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92-426: Google Flu Trends stopped publishing current estimates on 9 August 2015. Historical estimates are still available for download, and current data are offered for declared research purposes. The idea behind Google Flu Trends was that, by monitoring millions of users’ health tracking behaviors online, the large number of Google search queries gathered can be analyzed to reveal if there is the presence of flu-like illness in

184-504: A factor analysis . Both studies showed support for a general collective intelligence factor c underlying differences in group performance with an initial eigenvalue accounting for 43% (44% in study 2) of the variance, whereas the next factor accounted for only 18% (20%). That fits the range normally found in research regarding a general individual intelligence factor g typically accounting for 40% to 50% percent of between-individual performance differences on cognitive tests. Afterwards,

276-491: A "collective consciousness" and Teilhard de Chardin as a thinker who has developed the philosophical implications of the group mind. Tom Atlee focuses primarily on humans and on work to upgrade what Howard Bloom calls "the group IQ". Atlee feels that collective intelligence can be encouraged "to overcome ' groupthink ' and individual cognitive bias in order to allow a collective to cooperate on one process – while achieving enhanced intellectual performance." George Pór defined

368-439: A "public intelligence" that keeps public officials and corporate managers honest, turning the concept of "national intelligence" (previously concerned about spies and secrecy) on its head. According to Don Tapscott and Anthony D. Williams , collective intelligence is mass collaboration . In order for this concept to happen, four principles need to exist: A new scientific understanding of collective intelligence defines it as

460-447: A broader consideration of how to design "collectives" of self-interested adaptive agents to meet a system-wide goal. This was related to single-agent work on "reward shaping" and has been taken forward by numerous researchers in the game theory and engineering communities. Howard Bloom has discussed mass behavior – collective behavior from the level of quarks to the level of bacterial, plant, animal, and human societies. He stresses

552-419: A group (Group-IQ) parallel to an individual's intelligence quotient (IQ) even though the score is not a quotient per se. Mathematically, c and g are both variables summarizing positive correlations among different tasks supposing that performance on one task is comparable with performance on other similar tasks. c thus is a source of variance among groups and can only be considered as a group's standing on

644-453: A group's general ability to perform a wide range of tasks. Definition, operationalization and statistical methods are similar to the psychometric approach of general individual intelligence . Hereby, an individual's performance on a given set of cognitive tasks is used to measure general cognitive ability indicated by the general intelligence factor g proposed by English psychologist Charles Spearman and extracted via factor analysis . In

736-577: A human swarm challenge by CBS Interactive to predict the Kentucky Derby. The swarm correctly predicted the first four horses, in order, defying 542–1 odds and turning a $ 20 bet into $ 10,800. The value of parallel collective intelligence was demonstrated in medical applications by researchers at Stanford University School of Medicine and Unanimous AI in a set of published studies wherein groups of human doctors were connected by real-time swarming algorithms and tasked with diagnosing chest x-rays for

828-540: A master's degree in biomedical informatics and he did his residency at University of California, San Francisco (UCSF). He was an internist by training. He became interested in the application of technology in healthcare during his medical training, and noticing how difficult it was to find things in the medical records and how as time went on, the records got larger and more difficult to navigate. Zeiger did primary care for some time. Zeiger has been profiled for partnering tech companies to health efforts. Zeiger

920-525: A mean absolute error of also 0.20, and the benchmark of random prediction had 1.80). One source of problems is that people making flu-related Google searches may know very little about how to diagnose flu; searches for flu or flu symptoms may well be researching disease symptoms that are similar to flu, but are not actually flu. Furthermore, analysis of search terms reportedly tracked by Google, such as "fever" and "cough", as well as effects of changes in their search algorithm over time, have raised concerns about

1012-408: A more complex task was solved by each group to determine whether c factor scores predict performance on tasks beyond the original test. Criterion tasks were playing checkers (draughts) against a standardized computer in the first and a complex architectural design task in the second study. In a regression analysis using both individual intelligence of group members and c to predict performance on

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1104-461: A multiplier effect in group problem solving: "Three people working together in this augmented mode [would] seem to be more than three times as effective in solving a complex problem as is one augmented person working alone". In 1994, he coined the term 'collective IQ' as a measure of collective intelligence, to focus attention on the opportunity to significantly raise collective IQ in business and society. The idea of collective intelligence also forms

