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Question 1 Which of the following theories argues that minority influence and majority influence are all through one common underlying mechanism? Select one: a.Expectancy Violation Theory b.Self-efficacy Theory c.Divergent Theory d.Conversion Theory Question 2 Not yet answered Marked out of 1.00 Not flaggedFlag question Question text John found that after listening to the opinion of a member’s of out-group, people changed their opinion away from the out-group member. Which theory explains this phenomenon the best? Select one: a.Inter-group avoidance b.Self-categorization theory c.Conversion theory d.Double minority theory e.Social exchange theory Question 3 Not yet answered Marked out of 1.00 Not flaggedFlag question Question text Which one of the following statements is true regarding Nemeth’s argument on convergent vs. divergent thinking process involving majority and minority influence? Select one: a.The model holds a single process view. b.Convergent thinking process lead to increased persuasion. c.The model explains why ingroup minority exert greater influence than outgroup minority. d.The model argues only minority influence triggers a thoughtful response. Question 4 Not yet answered Marked out of 1.00 Not flaggedFlag question Question text Which one of the following factors are not the causes of shared information bias? Select one: a.Law of numbers b.Social validation c.Rehearsal effect d.Division of labor Question 5 Not yet answered Marked out of 1.00 Not flaggedFlag question Question text Which one of the following statement is TRUE regarding shared versus unshared information? Select one: a.Shared information is less likely to be repeated during group discussion. b.Shared information is less likely to be recalled after group discussion. c.Unshared information receives less suspicion from fellow group members. d.Unshared information more likely to be discussed in the later stage of group discussion. Question 6 Not yet answered Marked out of 1.00 Not flaggedFlag question Question text Based on Kozlowski and Kleins explanation for Composition vs. Compilation, provide a detailed example where a teams performance emerges through the composition process (a) and a detailed example where teams performance emerges through the compilation process (b). Question 7 Not yet answered Marked out of 1.00 Not flaggedFlag question Question text Explain your teamwork experience using one concept covered by any of the readings for this week (a). Come up with potential discussion question(s) from the readings for this week (b). Contents lists available at ScienceDirect Organizational Behavior and Human Decision Processes journal homepage: www.elsevier.com/locate/obhdp Thanks for your ideas: Gratitude and team creativity Nashita Pillaya,1, Guihyun Parkb,⁎,1, Ye Kang Kimc, Sujin Leec,⁎ a Set Apart, 2 Havelock Road #04-15, Singapore S059763, Singapore b Australian National University, Australia c Korea Advanced Institute of Science and Technology, South Korea A B S T R A C T Many ideas and products are borne out of collaborative efforts among members of teams and workgroups, and thus finding ways to improve team creativity is of significant interest. Adopting a collective information processing perspective, we argue that gratitude intervention for teams would serve as a powerful facilitator for information elaboration—whereby team members engage in more deliberate and thorough integration of others’ ideas—and, in turn, enhance team creativity. Study 1 found that teams in the gratitude condition increased information elaboration more than those in the neutral condition. Study 2 compared teams in gratitude emotion and teams in positive emotion in general. Teams in the gratitude condition generated highly creative ideas, due to more information elaboration. On the other hand, teams in the positive emotion condition expressed greater enthusiasm and confidence in their ideas and immediately accepted the ideas suggested, which led to an increase in the quantity of ideas. Our findings suggest that gratitude facilitates intellectual exchange in groups, which in turn enhances team creativity. We discuss our findings’ implications for team creativity and potential directions for future research. 1. Thanks for your ideas: Gratitude and team creativity Teams that achieve a high level of creative performance often find that their creative process is more like a journey filled with obstacles and uncertainties, in which members encourage, challenge, and de- velop each other’s ideas, continually deepen their understanding of the issue, and improve their solutions (Hargadon & Bechky, 2006; Harvey, 2014; Kurtzberg & Amabile, 2001). Given the nature of a creative task, no set routine serves as a checklist; specific individual contributions cannot be anticipated nor a clear outcome guaranteed. Creative teams often rely on each other’s knowledge and perspective as much as on the benevolence and prosocial intentions fueled by heartfelt recognition and appreciation of one’s team members. Hargadon and Bechky (2006) found that creative teams shape their ideas through an evolving cycle of asking for help, providing help, and engaging in collective reflection, whereby members experience a sense of gratefulness for each other’s efforts and contributions. This study aims to gain a deeper, richer, and more nuanced un- derstanding of team creativity by examining the effect of a specific form of positive emotion—gratitude—on team creativity by delineating its impact on collective information processing. Gratitude is defined as a positive emotion that stems from valuing and being aware of one’s surroundings, such as the presence of helpful others (McCullough, Kilpatrick, Emmons, & Larson, 2001); gratifying events (Graham & Barker, 1990); and even chance (Wood, Froh, & Geraghty, 2010). Of the multiple specific types of positive emotion (e.g., joy, serenity, awe, hope, pride; Fredrickson, 2013), we chose gratitude to examine team creativity because it is unique, due to its tendencies to find and re- ciprocate others’ contributions (Algoe, 2012; Fredrickson, 2013). Therefore, while positive emotion in general encourages team members to exhibit upbeat attitudes (George, 1990; Lyubomirsky, King, & Diener, 2005), gratitude triggers team members to reframe an experi- ence, by which they become aware of their teammates’ contributions. In turn, this can motivate them to think deeply about novel and useful ways to reciprocate and benefit others (e.g., DeSteno, Bartlett, Baumann, Williams, & Dickens, 2010; Fredrickson, 2004; Grant & Gino, 2010; McCullough et al., 2001). By focusing on a specific positive emotion (i.e., gratitude), we provide a much needed and nuanced understanding of what positive emotions actually do for group creativity. Indeed, the effects of positive emotions on group dynamics and information processing are largely paradoxical. Positive emotion facilitates and solidifies social bonds among members—but it may also discourage the rigorous processing of information (George & King, 2007; van Knippenberg, Kooij-de Bode, & van Ginkel, 2010). The hazards of groupthink are well known, by which team members’ optimism and confidence can result in failure to co- ordinate their collective intelligences (Janis, 1982). Positive emotions facilitate trust, inclusion, and lenient views of team members’ ideas https://doi.org/10.1016/j.obhdp.2019.11.005 Received 7 September 2017; Received in revised form 17 August 2019; Accepted 14 November 2019 ⁎ Corresponding authors at: Research School of Management, Australian National University, Canberra, ACT 2601, Australia (G. Park). Graduate School of Innovation and Technology Management, KAIST, Daejeon, South Korea (S. Lee). E-mail addresses: [email protected] (G. Park), [email protected] (S. Lee). 1 The first two authors contributed equally to this article. Organizational Behavior and Human Decision Processes 156 (2020) 69–81 0749-5978/ © 2019 Elsevier Inc. All rights reserved. T http://www.sciencedirect.com/science/journal/07495978 https://www.elsevier.com/locate/obhdp https://doi.org/10.1016/j.obhdp.2019.11.005 https://doi.org/10.1016/j.obhdp.2019.11.005 mailto:[email protected] mailto:[email protected] https://doi.org/10.1016/j.obhdp.2019.11.005 http://crossmark.crossref.org/dialog/?doi=10.1016/j.obhdp.2019.11.005&domain=pdf (Forgas & Moylan, 1987). Positive mood could put groups at risk of engaging in shallow processing and consensus-seeking tendencies (Forgas, 1992; Schwarz & Clore, 2003). Sunstein and Hastie (2015) warn against “happy talk,” by which expressions of enthusiasm and confidence erode the group’s likelihood of thoroughly considering di- verse perspectives. Gratitude is a deeply social emotion that focuses on the benefits received from others and motivates individuals to engage in thoughtful reciprocation (Fredrickson, 2004). Members feeling grateful, therefore, would be less likely to engage in the typically shallow chatter of groups that feel highly positive. Instead, an individual member’s ideas would be received and reciprocated with careful consideration by fellow members. Gratitude, therefore, provides a fertile environment for diverse ideas to be expressed, considered, and integrated during group discussion. Using a controlled laboratory study that randomly assigned parti- cipants to groups and manipulated three affective states—gratitude vs. neutral (Study 1) and gratitude vs. positive (Study 2)—we shed light on how experiencing gratitude influences the quality of team information processing and team creativity. Specifically, this study makes three unique contributions. First, by decomposing positive emotion as a specific positive emotion—gratitude—and examining its role, this study clarifies the creativity-boosting effect of positive emotion on teams and affords more precise prediction of team creativity. Second, using a group information processing approach, this study unpacks the “black box” of positive emotions and team creativity. That is, we examine the extent to which groups engage in shallow, consensus-seeking processing or careful, deliberative processing of ideas during discussion. Finally, while the benefits of gratitude have been widely discussed as an ante- cedent of individual-level well-being or satisfaction in close relation- ships (e.g., Emmons & McCullough, 2003; Froh, Sefick, & Emmons, 2008; Tsang, 2006), its impact on group-level performance has been little investigated in organizational science. Our research, which ex- amines gratitude’s impact on team information processing and team creativity, offers a precise and powerful tool for predicting and facil- itating team performance in organizations. 