Thomas W. Malone

Thomas W. Malone
Massachusetts Institute of Technology | MIT · MIT Sloan School of Management

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223
Publications
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28,625
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Publications

Publications (223)
Article
Full-text available
Significance Collective intelligence (CI) is critical to solving many scientific, business, and other problems. We find strong support for a general factor of CI using meta-analytic methods in a dataset comprising 22 studies, including 5,279 individuals in 1,356 groups. CI can predict performance in a range of out-of-sample criterion tasks. CI, in...
Article
In 2019-2020, the Collective Intelligence Design Lab (CIDL), an initiative of the MIT Center for Collective Intelligence (CCI), worked jointly with Takeda Pharmaceutical’s Center for Scientific Leadership and Innovation (CSLI) to address a challenge faced by Takeda. This paper describes the collaboration as a case study of university researchers in...
Preprint
Full-text available
Finding innovative solutions to complex problems is often about finding people who have access to novel information and alternative viewpoints. Research has found that most people are connected to each other through just a few degrees of separation, but successful social search is often difficult because it depends on people using their weak ties t...
Article
Full-text available
Organizations are increasingly looking for ways to reap the benefits of cognitive diversity for problem solving. A major unanswered question concerns the implications of cognitive diversity for longer-term outcomes such as team learning, with its broader effects on organizational learning and productivity. We study how cognitive style diversity in...
Article
Full-text available
Researchers in many disciplines have previously used a variety of mathematical techniques for analyzing group interactions. Here we use a new metric for this purpose, called “integrated information” or “phi.” Phi was originally developed by neuroscientists as a measure of consciousness in brains, but it captures, in a single mathematical quantity,...
Data
Average phi over time for various node sampling methods (top left to bottom right: Random Walk, Forest Fire, Breadth First and Random Nodes). In all cases node sample size = 100, and time step size δ = 100 ms. (DOCX)
Data
Average phi plotted over time (node sampling = random walk, node sample size = 150 (left) and 200 (right), time step size δ = 100 ms). For 150 nodes, β = 0.4477, p = 0.018; for 200 nodes, β = 0.6535, p = 0.00026. (DOCX)
Data
Task categories and verbal vs. non-verbal dimensions in the Collective Intelligence task battery (reproduced from [23]). (DOCX)
Data
Descriptive statistics of the number of articles, editors, edits, and edits per editor in various periods before quality changes in the Wikipedia dataset (time windows of 30-, 60-, and 90-days shown in panels A, B, and C, respectively). (DOCX)
Data
Average phi for groups editing Wikipedia articles of different quality levels in the 30-day period (A) and the 90-day period (B) before the articles were promoted to their current quality level. (DOCX)
Data
Summary of methods used to calculate phi in different studies. (DOCX)
Data
Hierarchical regression results for predicting collective intelligence from phi, condition (face-to-face vs. online), and the interaction of phi and condition (n = 61 groups). (DOCX)
Data
Regression results when predicting phi for each article from number of edits, average number of edits per editor, and newly acquired quality level of the article. (DOCX)
Data
Number of information packets, origin nodes and destination nodes for each month analyzed. (DOCX)
Data
Description of tasks used to measure collective intelligence of groups. (DOCX)
Data
Average phi plotted over time (node sampling = random walk, node sample size = 100, time step size δ = 50 ms (left) and 150ms (right). For 50ms, β = 0.8227, p = 0.000007; for 150ms, β = 1.333, p = 0.002. (DOCX)
Data
Regression coefficients for predicting phi from date with four different node sampling methods while only looking at a fixed number of packets (10,000,000 packets). (DOCX)
Article
Today, many complex tasks are assigned to teams, rather than individuals. One reason for teaming up is expansion of the skill coverage of each individual to the joint team skill set. However, numerous empirical studies of human groups suggest that the performance of equally skilled teams can widely differ. Two natural question arise: What are the f...
Data
Dataset and description of the team features, task scores, and communication logs used in analyses; correlation- and regression-related values obtained in the experiments. (ZIP)
Data
Descriptions of the tasks. (PDF)
Conference Paper
A key issue, whenever people work together to solve a complex problem, is how to divide the problem into parts done by different people and combine the parts into a solution for the whole problem. This paper presents a novel way of doing this with groups of contests called contest webs. Based on the analogy of supply chains for physical products, t...
Article
Full-text available
Recent research has demonstrated that (a) groups can be characterized by a collective intelligence (CI) factor that measures their ability to perform together on a wide range of different tasks, and (b) this factor can predict groups’ performance on other tasks in the future. The current study examines whether these results translate into the world...