1196-454: A non- Turing model of computation is used. This theory allows simple formal definition of collective intelligence as the property of social structure and seems to be working well for a wide spectrum of beings, from bacterial colonies up to human social structures. Collective intelligence considered as a specific computational process is providing a straightforward explanation of several social phenomena. For this model of collective intelligence,

1288-438: A population. Google Flu Trends compared these findings to a historic baseline level of influenza activity for its corresponding region and then reports the activity level as either minimal, low, moderate, high, or intense. These estimates have been generally consistent with conventional surveillance data collected by health agencies, both nationally and regionally. Roni Zeiger helped develop Google Flu Trends. Google Flu Trends

1380-610: A predictor of c was largely mediated by social sensitivity ( Sobel z = 1.93, P= 0.03) which is in vein with previous research showing that women score higher on social sensitivity tests. While a mediation , statistically speaking, clarifies the mechanism underlying the relationship between a dependent and an independent variable, Wolley agreed in an interview with the Harvard Business Review that these findings are saying that groups of women are smarter than groups of men. However, she relativizes this stating that

1472-743: A really clever way of using data that is created unintentionally by the users of Google to see patterns in the world that would otherwise be invisible,” said Thomas W. Malone, a professor at the Sloan School of Management at MIT. “I think we are just scratching the surface of what's possible with collective intelligence.” The initial Google paper stated that the Google Flu Trends predictions were 97% accurate comparing with CDC data. However subsequent reports asserted that Google Flu Trends' predictions have been very inaccurate, especially in two high-profile cases. Google Flu Trends failed to predict

1564-553: A similar result for groups working together online communicating only via text and confirmed the role of female proportion and social sensitivity in causing collective intelligence in both cases. Similarly to Wolley et al., they also measured social sensitivity with the RME which is actually meant to measure people's ability to detect mental states in other peoples' eyes. The online collaborating participants, however, did neither know nor see each other at all. The authors conclude that scores on

1656-633: A single organism. Wheeler saw this collaborative process at work in ants that acted like the cells of a single beast he called a superorganism . In 1912 Émile Durkheim identified society as the sole source of human logical thought. He argued in " The Elementary Forms of Religious Life " that society constitutes a higher intelligence because it transcends the individual over space and time. Other antecedents are Vladimir Vernadsky and Pierre Teilhard de Chardin 's concept of " noosphere " and H. G. Wells 's concept of " world brain ". Peter Russell, Elisabet Sahtouris , and Barbara Marx Hubbard (originator of

1748-474: A voting group is more likely than not to make a correct decision, the probability that the highest vote of the group is the correct decision increases with the number of members of the group. Many theorists have interpreted Aristotle 's statement in the Politics that "a feast to which many contribute is better than a dinner provided out of a single purse" to mean that just as many may bring different dishes to

1840-421: A wide range of tasks. Definition, operationalization and statistical methods are derived from g . Similarly as g is highly interrelated with the concept of IQ , this measurement of collective intelligence can be interpreted as intelligence quotient for groups (Group-IQ) even though the score is not a quotient per se. Causes for c and predictive validity are investigated as well. Writers who have influenced

1932-428: Is a ToM test for adults that shows sufficient test-retest reliability and constantly differentiates control groups from individuals with functional autism or Asperger Syndrome . It is one of the most widely accepted and well-validated tests for ToM within adults. ToM can be regarded as an associated subset of skills and abilities within the broader concept of emotional intelligence . The proportion of females as

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2024-430: Is a measure of collective intelligence, although it is often used interchangeably with the term collective intelligence. Collective intelligence has also been attributed to bacteria and animals. It can be understood as an emergent property from the synergies among: Or it can be more narrowly understood as an emergent property between people and ways of processing information. This notion of collective intelligence

2116-591: Is a select list of some of Zeiger's writings. Collective intelligence Collective intelligence ( CI ) is shared or group intelligence ( GI ) that emerges from the collaboration , collective efforts, and competition of many individuals and appears in consensus decision making . The term appears in sociobiology , political science and in context of mass peer review and crowdsourcing applications. It may involve consensus , social capital and formalisms such as voting systems , social media and other means of quantifying mass activity. Collective IQ

