own memories and the strategies they
employ to overcome the weaknesses.
Kalnikaite and Whittaker16 looked at
the interplay between organic memory and metamemory in determining
when people choose to access digital
conversational records, showing that
even when a digital record is accurate
and complete, users do not rely on it
if they feel they can remember the information unaided. The decision to
use a digital-memory aid also depends
on the efficiency with which a memory
aid can be accessed. Indeed, the study
found that efficiency of access sometimes overrides accuracy, with subjects
being willing to settle for less-than-per-fect accuracy, as long as the method is
quick and easy to use.
Lifelogging applications must be
better at analyzing these trade-offs.
When should people use efficient but
fallible organic memory instead of less
efficient but potentially more accurate
digital records? Rather than seeing
lifelogs as replacing memory, system
designers would be better off viewing
them as working in synergy with organic memory.
Lessons and Research Questions
For lifelogging research, prior work offers four key insights:
Selectivity, not total capture. Rather
than unfocused efforts to “capture everything,” system designers should
channel their efforts more fruitfully
by identifying the situations where human memory is poor or targeting the
things users most want to remember.
These situations are where the systems
would provide their greatest utility.
Furthermore, people may sometimes
want to forget, a view anathema to the
Cues not capture. System designers
must be explicit about the fact that these
systems do not “capture experiences”
but instead provide cues that might trigger different kinds of memories. This is
not a simple matter of infelicity in language, pointing instead to the need to
better understand cueing processes to
build systems that genuinely support
user requirements for memory support.
Memory refers to a complex, multi-fac-
eted set of concepts. There are different
types of memory, and system design-
ers must clarify the aspects of memory
they are targeting (such as recollection,
reminiscence, retrieval, reflection, and
remembering intentions). Greater clar-
ity should produce systems that better
fit their intended purpose and support
the user’s relevant cognitive processes.
Unless system designers know precise-
ly what their systems are intended to
do, they can’t determine whether their
designs are successful.
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Abigail J. Sellen ( email@example.com) is a principal
researcher at microsoft research in cambridge, u.k.,
and special Professor of interaction at the university of
Steve Whittaker ( firstname.lastname@example.org) is a
research scientist at ibm almaden research center, san