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The development of Artificial General Intelligence (AGI) promises to be a major event.
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Daniel Dennett · 1990
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Roger Penrose · 1994
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“Reinforcement Learning: An Introduction”
Richard Sutton and Andrew Barto · 1998
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“Algorithms for inverse reinforcement learning”
Andrew Ng and Stuart Russell · 2000
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“The emotional dog and its rational tail: a social intuitionist approach to moral judgment”
Jonathan Haidt · 2001
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“Forecasting the growth of complexity and change”
Theodore Modis · 2002
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“The AI-Box Experiment”, 2002
Eliezer Yudkowsky · 2002
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“Reasoning with Limited Resources and Assigning Probabilities to Arithmetical Statements”
Haim Gaifman · 2004
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“Universal Artificial Intelligence”
Marcus Hutter · 2005
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“The Singularity Is Near”
Ray Kurzweil · 2005
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“The Singularity Myth”
Theodore Modis · 2006
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“An application of reinforcement learning to aerobatic helicopter flight”
Pieter Abbeel, Adam Coates, Morgan Quigley and Andrew Ng · 2007
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“A Collection of Definitions of Intelligence”
Shane Legg and Marcus Hutter · 2007
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“Universal Intelligence: A definition of machine intelligence”
Shane Legg and Marcus Hutter · 2007
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“The Nature of Self-Improving Artificial Intelligence”
Stephen Omohundro · 2007
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“Godel Machines: Self-Referential Universal Problem Solvers Making Provably Optimal Self-Improvements”
Jürgen Schmidhuber · 2007
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“An “Ethical” Game-Theoretic Solution Concept for Two-Player Perfect-Information Games”
Joshua Letchford, Vincent Conitzer and Kamal Jain · 2008
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“The Basic AI Drives”
Stephen Omohundro · 2008
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“Moral Machines”
Wendell Wallach and Collin Allen · 2008
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“Artificial Intelligence as a Positive and Negative Factor in Global Risk”
Eliezer Yudkowsky · 2008
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“Hard Takeoff”
Eliezer Yudkowsky · 2008
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“Maximum Entropy Inverse Reinforcement Learning.”
Brian. Ziebart, Andrew Maas, J. Bagnell and Anind. Dey · 2008
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“Value is Fragile”
Eliezer Yudkowsky · 2009
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“How long until human-level AI? Results from an expert assessment”
Seth. Baum, Ben Goertzel and Ted. Goertzel · 2010
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“The singularity: A philosophical analysis”
David Chalmers · 2010
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“Inverse Reinforcement Learning in Partially Observable Environments”
Jaedung Choi and Kee-Eung Kim · 2011
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“The Neural Net Tank Urban Legend”, 2011
Gwern · 2011
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“Thinking, Fast and Slow”
Daniel Kahneman · 2011
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“Self-modification and mortality in artificial agents”
Laurent Orseau and Mark Ring · 2011
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“Delusion, Survival, and Intelligent Agents”
Mark Ring and Laurent Orseau · 2011
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“Thinking inside the box: Controlling and using an oracle AI”
Stuart Armstrong, Anders Sandberg and Nick Bostrom · 2012
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“The superintelligent will: Motivation and instrumental rationality in advanced artificial agents”
Nick Bostrom · 2012
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“Model-based Utility Functions”
Bill Hibbard · 2012
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Marcus Hutter · 2012
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“One Decade of Universal Artificial Intelligence”
Marcus Hutter · 2012
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“Space-time embedded intelligence”
Laurent Orseau and Mark Ring · 2012
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“Existential Risk Prevention as Global Priority”
Nick Bostrom · 2013
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“Algorithmic Progress in Six Domains”, 2013