2208-458: Is another potential parallel to individual intelligence where more intelligent people are found to acquire new material quicker. Individual intelligence can be used to predict plenty of life outcomes from school attainment and career success to health outcomes and even mortality. Whether collective intelligence is able to predict other outcomes besides group performance on mental tasks has still to be investigated. Gladwell (2008) showed that

2300-440: Is conversational turn-taking. Research further suggest that collectively intelligent groups communicate more in general as well as more equally; same applies for participation and is shown for face-to-face as well as online groups communicating only via writing. Bottom-up processes include group composition, namely the characteristics of group members which are aggregated to the team level. An example of such bottom-up processes

2392-404: Is interlinked with knowledge-based culture and sustained by collective idea sharing, and thus contributes to a better understanding of diverse society. Similar to the g factor ( g ) for general individual intelligence, a new scientific understanding of collective intelligence aims to extract a general collective intelligence factor c factor for groups indicating a group's ability to perform

2484-469: Is just moderately correlated with the intelligence of individual group members. According to Woolley et al.'s results, neither team cohesion nor motivation or satisfaction is correlated with c . However, they claim that three factors were found as significant correlates: the variance in the number of speaking turns, group members' average social sensitivity and the proportion of females. All three had similar predictive power for c , but only social sensitivity

2576-408: Is more than just the aggregation of the individual IQs or the influence of the group member with the highest IQ. Engel et al. (2014) replicated Woolley et al.'s findings applying an accelerated battery of tasks with a first factor in the factor analysis explaining 49% of the between-group variance in performance with the following factors explaining less than half of this amount. Moreover, they found

2668-422: Is nearly zero. This may explain why Woolley et al. found that the group's individual intelligence scores were not predictive of performance. In addition, low effort on tasks in human subjects research may inflate evidence for a supposed collective intelligence factor based on similarity of performance across tasks, because a team's low effort on one research task may generalize to low effort across many tasks. It

2760-419: Is notable that such a phenomenon is present merely because of the low stakes setting of laboratory research for research participants and not because it reflects how teams operate in organizations. Noteworthy is also that the involved researchers among the confirming findings widely overlap with each other and with the authors participating in the original first study around Anita Woolley. On 3 May 2022,

2852-412: Is referred to as "symbiotic intelligence" by Norman Lee Johnson. The concept is used in sociology , business , computer science and mass communications: it also appears in science fiction . Pierre Lévy defines collective intelligence as, "It is a form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills. I'll add

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2944-551: Is rooted in scientific community metaphor . The term group intelligence is sometimes used interchangeably with the term collective intelligence. Anita Woolley presents Collective intelligence as a measure of group intelligence and group creativity. The idea is that a measure of collective intelligence covers a broad range of features of the group, mainly group composition and group interaction. The features of composition that lead to increased levels of collective intelligence in groups include criteria such as higher numbers of women in

3036-471: Is the average social sensitivity or the average and maximum intelligence scores of group members. Furthermore, collective intelligence was found to be related to a group's cognitive diversity including thinking styles and perspectives. Groups that are moderately diverse in cognitive style have higher collective intelligence than those who are very similar in cognitive style or very different. Consequently, groups where members are too similar to each other lack

3128-478: Is the coefficient, while ε is the error term. Each of the 50 million queries is tested as Q to see if the result computed from a single query could match the actual history ILI data obtained from the U.S. Centers for Disease Control and Prevention (CDC). This process produces a list of top queries which gives the most accurate predictions of CDC ILI data when using the linear model. Then the top 45 queries are chosen because, when aggregated together, these queries fit

3220-574: The c factor compared to other groups in a given relevant population. The concept is in contrast to competing hypotheses including other correlational structures to explain group intelligence, such as a composition out of several equally important but independent factors as found in individual personality research . Besides, this scientific idea also aims to explore the causes affecting collective intelligence, such as group size, collaboration tools or group members' interpersonal skills. The MIT Center for Collective Intelligence , for instance, announced

3312-494: The " genetic algorithms ", concepts pioneered by John Holland . Bloom traced the evolution of collective intelligence to our bacterial ancestors 1 billion years ago and demonstrated how a multi-species intelligence has worked since the beginning of life. Ant societies exhibit more intelligence, in terms of technology, than any other animal except for humans and co-operate in keeping livestock, for example aphids for "milking". Leaf cutters care for fungi and carry leaves to feed