2. Theory and hypotheses 2.1. Definition of gratitude Gratitude, which is a specific positive emotion that stems from va- luing and being aware of one’s surroundings or events (Graham & Barker, 1990; McCullough et al., 2001; Wood et al., 2010), is a benefit- related experience that arises when an individual appraises a positive outcome as having been caused by external influence (Tugade, Shiota, & Kirby, 2014). Gratitude is often described as a high-level positive emotion, attitude, or experience initiated by a cognitive process such as pride, interest, or contentment (Fredrickson, 2004). While gratitude has positive emotional valence (Lazarus & Lazarus, 1994; Mayer, Salovey, Gomberg-Kaufman, & Blainey, 1991; Ortony, Clore, & Collins, 1988), it differs from happiness and other positive emotions because it is linked with the external attribution of positive feeling (Weiner, 1986) and stimulates actions to promote positive outcomes for others, including but not limited to the original benefactor (Fredrickson, 2004; Weiner, Russell, & Lerman, 1979). Gratitude is related to, but distinct from, optimism and hope; optimism is the expectation of good future out- comes (Emmons & McCullough, 2003), and hope is the pathway for attaining those outcomes (Geraghty, Wood, & Hyland, 2010). Gratitude carries unique implications for human sociality (Roberts, 2004). It distinctively produces constructive, meaningful interpersonal engagements and motivates generous actions that benefit others (McCullough et al., 2001). Other positive emotions, in contrast, are vague in their social implications. For example, pride is linked to an urge to share news of individual achievement and visions of greater future success; joy is linked to an urge to play and push physical limits; and interest is linked to an urge to explore, have new experiences, and gather information (Fredrickson, 2004). Bonnie and de Waal (2004) argue that a feeling of gratitude has evolved by allowing humans to engage in reciprocal exchanges of resources, which reinforces a cascade of beneficial actions as the result of more effective collective actions. Unlike perspective taking, which involves a cognitive effort to under- stand another’s perspective (Hoever, van Knippenberg, van Ginkel, & Barkema, 2012), feeling grateful involves finding or being reminded of positivity and the benefits associated with the person (Algoe, 2012). Gratitude is also distinct from indebtedness and obligation, which stem from negative or uncomfortable encounters; gratitude, in contrast, arises from contentment or positive experiences (McCullough et al., 2001). Feelings of gratitude can be induced by practicing gratitude—for instance, by writing in a journal about the generosity and benefits one has experienced (e.g., Ban Breathnach, 1996; Emmons & McCullough, 2003; Hay & Friends, 1996). 2.2. Gratitude as a team-level emotion Because this is the first study to examine gratitude in a team con- text, we use an inclusive definition of team gratitude: the average of group members’ feelings of gratitude, by which we assume that the team boundary contains a meaningful implication on the level of gra- titude its members experience during teamwork. An extensive literature examines how affective experiences can be treated as group property by considering how group members share and regulate their feelings while working together. Specifically, studies suggest that group emotions are formulated through social interaction in both top-down and bottom-up processes (Barsade & Knight, 2015; Bartel & Saavedra, 2000; George, 1990). A top-down perspective explains the mechanism by which group characteristics and shared events shape members’ feelings in the group (Barsade & Gibson, 1998; Barsade & Knight, 2015). Groups offer ample opportunities to experience events that can spur feelings of gratitude (Fehr, Fulmer, Awtrey, & Miller, 2017). Some groups may have a gra- titude-enhancing norm and culture (Fehr, Fulmer, Awtrey, & Miller, 2017). For instance, a group might have a ritual in which all members are expected to express and reciprocate their appreciation of one an- other while celebrating the end of a project. Group leaders can also promote the importance of recognizing contributions made during a project, which would enhance the gratitude felt by group members. The bottom-up mechanism causes an individual member’s emo- tional state to cascade upward to the group’s overall collective emotion (Barsade, 2002; Kelly & Barsade, 2001; Totterdell, 2000). An individual member’s feelings are transmitted through emotional contagion, vi- carious effects, and interaction synchrony. The individual functions as an emotional spark for his/her teammates, by which an initial emo- tional expression spirals through the group and induces an affective experience across group members. In particular, grateful people, feeling approved and cared by benefactors, tend to see others as potential benefactors for them and bind with others for the welfare and re- ciprocation of one another. Thus, boundaries of benefactors are ex- tended beyond a particular benefactor to collective level (Algoe & Haidt, 2009; Algoe, 2012; Algoe, Haidt, & Gable, 2008). In this way, individual members’ feeling of gratitude may trigger a group-level gratitude in a team. For instance, a member can express his/her grati- tude for a teammate in a range of ways, from a gesture or tone of voice to a card or a gift. The grateful person’s emotions are expressed such that the target person and other teammates experience a vicarious feeling of gratefulness—in this case, for the teammate’s gratitude for them. That is, grateful people are responsive to others’ needs, benefiting and providing utility for others and groups in which they are em- bedded. This feeling of mutual gratefulness would further escalate into a team-level state of thankfulness. N. Pillay, et al. Organizational Behavior and Human Decision Processes 156 (2020) 69–81 70 2.3. The collective information-processing perspective on team creativity The collective information-processing perspective on team crea- tivity highlights a team’s quality of information processing as a key antecedent for the production of creative ideas (De Dreu, Nijstad, & van Knippenberg, 2008; De Dreu, Baas, & Nijstad, 2008; Hinsz, Tindale, & Vollrath, 1997). Teams that engage in information elaboration, which is defined as actively deliberating on and systematically integrating team members’ ideas (Hoever et al., 2012; Paulus & Brown, 2007), are more likely to come up with creative solutions. Teams working on a creative task begin their idea deliberation process with members expressing undeveloped ideas and opinions. These initial ideas function as raw ingredients that can be further processed by teammates. Information elaboration transforms team members’ initially unconnected ideas into well-integrated, coherent sets of ideas of higher creative quality. In a team, one’s ideas are expressed and then acknowledged, endorsed, evaluated, and/or modified with the help of teammates during discus- sion. Team discussion that involves minimal information elabor- ation—that is, when team members merely focus on expressing and reinforcing their own ideas—gains little from the intersection of dif- ferent ideas. Team output, in this case, will merely be an assortment of unconnected ideas, with little advancement of their creative qualities. In contrast, team discussion can include extensive information ela- boration, whereby team members engage in a synergetic discussion of different ideas and advance those ideas with greater creativity (Kurtzberg & Amabile, 2001; Resick, Murase, Randall, & DeChurch, 2014). Hypothesis 1: Team information elaboration will promote team crea- tivity. 2.4. Gratitude, information elaboration, and team creativity In this section, we propose that teams with high gratitude would deeply and systematically process and respond to others’ ideas and put more effort into integrating team members’ ideas during team discus- sions. Gratitude entails recognizing others’ contributions and giving others credit (Algoe, 2012). Teams with high gratitude are more likely to be other-focused (DeSteno et al., 2010), by which they would attend to teammates’ ideas and suggestions with a positive and sincere attitude that encourages active listening and constructive conversation. Awareness of external contributions inspires grateful individuals to see the merits and benefits of conversing with teammates. By being more attentive and responsive to team members’ comments and suggestions, the whole team becomes involved in idea elaboration, which further improves and integrates their ideas (Paulus & Brown, 2007). In his essay on moral sentiments, Smith (1982) argues that gratitude helps society develop a balanced understanding of issues that are highly di- visive, such as theology, because it allows constituencies to remain respectful toward those with different perspectives and recognize the interdependencies that bring diverse ideas together. In contrast, when team members are feeling ungrateful, they would be less motivated to reciprocate their teammates’ contributions and efforts. Instead of col- lectively building creative ideas, members in ungrateful teams would be more likely to focus on expressing and reinforcing their own ideas throughout the discussion. Moreover, behaviors driven by gratitude are uniquely reciprocal and thoughtful in nature (Tsang, 2006) and accompanied by a strong focus on benefiting others and collectives (DeSteno et al., 2010). Fredrickson (2004) argues that grateful individuals are creative, be- cause they formulate actions that benefit others and their focus is not limited to the original benefactor. Also, gratitude does not foster a simple, mindless tit-for-tat or reciprocation for the exact benefit. In- stead, gratitude motivates individuals to remain generous and creative in their formulation of reciprocal actions and engage in mutually ben- eficial collaborations. Therefore, in grateful teams, initial ideas shared by team members would be more likely to trigger a response gesture by which the team works collectively to improve on the ideas. The more effort teams with higher gratitude put into thinking and systematically integrating others’ ideas, the more likely that these ideas will become intriguing or novel—and would otherwise have been harder to generate (Stasser & Titus, 1987). Team members who feel grateful should be motivated to think deeply and thoroughly about how to reciprocate the benefits they have received from others and, in turn, engage in more information elaboration during team discussion, thereby supporting and building on others’ ideas (e.g., Bonnie & de Waal, 2004; DeSteno et al., 2010; Tsang, 2006). Active intellectual exchanges among team members would increase the cross-fertilization of ideas, which in turn enables teams to develop novel ideas (Kurtzberg & Amabile, 2001; Nemeth, 1986). In sum, teams that feel grateful would integrate and elaborate on others’ ideas more during team dis- cussions, which in turn enhances team creativity (Bechtoldt, De Dreu, Nijstad, & Choi, 2010; Hoever et al., 2012). Hypothesis 2: A feeling of gratitude will facilitate information ela- boration in teams. Hypothesis 3: Information elaboration will mediate the effects of a feeling of gratitude on team creativity. 