A Lack of Uncertainty Impacts Learning in Adults

Healthy aging can lead to impairments in learning that affect many laboratory and real-life tasks. These tasks often involve the acquisition of dynamic contingencies, which requires adjusting the rate of learning to environmental statistics. For example, learning rate should increase when expectations are uncertain (uncertainty), outcomes are surprising (surprise) or contingencies are more likely to change (hazard rate). In this study, we combine computational modelling with an age-comparativ...

 Our Algorithms Must Continue Evolving

Actually, if cloud algorithms ever seem to come to rest and need little tending, that should be taken as a danger sign. In that eventuality, stasis would be an indication that people have allowed themselves to be overly defined and guided by old software and have stopped changing, or to put it another way, have stopped living fully. Living languages ought to require continued examples from living people in order for automated translation services to stay up to date. If the cloud has learned a...

 The Problem of Machine-Aggregated Knowledge

he nuts and bolts of artificial-intelligence research can often be more usefully interpreted without the concept of AI at all. For example, in 2011, IBM scientists unveiled a “question answering” machine that is designed to play the TV quiz show Jeopardy. Suppose IBM had dispensed with the theatrics, and declared it had done Google one better and come up with a new phrase-based search engine. This framing of exactly the same technology would have gained IBM’s team as much (deserved) recogniti...

 AI's and Algorithms Take Away Our Sense of Responsibility

the very idea of artificial intelligence gives us the cover to avoid accountability by pretending that machines can take on more and more human responsibility. This holds for things that we don