3404-554: The 2009 spring pandemic and over the interval 2011–2013 it consistently overestimated relative flu incidence, predicting twice as many doctors' visits over one interval in the 2012-2012 flu season as the CDC recorded. A 2022 study published (with commentaries) in the International Journal of Forecasting found that Google Flu Trends was outperformed by the recency heuristic, an instance of so-called "naive" forecasting, where

3496-483: The CDC identified influenza cases spiking in the mid-Atlantic region of the United States. However, Google's data of search queries about flu symptoms was able to show that same spike two weeks prior to the CDC report being released. “The earlier the warning, the earlier prevention and control measures can be put in place, and this could prevent cases of influenza,” said Dr. Lyn Finelli , lead for surveillance at

3588-507: The IP address associated with each search, the state in which this query was entered can be determined. A linear model is used to compute the log-odds of Influenza-like illness (ILI) physician visit and the log-odds of ILI-related search query: P is the percentage of ILI physician visit and Q is the ILI-related query fraction computed in previous steps. β 0 is the intercept and β 1

3680-587: The RME must be related to a broader set of abilities of social reasoning than only drawing inferences from other people's eye expressions. A collective intelligence factor c in the sense of Woolley et al. was further found in groups of MBA students working together over the course of a semester, in online gaming groups as well as in groups from different cultures and groups in different contexts in terms of short-term versus long-term groups. None of these investigations considered team members' individual intelligence scores as control variables. Note as well that

3772-743: The Reading the Mind in the Eyes Test (RME) and correlated .26 with c . Hereby, participants are asked to detect thinking or feeling expressed in other peoples' eyes presented on pictures and assessed in a multiple choice format. The test aims to measure peoples' theory of mind (ToM) , also called 'mentalizing' or 'mind reading', which refers to the ability to attribute mental states, such as beliefs, desires or intents, to other people and in how far people understand that others have beliefs, desires, intentions or perspectives different from their own ones. RME

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3864-538: The actual important thing is the high social sensitivity of group members. It is theorized that the collective intelligence factor c is an emergent property resulting from bottom-up as well as top-down processes. Hereby, bottom-up processes cover aggregated group-member characteristics. Top-down processes cover group structures and norms that influence a group's way of collaborating and coordinating. Top-down processes cover group interaction, such as structures, processes, and norms. An example of such top-down processes

3956-477: The algorithm developers "felt an unarticulated need to cloak the actual search terms identified". Google Flu Trends tries to avoid privacy violations by only aggregating millions of anonymous search queries, without identifying individuals that performed the search. Their search log contains the IP address of the user, which could be used to trace back to the region where the search query is originally submitted. Google runs programs on computers to access and calculate

4048-403: The authors of "Quantifying collective intelligence in human groups", who include Riedl and Woolley from the original 2010 paper on Collective Intelligence, issued a correction to the article after mathematically impossible findings reported in the article were noted publicly by researcher Marcus Credé. Among the corrections is an admission that the average variance extracted (AVE)--that is to say,

4140-502: The biological adaptations that have turned most of this earth's living beings into components of what he calls "a learning machine". In 1986 Bloom combined the concepts of apoptosis , parallel distributed processing , group selection , and the superorganism to produce a theory of how collective intelligence works. Later he showed how the collective intelligences of competing bacterial colonies and human societies can be explained in terms of computer-generated " complex adaptive systems " and

4232-476: The categorization of intelligence in fluid and crystallized intelligence or the hierarchical model of intelligence differences . Further supplementing explanations and conceptualizations for the factor structure of the Genomes of collective intelligence besides a general ' c factor', though, are missing yet. Other scholars explain team performance by aggregating team members' general intelligence to

4324-428: The collective intelligence phenomenon as "the capacity of human communities to evolve towards higher order complexity and harmony, through such innovation mechanisms as differentiation and integration, competition and collaboration." Atlee and Pór state that "collective intelligence also involves achieving a single focus of attention and standard of metrics which provide an appropriate threshold of action". Their approach

