Abstract
Coordination is a key problem for addressing goal–action gaps in many human endeavors. We define interpersonal coordination as a type of communicative action characterized by low interpersonal belief and goal conflict. Such situations are particularly well described as having collectively “intelligent”, “common good” solutions, viz., ones that almost everyone would agree constitute social improvements. Coordination is useful across the spectrum of interpersonal communication—from isolated individuals to organizational teams. Much attention has been paid to coordination in teams and organizations. In this paper we focus on the looser interpersonal structures we call active support networks (ASNs), and on technology that meets their needs. We describe two needfinding investigations focused on social support, which examined (a) four application areas for improving coordination in ASNs: (1) academic coaching, (2) vocational training, (3) early learning intervention, and (4) volunteer coordination; and (b) existing technology relevant to ASNs. We find a thus-far unmet need for personal task management software that allows smooth integration with an individual’s active support network. Based on identified needs, we then describe an open architecture for coordination that has been developed into working software. The design includes a set of capabilities we call “social prompting”, as well as templates for accomplishing multi-task goals, and an engine that controls coordination in the network. The resulting tool is currently available and in continuing development. We explain its use in ASNs with an example. Follow-up studies are underway in which the technology is being applied in existing support networks.
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This gap is not limited to prosocial behavior, but exists whenever short-term or personal needs/desires interfere with longer-term or broader goals. The gap can be between attitudes or values and behavioral intentions (see e.g. Vermeir and Verbeke 2006), or between intentions and actual behavior (Sniehotta et al. 2005; Kuo and Young 2008).
Cognitive challenges stem especially from the limitations of human attention and memory, which tend to be overwhelmed in the age of information. See Levitin (2014).
This idea echoes critiques by Greenfield (2013) and Sadowski (2016) of the concept of intelligence as applied to “smart cities”: that many/most policies and practices put in place in a city will benefit some citizens and harm others, or will accord with the beliefs of some but not all, so that in such cases there is no agreed upon standard for measuring whether a given action is “smart” in the context of a city. At the level of deep philosophy, Arrow’s impossibility theorem (Arrow 1963) and related results in the theory of social choice undergird an argument that the aggregation of preferences (and therefore of goals) across individuals cannot be performed in a way that produces collective rationality, viz., a single preference ordering that is well-ordered and consistent for any possible set of individual preferences, without resorting to dictatorial imposition that may be at odds with what most people want. For these reasons, we think it is best to view “intelligence” as a consensus concept, and to limit our use of “collective intelligence” (as opposed to intelligence exhibited individually by multiple people) to situations where the individuals’ beliefs and preferences can at least eventually come into rough alignment with respect to a particular set of outcomes.
For an overview of the classic work, see Baron (2007).
Examples include VolunteerMatch (http://www.volunteermatch.org/) and linkAges TimeBank (https://timebank.linkages.org/).
For example, Kaiser Permanente Thrive (https://thrive.kaiserpermanente.org/).
Brittleness has long been recognized as a problem in software and AI (see e.g. Lenat et al. 1985).
Social updating may also make goal accomplishment more likely under the public commitment effect when the goal owner desires the outcome (Staats et al. 2004; Hollenbeck et al. 1989), but there is also a danger that announcing one’s intentions will reduce motivation to achieve them if the goal is viewed more as a signal of identity than as truly desired (Gollwitzer et al. 2009).
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Acknowledgements
We have benefited from conversations with Jeff Shrager, Rich Levinson, and Marc Smith, as well as an email exchange with Doug Schuler and the comments of two anonymous reviewers.
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Rosenschein, S.J., Davies, T. Coordination technology for active support networks: context, needfinding, and design. AI & Soc 33, 113–123 (2018). https://doi.org/10.1007/s00146-017-0778-4
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DOI: https://doi.org/10.1007/s00146-017-0778-4