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SUMMARY:Symbiotic design for machine intelligence systems - Cecily Morriso
 n\, Microsoft Research Cambridge
DTSTART:20160104T093000Z
DTEND:20160104T103000Z
UID:TALK63045@talks.cam.ac.uk
CONTACT:44515
DESCRIPTION:This past year has seen a number of inspirational demos that i
 llustrate the rapid development and increasing power of machine intelligen
 ce technologies. These new possibilities present a provocative challenge t
 o researchers in human experience & design: how can machine intelligence b
 e utilised in applications that augment people’s everyday experiences in
  meaningful ways. Medicine has been highlighted as one field that might pa
 rticularly benefit from machine intelligence. In this talk\, I will illust
 rate some of the research challenges that arise when getting machine intel
 ligence working in a real-world setting. Drawing from the ASSESS MS projec
 t - a system for tracking disease progression in multiple sclerosis patien
 ts using machine intelligence and perception\, I will present three distin
 ct examples: the design of a prototype to capture high quality data\; the 
 development of a tool to efficiently and consistently provide ground truth
  labels for the depth videos captured\; and an iterative design process to
  develop visualisations that enable clinicians to integrate an algorithmic
  decision into their own clinical thinking. I close with the proposition o
 f symbiotic design for intelligent systems: the machine learning algorithm
 s at their core must shape as well as be shaped by the human activities th
 ey are designed to support.
LOCATION:Auditorium\, Microsoft Research Ltd\, 21 Station Road\, Cambridge
 \, CB1 2FB
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