4416-512: The criterion tasks, c had a significant effect, but average and maximum individual intelligence had not. While average (r=0.15, P=0.04) and maximum intelligence (r=0.19, P=0.008) of individual group members were moderately correlated with c , c was still a much better predictor of the criterion tasks. According to Woolley et al., this supports the existence of a collective intelligence factor c, because it demonstrates an effect over and beyond group members' individual intelligence and thus that c

4508-532: The data indicate that results may be driven in part by low-effort responding. For instance, Woolley et al.'s data indicates that at least one team scored a 0 on a task in which they were given 10 minutes to come up with as many uses for a brick as possible. Similarly, Woolley et al.'s data show that at least one team had an average score of 8 out of 50 on the WPT. Scholars have noted that the probability of this occurring with study participants who are putting forth effort

4600-704: The data, so no human is involved in the process. Google also implemented the policy to anonymize IP address in their search logs after 9 months. However, Google Flu Trends has raised privacy concerns among some privacy groups. Electronic Privacy Information Center and Patient Privacy Rights sent a letter to Eric Schmidt in 2008, then the CEO of Google. They conceded that the use of user-generated data could support public health effort in significant ways, but expressed their worries that "user-specific investigations could be compelled, even over Google's objection, by court order or Presidential authority". An initial motivation for GFT

4692-469: The detection of The Genome of Collective Intelligence as one of its main goals aiming to develop a "taxonomy of organizational building blocks, or genes, that can be combined and recombined to harness the intelligence of crowds". Individual intelligence is shown to be genetically and environmentally influenced. Analogously, collective intelligence research aims to explore reasons why certain groups perform more intelligently than other groups given that c

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4784-712: The development over time or the question of improving intelligence. Whereas it is controversial whether human intelligence can be enhanced via training, a group's collective intelligence potentially offers simpler opportunities for improvement by exchanging team members or implementing structures and technologies. Moreover, social sensitivity was found to be, at least temporarily, improvable by reading literary fiction as well as watching drama movies. In how far such training ultimately improves collective intelligence through social sensitivity remains an open question. There are further more advanced concepts and factor models attempting to explain individual cognitive ability including

4876-427: The errors seen in a model using CDC data alone by up to 52.7 per cent. By re-assessing the original GFT model, researchers uncovered that the model was aggregating queries about different health conditions, something that could lead to an over-prediction of ILI rates; in the same work, a series of more advanced linear and nonlinear better-performing approaches to ILI modelling have been proposed. However, followup work

4968-535: The evidence for collective intelligence—was only 19.6% from their Confirmatory Factor Analysis. Notable is that an AVE of at least 50% is generally required to demonstrate evidence for convergent validity of a single factor, with greater than 70% generally indicating good evidence for the factor. Therefore, the evidence for collective intelligence referred to as "robust" in Riedl et al. is in fact quite weak or nonexistent, as their primary evidence does not meet or near even

5060-414: The extent of human interactions. A broader definition was provided by Geoff Mulgan in a series of lectures and reports from 2006 onwards and in the book Big Mind which proposed a framework for analysing any thinking system, including both human and machine intelligence, in terms of functional elements (observation, prediction, creativity, judgement etc.), learning loops and forms of organisation. The aim

5152-432: The field of collective intelligence research is quite young and published empirical evidence is relatively rare yet. However, various proposals and working papers are in progress or already completed but (supposedly) still in a scholarly peer reviewing publication process. Next to predicting a group's performance on more complex criterion tasks as shown in the original experiments, the collective intelligence factor c

5244-455: The following indispensable characteristic to this definition: The basis and goal of collective intelligence is mutual recognition and enrichment of individuals rather than the cult of fetishized or hypostatized communities." According to researchers Pierre Lévy and Derrick de Kerckhove , it refers to capacity of networked ICTs (Information communication technologies) to enhance the collective pool of social knowledge by simultaneously expanding

5336-440: The formal definition of IQS (IQ Social) was proposed and was defined as "the probability function over the time and domain of N-element inferences which are reflecting inference activity of the social structure". While IQS seems to be computationally hard, modeling of social structure in terms of a computational process as described above gives a chance for approximation. Prospective applications are optimization of companies through

5428-435: The framework for contemporary democratic theories often referred to as epistemic democracy . Epistemic democratic theories refer to the capacity of the populace, either through deliberation or aggregation of knowledge, to track the truth and relies on mechanisms to synthesize and apply collective intelligence. Collective intelligence was introduced into the machine learning community in the late 20th century, and matured into

