Research Priorities for Robust and Beneficial Artificial Intelligence
Name
Research priorities for robust.pdf
Size
866 KB
Format
Adobe PDF
Checksum (MD5)
541651948a2e3e9ba9167b73429c1b11
Author(s)
Russell, Stuart
Tegmark, Max Erik
Dewey, Dan
Date Issued
December 2015
Journal
AI Magazine
Publisher
Association for the Advancement of Artificial Intelligence
Citation
Russell, Stuart; Dewey, Daniel and Tegmark, Max Erik. "Research Priorities for Robust and Beneficial Artificial Intelligence." AI Magazine 36, no. 4 (December 2015): 105-114. © 2015 Association for the Advancement of Artificial Intelligence.
Version
Final published version
Abstract
Artificial intelligence (AI) research has explored a variety of problems and approaches since its inception, but for the last 20 years or so has been focused on the problems surrounding the construction of intelligent agents —systems that perceive and act in some environment. In this context, the criterion for intelligence is related to statistical and economic notions of rationality — colloquially, the ability to make good decisions, plans, or inferences. The adoption of probabilistic representations and statistical learning
methods has led to a large degree of integration and cross-fertilization between AI, machine learning, statistics, control theory, neuroscience, and other fields. The establishment of shared theoretical frameworks, combined with the availability of data and processing power, has yielded remarkable suc-
cesses in various component tasks such as speech recognition, image classification, autonomous vehicles, machine translation, legged locomotion, and question-answering systems.
MIT Department
Massachusetts Institute of Technology. Department of Physics
MIT Kavli Institute for Astrophysics and Space Research
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://aaai.org/ojs/index.php/aimagazine/article/view/2577/2521
