… but there’s something fishy about the word ‘context’
Things that are machine readable
What’s relevant to the conversation
Blink vs wink
House vs home
Commute vs journey
Cooking for pleasure vs cooking for food intake
Things that are person readable
Source: P. Dourish, “What We Talk About When We Talk About Context.” Ubicomp 2004 ROI (getting people to value what you have) Culture (how people understand the world around them)
Which context you focus on leads you to different questions, which lead to different design choices and business models
Things that are machine readable
How much can I reliably detect? How many different data points can I throw together? How can I make machines mash it all up? What activity can I support? How do my end users interpret my data? People Context Things that are person readable
Sensor Context: Location +buddylist =ambient display of routine People Context: Relative to spouses and children Embedded in routines of ‘putting on the kettle’, practices of assurance-giving, as precise as conversations are , allows redefinition of home and away “ Whereabouts Clock”, Brown et al 2006 Location ≠ Context
Think very, very carefully about the following question.
The average office worker has 12 minutes to work before he/she gets interrupted.
You now have a device that tells you whether people of potential relevance to your work are in the office, based on location, other devices present, and historical interaction pattern.
Do you really want something to interrupt you to tell you that you are about to be interrupted?
Context-aware tourism applications Paris photo courtesy of Only_Point_Five
Easily machine sensed
People context present, ritualized
low demand for machine-inferred Eiffel Towers
Too many things to ‘sense’ (building? Shop? Construction materials?)
People context present, but unritualized (unpredictable)
High value– the ‘gem’ you discover on your trip!
Machine recognizable but (semi)long-tail. Who will connect the dots?
Value depends on people’s enthusiasm for a narrow art genre, not necessarily a particular place
Easy, low value Hard, high value Middling
Spurious connections between Sensor Context and People Context are fantastic for art, but cloud ‘prediction’ “ Home Health Horoscope” Gaver et al, 2007 Sensor Context: Condensation on windows + pattern of doors + weight of the coffeepot + … = home health People Context: Sensors mash up horoscopes and give them back to perplexed dwellers who infer their meaning (i.e., do the real ‘sensing’ work) Inferencing that involves more than 10 variables will deliver spurious connections. What will people make of these?
Current research: Mapping connections between People Context and Sensor Context
Data from 8 weeks of device activity used as a cultural probe
How the device ‘fits in’ to people’s daily patterns says a lot about both their lives and what they believe the device ‘does’
machine use is the aspect of life most likely to be interrupted, doesn’t do the interrupting
With a weak ecosystem of players focused on people context, we all suffer sustainability problems
Places for eyeballs to go become limited if no one interacts with the device
Creepyness factor becomes the foreground
People need a good reason to not notice they are creating a database for you
Bias towards literal accuracy can be more annoying rather than less
Non-traditional ads are by definition ‘out of place’—the bar is raised to get it right
If Location ≠ Context, then…
“ Context awareness” as a technical development obliges businesses to do MORE user-centered design, not less
Machine learning will only solve the problems you design it to solve
You don’t need an anthropologist to do this, just some good observations about daily life
Use people context to assess the value of sensors AND constrain the noise
Understanding how the two map on to each other helps you understand what people value
A ‘less is more’ approach to data is pretty useful before full AI happens
When you do it right, you’ve done something pretty powerful
you are creating a system of meanings that people use to perceive their world– this is culture
Orkut in Brazil: where People Context made Sensor Context mean something (accidentally)
In January 2005, Brazilians recruited masses of friends onto the social networking site Orkut in order to “beat the Americans”.
Math mattered unexpectedly: People felt they “had been counted” in a people context where they felt invisible (US-dominated Internet)
Nothing about social network density, size or shape could have inferred that a nascent social movement was brewing. Social history would have.
“ Takeover day”-the day when the number of Brazillians was greater than Americans- was a national event
this became ‘we’ This did not
An eComm 2008 presentation – http://eCommMedia.com for more