Designing Attentive Interfaces
Roel Vertegaal
Human Media Lab, CISC
Queen's University
Kingston, ON K7L 3N6
Canada
roel @ a c m . o r g www. hml. q u e e n s u , ca A B S T R A C TIn this paper, we propose a tentative framework for the classification o f Attentive Interfaces, a new category o f user interfaces. A n Attentive I n t e r f a c e is a user interface that dynamically prioritizes the information it presents to its users, such t h a t information processing resources o f both user and system are optimally distributed across a set o f tasks. The interface does this on the basis o f
knowledge - consisting o f a combination o f
measures and m o d e l s - o f the past, present and future state o f the user's attention, given the availability o f system resources. We will show how
the Attentive Interface provides a natural
extension to the windowing paradigm found in
Graphical User Interfaces. Our t a x o n o m y o f
Attentive Interfaces allows us to identify classes o f user interfaces that would benefit most from t h e ability to sense, model and optimize the user's attentive state. In particular, we show how systems that influence user workflow in concurrent task situations, such as those involved with m a n a g e m e n t o f multiparty communication, m a y benefit f r o m such facilities.
K e y w o r d s
Attentive Interfaces, Nonverbal Computing, E y e Tracking, Attention, User Interfaces.
1. I N T R O D U C T I O N
In recent years, there has been a resurge o f interest in the use o f eye tracking systems for interactive purposes. However, it is easy to be fooled by t h e interactive power o f eye tracking. When first Permission to make digital or hard copies of all or part of Ibis work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or cornmercial advantage and that copies bear this notice and the full citaUon on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee.
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encountering eye based interaction, most people are
genuinely impressed with the almost magical
window into the mind o f the user that it seems t o provide. There are two reasons w h y this belief m a y lead to subsequent disappointment. Firstly, although current eye tracking equipment is far superior to that used in the seventies and early eighties, it is by no means perfect. For example, there is still t h e tradeoff between the use o f an obtrusive head-based system or a desk-based system with limited head movement. Such technical problems continue to limit the usefulness o f eye tracking as a generic input. Secondly, there are real methodological problems regarding the interpretation o f eye input for use in graphical user interfaces. One example, the "Midas Touch" problem, is observed in systems that use eye movements to directly control a mouse cursor [20]. When does the system decide that a user is interested in a visual object? Systems t h a t implement dwell time for this purpose run the risk o f disallowing visual scanning behavior, requiring users to control their eye movements for t h e purposes o f output, rather than input. However, difficulties in the interpretation o f visual interest remain even when systems use another input
modality for signaling intent. Another classic
methodological problem is exemplified by t h e application o f eye m o v e m e n t recording in usability studies. Although eye fixations provide some o f t h e best measures o f visual interest, they do not provide a measure o f cognitive interest. It is one thing to determine whether a user has observed certain visual
information, but quite another to determine
whether this information has in fact been processed or understood [19].
Some o f our technological problems can and will be
solved. However, we believe that our
methodological issues point to a more fundamental
problem: What is the nature o f the input
what interactive functions can this i n f o r m a t i o n provide added value?
For now, it seems, the most successful applications have been those in which the information c o n v e y e d b y eye m o v e m e n t data is a direct measure o f t h e locus o f the user's (visual) attention. We argue t h a t in m a n y o f these applications, the function o f this information is to optimize the attention o f t h e user, the attention o f other users, or the processing resources o f the computing system itself. W e believe such applications in fact constitute a new category o f user interface: the Attentive Interface. 2. B A C K G R O U N D
The rationale for designing o f artifacts in such a w a y that t h e y optimize the attention o f their users
is not new. It existed long before personal
computers were born and was the backbone o f t h e
European abstract functional art m o v e m e n t
throughout m u c h o f the 20 th century. According t o Bauhaus director and architect Ludwig Mies van der Rohe, tools and other functional artifacts, such as buildings, needed to be designed using only t h o s e
materials necessary to keep the c o n s t r u c t i o n
structurally sound [3]. There were three m a i n arguments to his "Less is More" rationale: 1)
relinquishing unnecessary embellishments would
improve the c o m m u n i c a t i o n o f the a r t i f a c t ' s functionality; 2) simplifying the design would ease
automated manufacturing while i m p r o v i n g
structural soundness, thus cutting costs; 3) the focus on the essence rather than on the peripheral would increase the esthetic value o f the artifact. Figure 1 visualizes the design space constituted by the above trade-offs b e t w e e n the ease o f use, engineering requirements and esthetics o f a design. What Mies van der Rohe tried to argue was that i f the right design choices are made, the above parameters need
not be counteracting. Instead, they m a y
c o m p l e m e n t and strengthen each other, as
visualized in Figure 1 by a folding o f the design space.
