Fetching the paper…
Reading the bibliography…
Advances in artificial intelligence (AI) are shaping modern life, from transportation, health care, science, finance, to national defense.
Forecasting transformative AI: An expert survey
R. Gruetzemacher, D. Paradice, and K. B. Lee · 1901
Earlier work this paper cites.
Evaluating methods for modeling and aggregating continuous distributions of forecaster belief
J. Tidwell · 1903
Earlier work this paper cites.
Before and beyond the anticipatory intelligence: Assessing the potential for crowdsourcing and intelligence studies
A. Halman · 1944
Earlier work this paper cites.
Smoothing parameter selection in nonparametric regression using an improved akaike information criterion
C. M. Hurvich, J. S. Simonoff, and C.-L. Tsai · 1998
Earlier work this paper cites.
Expert Political Judgment: How Good Is It? How Can We Know?
P. E. Tetlock · 2006
Earlier work this paper cites.
Robust tests for the equality of variances for clustered data
I. Iachine, H. C. Petersen, and K. O. Kyvik · 2010
Earlier work this paper cites.
Two reasons to make aggregated probability forecasts more extreme
J. Baron, B. A. Mellers, P. E. Tetlock, E. Stone, and L. H. Ungar · 2014
Earlier work this paper cites.
Revisiting francis galton’s forecasting competition
K. F. Wallis · 2014
Earlier work this paper cites.
Superforecasting: The Art and Science of Prediction
P. E. Tetlock and D. Gardner · 2015
Earlier work this paper cites.
No, the experts don’t think superintelligent AI is a threat to humanity, September 2016
O. Etzioni · 2016
Earlier work this paper cites.
Future progress in artificial intelligence: A survey of expert opinion
V. C. Müller and N. Bostrom · 2016
Earlier work this paper cites.
Efficiently encoding and modeling subjective probability distributions for quantitative variables
T. S. Wallsten, Y. Shlomi, C. Nataf, and T. Tomlinson · 2016
Earlier work this paper cites.
Nonparametric combination (NPC): A framework for testing elaborate theories
D. Caughey, A. Dafoe, and J. Seawright · 2017
Cited alongside, same era.
EFF AI Progress Measurement Project, (2017-), 2017
P. Eckersley, Y. Nasser, Y. Bayle, O. Evans, G. Gebhart, and D. Schwenk · 2017
Cited alongside, same era.
AI and compute, May 2018
D. Amodei, D. Hernandez, G. Sastry, J. Clark, G. Brockman, and I. Sutskever · 2018
Cited alongside, same era.
When will AI exceed human performance? evidence from ai experts
K. Grace, J. Salvatier, A. Dafoe, B. Zhang, and O. Evans · 2018
Cited alongside, same era.
Dual indicators to analyze ai benchmarks: Difficulty, discrimination, ability, and generality
F. Martínez-Plumed and J. Hernández-Orallo · 2018
Cited alongside, same era.
Expert and non-expert opinion about technological unemployment
T. Walsh · 2018
Language models are few-shot learners
T. B. Brown, B. Mann, N. Ryder, M. Subbiah, J. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, S. Agarwal, A. Herbert-Voss, G. Krueger, T. Henighan, R. Child, A. Ramesh, D. M. Ziegler, J. Wu, C. Winter, C. Hesse, M. Chen, E. Sigler, M. Litwin, S. Gray, B. Chess, J. Clark, C. Berner, S. McCandlish, A. Radford, I. Sutskever, and D. Amodei · 2020
Later among the works it cites.
A better crystal ball: The right way to think about the future
J. P. Scoblic and P. E. Tetlock · 2020
Later among the works it cites.
QES: Eliciting and modeling probability forecasts of continuous quantities, Jan 2020
J. Tidwell, T. S. Wallsten, and D. A. Moore · 2020
Later among the works it cites.
Forecasting ai progress: A research agenda
R. Gruetzemacher, F. E. Dorner, N. Bernaola-Alvarez, C. Giattino, and D. Manheim · 2021
Later among the works it cites.