5520-462: The fungi. David Skrbina cites the concept of a 'group mind' as being derived from Plato's concept of panpsychism (that mind or consciousness is omnipresent and exists in all matter). He develops the concept of a 'group mind' as articulated by Thomas Hobbes in Leviathan and Fechner 's arguments for a collective consciousness of mankind. He cites Durkheim as the most notable advocate of

5612-516: The future. Yet tasks, hereby, refer to mental or intellectual tasks performed by small groups even though the concept is hoped to be transferable to other performances and any groups or crowds reaching from families to companies and even whole cities. Since individuals' g factor scores are highly correlated with full-scale IQ scores, which are in turn regarded as good estimates of g , this measurement of collective intelligence can also be seen as an intelligence indicator or quotient respectively for

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5704-483: The group as well as increased diversity of the group. Atlee and Pór suggest that the field of collective intelligence should primarily be seen as a human enterprise in which mind-sets, a willingness to share and an openness to the value of distributed intelligence for the common good are paramount, though group theory and artificial intelligence have something to offer. Individuals who respect collective intelligence are confident of their own abilities and recognize that

5796-459: The history data the most accurately. Using the sum of top 45 ILI-related queries, the linear model is fitted to the weekly ILI data between 2003 and 2007 so that the coefficient can be gained. Finally, the trained model is used to predict flu outbreak across all regions in the United States. This algorithm has been subsequently revised by Google, partially in response to concerns about accuracy, and attempts to replicate its results have suggested that

5888-521: The idea of collective intelligence include Francis Galton , Douglas Hofstadter (1979), Peter Russell (1983), Tom Atlee (1993), Pierre Lévy (1994), Howard Bloom (1995), Francis Heylighen (1995), Douglas Engelbart , Louis Rosenberg, Cliff Joslyn , Ron Dembo , Gottfried Mayer-Kress (2003), and Geoff Mulgan . The concept (although not so named) originated in 1785 with the Marquis de Condorcet , whose "jury theorem" states that if each member of

5980-438: The influenza division of the CDC. “From 5 to 20 percent of the nation's population contract the flu each year, leading to roughly 36,000 deaths on average.” Google Flu Trends is an example of collective intelligence that can be used to identify trends and calculate predictions. The data amassed by search engines is significantly insightful because the search queries represent people's unfiltered wants and needs. “This seems like

6072-531: The lowest thresholds of acceptable evidence for a latent factor. Curiously, despite this and several other factual inaccuracies found throughout the article, the paper has not been retracted, and these inaccuracies were apparently not originally detected by the author team, peer reviewers, or editors of the journal. In 2001, Tadeusz (Tad) Szuba from the AGH University in Poland proposed a formal model for

6164-403: The maximization of their IQS, and the analysis of drug resistance against collective intelligence of bacterial colonies. One measure sometimes applied, especially by more artificial intelligence focused theorists, is a "collective intelligence quotient" (or "cooperation quotient") – which can be normalized from the "individual" intelligence quotient (IQ) – thus making it possible to determine

6256-497: The meaning of its predictions. In fall 2013, Google began attempting to compensate for increases in searches due to prominence of flu in the news, which was found to have previously skewed results. However, one analysis concluded that "by combining GFT and lagged CDC data, as well as dynamically recalibrating GFT, we can substantially improve on the performance of GFT or the CDC alone." A later study also demonstrates that Google search data can indeed be used to improve estimates, reducing

6348-580: The phenomenon of collective intelligence. It is assumed to be an unconscious, random, parallel, and distributed computational process, run in mathematical logic by the social structure. In this model, beings and information are modeled as abstract information molecules carrying expressions of mathematical logic. They are quasi-randomly displacing due to their interaction with their environments with their intended displacements. Their interaction in abstract computational space creates multi-thread inference process which we perceive as collective intelligence. Thus,

6440-534: The positive effects of group cohesion , motivation and satisfaction on group performance. Some scholars have noted that the evidence for collective intelligence in the body of work by Wolley et al. is weak and may contain errors or misunderstandings of the data. For example, Woolley et al. stated in their findings that the maximum individual score on the Wonderlic Personnel Test (WPT; an individual intelligence test used in their research)

