Success in the quest for artificial intelligence has the potential to bring
unprecedented benefits to humanity, and it is therefore worthwhile to
investigate how to maximize these benefits while avoiding potential pitfalls.
This article gives numerous examples (which should by no means be construed as
an exhaustive list) of such worthwhile research aimed at ensuring that AI
remains robust and beneficial.Comment: This article gives examples of the type of research advocated by the
  open letter for robust & beneficial AI at
  http://futureoflife.org/ai-open-lette

Dewey, Daniel

Russell, Stuart

Tegmark, Max

AI Magazine

English

arXiv

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

Tegmark, Max Erik

Dewey, Dan

DSpace@MIT

Research Priorities for Robust and Beneficial Artificial Intelligence

Success in the quest for artificial intelligence has the potential to bring unprecedented benefits to humanity, and it is therefore worthwhile to investigate how to maximize these benefits while avoiding potential pitfalls. This article gives numerous examples (which should by no means be construed as an exhaustive list) of such worthwhile research aimed at ensuring that AI remains robust and beneficial.</jats:p

Stuart Russell

Daniel Dewey

Max Tegmark

Crossref

Research Priorities for Robust and Beneficial Artificial Intelligence

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