It is exactly this principle o f e c o n o m y o f resources
that drives human attention. Although humans
have vast mental resources, they are o f course limited. N o r m a n [13] argued that for this reason, humans require a m a n a g e m e n t system that selects and filters only that information that is m o s t relevant. There has been m u c h c o n t r o v e r s y as t o h o w this selection process might operate. Von Helmholtz [8], and later Broadbent [2], considered h u m a n attention m o s t l y as a physical filter, t h a t selects information before entry into the brain.
Engineering Esthetics
.A
~,iiiii!ii !~!:, Esthetics Human FactorsEngineeri tman Factors
Figure 1. Folding a design space such that
constraints function as complements rather than tradeof~.
This is certainly the case with the eye, as t h e information bandwidth o f the retina is a function o f the distance to the center o f the e y e ' s visual axis. However, James [10], and later Deutch & D e u t c h [4], emphasized the (semantic) filtering that occurs after information has entered the brain. This is evidenced in the eye by the so-called A t t e n t i o n a l Spotlight: that part o f the retina that the brain selects for visual processing [14]. The c o n t r o v e r s y was not just a question o f whether a t t e n t i v e filtering occurs early or late in h u m a n i n f o r m a t i o n
processing. It was also a question o f w h a t
determines the selection o f information: is
selection triggered b y external stimuli or b y
anticipation through prior knowledge? This
c o n t r o v e r s y was only recently concluded with
T r e i s m a n ' s Feature Integration Theory: t h a t
attentive selection is guided by both input and
cognition [17]. The question o f input-driven versus k n o w l e d g e - d r i v e n selection is v e r y relevant to t h e
design o f an Attentive Interface. M a n y o f t h e
methodological problems associated with e y e
tracking applications are due to the fact that e y e
tracking input alone provides insufficient
Figure 2. Passive attentive toilet design (Amsterdam
Schiphol Airport, The Netherlands).
2.1 Early Attentive Interfaces
The question o f input-driven versus knowledge- driven information filtering also relates Mies v a n der Rohe's design rationale to the economy o f user information processing in the context o f a set o f tasks. We should design each tool such that the minimum information is provided to trigger t h e knowledge required to operate the tool [28]. We can thus interpret Mies van der Rohe's adage as a principle o f information preservation. As any designer knows, this information comes in the f o r m o f the user's sequencing o f intent and the task knowledge structures triggered by that intent [18]. An excellent example o f how one can effectively influence the user's current intent on the basis o f information about the user's goal intent is provided by the Attentive Toilets found at A m s t e r d a m ' s Schiphol airport (see Figure 2). Indeed, the designer o f these toilets has found a very simple y e t effective mechanism to direct the intent o f the user. However, in cases where the user's intent is in constant flux, artifacts need to have the capabilities
to dynamically prioritize their i n f o r m a t i o n
presentation on the basis o f changes in that intent. Graphical User Interfaces were designed to do just that. According to Smith et al. [16], the rationale for the design o f windowing systems is to allow users to focus on the task with the highest priority, in the context o f other tasks o f lower priority. In a typical graphical user interface, windows relevant to the present task will occupy the display space on which the user is currently fixating. Tasks o f lower priorities are represented by icons that occupy peripheral vision. By selecting and positioning on- screen windows with a mouse, the user not only
optimizes the information representation o f t h e system according to her own attention, but also optimizes that o f the computer system itself. By focusing processing priority on windows in the
foreground, the resources o f the system are
optimally employed to comply with the current intent o f the user. However, for the most part, it is the user's responsibility to optimize the e c o n o m y o f attention between system and user through a pointing device.
We do not have to look far to find examples o f systems that seek information about the intent o f their users through means that are much m o r e proactive and implicit. A sophisticated application o f this principle can be found in m o d e m traffic
light control systems. These actively seek
information about the user's intent by implicitly sensing the focus o f their attention through coils in the road surface. Traffic control systems do n o t rely solely on the input provided by their sensors. They apply knowledge rules based on statistical
measures o f traffic flow to decide which
information to present to what user.
