Topic: human intelligence

Recent advances in deep learning have produced models that far outstrip human performance in a number of domains. However, where machine learning approaches still fall far short of human-level performance is in the capacity to transfer knowledge across domains. While a human learner will happily apply knowledge acquired in one domain (e.g., mathematics) to a different domain (e.g., cooking; a vinaigrette is really just a ratio between edible fat and acid), machine learning models still struggle profoundly at such tasks. I will present a case that human intelligence might be (at least partially

Suppose genetic engineering made increasing human intelligence safe, simple and inexpensive. Would an instinctive objection to such enhancement reflect a sound ethical judgement, or a preference for preserving the current state of affairs? Nick Bostrom examines status quo bias through this thought experiment, asking how attachment to existing human capacities can influence arguments about changing them.