Katja Grace · 2013
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“Intriguing properties of neural networks”, 2013, pp. 1–10
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian. Goodfellow and Rob Fergus · 2013
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“Superintelligence: Paths, Dangers, Strategies”
Nick Bostrom · 2014
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“Limitations and risks of machine ethics”
Miles Brundage · 2014
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“Approval-directed agents”
Paul Christiano · 2014
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“Ethical guidelines for a superintelligence”
Ernest Davis · 2014
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“Problems of self-reference in self-improving space-time embedded intelligence”
Benya Fallenstein and Nate Soares · 2014
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“Explaining and Harnessing Adversarial Examples”, 2014
Ian. Goodfellow, Jonathon Shlens and Christian Szegedy · 2014
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“Program Equilibrium in the Prisoner’s Dilemma via Löb’s Theorem”
Patrick LaVictoire, Benya Fallenstein, Eliezer Yudkowsky, Mihaly Barasz, Paul Christiano and Marcello Herreshoff · 2014
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“Teleporting universal intelligent agents”
Laurent Orseau · 2014
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“The multi-slot framework: A formal model for multiple, copiable AIs”
Laurent Orseau · 2014
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“Universal Knowledge-seeking Agents”
Laurent Orseau · 2014
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“Aligning Superintelligence with Human Interests: A Technical Research Agenda”, 2014
Nate Soares and Benya Fallenstein · 2014
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“Responses to catastrophic AGI risk: a survey”
Kaj Sotala and Roman Yampolskiy · 2014
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“Motivated Value Selection for Artificial Agents”
Stuart Armstrong · 2015
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“Davis on AI capability and motivation”
Rob Bensinger · 2015
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“Concrete approval-directed agents”
Paul Christiano · 2015
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“MDL Intelligence Distillation: Exploring strategies for safe access to superintelligent problem-solving capabilities”, 2015
K Drexler · 2015
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“Sequential Extensions of Causal and Evidential Decision Theory”
Tom Everitt, Jan Leike and Marcus Hutter · 2015
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“Proof-producing reflection for HOL with an application to model polymorphism”
Benya Fallenstein and Ramana Kumar · 2015
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“Vingean Reflection: Reliable Reasoning for Self-Improving Agents Vingean Reflection”, 2015
Benya Fallenstein and Nate Soares · 2015
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“A Comprehensive Survey on Safe Reinforcement Learning”
Javier García and Fernando Fernández · 2015
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“Reasons without Persons: Rationality, Identity, and Time”
Brian Hedden · 2015
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“An Empirical Evaluation of Deep Learning on Highway Driving”, 2015
Brody Huval et al · 2015
Cited alongside, same era.
“Human-level control through deep reinforcement learning”
Volodymyr Mnih et al · 2015
Cited alongside, same era.
“AGI Risk and Friendly AI Policy Solutions”, 2015, pp. 1–16
Chris Nota · 2015
Cited alongside, same era.
“Questions of Reasoning Under Logical Uncertainty”, 2015
Nate Soares and Benya Fallenstein · 2015
Cited alongside, same era.
“Corrigibility”
Nate Soares, Benya Fallenstein, Eliezer Yudkowsky and Stuart Armstrong · 2015
Cited alongside, same era.
“Rainbow: Combining Improvements in Deep Reinforcement Learning”, 2017
Matteo Hessel, Joseph Modayil, Hado van Hasselt, Tom Schaul, Georg Ostrovski, Will Dabney, Dan Horgan, Bilal Piot, Mohammad Azar and David Silver · 2017
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“Artificial Intelligence: Calling on Policy Makers to Take a Leading Role in Setting a Long-Term AI Strategy”, 2017
IEEE · 2017
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“Safety and Beneficence of Artificial General Intelligence (AGI) and Artificial Superintelligence (ASI)”, 2017
IEEE · 2017
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“Artificial Intelligence The Public Policy Opportunity”, 2017
Intel · 2017
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“ISO/IEC JTC 1/SC 42”, 2017
ISO/IEC · 2017
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“Conceptual-Linguistic Superintelligence”
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“Reinforcement Learning As a Framework for Ethical Decision Making”
David Abel, James Macglashan and Michael Littman · 2016
Cited alongside, same era.