Article
Researchers in many disciplines have previously used a variety of mathematical techniques for analyzing group interactions. Here we use a new metric for this purpose, called 'integrated information' or 'phi.' Phi was originally developed by neuroscientists as a measure of consciousness in brains, but it captures, in a single mathematical quantity,...
Article
On the Web, there is always a need to aggregate opinions from the crowd (as in posts, social networks, forums, etc.). Different mechanisms have been implemented to capture these opinions such as “Like” in Facebook, “Favorite” in Twitter, thumbs-up/down, flagging, and so on. However, in more contested domains (e.g. Wikipedia, political discussion, a...
Article
Full-text available
We review recent research on collective intelligence, which we define as the ability of a group to perform a wide variety of tasks. We focus on two influences on a group’s collective intelligence: (a) group composition (e.g., the members’ skills, diversity, and intelligence) and (b) group interaction (e.g., structures, processes, and norms). We als...
Article
Full-text available
Collective intelligence (CI) is a property of groups that emerges from the coordination and collaboration of members and predicts group performance on a wide range of tasks. Previous studies of CI have been conducted with lab-based groups in the USA. We introduce a new standardized online battery to measure CI and demonstrate consistent emergence o...
Article
Panelists will discuss how collective intelligence can be applied to large-scale problems through collaborative online systems. The features and affordances of several such systems will be described, inviting discussion about how such systems can be better designed by the CSCW community.
Chapter
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In the 2014 Winter Olympic games in Sochi, the Russian men's ice hockey team seemed poised to sweep their competition. With star players from the National Hockey League in North America and the Kontinental Hockey League in Russia, and even with a home field advantage in Russia, fans thought they were sure to win the gold medal. In fact, Russian Pre...
Article
Full-text available
Recent research with face-to-face groups found that a measure of general group effectiveness (called "collective intelligence") predicted a group's performance on a wide range of different tasks. The same research also found that collective intelligence was correlated with the individual group members' ability to reason about the mental states of o...
Article
An extensive literature in psychology, economics, statistics, operations research and management science has dealt with comparing forecasts based on human-expert judgment vs. (statistical) models in a variety of scenarios, mostly finding advantage of the latter, yet acknowledging the necessity of the former. Although computers can use vast amounts...
Article
Full-text available
New ways of combining networked humans and computers, such as collective intelligence and social computing, are important and likely to become truly transformative in domains such as education, industry, government, and arts. Systems that cover an enormous range of approaches, have been developed that look for individual task-focused geniuses. The...
Article
This volume holds the proceedings of the Collective Intelligence 2012 conference in Cambridge, Massachusetts. It contains the full papers, poster papers, and plenary abstracts. Collective intelligence has existed at least as long as humans have, because families, armies, countries, and companies have all - at least sometimes - acted collectively in...
Article
Full-text available
Global climate change is one of the most challenging problems humanity has ever faced. Fortunately, a new way of solving large, complex problems has become possible in just the last decade or so. Examples like Wikipedia and Linux illustrate how the work of thousands of people can be combined in ways that would have been impossible only a few years...
Article
Full-text available
Computational simulation models help support scientifically grounded "what if" analyses by translating specialized knowledge into tools that can project the likely future impact of current actions. Models have thus become important in a variety of policy domains. In recent years, several software platforms for environmental policy-making and urban...
Article
Statistical models almost always yield predictions that are more accurate than those of human experts. However, humans are better at data acquisition and at recognizing atypical circumstances. We use prediction markets to combine predictions from groups of humans and artificial-intelligence agents and show that they are more robust than those from...
Article
Full-text available
The Climate CoLab is a system to help thousands of people around the world collectively develop plans for what humans should do about global climate change. This paper shows how the system combines three design elements (model-based planning, on-line debates, and electronic voting) in a synergistic way. The paper also reports early usage experience...
Conference Paper
Computers can use vast amounts of data to make predictions that are often more accurate than those by human experts. Yet, humans are more adept at processing unstructured information and at recognizing unusual circumstances and their consequences. Can we combine predictions from humans and machines to get predictions that are better than either cou...
Article
Full-text available
Technology-mediated social-participation systems, such as Wikipedia and TopCoder, allow a vast user base to collaborate to solve difficult problems. TMSP could be applied to many current social issues, but doing so requires new theory and infrastructure for social design.
Article
Full-text available
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 peop...
Article
Google. Wikipedia. Threadless. All are platinum exemplars of collective intelligence in action. Two of them are famous. The third is getting there. Each of the three helps demonstrate how large, loosely organized groups of people can work together electronically in surprisingly effective ways sometimes even without knowing that they are working tog...
