by Rutger Rienks, Anton Nijholt, Paulo Barthelmess
Introduction
Meetings are often inefficient. Starting with probably the first meeting ever held by humans, people have looked at techniques and protocols to enhance them. The development of technology to support meetings has therefore long been a subject of research.
Meetings can nowadays be assisted by a wide variety of tools and technologies, facilitating interaction, saving money and time, and creating opportunities that would not be possible without technology. The foremost benefit of technology so far is its support for meetings in which participants are distributed. Being able to attend meetings remotely results in substantial savings of time and money that might have been otherwise spent on travel. Tele-conferencing systems augmented with additional advanced services such as instant messaging, file transfer and application sharing are becoming more and more prevalent. In the near future meetings will be possible in virtual worlds where participants will be represented by virtual humans.
There is also evidence that technology-enabled processes can positively impact meeting performance. Studies reported by De Vreede et al. and Nunamaker Jr. et al.show a significant reduction in labor cost and overall project duration when Group Support Systems (GSS), or Electronic Meeting Systems (EMS) are used. These systems support alternative, technology-enabled meeting processes that can help participants with the formulation of and search for solutions to ‘problems’ listed on the agenda. A participant generally has a computer terminal connected to a central server at his or her disposal through which several problem resolution tools are available. Typical tools are an electronic brainstorming tool, an idea organizer, a topic commenter and a voting support tool.
Despite the huge savings and proven increased efficiency brought about by GSS and similar technology, its adoption has proven sometimes problematic. There are instances in which the use of these systems has been discontinued due to stakeholders’ objections to the (radical) changes in work practices that are introduced by them. This leads us to investigate alternative means for positively influencing meeting outcomes in ways that would encounter less resistance. In particular, we want to investigate how pro-active meeting assistants can be exploited to reap the benefits of technology-enabled meetings instead of being exposed to its drawbacks. Successful automated meeting assistants can potentially integrate themselves into their surrounding social environment, offering support that blends more seamlessly into users’ work practices.
Technology in the field of meeting support ranges from completely passive objects like microphones to pro-active autonomous actors such as virtual meeting participants. In earlier work we defined several dimensions that can be distinguished in this spectrum, with the major ones being the reasoning ability, the acting ability and the sensing ability. In this paper we will focus on pro-active meeting assistants that are able to act autonomously. Pro-active meeting assistants are those that (preferably in real-time) support the participants and act autonomously in the process either before, during, or after a meeting. For this type of assistants, its operating dimensions are highly dependent on their functionality.
This functionality or sophistication directly depends on the state of the art of automatic collection of appropriate meeting information (the sensing) as well as on the required intelligence to use it (its reasoning ability) and the means through which the assistant can influence a meeting (its acting ability). To aid in this process, so-called ‘smart’ meeting rooms appeared. These smart rooms embed all sorts of sensors, providing data about the meeting and hence create the opportunity to collect and learn from this data in order to build models. These models may in turn provide insights into interactions and their contents. The first project presenting ideas to augment meetings with various ‘smart’ technologies was probably Project Nick. This project discussed the incorporation of screens displaying both the agenda and live meeting statistics to aid the meeting process. From that point onward smart meeting rooms appeared at several institutions
where large meeting corpora were recorded. In the last four to five years there has been a surge in interest in meeting support. Many large projects were established, including consortia with partners from all over the globe, working on meeting collection, and research on meeting models and support technology [IM2 Website, CALO Website, Nectar Website].
The remainder of this paper will elaborate on the concept of pro-active meeting assistants, in particular software agents that aim to assist the meeting process and thereby facilitate more effective and efficient meetings. As there are a lot of ideas but hardly any implemented systems yet, we will, apart from looking at the existing ideas, show how to get from ideas to a full requirements specification. We also present a Wizard of Oz experiment where we simulate several forms of pro-active meeting assistants designed to streamline the meeting process.