2.5. Differential effects of gratitude vs. positive emotion Despite the prevalence and significance of positive emotion for teams, the literature has largely been divided: Positive emotions boost collective morale, yet they can weaken the epistemic rigor of teams, which is essential for team creativity (George & King, 2007; Jones & Kelly, 2009; Sunstein & Hastie, 2015). We propose that a feeling of positive emotions in general and of gratitude in particular trigger dif- ferent interpersonal and social dynamics during group discussion, which in turn dampen or contribute to team creativity. Specifically, we expect that compared to teams that feel positive emotion, teams feeling grateful would be more likely to engage in careful information processing. Without feeling grateful, other positive emotion would prompt teams to engage in superficial chatter, in which members focus on demonstrating excitement about and enthusiasm for ideas during discussion. Positive emotion signals success and solidifies social bonds, by which teams feel an enhanced sense of unity and confidence (e.g., Keltner & Haidt, 1999). When simply feeling positive, teams would feel optimistic regarding their chances of success and members would share more lenient evaluations of ideas suggested by others (e.g., Bohner, Crow, Erb, & Schwarz, 1992; Isen & Means, 1983). Under the influence of positive emotion, ideas would be shared with a high level of enthusiasm and conviction, which triggers immediate agreement with and acceptance of teammates’ ideas. In support of our prediction, studies have shown that when speakers exhibit a highly energetic, enthusiastic attitude, their ideas are per- ceived as creative and convincing (Elsbach & Kramer, 2003; Goncalo, Flynn, & Kim, 2010). When feeling positive, team members would ex- hibit greater fervor and confidence regarding their ideas, and be more likely to accept teammates’ ideas. Therefore, teams in the positive emotion condition, compared to teams in the gratitude condition, would be more likely to lose their opportunity to integrate and advance their ideas. Instead, their ideas would remain largely unconnected in the midst of a greater quantity. On the other hand, gratitude is associated with distinct re- ciprocating, binding behavioral tendencies that would reinforce highly engaging discourse on others’ ideas and have an enduring positive impact on the quality of group discussion. Gratitude would be more likely to create chains of events that carry positive meaning for team members, which fosters the successful integration of different ideas during team discussion (Algoe & Haidt, 2009; Algoe et al., 2008; Algoe, 2012). Gratitude would function as a powerful reinforcement that prompts individual to reciprocate others’ generosity (which is not N. Pillay, et al. Organizational Behavior and Human Decision Processes 156 (2020) 69–81 71 necessarily related to other kinds of positive affect), and should thus lead to more constructive responses to and elaboration on others’ ideas. This, in turn should induce helpful suggestions and comments about team members’ ideas. When a team member feels grateful, they would not present their ideas with great ardor, which prompts the immediate acceptance of their ideas. Rather, grateful team members would focus on building on each other’s ideas collectively and reflecting on their team members’ suggestions and comments. Hypothesis 4: A feeling of gratitude (vs. positive emotion) will decrease team members’ engagement in shallow information processing, such that grateful (vs. positive) members will show less enthusiasm for and con- fidence in their ideas (Hypothesis 4a) and are less likely to immediately accept teammates’ ideas (Hypothesis 4b). Furthermore, we predict that due to the negative impact of gratitude on shallow information processing, gratitude will decrease the number of ideas generated by teams. Teams that feel positive emotion in general are expected to engage in superficial information processing, during which they produce ideas that are large in quantity but lacking in quality. Specifically, in the absence of gratitude, teams in the positive emotion condition would spend more time complimenting each other and praising themselves for how valuable they and their ideas are. On these occasions, letting teams indulge in exuberant feelings would allow them to run wild with their positive spirits and express as many ideas as possible. In such teams, the initial ideas shared by team members would remain a mere list—unevaluated, unelaborated on, and unconnected. In contrast, because grateful (vs. positive) teams would engage in less superficial and more deliberate information processing, the overall quantity of ideas that teams generate would be lower. Thanking each other for their contributions and elaborating on each other’s ideas would take time, and thus hamper the generation of a large number of ideas. Hypothesis 5: A feeling of gratitude (vs. positive emotion) will decrease the number of ideas teams generate via its impact on shallow information processing. 2.6. Overview of the studies We tested our proposed relationship—that gratitude leads to in- formation elaboration and then team creativity—in two lab experi- ments. Specifically, we manipulated a feeling of gratitude to examine the causal mechanism involved in team creativity. Furthermore, by manipulating gratitude, we sought to determine whether organizations could use it as a practical tool to enhance team creativity. Study 1 compared teams in a gratitude condition with those in a neutral con- dition to determine whether gratitude increases team information processing and team creativity from the baseline (Hypotheses 1–3). In particular, Study 1 adopted the top-down perspective of group emotion by letting participants work on a team task and then assigning them to the condition of feeling gratitude or not. Study 2 further demonstrated the differential effects of gratitude compared to positive emotion in general on team information processing and the quantity and creative quality of team ideas (Hypotheses 4–5). Here we adopted the bottom-up perspective of group emotion: participants individually responded to our gratitude manipulation without a preceding group task. Prior to conducting the study, following Cohen (1992) power analysis with power = 0.80 and a large effect size (d > 0.50) assumption, we tar- geted a sample size of 30 groups for each condition, similar to related studies by Hoever et al. (2012) and Park and DeShon (2018). 3. Study 1 3.1. Participants Two hundred and twelve undergraduate students (60 teams) were recruited from psychology classes at a large public university in Singapore and received extra credit. Of the participants, 70\% were fe- male and 88.3\% Chinese; mean age was 21.04 (SD = 1.59). 3.2. Procedure and experimental manipulation Groups of 6–8 individuals were directed to arrive at our laboratory at a given time. On arrival, each group was randomly divided into two teams of 3–4 members each and seated in separate rooms. Participants were then told that they were going to work on three different tasks (i.e., arithmetic, writing, and creativity tasks) as a team and given 3 min to introduce themselves and come up with a team name. For the first task, teams worked on a collective task in which they collaborated to solve puzzles. Specifically, each team member was given a Sudoku puzzle of medium difficulty on a sheet of paper. Participants were then told that they were going to solve the puzzles together by passing the puzzle they were working on to the team member on their right every 90 s. After being informed that the top 10\% of individuals with the most correct solutions would win $10, they had 90s to complete as much as possible of the first puzzle they were given. At the end of this interval, team members passed their puzzles to the right and, in turn, began working on the puzzle given to them by the team member on their left. This was repeated until everyone had worked on each puzzle once. After this, participants were told that they were going to work on a writing task for 5 min. We adopted a manipulation that has been widely used in previous research on gratitude (Emmons & McCullough, 2003; Froh et al., 2008; Lyubomirsky, Sheldon, & Schkade, 2005; Watkins, Grimm, & Kolts, 2004). As this study aims to motivate participants to feel grateful by recalling instances in which they were grateful to their teammates, we asked participants to write about their teamwork ex- periences for five min. Half of the participants were randomly assigned to the gratitude condition (n = 106; 30 teams) and given the following to read: There are many things in our lives, both large and small, that we might be grateful about. For the next 5 min, think back and write in detail about why you are grateful or thankful for your team members. These team members include the people you just worked with and past team mem- bers. Please elaborate on why you feel grateful or thankful and provide contextual information where necessary. The other half of the participants were randomly assigned to the neutral condition (n = 106; 30 teams) and asked to write in detail about their activities on a typical day and given the following to read: For the next 5 min, write about your typical day starting with the first thing you do in the morning. Please only write about the objective actions that you … DOI: 10.1126/science.1193147 , 686 (2010); 330Science et al.Anita Williams Woolley, Performance of Human Groups Evidence for a Collective Intelligence Factor in the This copy is for your personal, non-commercial use only. . clicking herecolleagues, clients, or customers by , you can order high-quality copies for yourIf you wish to distribute this article to others . herefollowing the guidelines can be obtained byPermission to republish or repurpose articles or portions of articles (this information is current as of October 29, 2010 ): The following resources related to this article are available online at www.sciencemag.org http://www.sciencemag.org/cgi/content/full/330/6004/686 version of this article at: including