The above are all examples o f interfaces
predominantly occupied with the optimization o f the user's current attention. A diary is a prime
example o f a tool that seeks to optimize the
future
attention o f its user. As with traffic lights, the automation and interconnection o f diaries, e.g., in hand held devices, has allowed the preemption o f
user attention through active interruption.
However, as opposed to traffic lights, diaries know little about the current state o f the user's a t t e n t i v e resources. The same applies to t e l e c o m m u n i c a t i o n and networked information systems such as email. It is in the notification structure associated with these systems that an attentive interface would perhaps be most pertinent. Indeed, according to Goldhaber [7], the Internet itself can be seen as an economy o f the combined attentive resources o f its users. He argues that in this e c o n o m y the a t t e n t i o n span o f the consumers is a valuable limited resource. This is demonstrated by the current practice o f internet based advertising agencies to sell the attention o f web site users as measured by page views.
3. F E A T U R E S O F A T T E N T I V E I N T E R F A C E S
So what defines an attentive interface? A n
attentive interface is a user interface t h a t
dynamically prioritizes the i n f o r m a t i o n it presents
to its users, such that information processing
resources o f both user and system are o p t i m a l l y distributed across a set o f tasks. The interface does this on the basis o f k n o w l e d g e - consisting o f a combination o f measures and models - o f the past, present and future state o f the user's a t t e n t i o n , taking into account the availability o f s y s t e m resources. As we have seen in the introduction, there can be m a n y types o f attentive interfaces. Given a set o f examples, we will, however, try t o identify a n u m b e r o f c o m m o n themes, imposing t h e tentative classification shown in Table 1. Firstly, attentive interfaces can be differentiated on t h e basis o f their ability to actively m o n i t o r the user's
attentive state. The attentive toilet shown in
Figure 1 is an example o f a system that manipulates the attention o f its user without any e x t e r n a l measures. Although w i n d o w i n g systems o f graphical user interfaces have no means to measure the user's attentive state implicitly, t h e y do allow the user t o c o m m u n i c a t e their attention explicitly through t h e m a n u a l organization o f windows. We t h e r e f o r e
classify these as
explicit.
Systems that e m p l o ysensing technology such as eye tracking to measure the u s e r ' s current state o f attention are classified as
implicit.
The next feature determines what is m e a s u r e d by such sensing technology: the locus o f a user's attention, or its span. Typically, a t t e n t i v e interfaces will e m p l o y a c o m b i n a t i o n o f t h e s e techniques. A n o t h e r important descriptor o f anattentive interface is the type o f sensing
t e c h n o l o g y employed. In most explicit systems, this will simply be the user's pointing device. According to Vertegaal [26], systems that e m p l o y m o r e implicit measures m a y use a c o m b i n a t i o n o f user presence, b o d y orientation, head o r i e n t a t i o n and ultimately eye orientation to detect a t t e n t i v e state. A n o t h e r important feature is w h e t h e r t h e system stores any o f the above measures as a model. For example, traffic control systems m a k e their decisions on the basis o f rules about t h e normal flow and v o l u m e o f traffic. Finally, we consider the w a y in which an attentive system m a y increase or decrease the attentive load o f the user, system, or network. A cell phone c o m m a n d s t h e
user" s immediate attention through active
interruption, y e t does little to optimize the user's mental load.
4. C L A S S I F Y I N G A T T E N T I V E I N T E R F A C E S
However, the main classification provided by
Table 1 is that according to utility: the task t h e
Attentive Interface seeks to optimize. Our
categories are ranked according to the level o f mental processing required for the task.
