Page 242 - Designing Sociable Robots

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Social Constraints on Animate Vision 223

Another limitation of the visual system is how quickly it can track moving objects. If
objects or people move at excessive speeds, Kismet has difficulty tracking them continu-
ously. To bias people away from excessively boisterous behavior in their own movements
or in the movement of objects they manipulate, Kismet shows irritation when its tracker is
at the limits of its ability. These limits are either physical (the maximum rate at which the
eyes and neck move), or computational (the maximum displacement per frame from the
cameras over which a target is searched for).
Such regulatory mechanisms play roles in more complex social interactions, such as
conversational turn-taking. Here control of gaze direction is important for regulating
conversation rate (Cassell, 1999a). In general, people are likely to glance aside when they
begin their turn, and make eye contact when they are prepared to relinquish their turn and
await a response. Blinks occur most frequently at the end of an utterance. These and other
cues allow Kismet to influence the flow of conversation to the advantage of its auditory
processing. Kismet, however, does not perceive these gaze cues when used by others. Here,
the visual-motor system is driven by the requirements of a nominally unrelated sensory
modality, just as behaviors that seem completely orthogonal to vision (such as ear-wiggling
during the calling behavior to attract a person’s attention) are nevertheless recruited for the
purposes of regulation.
These mechanisms also help protect the robot. Objects that suddenly appear close to the
robot trigger a looming reflex, causing the robot to quickly withdraw and appear startled. If
the event is repeated, the response quickly habituates and the robot simply appears annoyed,
sinceitsbeststrategyforendingtheserepetitionsistoclearlysignalthattheyareundesirable.
Similarly, rapidly moving objects close to the robot are “threatening” and trigger an escape
response.
These mechanisms are all designed to elicit natural and intuitive responses from humans,
without any special training. But even without these carefully crafted mechanisms, it is often
clear to a human when Kismet’s perception is failing, and what corrective action would
help. This is because the robot’s perception is reflected in familiar behavior. Inferences
made based on our human preconceptions are actually likely to work.

12.7 Evidence of Social Amplification

To evaluate the social implications of Kismet’s behavior, we invited a few people to interact
with the robot in a free-form exchange. There were four subjects in the study, two males
(one adult and one child) and two females (both adults). They ranged in age from twelve to
twenty-eight. None of the subjects were affiliated with MIT. All had substantial experience
with computers. None of the subjects had any prior experience with Kismet. The child had