high-resolution figures, can be found in the onlineUpdated information and services, http://www.sciencemag.org/cgi/content/full/science.1193147/DC1 can be found at: Supporting Online Material http://www.sciencemag.org/cgi/content/full/330/6004/686#otherarticles , 2 of which can be accessed for free: cites 10 articlesThis article http://www.sciencemag.org/cgi/collection/psychology Psychology : subject collectionsThis article appears in the following registered trademark of AAAS. is aScience2010 by the American Association for the Advancement of Science; all rights reserved. The title CopyrightAmerican Association for the Advancement of Science, 1200 New York Avenue NW, Washington, DC 20005. (print ISSN 0036-8075; online ISSN 1095-9203) is published weekly, except the last week in December, by theScience o n O ct o b e r 2 9 , 2 0 1 0 w w w .s ci e n ce m a g .o rg D o w n lo a d e d f ro m http://www.sciencemag.org/about/permissions.dtl http://www.sciencemag.org/help/about/permissions.dtl http://www.sciencemag.org/cgi/content/full/330/6004/686 http://www.sciencemag.org/cgi/content/full/science.1193147/DC1 http://www.sciencemag.org/cgi/content/full/330/6004/686#otherarticles http://www.sciencemag.org/cgi/collection/psychology http://www.sciencemag.org task (correct, error, inserted error, and corrected error) to allow typists to distinguish sources of errors and correct responses and, therefore, provide a stronger test of illusions of authorship. We asked 24 skilled typists (WPM = 70.7 T 16.4) to type 600 words, each of which was followed by a four- alternative explicit report screen. Typists typed 91.8\% of the words correctly. Mean interkeystroke intervals, plotted in Fig. 3A, show post-error slow- ing for incorrect responses (F1,138 = 117.7, p < 0.01) and corrected errors (F1,138 = 120.0, p < 0.01), but not for inserted errors (F < 1.0), indicating that inner-loop detection distinguishes between actual errors and correct responses. Explicit detection probabilities, plotted in Fig. 3B, show good discrimination between correct and error responses. For correct responses, typists said “correct” more than “error” [t(23) = 97.29, p < 0.01]; for error responses, typists said “error” more than “correct” [t(23) = 8.22, p < 0.01]. Typ- ists distinguished actual errors from inserted errors well, avoiding an illusion of authorship. They said “error” more than “inserted” for actual errors [t(23) = 7.06, p < 0.01] and “inserted” more than “error” for inserted errors [t(23) = 14.75, p < 0.01]. However, typists showed a strong illusion of authorship with corrected errors. They were just as likely to call them correct responses as corrected errors [t(23) = 1.38]. The post-error slowing and post-trial report data show a dissociation between inner- and outer- loop error detection. We assessed the dissociation further by comparing post-error slowing on trials in which typists did and did not experience illusions of authorship (21). The pattern of post- error slowing was the same for both sets of trials (fig. S6), suggesting that the pattern in Fig. 3A is representative of all trials. The three experiments found strong dissocia- tions between explicit error reports and post-error slowing. These dissociations are consistent with the hierarchical error-detection mechanism that we proposed, with an outer loop that mediates ex- plicit reports and an inner loop that mediates post- error slowing. This nested-loop description of error detection is consistent with hierarchical models of cognitive control in typewriting (9, 10, 15–17) and with models of hierarchical control in other complex tasks (2, 8, 22). Speaking, playing music, and navigating through space may all involve inner loops that take care of the details of per- formance (e.g., uttering phonemes, playing notes, and walking) and outer loops that ensure that in- tentions are fulfilled (e.g., messages communi- cated, songs performed, and destinations reached). Hierarchical control may be prevalent in highly skilled performers who have had enough practice to develop an autonomous inner loop. Previous studies of error detection in simple tasks may describe inner-loop processing. The novel con- tribution of our research is to dissociate the outer loop from the inner loop. The three experiments demonstrate cogni- tive illusions of authorship in skilled typewriting (11–14). Typists readily take credit for correct output on the screen, interpreting corrected errors as their own correct responses. They take the blame for inserted errors, as in the first and sec- ond experiments, but they also blame the com- puter, as in the third experiment. These illusions are consistent with the hierarchical model of error detection, with the outer loop assigning credit and blame and the inner loop doing the work of typing (10, 17). Thus, illusions of authorship may be a hallmark of hierarchical control systems (2, 11, 22, 23). References and Notes 1. P. M. A. Rabbitt, J. Exp. Psychol. 71, 264 (1966). 2. D. A. Norman, Psychol. Rev. 88, 1 (1981). 3. C. B. Holroyd, M. G. H. Coles, Psychol. Rev. 109, 679 (2002). 4. N. Yeung, M. M. Botvinick, J. D. Cohen, Psychol. Rev. 111, 931 (2004). 5. W. J. Gehring, B. Goss, M. G. H. Coles, D. E. Meyer, E. Donchin, Psychol. Sci. 4, 385 (1993). 6. S. Dehaene, M. I. Posner, D. M. Tucker, Psychol. Sci. 5, 303 (1994). 7. C. S. Carter et al., Science 280, 747 (1998). 8. K. S. Lashley, in Cerebral Mechanisms in Behavior, L. A. Jeffress, Ed. (Wiley, New York, 1951), pp. 112–136. 9. T. A. Salthouse, Psychol. Bull. 99, 303 (1986). 10. G. D. Logan, M. J. C. Crump, Psychol. Sci. 20, 1296 (2009). 11. T. I. Nielsen, Scand. J. Psychol. 4, 225 (1963). 12. M. M. Botvinick, J. D. Cohen, Nature 391, 756 (1998). 13. D. M. Wegner, The Illusion of Conscious Will (MIT Press, Cambridge, MA, 2002). 14. G. Knoblich, T. T. J. Kircher, J. Exp. Psychol. Hum. Percept. Perform. 30, 657 (2004). 15. D. E. Rumelhart, D. A. Norman, Cogn. Sci. 6, 1 (1982). 16. L. H. Shaffer, Psychol. Rev. 83, 375 (1976). 17. X. Liu, M. J. C. Crump, G. D. Logan, Mem. Cognit. 38, 474 (2010). 18. A. M. Gordon, J. F. Soechting, Exp. Brain Res. 107, 281 (1995). 19. J. Long, Ergonomics 19, 93 (1976). 20. P. Rabbitt, Ergonomics 21, 945 (1978). 21. Materials and methods are available as supporting material on Science Online. 22. M. M. Botvinick, Trends Cogn. Sci. 12, 201 (2008). 23. R. Cooper, T. Shallice, Cogn. Neuropsychol. 17, 297 (2000). 24. We thank J. D. Schall for comments on the manuscript. This research was supported by grants BCS 0646588 and BCS 0957074 from the NSF. Supporting Online Material www.sciencemag.org/cgi/content/full/330/6004/683/DC1 Materials and Methods SOM Text Figs. S1 to S6 References 5 April 2010; accepted 13 September 2010 10.1126/science.1190483 Evidence for a Collective Intelligence Factor in the Performance of Human Groups Anita Williams Woolley,1* Christopher F. Chabris,2,3 Alex Pentland,3,4 Nada Hashmi,3,5 Thomas W. Malone3,5 Psychologists have repeatedly shown that a single statistical factor—often called “general intelligence”—emerges from the correlations among people’s performance on a wide variety of cognitive tasks. But no one has systematically examined whether a similar kind of “collective intelligence” exists for groups of people. In two studies with 699 people, working in groups of two to five, we find converging evidence of a general collective intelligence factor that explains a group’s performance on a wide variety of tasks. This “c factor” is not strongly correlated with the average or maximum individual intelligence of group members but is correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group. A s research, management, and many other kinds of tasks are increasingly accom- plished by groups—working both face- to-face and virtually (1–3)—it is becoming ever more important to understand the determinants of group performance. Over the past century, psychologists made considerable progress in defining and systematically measuring intelli- gence in individuals (4). We have used the sta- tistical approach they developed for individual intelligence to systematically measure the intelli- gence of groups. Even though social psycholo- gists and others have studied for decades how well groups perform specific tasks (5, 6), they have not attempted to measure group intelligence in the same way individual intelligence is measured— by assessing how well a single group can perform a wide range of different tasks and using that information to predict how that same group will perform other tasks in the future. The goal of the research reported here was to test the hypothesis that groups, like individuals, do have character- istic levels of intelligence, which can be measured and used to predict the groups’ performance on a wide variety of tasks. Although controversy has surrounded it, the concept of measurable human intelligence is based on a fact that is still as remarkable as it was to Spearman when he first documented it in 1904 1Carnegie Mellon University, Tepper School of Business, Pitts- burgh, PA 15213, USA. 2Union College, Schenectady, NY 12308, USA. 3Massachusetts Institute of Technology (MIT) Center for Collective Intelligence, Cambridge, MA 02142, USA. 4MIT Media Lab, Cambridge, MA 02139, USA. 5MIT Sloan School of Management, Cambridge, MA 02142, USA. *To whom correspondence should be addressed. E-mail: [email protected] 29 OCTOBER 2010 VOL 330 SCIENCE www.sciencemag.org686 REPORTS o n O ct o b e r 2 9 , 2 0 1 0 w w w .s ci e n ce m a g .o rg D o w n lo a d e d f ro m http://www.sciencemag.org (7): People who do well on one mental task tend to do well on most others, despite large variations in the tests’ contents and methods of administration (4). In principle, performance on cognitive tasks could be largely uncorrelated, as one might expect if each relied on a specific set of capacities that was not used by other tasks (8). It could even be negatively correlated, if practicing to improve one task caused neglect of others (9). The empirical fact of general cognitive ability as first demon- strated by Spearman is now, arguably, the most replicated result in all of psychology (4). Evidence of general intelligence comes from the observation that the average correlation among individuals’ performance scores on a relatively diverse set of cognitive tasks is positive, the first factor extracted in a factor analysis of these scores generally accounts for 30 to 50\% of the variance, and subsequent factors extracted account for substantially less variance. This first factor extracted in an analysis of individual intelligence tests is referred to as general cognitive ability, or g, and it is the main factor that intelligence tests measure. What makes intelligence tests of