Consider the Source: In Whose Interests, and How, of Big, Small and Other Data? Exploring data science through wellth scenarios.

Consider the Source: In Whose Interests, and How, of Big, Small and Other Data? Exploring data science through wellth scenarios.

We're not a particularly healthy culture. Our "normal" practices are not optimised for our wellbeing. From the morning commute to the number of hours we believe we need to put in to complete a task that may itself be unreasonable, to the choices we make about time to prepare food to fit into these constraints - all these operations tend to make us feel forced into treating ourselves as secondary to our jobs. How can data help improve our quality of life? FitBits and AppleWatches highlight the strengths and limits of Things that Count, not the least of which is the rather low uptake of things like FITBITS and apple watches. So once we ask the question about how data might improve quality of life, we may need to add the caveat: pervasively, ubiquitously, in the rich variety of contexts that isn't all about Counting. And once we think about such all seeing all knowing environments, we then need to think about privacy and anonymity. That is: does everything have to be connected to the internet to deliver on a vision of improved quality of life through data? And if there is a Big Ubiquity - should we think about inverting new norms, like how to make personal clouds and personal data stores far more easy to manage - rather than outsourcing so much data and computation? In this short talk, I'd like to consider three scenarios about Going where too few humans have gone before to help others The challenges of qualitative data Supporting privacy and content to motivate thinking about data capture, re-use and re-presentation, and opportunities across ECS for machine learning, AI, infoviz and hci.