The Quantified Self (QS) vision argues for collecting and analyzing rich collections of personal data. According to the vision, such personal data facilitate greater self-insight promoting behaviour change. But although self quantification is common, quantified self technologies show poor rates of adoption. This talk explores reasons for this failure. I will revisit the QS vision, identifying its flaws, arguing that it is overly analytic, overly rational and overly authoritative. I will present deployments of three new QS systems that address these problems proposing a new design approach to personal data systems. 

Bio: Prof. Steve Whittaker, Human Computer Interaction, University of California at  Santa Cruz,

Steve works at the intersection of Psychology and Computer Science. He studies how technology is affecting fundamental aspects of our everyday lives, and uses insights from Cognitive and Social Science to design new digital tools to support memory and collaboration and to help manage personal information. His past research was funded by the EU, NSF, EPSRC (UK), Google and Microsoft. He currently has an NSF grant to research Technology Mediation for Emotion Regulation, and a Google grant looking at collaborative file sharing.

Steve is Editor of Human Computer Interaction and was recently awarded a Lifetime Research Achievement Award from SIGCHI, the society of Human Computer Interaction professionals. He is also a Fellow of the Association of Computational Machinery (ACM).