substantial prac- tical (not just theoretical) importance is that in- telligence can be measured in an hour or less, and is a reliable predictor of a very wide range of important life outcomes over a long span of time, including grades in school, success in many occupations, and even life expectancy (4). By analogy with individual intelligence, we define a group’s collective intelligence (c) as the general ability of the group to perform a wide variety of tasks. Empirically, collective intelligence is the inference one draws when the ability of a group to perform one task is correlated with that group’s ability to perform a wide range of other tasks. This kind of collective intelligence is a prop- erty of the group itself, not just the individuals in it. Unlike previous work that examined the effect on group performance of the average intelligence of individual group members (10), one of our goals is to determine whether the collective intelligence of the group as a whole has predictive power above and beyond what can be explained by knowing the abilities of the individual group members. The first question we examined was whether collective intelligence—in this sense—even exists. Is there a single factor for groups, a c factor, that functions in the same way for groups as general intelligence does for individuals? Or does group performance, instead, have some other correla- tional structure, such as several equally important but independent factors, as is typically found in research on individual personality (11)? To answer this question, we randomly as- signed individuals to groups and asked them to perform a variety of different tasks (12). In Study 1, 40 three-person groups worked together for up to 5 hours on a diverse set of simple group tasks plus a more complex criterion task. To guide our task sampling, we drew tasks from all quadrants of the McGrath Task Circumplex (6, 12), a well- established taxonomy of group tasks based on the coordination processes they require. Tasks in- cluded solving visual puzzles, brainstorming, making collective moral judgments, and negoti- ating over limited resources. At the beginning of each session, we measured team members’ indi- vidual intelligence. And, as a criterion task at the end of each session, each group played checkers against a standardized computer opponent. The results support the hypothesis that a general collective intelligence factor (c) exists in groups. First, the average inter-item correlation for group scores on different tasks is positive (r = 0.28) (Table 1). Next, factor analysis of team scores yielded one factor with an initial eigen- value accounting for more than 43\% of the variance (in the middle of the 30 to 50\% range typical in individual intelligence tests), whereas the next factor accounted for only 18\%. Confir- matory factor analysis supported the fit of a single latent factor model with the data [c2 = 1.66, P = 0.89, df = 5; comparative fit index (CFI) =.99, root mean square error of approxi- mation (RMSEA) = 0.01]. Furthermore, when the factor loadings for different tasks on the first general factor are used to calculate a c score for each group, this score strongly predicts perform- ance on the criterion task (r = 0.52, P = 0.01). Finally, the average and maximum intelligence scores of individual group members are not significantly correlated with c [r = 0.19, not significant (ns); r = 0.27, ns, respectively] and not predictive of criterion task performance (r = 0.18, ns; r = 0.13, ns, respectively). In a regres- sion using both individual intelligence and c to predict performance on the criterion task, c has a significant effect (b = 0.51, P = 0.001), but average individual intelligence (b = 0.08, ns) and maximum individual intelligence (b =.01, ns) do not (Fig. 1). In Study 2, we used 152 groups ranging from two to five members. Our goal was to replicate these findings in groups of different sizes, using a broader sample of tasks and an alternative mea- sure of individual intelligence. As expected, this study replicated the findings of Study 1, yielding a first factor explaining 44\% of the variance and a second factor explaining only 20\%. In addition, a confirmatory factor analysis suggests an excel- lent fit of the single-factor model with the data (c2 = 5.85, P = 0.32, df = 5; CFI = 0.98, NFI = 0.89, RMSEA = 0.03). In addition, for a subset of the groups in Study 2, we included five additional tasks, for a total of ten. The results from analyses incorporating all ten tasks were also consistent with the hypothesis that a general c factor exists (see Fig. 2). The scree test (13) clearly suggests that a one-factor model is the best fit for the data from both studies [Akaike Information Criterion (AIC) = 0.00 for single-factor solution]. Furthermore, parallel anal- ysis (13) suggests that only factors with an eigen- value above 1.38 should be retained, and there is only one such factor in each sample. These conclu- sions are supported by examining the eigenvalues both before and after principal axis extraction, which yields a first factor explaining 31\% of Table 1. Correlations among group tasks and descriptive statistics for Study 1. n = 40 groups; *P ≤ 0.05; **P ≤ 0.001. 1 2 3 4 5 6 7 8 9 1 Collective intelligence (c) 2 Brainstorming 0.38* 3 Group matrix reasoning 0.86** 0.30* 4 Group moral reasoning 0.42* 0.12 0.27 5 Plan shopping trip 0.66** 0.21 0.38* 0.18 6 Group typing 0.80** 0.13 0.50** 0.25* 0.43* 7 Avg member intelligence 0.19 0.11 0.19 0.12 –0.06 0.22 8 Max member intelligence 0.27 0.09 0.33* 0.05 –0.04 0.28 0.73** 9 Video game 0.52* 0.17 0.38* 0.37* 0.39* 0.44* 0.18 0.13 Minimum –2.67 9 2 32 –10.80 148 4.00 8.00 26 Maximum 1.56 55 17 81 82.40 1169 12.67 15.67 96 Mean 0 28.33 11.05 57.35 46.92 596.13 8.92 11.67 61.80 SD 1.00 11.36 3.02 10.96 19.64 263.74 1.82 1.69 17.56 Fig. 1. Standardized regression coefficients for collective intelligence (c) and average individual member intelligence when both are regressed to- gether on criterion task performance in Studies 1 and 2 (controlling for group size in Study 2). Coefficient for maximum member intelligence is also shown for comparison, calculated in a separate regression because it is too highly correlated with individual member intelligence to incorporate both in a single analysis (r = 0.73 and 0.62 in Studies 1 and 2, respectively). Error bars, mean T SE. www.sciencemag.org SCIENCE VOL 330 29 OCTOBER 2010 687 REPORTS o n O ct o b e r 2 9 , 2 0 1 0 w w w .s ci e n ce m a g .o rg D o w n lo a d e d f ro m http://www.sciencemag.org the variance in Study 1 and 35\% of the variance in Study 2. Multiple-group confirmatory factor analysis suggests that the factor structures of the two studies are invariant (c2 = 11.34, P = 0.66, df = 14; CFI = 0.99, RMSEA = 0.01). Taken together, these results provide strong support for the existence of a single dominant c factor underlying group performance. The criterion task used in Study 2 was an ar- chitectural design task modeled after a complex research and development problem (14). We had a sample of 63 individuals complete this task working alone, and under these circumstances, individual intelligence was a significant predictor of performance on the task (r = 0.33, P = 0.009). When the same task was done by groups, however, the average individual intelligence of the group members was not a significant predictor of group performance (r = 0.18, ns). When both individual intelligence and c are used to predict group performance, c is a significant predictor (b = 0.36, P = 0.0001), but average group member intelligence (b = 0.05, ns) and maximum member intelligence (b = 0.12, ns) are not (Fig. 1). If c exists, what causes it? Combining the find- ings of the two studies, the average intelligence of individual group members was moderately cor- related with c (r = 0.15, P = 0.04), and so was the intelligence of the highest-scoring team member (r = 0.19, P = 0.008). However, for both studies, c was still a much better predictor of group per- formance on the criterion tasks than the average or maximum individual intelligence (Fig. 1). We also examined a number of group and indi- vidual factors that might be good predictors of c. We found that many of the factors one might have ex- pected to predict group performance—such as group cohesion, motivation, and satisfaction—did not. However, three factors were significantly cor- related with c. First, there was a significant corre- lation between c and the average social sensitivity of group members, as measured by the “Reading the Mind in the Eyes” test (15) (r = 0.26, P = 0.002). Second, c was negatively correlated with the variance in the number of speaking turns by group members, as measured by the sociometric badges worn by a subset of the groups (16) (r = –0.41, P = 0.01). In other words, groups where a few people dominated the conversation were less collectively intelligent than those with a more equal distribution of conversational turn-taking. Finally, c was positively and significantly correlated with the proportion of females in the group (r = 0.23, P = 0.007). However, this result appears to be largely mediated by social sensitiv- ity (Sobel z = 1.93, P = 0.03), because (consistent with previous research) women in our sample scored better on the social sensitivity measure than men [t(441) = 3.42, P = 0.001]. In a regres- sion analysis with the groups for which all three variables (social sensitivity, speaking turn vari- ance, and percent female) were available, all had similar predictive power for c, although only social sensitivity reached statistical significance (b = 0.33, P = 0.05) (12). These results provide substantial evidence for the existence of c in groups, analogous to a well- known similar ability in individuals. Notably, this collective intelligence factor appears to depend both on the composition of the group (e.g., aver- agememberintelligence)andonfactorsthatemerge from the way group members interact when they are assembled (e.g., their conversational turn- taking behavior) (17, 18). These findings raise many additional questions. For example, could a short collective inteligence test predict a sales team’s or a top management team’s long-term effectiveness? More important- ly, it would seem to be much easier to raise the intelligence of a group than an individual. Could a group’s collective intelligence be increased by, for example, better electronic collaboration tools? Many previous studies have addressed ques- tions like these for specific tasks, but by measur- ing the effects of specific interventions on a group’s c, one can predict the effects of those interventions on a wide range of tasks. Thus, the ability to measure collective intelligence as a stable property of groups provides both a substantial economy of effort and a range of new questions to explore in building a science of collective performance. References and Notes 1. S. Wuchty, B. F. Jones, B. Uzzi, Science 316, 1036 (2007). 