6532-403: The predicted flu incidence equals the most recently observed flu incidence. For all weeks from March 18, 2007, to August 9, 2015 (the horizon for which Google Flu Trends predictions are available), the mean absolute error of Google Flu Trends was 0.38 and of the recency heuristic 0.20 (both in percentage points; linear regression with a single predictor, the most recently observed flu incidence, had

6624-467: The presence of pneumonia. When working together as "human swarms," the groups of experienced radiologists demonstrated a 33% reduction in diagnostic errors as compared to traditional methods. Woolley, Chabris, Pentland, Hashmi, & Malone (2010), the originators of this scientific understanding of collective intelligence, found a single statistical factor for collective intelligence in their research across 192 groups with people randomly recruited from

6716-478: The public. In Woolley et al.'s two initial studies, groups worked together on different tasks from the McGrath Task Circumplex , a well-established taxonomy of group tasks. Tasks were chosen from all four quadrants of the circumplex and included visual puzzles, brainstorming, making collective moral judgments, and negotiating over limited resources. The results in these tasks were taken to conduct

6808-507: The relationship between individual IQ and success works only to a certain point and that additional IQ points over an estimate of IQ 120 do not translate into real life advantages. If a similar border exists for Group-IQ or if advantages are linear and infinite, has still to be explored. Similarly, demand for further research on possible connections of individual and collective intelligence exists within plenty of other potentially transferable logics of individual intelligence, such as, for instance,

6900-442: The same vein as g serves to display between-individual performance differences on cognitive tasks, collective intelligence research aims to find a parallel intelligence factor for groups ' c factor' (also called 'collective intelligence factor' ( CI ) ) displaying between-group differences on task performance. The collective intelligence score then is used to predict how this same group will perform on any other similar task in

6992-835: The serialized process has been found to introduce substantial noise that distorts the collective output of the group. In one significant study of serialized collective intelligence, it was found that the first vote contributed to a serialized voting system can distort the final result by 34%. To address the problems of serialized aggregation of input among large-scale groups, recent advancements collective intelligence have worked to replace serialized votes, polls, and markets, with parallel systems such as " human swarms " modeled after synchronous swarms in nature. Based on natural process of Swarm Intelligence , these artificial swarms of networked humans enable participants to work together in parallel to answer questions and make predictions as an emergent collective intelligence. In one high-profile example,

7084-684: The spatial and temporal spreading of the disease. Roni Zeiger Roni F. Zeiger is an American physician and technologist. He is notable for his work as the Chief Health Strategist (2006–2012) at Google where he developed Google Health and Google Flu Trends . He is a co-founder of the Smart Patients project. In 2019, Zeiger announced he would be joining Facebook as the Head of Health Strategy. Zeiger received his medical degree at Stanford University , including

7176-487: The table, so in a deliberation many may contribute different pieces of information to generate a better decision. Recent scholarship, however, suggests that this was probably not what Aristotle meant but is a modern interpretation based on what we now know about team intelligence. A precursor of the concept is found in entomologist William Morton Wheeler 's observation in 1910 that seemingly independent individuals can cooperate so closely as to become indistinguishable from

7268-474: The team level instead of building an own overall collective intelligence measure. Devine and Philips (2001) showed in a meta-analysis that mean cognitive ability predicts team performance in laboratory settings (0.37) as well as field settings (0.14) – note that this is only a small effect. Suggesting a strong dependence on the relevant tasks, other scholars showed that tasks requiring a high degree of communication and cooperation are found to be most influenced by

7360-506: The team member with the lowest cognitive ability. Tasks in which selecting the best team member is the most successful strategy, are shown to be most influenced by the member with the highest cognitive ability. Since Woolley et al.'s results do not show any influence of group satisfaction, group cohesiveness , or motivation, they, at least implicitly, challenge these concepts regarding the importance for group performance in general and thus contrast meta-analytically proven evidence concerning

7452-444: The term "conscious evolution") are inspired by the visions of a noosphere – a transcendent, rapidly evolving collective intelligence – an informational cortex of the planet. The notion has more recently been examined by the philosopher Pierre Lévy. In a 1962 research report, Douglas Engelbart linked collective intelligence to organizational effectiveness, and predicted that pro-actively 'augmenting human intellect' would yield

