Topic: Algorithmic bias

Anna Truzzi and Luca Pellegrino discuss experiments on a historical antibacterial preparation and the sources of bias in AI systems. An external segment with Ian Scott and Ilaria Zanardi explores elephant communication, including low-frequency sound, long-distance signalling and the evidence for individually distinctive calls.

The possibilities of machine learning and neural networks in particular are ever expanding. With increased opportunities to do good, however there are just as many opportunities to do harm and even in the case that good intentions are at the helm, evidence suggests that opportunities for good may eventually prove to be the opposite. The greatest threat to what machine learning is able to achieve and to us as humans, is machine learning that does not reflect the diversity of the users it is meant to serve. It is important that we are not so pre-occupied with advancing technology into the future