2. T. Gowers, M. Nielsen, Nature 461, 879 (2009). 3. J. R. Hackman, Leading Teams: Setting the Stage for Great Performances (Harvard Business School Press, Boston, 2002). 4. I. J. Deary, Looking Down on Human Intelligence: From Psychometrics to the Brain (Oxford Univ. Press, New York, 2000). 5. J. R. Hackman, C. G. Morris, in Small Groups and Social Interaction, Volume 1, H. H. Blumberg, A. P. Hare, V. Kent, M. Davies, Eds. (Wiley, Chichester, UK, 1983), pp. 331–345. 6. J. E. McGrath, Groups: Interaction and Performance (Prentice-Hall, Englewood Cliffs, NJ, 1984). 7. C. Spearman, Am. J. Psychol. 15, 201 (1904). 8. C. F. Chabris, in Integrating the Mind: Domain General Versus Domain Specific Processes in Higher Cognition, M. J. Roberts, Ed. (Psychology Press, Hove, UK, 2007), pp. 449–491. 9. C. Brand, The g Factor (Wiley, Chichester, UK, 1996). 10. D. J. Devine, J. L. Philips, Small Group Res. 32, 507 (2001). 11. R. R. McCrae, P. T. Costa Jr., J. Pers. Soc. Psychol. 52, 81 (1987). 12. Materials and methods are available as supporting material on Science Online. 13. R. B. Cattell, Multivariate Behav. Res. 1, 245 (1966). 14. A. W. Woolley, Organ. Sci. 20, 500 (2009). 15. S. Baron-Cohen, S. Wheelwright, J. Hill, Y. Raste, I. Plumb, J. Child Psychol. Psychiatry 42, 241 (2001). 16. A. Pentland, Honest Signals: How They Shape Our World (Bradford Books, Cambridge, MA, 2008). 17. L. K. Michaelsen, W. E. Watson, R. H. Black, J. Appl. Psychol. 74, 834 (1989). 18. R. S. Tindale, J. R. Larson, J. Appl. Psychol. 77, 102 (1992). 19. This work was made possible by financial support from the National Science Foundation (grant IIS-0963451), the Army Research Office (grant 56692-MA), the Berkman Faculty Development Fund at Carnegie Mellon University, and Cisco Systems, Inc., through their sponsorship of the MIT Center for Collective Intelligence. We would especially like to thank S. Kosslyn for his invaluable help in the initial conceptualization and early stages of this work and I. Aggarwal and W. Dong for substantial help with data collection and analysis. We are also grateful for comments and research assistance from L. Argote, E. Anderson, J. Chapman, M. Ding, S. Gaikwad, C. Huang, J. Introne, C. Lee, N. Nath, S. Pandey, N. Peterson, H. Ra, C. Ritter, F. Sun, E. Sievers, K. Tenabe, and R. Wong. The hardware and software used in collecting sociometric data are the subject of an MIT patent application and will be provided for academic research via a not-for-profit arrangement through A.P. In addition to the affiliations listed above, T.W.M. is also a member of the Strategic Advisory Board at InnoCentive, Inc.; a director of Seriosity, Inc.; and chairman of Phios Corporation. Supporting Online Material www.sciencemag.org/cgi/content/full/science.1193147/DC1 Materials and Methods Tables S1 to S4 References 2 June 2010; accepted 10 September 2010 Published online 30 September 2010; 10.1126/science.1193147 Include this information when citing this paper. Fig. 2. Scree plot demonstrating the first factor from each study ac- counting for more than twice as much variance as subsequent fac- tors. Factor analysis of items from the Wonderlic Personnel Test of In- dividual intelligence administered to 642 individuals is included as a comparison. 29 OCTOBER 2010 VOL 330 SCIENCE www.sciencemag.org688 REPORTS o n O ct o b e r 2 9 , 2 0 1 0 w w w .s ci e n ce m a g .o rg D o w n lo a d e d f ro m http://www.sciencemag.org alvaro Resaltado INTRODUCTION FEAR CONSENSUS, LOVE DISSENT THIS BOOK IS FUNDAMENTALLY ABOUT HOW WE MAKE DECISIONS and judgments. In particular, it is about the influence of others on our judgments. People influence us in a distinctly different manner depending on whether they are a majority and have consensus or whether they are a minority voice expressing dissent. We will see in this book that a consensus position can sway our judgments even when it is in error, and even when the facts are in front of our face. The more insidious aspect of consensus is that, whether or not we come to agree with the majority, it shapes the way we think. We start to view the world from the majority perspective. Whether we are seeking and interpreting information, using a strategy in problem-solving, or finding solutions, we take the perspective of that majority. We think in narrow ways—the majority’s ways. On balance, we make poorer decisions and think less creatively when we adopt the majority perspective. Dissent, the minority voice, also influences us. Dissenters, too, can sway us to their opinion. Theirs is an uphill battle, but they can get us to agree with them. The “why” and the “how” of a dissenter’s ability to persuade us are very different from how a majority persuades us. Persuasion by a dissenter is more indirect, requires more time, and follows a more subtle choreography of argument. Perhaps most importantly, dissent also shapes the way we think about an issue, the way we arrive at our position or decision. When we are exposed to dissent, our thinking does not narrow as it does when we are exposed to consensus. In fact, dissent broadens our thinking. Relative to what we would do on our own if we had not been exposed to dissent, we think in more open ways and in multiple directions. We consider more information and more options, and we use multiple strategies in problem-solving. We think more divergently, more creatively. The implications of dissent are important for the quality of our decision-making. On balance, consensus impairs the quality of our decisions while dissent benefits it. As beneficial as dissent may be, it is not easy for someone who holds a dissenting viewpoint to express it. When we think or believe differently from those around us, we are not sure that we are right. In fact, we are prone to think that “truth lies in numbers,” and when we find ourselves in a minority we think we must be wrong. Additionally, we are afraid of the ridicule or rejection that are likely to come from dissenting. We hesitate. We put our heads down. We are silent. Not speaking up, however, has consequences. If the individual does not speak up, the group suffers and misses opportunities. Worse, a group compelled to make quick judgments while operating from only one perspective can make very bad decisions. Some are fatal. Three days before Christmas, in 1978, United Airlines Flight 173 was headed from JFK Airport in New York to Portland, Oregon, with a scheduled stop in Denver. It was expected to arrive in Portland a little after 5:00 p.m. There were 196 people on board. The crew was experienced. Everything seemed fine. Everything seemed routine. As the flight approached Portland, the time came to lower the landing gear. Suddenly there was a loud thump, and the plane started to vibrate and rotate. Something was wrong. The crew started to question whether the landing gear was in fact down and whether it was locked. While not knowing exactly what was wrong, they certainly knew that something was not right. The pilot made what seemed to be a cautious and wise decision. He decided to abort the landing in order to check out the problem and determine the best course of action. The plane was put in a holding pattern. For around forty-five minutes, the captain and crew diligently investigated the problem and prepared the passengers. Everyone was “on board,” so to speak. However, another problem was developing. The plane was running out of fuel. They had more than enough fuel when they left Denver, but they were burning it up while focusing on the landing gear problem. The crew hadn’t taken this fully into account. In fact, they didn’t calculate how much time remained before they would run out of fuel because they had become blind to this issue. As the plane ran out of fuel, the engines failed, one after the other. The plane nosed downward and crashed into a suburban area of Portland around 6:15 p.m., only six miles from the airport. The plane literally fell out of the sky. Ten people died—two crew members and eight passengers. Another twenty-three people were seriously injured. How could this have happened? Not because of any of the “usual suspects.” There was no inexperience or dereliction of duty among the crew, nor were drugs or lack of sleep a factor. One important reason the tragedy occurred was that the crew members didn’t speak up—or at least, not with conviction. Why? Real-life situations are always multiply determined. There is never one reason for a sequence of events. Several possibilities come to mind in this case. Perhaps the crew just followed authority, the captain, who was focused on the landing gear. Perhaps the stress prevented them from noticing the fuel level; studies show that high levels of stress narrow attention. Still, when they did notice that the fuel was low, why did they not realize what that meant? Why weren’t they aware of the danger it posed? Why did no one speak up? I would suggest that the consensus itself inhibited the expression of dissent but also shaped the crew’s thinking to that perspective. It was not just where the crew’s attention was focused that was a problem, but also the information they sought, the alternatives they considered, and the strategies they employed. Once everyone was on the same page, all focusing on the landing gear, they narrowly viewed the situation only from that perspective. They sought information about the landing gear. They considered alternatives only within the context of the landing gear problem. They did not consider the possibility that such a focus had a downside. When faced with information pertinent to another problem—namely, the fuel situation—they failed to fully consider it or to appreciate the growing danger. In fact, they did not even calculate the amount of time remaining before they would run out of fuel. We see the consequences of this thinking in the National Transportation Safety Board accident report’s summary of the last thirteen minutes of United Airlines Flight 173. In the cockpit at 18:02:22, the flight engineer said that they had about “three [3,000 pounds] on the fuel and that’s it.” They were only five miles south of the airport. At 18:03:23, Portland approach asked about the fuel, and the captain said, “About four thousand, well, make it three thousand, pounds of fuel.” About three minutes later, the captain said that they would be landing in around five minutes. Almost simultaneously, however, the first officer said, “I think you just lost number four [engine].” He added, a few seconds later, “We’re going to lose an