Causal Bayesian Networks: A flexible tool to enable fairer machine learning
Decisions based on machine learning (ML) are potentially advantageous over human decisions, but the data used to train them often contains human and societal biases that can lead to harmful decisions.
Episode 8: Demis Hassabis – The interview
In this special extended episode, Hannah meets Demis Hassabis, the CEO and co-founder of DeepMind.
Episode 7: Towards the future
AI researchers around the world are trying to create a general purpose learning system that can learn to solve a broad range of problems without being taught how. Hannah explores the journey to get there.
Replay in biological and artificial neural networks
Our waking and sleeping lives are punctuated by fragments of recalled memories: a sudden connection in the shower between seemingly disparate thoughts, or an ill-fated choice decades ago that haunts us as we struggle to fall asleep.
Episode 6: AI for everyone
Hannah investigates the more human side of the technology, some ethical issues around how it is developed and used, and the efforts to create a future of AI that works for everyone.
Episode 5: Out of the lab
Hannah Fry meets the scientists building systems that could be used to save the sight of thousands; help us solve one of the most fundamental problems in biology, and reduce energy consumption in an effort to combat climate change.
Episode 4: AI, Robot
Forget what sci-fi has told you about superintelligent robots that are uncannily human-like; the reality is more prosaic. Inside DeepMinds robotics laboratory, Hannah explores what researchers call embodied AI.