My personal take on “problem finding” and “idea development”

1. My personal take on “problem finding” and “idea development”

2. How I conceived of (my part of) this project, As a guided tour of how I find problems and develop ideas

3. Conceptual framework At least two distinct tasks in HCI research Discovery and Invention (Sorry, this is a partial repeat for ¾ of the class)

4. Activities of discovery & invention • Discovery (Science) • Central: uncover truth (knowledge) • Methodology important (do you trust result) • Work towards finer and simpler phenomena • Deciding between competing theories • Invention (Engineering & Design) • Central: Building good new things (innovation) • The thing is important, knowledge is a tool • Work towards bigger and more complex

5. Discovery and Invention • A lot of common vocabulary and even methodology • But a lot of subtle differences • Often unrecognized • Example: “Theory” • Need both activities for HCI • Important to keep in mind the differences and resulting points of view

6. Scott’s rule for how to tell HCI researchers apart • Scientists are interested in the low order bits • Designers are interested in the high order bits • Computer Scientists are interested in the bits themselves

7. Characterizing “the work of invention” • Task: Find needs in “the world” that… • You feel passionate about addressing • Interest and inclination • Are worthwhile addressing • Of some sort of value • E.g., “change the world” (a little) • You can make some progress on • Unique insight or approach • New/unique technological “lever” “Preferably two of these” -Scott The “country music” rule (Loretta Lynn) “You have to be first, best, or different” • Invent things to address the need

8. My approaches • Lots of problems in the world (although fewer “within striking distance”) • I have fairly wide ranging interests • Keys to my progress tend to be “unique insights” and “technology levers”

9. Characterizing approaches • “Top-down” • Careful analysis and decomposition of problem • Theory building (conceptual abstractions) • “Bottom up” • Collect “technological levers” (and patterns) • Wait for opportunities to apply them • “Middle out” • Actively seek insights • Users • Self use

10. Some ways to have unique insights, etc. • Import a body of knowledge • Moving stuff from one sub-field to another can be a big win of interdisciplinary work • Create/refine a body of knowledge • Have a good predictive or abstracting theory • Fewer false steps • Taming complexity • Import/borrow technology • Being the first technologist on your block to understand that this “screwdriver” is a “pry bar” • “Using money as a time machine” • Invent technology

11. How this project came about as an illustration…

12. “The failed experiment” • At Georgia Tech my student (Ian Smith) did several internships at Xerox PARC • Worked with early awareness systems • Got me interested in them • We hacked together crude “media space”

13. Background: media spaces • Distributed collaboration is not as effective as co-located work • Many missing cues and affordances that make interaction and collaboration flow smoothly • Tend to be subtle, informal, and serendipitous • “Bumping into” people in the hall • General awareness of their “status” and activities • Just being reminded that the person exists • Media spaces are an attempt to put back affordances for these things using “media” • e.g., transmitted audio and video • Create a virtual “space” (really place) for collaboration

14. Our media space • Camera and microphone on workstations • A/V over network to others “in the space” • Offices down the hall from each other • Network video was just becoming “off the shelf” back then (1993-94) • Most previous had been switched analog

15. Media space video • Video was small and slow (~1-2fps) but ok • Reiterated lesson we knew: better quality (frame rate, size, etc.) was not going to help awareness a lot • Privacy issues • Screen space and machine load issues • Illustrated some known issues from literature (i.e., can’t see who’s present in remote space) • Apparent usefulness • e.g., “are they in?” & quick conversations • But few big insights

16. Media space audio • Was a disaster… • Awkward to use (half duplex due to major echo issue) • Serious privacy concerns  push to talk • Lesson: (In an office environment) audio is much more sensitive than video • Lesson: privacy is not just about information flow • Social checks and balances afforded in the real world by visibility (e.g., reciprocity) lost in the virtual world • already knew this from the literature, but… • Explicit action  lost properties of a “space” • Lesson: low engagement critical for this

17. Disaster (cont.) Conflict of spaces • Social setting of virtual space (broadcast conversations going on across network audio) conflicted with social setting of real space (meeting in my office) I would turn it off during meetings… … and forget to turn it back on. • Lesson: the “lens cap” theory of privacy does not work in practice

18. The failed experiment • Experiment was ill-conceived in a number of ways • Replicated things from literature • Unrealistic setting (just down the hall) • Self use, but “the user is not like me” • Half-baked technology • Not usable in the end • Nothing to publish • But one of the best things I’ve ever done

19. The win of self-use: insight building “The user is not like me” but… … “You can’t learn to swim by watching from the side of the pool” • Being personally irritated is a good thing! • Visceral understanding of the issues • Many small practical details hard to get second hand • Sets the stage for much of my later work • Sets of things you can get from self-use that are a lot harder to get from users • But don’t do just self-use; don’t over generalize Remember “the user is not like me”

20. Discussion

21. Next steps • With problem insights in hand go “top down” • Abstract the issues • New characterization as tradeoffs • Tradeoffs are central to design • Conceptual structure leads to a new insight: • less information can be better because human costs (e.g. privacy and attention issues) dominate • Now we innovate: Technological approaches to delivering less information • but the right information • Inventions  CSCW paper

22. CSCW paper • Central point is characterization as tradeoffs on dual scales • Info out vs. privacy • Info in vs. disruption (attention demand) • And innovative approaches leading from that view • Most interesting “shadow-view”

23. Shadow-View • Motivated by home use (’96 Olympics)which pushed privacy to limits

24. Shadow-View

25. Demo Video

26. Discussion

27. Threads leading to current project • Human costs as dominant issues • Awareness without images motion sensor, seat sensor  sensors more generally • Social aspects were key, but how to characterize and understand them enough to apply technology to address them? • Came to CMU and met Bob and Sara

28. Next step • Bob seemed somewhat intrigued • Sara basically told me I hadn’t done my homework and I should do some basic reading I read: Behavior in Public Places, Erving Goffman, 1963 A big win of interdisciplinary work A conceptual framework (and vocabulary) Start on a body of knowledge  A new “technological lever”: social science (Really “importing a body of knowledge”)

29. Next steps Bottom up technology • Leads to my (naïve?) belief that social models are possible • Connection to sensing thread • Generalize notion of modeling • “Disruption” (attention) becomes key • Connects to ambient displays • Refinement of high concept “Tradeoffs”  “Parsimonious interfaces” (less information better)  “Sense, model, act appropriately” Top down analysis Bottom up technology Etc…

30. Discussion

31. HCI P&T Week 3

32. Week 3: Ideation or "Seeds" for Student Projects Monday, Sept. 10 in Wean 4623 4:30 Sara Kiesler 5:00 Chris Neuwirth 5:30 Dan Siewiorek Friday, Sept. 14 in NSH 1507 12:00 Randy Pausch 12:30 Jie Yang 1:00 Pamela Jennings 1:30 Chris Atkenson