engine.” “Why?” asked the captain. “We’re losing an engine,” the first officer said again. “Why?” the captain repeated. “Fuel,” said the first officer. Almost seven minutes later, the first officer warned Portland approach: “Portland tower, United one seventy three heavy. Mayday. We’re—the engines are flaming out. We’re going down. We’re not going to be able to make the airport.” A minute later, the plane crashed into a wooded section of suburban Portland. United Airlines Flight 173 had plenty of fuel when it left Denver. At the crash site, however, there was no “usable fuel” left. The plane had literally run out of gas. “That’s it” when reporting a low fuel level of 3,000 pounds? Why did no one shout, “We’re running out of fuel!” or, “We’re running out of time and need to land!” Everyone seemed to be in agreement, busily trying to find the problem with the landing gear. Even the captain asked, “Why?” when told they had lost an engine. No one seemed to appreciate the importance of the low amount of fuel remaining because they had only one focus. Which of us would have thought differently? Which of us would have spoken up? Doing so would have meant challenging the captain and the crew members who were all “on the same page.” More importantly, which of us would have even noticed that the plane was out of fuel? When everyone is focused on one thing, they all lose sight of relevant information and options. What we will see in this book is that consensus creates one focus—the group’s. It causes us to miss even the obvious. In this example, most people recognize that dissent could have had value if it had been correct. If someone had spoken up more forcefully about the diminishing fuel, the crew might have paid more attention to it. Even then, we know that people do not always follow the truth. Not only does it depend on who holds the truth, but people are more inclined to follow the majority than the minority, right or wrong. However, what is less recognized is that dissent has value, even when it is not correct. What we will see in this book is that the value of dissent does not lie in its correctness. Even when wrong, dissent does two things directly pertinent to the example. It breaks the blind following of the majority. People think more independently when consensus is challenged. Perhaps more importantly— and this is the core message of this book—dissent stimulates thought that is more divergent and less biased. Dissent motivates us to seek more information and to consider more alternatives than we would otherwise, spurring us to contemplate the cons as well as the pros of various positions. I would hazard a guess that had someone on United Airlines Flight 173 challenged the focus on the landing gear, the crew’s thinking about other possible problems—including most likely the fuel—would have been stimulated. I worry when I see colleagues and friends parse their words or remain silent about their objections when they see the presence of the will of the majority. I worry when I watch individuals with a strong need for control at the helm of groups. Whether it is in an organization or a start-up, in a cult or on the board of a co-op building, we see how power coupled with a need for control can manifest itself in hubris and a tendency to silence opposition. Rather than encouraging a culture that welcomes different views, such leaders make sure that dissent is not present—or if it arises, that it is punished. I have even seen board contracts with a friendly “be a team player” provision cautioning new numbers to “respect the collective authority… by not undermining majority decisions… even when [they] may disagree.” The message about dissent is clear. It is not welcomed. The claims of this book are broad, but I don’t want you to take them as pronouncements. I don’t want to persuade you through stories, counting on your intuitive acceptance of the claims. I want to persuade you by research facts, drawn from research that has held up over time and in multiple settings. When I do use narratives, it’s to illustrate the range and applicability of the ideas I discuss, informed by the research. They range from the United Airlines disaster to Edward Snowden’s revelations about the National Security Agency (NSA), to the Jonestown massacre, to the decision-making procedures of successful hedge funds. My own interviews with CEOs add to the mix. My aim is to help you recognize the patterns of influence in the groups to which you belong yourself and their effect on the quality of your own thoughts and decisions. This book will address the complexity of influence processes and hopefully will cause you to reconsider advice that overestimates the value of consensus and underestimates the value of dissent. A CHALLENGE TO THE POPULAR VIEW OF CONSENSUS The ideas presented here contrast with much common advice as well as some popular books, such as the New York Times best-seller The Wisdom of Crowds by James Surowiecki, which points out the superiority of the judgments of “the many.” Although that book is a good corrective to the value placed on the single “expert,” the accuracy of large numbers of people is limited. The research supports the relative accuracy of large numbers of people when the task involves common knowledge and the judgments are independent—that is, when people are not influenced by one another. These constraints are important in assessing situations where numbers may provide a statistical advantage. However, the larger concern is that such books can inadvertently give the impression that majorities are likely correct, rather than that they may be correct under certain circumstances. This book also serves as a counter to books, such as James Collins and Jerry Porras’s Built to Last, that link success to cultlike corporate cultures that foster like-mindedness and suppress dissent. Those are the cultures that recommend being a team player, promoting consensus, and being diplomatic (or silent) about disagreements. This book also contrasts with the work of many researchers of social influence, a field with a long history in social psychology. Social influence is often considered the core issue, since it deals with the influence “that people have upon the beliefs or behavior of others.” Most of that research has been guided, however, by two tendencies. One is an assumption that influence flows from the strong to the weak, from the many to the few. Thus, there have been many studies of the persuasive power of the majority, but far fewer studies of the ways in which the minority persuades. Though research has now documented the ability of the minority voice to persuade, many in the field still view it as unlikely or assume that it is subject to the same patterns as persuasion by a majority. We will see that this is not correct. The ways in which majority and minority voices persuade others of their position are very different and are manifested in different ways. The other tendency in the research literature is to reduce the complexity of the ways in which people affect our thoughts, beliefs, and behaviors to one of gaining our agreement. Reducing the broad area of social influence to persuasion is akin to a focus solely on winning—getting people to agree with you, to say yes to you, or to adopt your position. Your coworker doesn’t like your preference for a new hire, so you get her to agree with you. You favor a guilty verdict when serving on a jury and convince a fellow juror to vote that way. For decades, social psychologists have studied influence in this narrow sense of persuasion—who, when, how, and why you can get people to agree with you—and used a relatively easy measure for it. If you start out taking position A and I take position B, then your movement from position A to position B indicates that I have persuaded you. Research is easier when we confine it to scales that measure movement from A to B. But persuasion is different from changing the way someone thinks about an issue, and it’s different from stimulating thought. If upon hearing your position on the defendant’s guilt or innocence I look at the evidence again and consider the pros and cons of each position and alternative possibilities, you have influenced my thinking. I may not agree with you in the end, but you have influenced how I think and the quality of the judgments and decisions I make. I have engaged in what most researchers consider good decision-making—the kind that on balance leads to better decisions. Did a person standing over the body at the crime scene flee because he was guilty, or did he flee because he was afraid he would be accused? If I consider both options rather than rush to judgment, I am likely to make a better decision. From a research point of view, it is harder to study something like stimulated thought, which is not as easily schematized as persuasion. You have to find ways to measure the information people seek, the options they consider, the quality of their decisions, and the creativity of their solutions. Thankfully, as this book will demonstrate, we have found reliable ways to do this. If we study only persuasion—that more narrow form of influence aimed at gaining agreement—we don’t get to the quality of the decision. We rarely know whether a decision was right or not, since our assessment partly depends on our own values. Was the merger a good idea? Was the majority on a 10–2 verdict correct? Would a 12–0 verdict have been correct? We can’t know for sure. In the O. J. Simpson case, which jury was correct: the jury that came to a “not guilty” verdict in the criminal case or the jury that voted “guilty” in the civil case? We all have our opinions on this case, and we all know how clever we can be when we justify our positions. The best way of assessing quality is to instead assess the decision-making process. We do know something about the process of good decision- making. On balance, a good process leads to a good decision. Good decision-making, at its heart, is divergent thinking. When we think divergently, we think in multiple directions, seek information and consider facts on all sides of the issue, and think about the cons as well as the pros. Bad decision- making is the reverse. Thinking convergently, we focus more narrowly, usually in one direction. We seek information and consider facts that support an initial preference. We tend not to consider the cons of the position, nor do we look at alternative ways of interpreting the facts. Perhaps you had a grade school arithmetic teacher who taught you to check your work by doing it two different ways. To this day, I don’t just add things up the same way a second or third time to check a calculation. Rather than likely repeat the same mistake, I check my work a