Perhaps the most urgent c a t e g o r y is that o f
attentive interfaces involved in the m a n a g e m e n t o f group c o m m u n i c a t i o n . According to D u n c a n [6], turn taking in group conversations is v e r y m u c h a function o f the optimization o f group a t t e n t i o n : listeners choose to be silent such that e v e r y o n e c a n focus all attentive resources on a single speaker. Vertegaal et al. [24, 25] demonstrated that p e o p l e indeed use i n f o r m a t i o n about each other a t t e n t i v e state, as given by their gaze direction, in this process. The G A Z E Groupware System [21] is a
video c o n f e r e n c i n g system that exploits this
principle. It conveys the gaze direction o f
conversational partners across a n e t w o r k by
rotating images o f the participants toward t h e person t h e y look at. The s y s t e m measures w h o m participants look at using an eye tracker. Other user interfaces that fall in this c a t e g o r y are avatar-based
c o m m u n i c a t i o n systems and m u l t i - a g e n t
conversational systems such as FRED [23]. T h e next category deals with the m a n a g e m e n t o f o f f l i n e communication. The sheer v o l u m e o f t o d a y ' s email
messaging has rendered the crude form o f
notification m a n a g e m e n t present in t o d a y ' s email
clients inappropriate. To solve this p r o b l e m ,
Horvitz [9] d e v e l o p e d
Priorities,
a messaging t o o l that collects attentive i n f o r m a t i o n - e.g., about t h e frequency with which users respond to messages from certain people - t o prioritize the delivery o f messages. Messages with a high priority rating are, for example, forwarded to an offfline user's pager, while messages with low priority wait until the user checks them. A l t h o u g hPriorities
builds a model o f the user's attentive behavior, its ability to o b t a i n i n f o r m a t i o n about the current state o f the users' attention is limited. The third category deals with the opening and closing o f dyadic c o m m u n i c a t i o n channels. The E y e R glasses developed b y Selker [15] use infrared light to sense w h e t h e r a user is orienting his head towards a n o t h e r user. This information is then applied to regulate the o p e n i n gand closing o f c o m m u n i c a t i o n channels, f o r
example with a robot dog. W h e n the user orients h i m s e l f towards the robot dog, it starts barking.
E y e C o n t a c t , developed by Vertegaal [22] is a
eye tracking technology to detect fixations at t h e user by other people. It can be used to modify the interruption state o f incoming cell phone calls according to whether the user is currently engaged
in a conversation, thus creating attentive cell
phone technology [22].
Our next category pertains to what is perhaps the most basic feature o f any attentive interface: the optimization o f concurrent task execution. In the classic computer game Pong, the objective is to bounce a ball against a wall using a paddle. In traditional systems, the paddle is controlled by a
joystick, leading to considerable e y e - h a n d
coordination problems. LC Technologies developed an eye-based pong that instead uses the horizontal coordinate o f eye movements to control t h e position o f the paddle, making this a game y o u cannot lose [11]. The windowing systems e m p l o y e d by graphical user interfaces are another example in
this category. The most striking differences
between Eye-based Pong and classic windowing systems is o f course the absence o f implicit measures in the latter. The MAGIC pointing system described by Zhai et al. [27] provides a hybrid between the two approaches. In MAGIC pointing, the user's eye coordinates are used to preposition the mouse cursor such that it reduces m o v e m e n t time toward a visual target.
Our final three categories pertain to t h e
management o f the user's basic attentive resources. Attentive interfaces involved in the m a n a g e m e n t
o f the user's physical transportation seek to
optimize the user's attentive resources at the presence level. As such, they regulate the physical m o v e m e n t o f users. Traffic control systems are prime examples o f this category. More basic systems in this category are automatic doors and other presence-operated devices.
One should note that attentive interfaces need n o t optimize the attentive resources o f a user or system solely by a reduction in load. They can also empower the user by enlarging their a t t e n t i v e capacity. Indeed, most gaze contingent displays seek to augment the basic attentive resources o f the user or system. Attention-based video compression
[5] and gaze-contingent 3D level-of-detail
rendering [12] are examples o f this category. Our final category pertains those interfaces with the most basic o f attentive tasks: to attract the user's attention. The attentive toilet shown in Figure 1 is a prime example o f this, as are most security monitoring systems.
5. D I S C U S S I O N
The proposed classification allows us to reason explicitly about the design attributes o f a t t e n t i v e interfaces. It allows us to identify the categories o f user interfaces that are most likely to require
attentive enhancements through tracking
technologies and priority models. We have listed a number o f these candidates in Table 1, some o f which we will now discuss. Likely candidates f o r attentive enhancement in the category o f group communication systems are systems that r e p r e s e n t users in a virtual space in the form o f avatars. Some systems in this category already employ a crude form o f attention m a n a g e m e n t that uses co- alignment o f avatars to decide whether to open or close audio connections [1]. However, systems in this category are very likely to benefit from the use o f more implicit sensing technologies, such as t h e measurement of eye, head or body orientation. In
the category o f dyadic c o m m u n i c a t i o n
management, cell phones are the most obvious
candidates for improvement. Interruption o f
multiparty conversation through cell phones has become such a problem that it has prompted t h e installation o f cell phone j a m m i n g technology in certain meeting areas. Cell phones should be capable o f adjusting their interruption priorities according to the user's current state o f attention [22].