“The Obama Administration’s Roadmap for AI Policy”
Ajay Agrawal, Joshua Gans and Avi Goldfarb · 2016
Cited alongside, same era.
“Superintelligence cannot be contained: Lessons from Computability Theory”, 2016
Manuel Alfonseca, Manuel Cebrian, Antonio Anta, Lorenzo Coviello, Andres Abeliuk and Iyad Rahwan · 2016
Cited alongside, same era.
“Concrete Problems in AI Safety”, 2016, pp. 1–29
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman and Dan Mané · 2016
Cited alongside, same era.
“Racing to the Precipice: A Model of Artificial Intelligence Development”
Stuart Armstrong, Nick Bostrom and Carl Shulman · 2016
Cited alongside, same era.
“End to End Learning for Self-Driving Cars”, 2016
Mariusz Bojarski et al · 2016
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David Jilk · 2017
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“Anthropomorphic reasoning about neuromorphic AGI safety”
David Jilk, Seth Herd, Stephen Read and Randall Reilly · 2017
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“Reluplex: An efficient SMT solver for verifying deep neural networks”
Guy Katz, Clark Barrett, David. Dill, Kyle Julian and Mykel. Kochenderfer · 2017
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“Learning a commonsense moral theory”
Max Kleiman-Weiner, Rebecca Saxe and Joshua Tenenbaum · 2017
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“Universal Paperclips”
Frank Lantz · 2017
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Jan Leike, Miljan Martic, Victoria Krakovna, Pedro. Ortega, Tom Everitt, Andrew Lefrancq, Laurent Orseau and Shane Legg · 2017
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“Should robots be obedient?”
Smitha Milli, Dylan Hadfield-Menell, Anca Dragan and Stuart Russell · 2017
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“Stoic ethics for artificial agents”
Gabriel Murray · 2017
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“AI: Intelligent Machines, Smart Policies”, 2017
OECD · 2017
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“Feature Visualization: How neural networks build up their understanding of images”
Chris Olah, Alexander Mordvintsev and Ludwig Schubert · 2017
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“New Generation of Artificial Intelligence Development Plan”, 2017
PRC State Council · 2017
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“CS 333: Safe and Interactive Robotics”
Dorsa Sadigh · 2017
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“Robust Computer Algebra, Theorem Proving, and Oracle AI”
Gopal Sarma and Nick Hay · 2017
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“AI Safety and Reproducibility: Establishing Robust Foundations for the Neuroscience of Human Values”, 2017
Gopal. Sarma, Nick. Hay and Adam Safron · 2017
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“Trial without Error: Towards Safe Reinforcement Learning via Human Intervention”, 2017
William Saunders, Girish Sastry, Andreas Stuhlmüller and Owain Evans · 2017
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“Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm”, 2017
David Silver et al · 2017
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“Mastering the game of Go without human knowledge”
David Silver et al · 2017
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“Agent Foundations for Aligning Machine Intelligence with Human Interests: A Technical Research Agenda”
Nate Soares and Benya Fallenstein · 2017
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“How feasible is the rapid development of artificial superintelligence?”