7544-795: The variety of perspectives and skills needed to perform well. On the other hand, groups whose members are too different seem to have difficulties to communicate and coordinate effectively. For most of human history, collective intelligence was confined to small tribal groups in which opinions were aggregated through real-time parallel interactions among members. In modern times, mass communication, mass media, and networking technologies have enabled collective intelligence to span massive groups, distributed across continents and time-zones. To accommodate this shift in scale, collective intelligence in large-scale groups been dominated by serialized polling processes such as aggregating up-votes, likes, and ratings over time. While modern systems benefit from larger group size,

7636-409: The way people are learning to participate in knowledge cultures outside formal learning settings. Henry Jenkins criticizes schools which promote 'autonomous problem solvers and self-contained learners' while remaining hostile to learning through the means of collective intelligence. Both Pierre Lévy and Henry Jenkins support the claim that collective intelligence is important for democratization , as it

7728-684: The whole is indeed greater than the sum of any individual parts. Maximizing collective intelligence relies on the ability of an organization to accept and develop "The Golden Suggestion", which is any potentially useful input from any member. Groupthink often hampers collective intelligence by limiting input to a select few individuals or filtering potential Golden Suggestions without fully developing them to implementation. Robert David Steele Vivas in The New Craft of Intelligence portrayed all citizens as "intelligence minutemen", drawing only on legal and ethical sources of information, able to create

7820-466: Was 39, but also that the maximum averaged team score on the same test was also a 39. This indicates that their sample seemingly had a team composed entirely of people who, individually, got exactly the same score on the WPT, and also all happened to all have achieved the highest scores on the WPT found in Woolley et al. This was noted by scholars as particularly unlikely to occur. Other anomalies found in

7912-536: Was Chief Health Strategist (2006–2012) at Google where he worked on Google Health , symptom, anatomy, and health search on Google Search , and Google Flu Trends . With Gilles Frydman, founder of the Association of Cancer Online Resources, Zeiger co-founded the Smart Patients project. The project is a search engine and social media platform which connects clinical trial participants in cancer studies to each other for personal conversations. This

8004-509: Was able to substantially improve the accuracy of GFT through the use of a random forest regression model trained on both the incidence of influenza-like illness and the output of the original GFT model. Similar projects such as the flu-prediction project by the Institute of Cognitive Science at Universitat Osnabrück carry the basic idea forward, by combining social media data e.g. Twitter with CDC data, and structural models that infer

8096-503: Was also found to predict group performance in diverse tasks in MBA classes lasting over several months. Thereby, highly collectively intelligent groups earned significantly higher scores on their group assignments although their members did not do any better on other individually performed assignments. Moreover, highly collective intelligent teams improved performance over time suggesting that more collectively intelligent teams learn better. This

8188-400: Was described as using the following method to gather information about flu trends. First, a time series is computed for about 50 million common queries entered weekly within the United States from 2003 to 2008. A query's time series is computed separately for each state and normalized into a fraction by dividing the number of each query by the number of all queries in that state. By identifying

8280-402: Was statistically significant (b=0.33, P=0.05). The number speaking turns indicates that "groups where a few people dominated the conversation were less collectively intelligent than those with a more equal distribution of conversational turn-taking". Hence, providing multiple team members the chance to speak up made a group more intelligent. Group members' social sensitivity was measured via

8372-433: Was that being able to identify disease activity early and respond quickly could reduce the impact of seasonal and pandemic influenza. One report was that Google Flu Trends was able to predict regional outbreaks of flu up to 10 days before they were reported by the CDC (Centers for Disease Control and Prevention). In the 2009 flu pandemic Google Flu Trends tracked information about flu in the United States. In February 2010,

8464-618: Was to provide a way to diagnose, and improve, the collective intelligence of a city, business, NGO or parliament. Collective intelligence strongly contributes to the shift of knowledge and power from the individual to the collective. According to Eric S. Raymond in 1998 and JC Herz in 2005, open-source intelligence will eventually generate superior outcomes to knowledge generated by proprietary software developed within corporations. Media theorist Henry Jenkins sees collective intelligence as an 'alternative source of media power', related to convergence culture. He draws attention to education and

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