Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 4 of 4
Full-Text Articles in Engineering
Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong
Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong
Faculty Scholarship
To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might …
Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy
Artificial Stupidity: Data We Need To Make Machines Our Equals, Michaël Trazzi, Roman V. Yampolskiy
Faculty Scholarship
AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. The data science community has to work on collecting and aggregating such data in a common and widely available format, so that any AI researcher can easily look up the applicable limit measurements for their latest project. AI must understand human limitations to provide good service and safe interactions. Standardized data on human limits would be valuable in many domains but is not available. Data science community has to work on collecting and …
The Sounds Of Science - A Symphony For Many Instruments And Voices, Gerianne Alexander, Roland E. Allen, Anthony Atala, Warwick P. Bowen, Alan A. Coley, John B. Goodenough, Mikhail I. Katsnelson, Eugene V. Koonin, Mario Krenn, Lars S. Madsen, Martin Månsson, Nicolas P. Mauranyapin, Art I. Melvin, Ernst Rasel, Linda E. Reichl, Roman Yampolskiy, Philip B. Yasskin, Anton Zeilinger, Suzy Lidström
The Sounds Of Science - A Symphony For Many Instruments And Voices, Gerianne Alexander, Roland E. Allen, Anthony Atala, Warwick P. Bowen, Alan A. Coley, John B. Goodenough, Mikhail I. Katsnelson, Eugene V. Koonin, Mario Krenn, Lars S. Madsen, Martin Månsson, Nicolas P. Mauranyapin, Art I. Melvin, Ernst Rasel, Linda E. Reichl, Roman Yampolskiy, Philip B. Yasskin, Anton Zeilinger, Suzy Lidström
Faculty Scholarship
Sounds of Science is the first movement of a symphony for many (scientific) instruments and voices, united in celebration of the frontiers of science and intended for a general audience. John Goodenough, the maestro who transformed energy usage and technology through the invention of the lithium-ion battery, opens the programme, reflecting on the ultimate limits of battery technology. This applied theme continues through the subsequent pieces on energy-related topics - the sodium-ion battery and artificial fuels, by Martin Månsson - and the ultimate challenge for 3D printing, the eventual production of life, by Anthony Atala. A passage by Gerianne Alexander …
Modeling And Counteracting Exposure Bias In Recommender Systems, Sami Khenissi, Olfa Nasraoui
Modeling And Counteracting Exposure Bias In Recommender Systems, Sami Khenissi, Olfa Nasraoui
Faculty Scholarship
What we discover and see online, and consequently our opinions and decisions, are becoming increasingly affected by automated machine learned predictions. Similarly, the predictive accuracy of learning machines heavily depends on the feedback data that we provide them. This mutual influence can lead to closed-loop interactions that may cause unknown biases which can be exacerbated after several iterations of machine learning predictions and user feedback. Machine-caused biases risk leading to undesirable social effects ranging from polarization to unfairness and filter bubbles. In this paper, we study the bias inherent in widely used recommendation strategies such as matrix factorization. Then we …