Scaling language models: Methods, analysis & insights from training gopher, 2021
J. W. Rae, S. Borgeaud, T. Cai, K. Millican, J. Hoffmann, F. Song, J. Aslanides, S. Henderson, R. Ring, S. Young, E. Rutherford, T. Hennigan, J. Menick, A. Cassirer, R. Powell, G. v. d. Driessche, L. A. Hendricks, M. Rauh, P.-S. Huang, A. Glaese, J. Welbl, S. Dathathri, S. Huang, J. Uesato, J. Mellor, I. Higgins, A. Creswell, N. McAleese, A. Wu, E. Elsen, S. Jayakumar, E. Buchatskaya, D. Budden, E. Sutherland, K. Simonyan, M. Paganini, L. Sifre, L. Martens, X. L. Li, A. Kuncoro, A. Nematzadeh, E. Gribovskaya, D. Donato, A. Lazaridou, A. Mensch, J.-B. Lespiau, M. Tsimpoukelli, N. Grigorev, D. Fritz, T. Sottiaux, M. Pajarskas, T. Pohlen, Z. Gong, D. Toyama, C. d. M. d’Autume, Y. Li, T. Terzi, V. Mikulik, I. Babuschkin, A. Clark, D. d. L. Casas, A. Guy, C. Jones, J. Bradbury, M. Johnson, B. Hechtman, L. Weidinger, I. Gabriel, W. Isaac, E. Lockhart, S. Osindero, L. Rimell, C. Dyer, O. Vinyals, K. Ayoub, J. Stanway, L. Bennett, D. Hassabis, K. Kavukcuoglu, and G. Irving · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Superhuman ai for multiplayer poker
N. Brown and T. Sandholm · 2019
Cited alongside, same era.
BERT: Pre-training of deep bidirectional transformers for language understanding
J. Devlin, M.-W. Chang, K. Lee, and K. Toutanova · 2019
Cited alongside, same era.
Grandmaster level in StarCraft II using multi-agent reinforcement learning
O. Vinyals, I. Babuschkin, W. M. Czarnecki, M. Mathieu, A. Dudzik, J. Chung, D. H. Choi, R. Powell, T. Ewalds, P. Georgiev, J. Oh, D. Horgan, M. Kroiss, I. Danihelka, A. Huang, L. Sifre, T. Cai, J. P. Agapiou, M. Jaderberg, A. S. Vezhnevets, R. Leblond, T. Pohlen, V. Dalibard, D. Budden, Y. Sulsky, J. Molloy, T. L. Paine, C. Gulcehre, Z. Wang, T. Pfaff, Y. Wu, R. Ring, D. Yogatama, D. Wünsch, K. McKinney, O. Smith, T. Schaul, T. Lillicrap, K. Kavukcuoglu, D. Hassabis, C. Apps, and D. Silver · 2019
Cited alongside, same era.
Strengthening the U.S. AI Workforce: A Policy and Research Agenda
R. Zwetsloot, R. Heston, and Z. Arnold · 2019
Cited alongside, same era.
Agent57: Outperforming the atari human benchmark
A. P. Badia, B. Piot, S. Kapturowski, P. Sprechmann, A. Vitvitskyi, Z. D. Guo, and C. Blundell · 2020
Cited alongside, same era.
Hardware and AI Timelines
AI Impacts
Cited in the paper.
Later among the works it cites.
Why and how governments should monitor AI development, 2021
J. Whittlestone and J. Clark · 2021
Later among the works it cites.
Phy-q: A benchmark for physical reasoning
C. Xue, V. Pinto, C. Gamage, E. Nikonova, P. Zhang, and J. Renz · 2021
Later among the works it cites.
The AI index 2021 annual report
D. Zhang, S. Mishra, E. Brynjolfsson, J. Etchemendy, D. Ganguli, B. Grosz, T. Lyons, J. Manyika, J. C. Niebles, M. Sellitto, et al · 2021
Later among the works it cites.
Skilled and mobile: Survey evidence of ai researchers’ immigration preferences
R. Zwetsloot, B. Zhang, N. Dreksler, L. Kahn, M. Anderljung, A. Dafoe, and M. C. Horowitz · 2021
Later among the works it cites.
AI birds.org Angry Birds AI Competition, 2022
A. Birds · 2022
Closest in time.
Democratising risk: In search of a methodology to study existential risk
C. Z. Cremer and L. Kemp · 2022
Closest in time.