E Bluemke, ...
arXiv preprint arXiv:2305.07153, 2023
462023
Computing Power and the Governance of Artificial Intelligence
G Sastry, L Heim, H Belfield, M Anderljung, M Brundage, J Hazell, ...
arXiv preprint arXiv:2402.08797, 2024
442024
Open-sourcing highly capable foundation models: An evaluation of risks, benefits, and alternative methods for pursuing open-source objectives
E Seger, N Dreksler, R Moulange, E Dardaman, J Schuett, K Wei, ...
arXiv preprint arXiv:2311.09227, 2023
442023
Protecting society from AI misuse: when are restrictions on capabilities warranted?
M Anderljung, J Hazell, M von Knebel
AI & SOCIETY, 1-17, 2024
402024
Forecasting AI progress: Evidence from a survey of machine learning researchers
B Zhang, N Dreksler, M Anderljung, L Kahn, C Giattino, A Dafoe, ...
arXiv preprint arXiv:2206.04132, 2022
332022
Towards publicly accountable frontier llms
M Anderljung, E Smith, J O'Brien, L Soder, B Bucknall, E Bluemke, ...
Socially Responsible Language Modelling Research, 2023
26*2023
Open problems in technical ai governance
A Reuel, B Bucknall, S Casper, T Fist, L Soder, O Aarne, L Hammond, ...
arXiv preprint arXiv:2407.14981, 2024
252024
Visibility into AI Agents
A Chan, C Ezell, M Kaufmann, K Wei, L Hammond, H Bradley, E Bluemke, ...
The 2024 ACM Conference on Fairness, Accountability, and Transparency, 958-973, 2024
222024
Social and governance implications of improved data efficiency
AD Tucker, M Anderljung, A Dafoe
Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society, 378-384, 2020
192020
Responsible Reporting for Frontier AI Development
N Kolt, M Anderljung, J Barnhart, A Brass, K Esvelt, GK Hadfield, L Heim, ...
arXiv preprint arXiv:2404.02675, 2024
162024
Model evaluation for extreme risks. 2023
T Shevlane, S Farquhar, B Garfinkel, M Phuong, J Whittlestone, J Leung, ...
Cited on, 27, 0
16
Beyond static AI evaluations: advancing human interaction evaluations for LLM harms and risks
L Ibrahim, S Huang, L Ahmad, M Anderljung
arXiv preprint arXiv:2405.10632, 2024
122024
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