On Ensuring that Intelligent Machines Are Well-Behaved

@article{Thomas2017OnET,
  title={On Ensuring that Intelligent Machines Are Well-Behaved},
  author={Philip S. Thomas and Bruno Castro da Silva and Andrew G. Barto and Emma Brunskill},
  journal={CoRR},
  year={2017},
  volume={abs/1708.05448}
}
Machine learning algorithms are everywhere, ranging from simple data analysis and pattern recognition tools used across the sciences to complex systems that achieve super-human performance on various tasks. Ensuring that they are well-behaved— that they do not, for example, cause harm to humans or act in a racist or sexist way—is therefore not a hypothetical problem to be dealt with in the future, but a pressing one that we address here. We propose a new framework for designing machine learning… CONTINUE READING
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