Corpus ID: 221818767

Hidden Incentives for Auto-Induced Distributional Shift

@article{Krueger2020HiddenIF,
  title={Hidden Incentives for Auto-Induced Distributional Shift},
  author={David Krueger and Tegan Maharaj and Jan Leike},
  journal={ArXiv},
  year={2020},
  volume={abs/2009.09153}
}
Decisions made by machine learning systems have increasing influence on the world, yet it is common for machine learning algorithms to assume that no such influence exists. An example is the use of the i.i.d. assumption in content recommendation. In fact, the (choice of) content displayed can change users' perceptions and preferences, or even drive them away, causing a shift in the distribution of users. We introduce the term auto-induced distributional shift (ADS) to describe the phenomenon of… Expand
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