different way. I subtract one element from the sum to see what remains. I can add up 15 + 28 several times and continue to think it equals 33 (instead of 43). If I subtract 15 from 33, I will see that I made a mistake: 33 − 15 doesn’t equal 28. I am then far more likely to look more carefully and find that the sum is 43. By using divergent thinking—that is, approaching an issue from several vantage points—we are likely to make better decisions. This is the kind of thinking that dissent stimulates. My own recognition of the importance of stimulated thought stemmed from my long-standing interest in jury decision-making. It was in doing research on juries and consulting with lawyers that I came to recognize that influence is far more powerful than persuasion. I also realized that I was less interested in who “won” than in the quality of the decisions reached by juries. I could make money—a lot of it— advising lawyers on how to win by crafting their opening and closing arguments for persuasive impact. I could also show lawyers how to assess the dynamics of a jury in order to know which jurors to remove by peremptory challenge, not just because of their likely vote but also because of their ability to persuade the others. When the focus is on winning, everything is about persuasion—about gaining agreement with the position I favor. However, it became clear to me that my interests were in the quality of the decision—and in justice. Regardless of who wins, is the verdict the correct one? In our initial studies, my colleagues and I noticed that, when there is dissent, the decision-making improves. Our simulated juries that included dissenters considered more facts and more ways of viewing those facts. This led to decades of research on the ways in which dissent stimulates the way we think, the way we solve problems, and the way we detect solutions. However, we also learned about the power of consensus to stimulate our thinking as well—in diametrically different ways. We designed most of our experiments to study both consensus and dissent. We predicted and found very different results simply on the basis of whether we were looking at the influence of “the many” or “the few.” Moreover, we found the same pattern of results over and over. Consensus narrows, while dissent opens, the mind. Both affect the quality of our decisions. The take-home message of the research and this book is that there are perils in consensus and there is value in dissent. This message flies in the face of much advice these days. We are told the benefits of liking and being liked, of “fitting in” with the culture. We are taught to believe in the wisdom of the majority and reminded of the likely repercussions of being different, of not “fitting in” or of “speaking up” when we disagree. Many books, consultants, and academicians echo this advice of “fitting in.” Some of it is correct. There are certainly benefits to being liked and to belonging, and there are certainly risks associated with dissent. What is often not reported is that belonging has a price—our agreement. Paying this price often leads to unreflective thinking, bad decisions, and reduced creativity, not to mention boredom, vulnerability, and deadened affect. Have you ever wanted to scream when everyone was pandering and praising each other and no one would talk about the elephant in the room? For example, have you wanted to yell, “Are we crazy to hire this guy?” or, “Should we really be making this merger?” As the Japanese saying goes: the nail that sticks up will be hammered down. However, too often there is no nail standing up. Consensus prevails, conformity ensues, and group processes look more like groupthink. Ethical violations and problems within an organization go unreported and are not considered. Everyone is walking on eggshells, strategizing and deciding when to speak up and when to be quiet. All the while, we are in these deadening meetings and interactions where many people are often a bit fake—often opportunistic. This isn’t the case for everyone, of course. Some genuinely believe in the majority position, but they are still influenced by the incentives to agree and belong. When groupthink takes over, we can lose the value of each individual’s input, the experiences and opinions each can bring to bear on a decision or problem. We also lose the stimulating properties of dissent. Challenging the opinions of others takes courage. I would argue that it also takes conviction to dissent. People don’t like it when you argue another position. I myself still get irritated when people disagree with me. If I am honest, I am sure that they are at best misinformed. And I study this stuff. What I do know, however, is that the challenge that they pose makes me a better decision-maker and a more creative problem-solver. What I also know is that these benefits do not derive from a diversity of demographics (age, gender, race, and so on). Nor do they come from education and training, which, even though well meant, are limited and have benefits that are often overblown. What I have learned is that these benefits accrue from dissent, from being challenged. We benefit when there are dissenting views that are authentically held and that are expressed over times. THE BLUEPRINT OF THE BOOK In Part I, we focus on persuasion and the substantial research that helps us to understand how majority and minority views get us to agree with them. I want you to see and worry about the power of the majority, especially when it is unchallenged, for we tend to follow and agree with the majority right or wrong. Too often we assume that truth lies in numbers rather than assess the information rationally. The problem is that we do this unreflectively. We blindly follow the majority. This tendency can be seen in consumer behavior, in ad campaigns, in stock bubbles, and in what we see and believe even in our daily lives. Even in these situations, I want you to see that dissent provides value. It takes only one dissenting voice to liberate us from the hold of the majority. Dissent makes us better able to think independently, to “know what we know.” Dissent can also persuade us, gaining our agreement with its position. We will see that persuasion by dissent is a more artful journey than persuasion by the majority. Considering that people have many reasons to resist agreement with a dissenter, we will see how the clever use of procedures and techniques as simple as varying the order in which people speak can make all the difference for the dissenter’s ability to persuade. Once we better understand how consensus and dissent gain agreement, we are in a position to understand why they stimulate different kinds of thinking. This area, covered in Part II, is where I have spent the greater part of my professional career. We will see detailed research evidence on how consensus and dissent stimulate the ways in which we think and decide, and we will see these processes replicated across experiments and real-life situations such as the Jonestown massacre and Edward Snowden’s leak of NSA data. Part III turns to groups and applications. Groups are complicated, as they involve several people in interaction. However, scores of studies have uncovered well-established patterns for how and why groups find consensus. Groups often arrive at consensus too soon—and not for good reasons. Some of these patterns are captured by the popular term “groupthink.” We will also see the role of dissent in improving group decision-making. Dissent does not just thwart groupthink; it actually increases the quality of the decision- making process. The message of this book is not that we should create dissent, but that we should permit dissent and embrace it when it is present. The distinction is important, as the most important element of effective dissent is its authenticity, as our research repeatedly underscores. This is one reason why techniques such as playing devil’s advocate do not work. They are role-playing and do not challenge bias or stimulate divergent thinking, as does authentic dissent. Authenticity is also a reason why, when brainstorming, rules such as “do not criticize each other’s ideas” are ill advised. When you finish this book, I hope that you will be wary of consensus because you recognize its pitfalls, especially in your own thinking, that you will use mechanisms to reduce automatic thinking, and that you will better recognize the importance of thinking for yourself. As a leader, the hope is that you will better manage group processes and will have techniques at your fingertips to keep discussion open, avoiding premature closure on decisions. Just as important, I hope that you will learn to welcome dissent and not just tolerate it, having come to understand that it has value even when it is wrong. Above all, I hope that this book persuades you not to suppress dissent. We are all subject to biases and our own prejudices, including our tendency to try to silence those who irritate us by disagreeing with us. However, dissent makes us more complex thinkers. In prompting us to consider the pros and cons of all positions, dissent makes us reconsider our own position, which itself inevitably has cons as well as pros, if we bother to analyze it carefully. The grand hope of this book is that it will liberate you. One form of this is the liberation to “speak up”—being brave enough to tell the surgeon that he may be operating on the wrong limb, or to tell your boss that his latest plan has a fatal flaw, or to let your best friend know that she is about to buy an expensive dress that is ill suited to her. You will hopefully confront what you think are wrong decisions knowing that, even if you don’t persuade the other person, you will stimulate her thinking. You will know that, on balance, your speaking up has improved the decisions and judgments of your groups. Another form of liberation is to be less afraid to think differently from others. Whether or not you decide to express it, you don’t want to lose the ability to “know what you know.” Nor do you want to fall prey to the self-brainwashing that often accompanies consensus and a need to belong. Cults know the power of self-brainwashing all too well. So do abusive individuals. There is liberation in recognizing the source of their power as well as your own. A quote I often use and have always loved comes to us from Senator William Fulbright: “We must learn to welcome and not to fear the voices of dissent.” I could not summarize this book more succinctly—unless by adding this remark from Mark Twain: “Whenever you find that you are on the side of the majority, it is time to reform—(or pause and reflect).” TITLE PAGE COPYRIGHT DEDICATION ACKNOWLEDGMENTS INTRODUCTION: FEAR CONSENSUS, LOVE …