From our categorization it also becomes clear t h a t there are very few systems indeed that employ a
model o f the user's past attention in their
prioritization o f current information. One reason for this is that the required statistical reasoning
techniques are still in their infancy [9]. As
Microsoft's Office Assistant exemplifies, it is better not to incorporate any model than it is t o incorporate a poor model. However, we believe t h a t as the technology improves, we will increasingly see
statistical learning techniques incorporated in
Group C o m m u n i c a t i o n M a n a g e m e n t
GAZE Video Conferencing
Attentive Agents Avatars O f l l i n e C o m m u n i c a t i o n M a n a g e m e n t Priorities System Email Diary Headline D y a d i c C o m m u n i c a t i o n M a n a g e m e n t EyeR EyeContaet Sensor Cellphone C o n c u r r e n t T a s k M a n a g e m e n t Eye-based Pong MAGIC pointing Windows Physical Transportation M a n a g e m e n t
Presence Operated Devices Traffic Control Systems Door A u g m e n t A t t e n t i v e R e s o u r c e s Gaze-Contingent Displays Attention-based Compression Canon EOS-5 D i r e c t A t t e n t i v e R e s o u r c e s Securi W Monitoring Systems Attentive Toilet A c t i v e Implicit Implicit E x p l i c ~ l m p ~ c ~ ExpHcit N o No I m p l i c ~ l m p ~ c ~ Explicit Implicit Implicit Explicit I m p l i c i t Implicit N o Implicit I m p l i c i t ImplicH Locus/ Span Locus Both L o c u s Span S p a n B o t h B o t h span Locus Both B o t h Both B o t h Locus B o t h L o c u s Sensor Eye Eye H a n d H a n d H a n d H e a d Eye H a n d E y e H a n d Body Body E y e Eye Eye A t t e n t i o n A c t i v e R e d u c e L o a d M o d e l I n t e r r u p t User S y s t e m N e t w o r k U s e r S y s t e m U s e r N e t w o r k U s e r N e t w o r k None U s e r User U s e r S y s t e m n e t w o r k U s e r S y s t e m N e t w o r k N o n e U s e r U s e r User S y s t e m N o n e U s e r S y s t e m I m p l i c i t L o c u s No Body N o n e User S y s t e m U s e r S y x t e m N e t w o r k U s e r S y s t e m User S y s t e m T a b l e 1. C l a s s i f i c a t i o n o f A t t e n t i v e I n t e r f a c e s w i t h e x a m p l e s .
6. C O N C L U S I O N S
In this paper, we proposed a tentative f r a m e w o r k for the classification o f Attentive Interfaces, a new
category o f user interfaces. We defined an
Attentive Interface as a user interface t h a t
dynamically prioritizes the i n f o r m a t i o n it presents to its users, such that information processing resources o f both user and system are o p t i m a l l y distributed across a set o f tasks. The interface does this on the basis o f knowledge - consisting o f a combination o f measures and models - o f the past, present and future state o f the user's a t t e n t i o n , given the availability o f system resources. Measures
are provided by tracking presence, body
orientation, head orientation or eye orientation o f users. Models may consist o f rules and heuristics based on previously observed patterns o f a t t e n t i v e behavior. We have shown h o w Attentive Interfaces provide a natural extension to the windowing paradigm o f the Graphical User Interface. One o f the main benefits o f our classification o f A t t e n t i v e Interfaces is that it makes explicit those categories o f user interfaces that would benefit most from t h e ability to sense and model the user's attentive state. In particular, we showed h o w systems that influence user workflow in concurrent task situations, such as those involved with m a n a g e m e n t o f m u l t i p a r t y communication, m a y benefit from such facilities. 7. A C K N O W L E D G E M E N T S
This work was supported by grants from NSERC,
OIT, CITO & CFI o f Canada and by LC
Technologies, Inc. We thank all members o f t h e H u m a n Media Lab at Queen's, particularly C o n n o r Dickie, Changuk Sohn, Ryan Brown, Jeff Shell, A n t h o n y Legault and Ivo Weevers. We also t h a n k Myron Flickner and David Koons o f IBM A l m a d e n Research Center for their support.
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