Kaj Sotala · 2017
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“Superintelligence as a Cause or Cure for Risks of Astronomical Suffering Suffering risks as risks of extreme severity”
Kaj Sotala and Lukas Gloor · 2017
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“A Berkeley View of Systems Challenges for AI”, 2017
Ion Stoica et al · 2017
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“Two winds are blowing through Japan”
Heizo Takenaka · 2017
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“Life 3.0”
Max Tegmark · 2017
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“Building Safe A.I: A Tutorial for Encrypted Deep Learning”
Andrew Trask · 2017
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“Science and Technology Select Committee Report on Robots and Artificial Intelligence”, 2017
UK Parliament · 2017
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“Now it’s personal: South Korea calls to arms in AI race after Go Master felled by AlphaGo”
David Volodzsko · 2017
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“A Game-Theoretic Analysis of the Off-Switch Game”
Tobias Wängberg, Mikael Böörs, Elliot Catt, Tom Everitt and Marcus Hutter · 2017
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“Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces”, 2017
Garrett Warnell, Nicholas Waytowich, Vernon Lawhern and Peter Stone · 2017
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“The Singularity May Be Near”, 2017
Roman Yampolskiy · 2017
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“Security Mindset and Ordinary Paranoia”
Eliezer Yudkowsky · 2017
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“Functional Decision Theory: A New Theory of Instrumental Rationality”, 2017
Eliezer Yudkowsky and Nate Soares · 2017
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“Recent trend in the cost of computing”, 2018
AI Impacts · 2018
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“Trends in algorithmic progress”, 2018
AI Impacts · 2018
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“AI and Compute”
Dario Amodei and Fanny Hernandez · 2018
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“Reflective stability”, 2018
Arbital · 2018
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“The “big red button” is too late: an alternative model for the ethical evaluation of AI systems”
Thomas Arnold and Matthias Scheutz · 2018
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“The Malicious Use of Artificial Intelligence: Forecasting, Prevention, and Mitigation”, 2018
Miles Brundage, Shahar Avin, Jack Clark, Gregory Allen, Carrick Flynn, Sebastian Farquhar, Rebecca Crootof and Joanna Bryson · 2018
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“Incorrigibility in the CIRL Framework”
Ryan Carey · 2018
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“An AI Race for Strategic Advantage: Rhetoric and Risks”
Stephen Cave and Seán ÓhÉigeartaigh · 2018
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“Iterated Distillation and Amplification”
Ajeya Cotra · 2018
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“Chinese firms enter the battle for AI talent”
David Cyranoski · 2018
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“Deciphering China’s AI Dream”, 2018
Jeffrey Ding · 2018
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“AI Progress Measurement”, 2018
Peter Eckersley and Yomna Nasser · 2018
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“Regulating Artificial Intelligence Proposal for a Global Solution”
Olivia Erdelyi and Judy Goldsmith · 2018
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“The Alignment Problem for Bayesian History-Based Reinforcement Learners”
Tom Everitt and Marcus Hutter · 2018
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“Universal Artificial Intelligence: Practical Agents and Fundamental Challengs”
Tom Everitt and Marcus Hutter · 2018
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“AGI Safety Literature Review”
Tom Everitt, Gary Lea and Marcus Hutter · 2018
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“MIT 6.S099: Artificial General Intelligence”, 2018
Lex Fridman · 2018
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“Artificial Intelligence: The Race Is On”
FTI Consulting · 2018
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“Incomplete Contracting and AI Alignment”, 2018
Dylan Hadfield-Menell and Gillian Hadfield · 2018
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“Bias in AI: How we Build Fair AI Systems and Less-Biased Humans”
IBM · 2018
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“Deep Reinforcement Learning Doesn’t Work Yet”
Alex Irpan · 2018
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Geoffrey Irving, Paul Christiano and Dario Amodei · 2018
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“China’s AI Agenda Advances”
Elsa Kania · 2018
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Joel Lehman et al · 2018
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“Psychlab: A Psychology Laboratory for Deep Reinforcement Learning Agents”, 2018
Joel. Leibo et al · 2018
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“Categorizing Variants of Goodhart’s Law”, 2018
David Manheim and Scott Garrabrant · 2018
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“As China Marches Forward on A.I., the White House Is Silent”
Cade Metz · 2018
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Hannah Miller, André Petheram and Emma Martinho-Truswell · 2018
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Nolan Shaw, Andreas Stöckel, Ryan Orr, Thomas Lidbetter and Robin Cohen · 2018
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“Disjunctive Scenarios of AI Risk”
Kaj Sotala · 2018
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Alexey Turchin · 2018
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“Human-aligned artificial intelligence is a multiobjective problem”
Peter Vamplew, Richard Dazeley, Cameron Foale, Sally Firmin and Jane Mummery · 2018
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“Making the most of robotics and artificial intelligence in Europe”
Andrus Ansip · 2019
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