Article
Agile development deemphasizes long-term planning in favor of short-term adaptiveness. This is a strength in a rapidly changing development environment. However, this short-term focus creates a temptation to neglect best practices that are essential ...
Article
Over the past decade, the rise of the Internet has enabled the emergence of surprising new forms of collective intelligence. Examples include Google, Wikipedia, Threadless, and many others. To take advantage of the possibilities these new systems represent, it is necessary to go beyond just seeing them as a fuzzy collection of “cool” ideas. What is...
Article
Full-text available
Simulation modeling can be valuable in many areas of management science, but it is often costly, time-consuming, and difficult to do. To reduce these problems, system dynamics researchers have previously developed standard pieces of model structure, called molecules, that can be reused in different models. However, the models assembled from these m...
Article
Simulation modeling can be valuable in many areas of management science, but is often costly, time-consuming and difficult to do. This paper describes a new approach to simulation that has the potential to be much cheaper, faster and easier to use in many situations. In this approach, users start with a very simple generic model and then progressiv...
Article
This document discusses a few versatile, tool-like crowd performance algorithms necessary for humans to employ internet technologies to make better decisions collectively. This document also readily acknowledges that true collective intelligence approaches are foremost about organizational culture change and encouraging shared group norms (i.e., va...
Article
Multiplayer online role-playing games are sprawling cybercommunities that offer a sneak preview of tomorrow's business environment. Players who lead teams in these online worlds hone the skills that they will need as business leaders in the future. Games also provide an environment that makes being an effective leader easier and that today's busine...
Article
Tens of millions of people are honing their leadership skills in multiplayer online games. The tools and techniques they're using will change how leaders function tomorrow— and could make them more effective today.
Conference Paper
Full-text available
While people have talked about collective intelligence for decades, new communication technologies— especially the Internet—now allow huge numbers of people all over the planet to work together in new ways. The recent successes of systems like Google and Wikipedia suggest that the time is now ripe for many more such systems, and this talk will exam...
Article
Today's top executives are expected to do everything right, from coming up with solutions to unfathomably complex problems to having the charisma and prescience to rally stakeholders around a perfect vision of the future. But no one leader can be all things to all people. It's time to end the myth of the complete leader, say the authors. Those at t...
Article
Full-text available
Global climate change, caused by human-generated greenhouse-gas emissions, is perhaps the most pressing and important problem currently facing humanity. It is also unique by virtue of being a truly systemic problem of vast complexity: it affects every one of us, and is directly affected by every one of our actions. Like nothing else, the climate cr...
Article
Today's top executives are expected to do everything right, from coming up with solutions to unfathomably complex problems to having the charisma and prescience to rally stakeholders around a perfect vision of the future. But no one leader can be all things to all people. It's time to end the myth of the complete leader, say the authors. Those at t...
Article
Full-text available
This paper defines four basic business models based on what asset rights are sold (Creators, Distributors, Landlords and Brokers) and four variations of each based on what type of assets are involved (Financial, Physical, Intangible, and Human). Using this framework, we classified the business models of all 10,970 publicly traded firms in the US ec...
Article
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Abstract A central question in strategic management,is: what explains the difference in performance among,firms? The traditional debate is whether firm or industry effects are the dominant explanation. Yet, among practitioners, a very different explanation, in the form of “business model,” is commonly offered for why some firms do better than other...
Article
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Article
I study a budget-constrained, private-valuation, sealed-bid sequential auction with two incompletely-informed, risk-neutral bidders in which the valuations and income may be non-monotonic functions of a bidder's type. Multiple equilibrium symmetric bidding functions may exist that differ in allocation, efficiency and revenue. The sequence of sale a...
Article
In the postindustrial high-tech world, competition involves far more than money.
Article
During the dot-com boom, many people saw the potential for new communication technologies to enable radically new business models, but they were far too optimistic about the speed with which the revolution would occur. Now, as the bitter disillusionment of the dot-com bust begins to fade, we have a chance to think again--this time more rationally--...
Article
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"August 1985." Bibliography: p. 12. Thomas W. Malone ... [et al.].
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"April 1985." "This paper appeared in the Proceedings of the CHI'85 Conference on Human Factors on Computing Systems, ... San Francisco, CA, April 14-18, 1985."--P. [5]
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"September 1985." "In J. Carroll (ed.), Interfacing thought : cognitive aspects of human computer interactions, ... l986."
Article
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"December, 1986." "A slightly revised version of this paper will appear in Communications of the ACM."
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"December 1986." "Published in the Proceedings of the Conference on Computer-Supported Cooperative Work, Austin, Texas, December 3-5, 1986."