Happiness: what is it? What drives it and how do you measure it?
The Royal Society and Digital Catapult are holding a hackathon on 16-17 January to establish if machine learning can be used to help answer these questions.
But can machine learning be used to understand what makes us happy? Is it possible for machine learning to help increase our wellbeing and happiness?
With participants from Microsoft Research Cambridge and other leading tech organisations, a diverse array of data sets, some of which are previously unpublished, and a judging panel involving Google DeepMind, this promises to be a great event.
Why Machine Learning?
Machine learning has successfully been applied to a range of different questions that we ask every day. It is now part of our daily lives and can be even be found in internet spam filters and voice recognition systems on our phones. There is the wider potential for applications in multiple sectors from healthcare to transport, and education to policing.
Machine Learning is also the subject of a major policy project at the Royal Society, which is looking at the opportunities and challenges associated with this technology, and will make evidence based recommendations for policy makers to help guide the future of this technology in the UK.
The pursuit of happiness and its understanding has absorbed some of our greatest philosophical, psychological, and religious minds since Aristotle’s time; now the Royal Society and the Digital Catapult are joining in this journey.
How do you measure happiness? What drives it? Is it related to GDP? Employment levels? Access to green space?
Participants will be free to apply their creative minds and computer skills to the data of their choice to come up with innovative ways to understand, measure and increase happiness.