Meeting Assistants
Meeting assistants have been the topic of research in various projects, e.g., the Neem Project. In Neem, a basic premise is that assistance has to be provided along multiple dimensions, including the organizational, but also the social and informational. A good meeting is one in which organizational goals are achieved, but not at the expense of the social well-being of a group. Support in Neem revolves around tools and virtual participants, both of which are designed to explore aspects along the organizational, social and informational dimensions. Tools are artifacts that crystallize certain aspects of an interaction, allowing for participants to become aware of and be able to influence these aspects. (e.g. by being able to manipulate items of discussion within an agenda tool.) Virtual participants are anthropomorphic assistants. They are designed to have consistent personalities and well-determined roles. Kwaku is a virtual participant that takes care of the organizational aspects of a meeting. Kwaku for instance reacts to discussions that extend over the pre-allocated period of time by reminding participants that they might want to move on to the next agenda item. Kwaku “listens” to the reaction of the group (by examining transcribed speech and text message channels) and will either update the agenda tool, moving it to the next agenda item in case of agreement, or leaving it in the current item if its perception is that the suggestion was overruled by the group. Kwabena on the other hand is a social facilitator. Kwabena looks after the participants’ social well-being, monitoring the actions a group would want to undertake at each point in time, such as take a break, switch topics, change the level of detail, or pace of the interaction. These wishes are expressed via a ‘Moodbar’ tool that displays a set of possible actions that participants can select by clicking on corresponding buttons. A mechanism is provided to poll the input from the different participants. Kwabena takes the initiative to suggest the course of action (e.g. taking a break) expressed by the group. (e.g. by voicing the suggestion via all participants’ audio systems.) Conversely, if a particular participant is expressing wishes that disagree with the rest of the group, Kwabena communicates in private with this participant, letting him or her know that the rest of the group seems to think differently. Finally, Kweisi is responsible for providing the group with additional information. This can happen upon request of one or more participants, but also autonomously, as Kweisi perceives (again by analyzing the content of the speech and typed messages) that a certain topic is under discussion for which additional documents are available.
All these assistants can be realized as embodied pervasive software systems that operate alone or in groups, interact with the users and with other participants, and learn user preferences. Neem illustrates an approach to assistance during the meeting. We will now frame ongoing research in the domain of meeting assistants by making a division into assistants that support activities that take place before, during as well as after the meeting.
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Some findings and results
To verify whether meeting assisting agents can benefit the meeting process we compared the predefined given agendas with the actual agendas of the meetings of the various systems. The results averaged for the two groups are shown in figure b. It appears that when no system is used at all, the meetings lasted on average 57% longer than what had actually been planned. With System 3 we reached an optimum, shortening the meeting by 27%. Although chairmen might have improved their planning capabilities in the meantime, they were not informed about any of the results.
When we look at the participants’ ratings of degree of intrusiveness versus efficiency, figure (d)) shows that the added intrusiveness of System 3 pays off in terms of meeting efficiency. Notable is the fact that the perceived efficiency appears to be in-line with the actual efficiency. System 3 also resulted in a slight disturbance increase, whereas its ”enjoyability” is rated much lower than Systems 1 and 2 (See c).
After every session the chairmen were asked again to give their opinion about the disturbance and efficiency for both the voice as well as the screen feedback strategies. It appeared that in contrast to the pre-meeting questionnaire results, they now rated them equally for efficiency. Voice messages were still found more intrusive than the text messages, though. An interesting side result was that when the system uses voiced feedback, the participants of the meeting appeared to be much more aware of their own behavior. When they tended to go off topic for example they corrected themselves very quickly, sometimes saying: “off-topic” before continuing with the current item on the agenda. This is probably due to the fact that the system can speak directly to specific participants; participants would therefore try to prevent being corrected by the system.
After getting used to a system with voice output, participants did notice and use the information, but did not interrupt their talking. It should be noted that although the above findings speak in favor of a system that assists the meeting process, a lot of additional research is required, for instance by examining a larger number of groups over a longer period of time.
Some results of the Wizard of Oz experiment
Conclusion
We have shown that there is potential for ambient intelligent systems that aid the meeting process. We have discussed a wide variety of possible applications and application areas. A concrete example of how requirements for a conflict management meeting assistant can be developed has been given. We have shown that the results of an experiment utilizing multiple system paradigms of varying degree of intrusiveness; the experiments employed a Wizard of Oz technique. The results show that meeting efficiency can be improved with respect to a baseline in which no meeting assistants are employed.
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