Richard P. O’Neill is President of The Highlands Group, a consulting and analysis network. In 1994 he created and still directs The Highlands Forum, an internationally recognized forum of leaders from industry, academia, government, the arts and the professions, supporting the Secretary of Defense . Dick leads a research group that informs government leaders and conducts Highlands Forum meetings to further high-level government policy and strategy development. Highlands maintains broad interests but particularly focuses on information and information technologies and their impact on international relations, economics, and security. He has since established similar forums for other U.S. government agencies as well as ministerial departments of other nations. Dick previously served in government, in his last position as Deputy for Strategy and Policy in the Office of the U.S. Assistant Secretary of Defense. He graduated from Holy Cross College, receiving a Bachelor of Arts in Political Science and holds Masters degrees from Georgetown University, the Naval Postgraduate School and the Naval War College. Mr O'Neill gave a lecture invited by Oskar's Cafe' in Washington DC on January 11.
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Complex global problems may be too large for any single nation or even group of nations to solve, however we may be able to make a new start in fixing the future through collective intelligence. The broadest definition of collective intelligence (CI), as it applies today, is, “Groups of individuals acting collectively in ways that seem intelligent.” CI is about sharing knowledge, not merely creating it; about getting knowledge out of channels and onto a network; and about creating an “ecosystem of knowledge.” The best CI is organic in nature. New information technologies enable dramatic new possibilities for de-centralized CI. The key question for users of CI, though, is, “How can people and computers be connected so that they act more intelligently – collectively – than any one person, group, or computer ever has ever done before?” The possibilities range from low tech to high tech information sharing, but the key is collaboration across all means.
In the past two decades we have seen a democratizing of the tools of production (the PC); lowered costs of consumption (the Internet); and the ability to connect consumers to interesting niche products and elevate those goods (Google, YouTube, FaceBook); along with the key phenomenon of user-generated content (Wikipedia). This shifts the power balance in remarkable ways from institutions to individuals. Peers end up trusting peers more as peers convey authenticity; “ants have megaphones”. Institutions cannot control the conversation; at best they might influence it.
James Surowiecki, in The Wisdom of Crowds, maintains that a network of people not only has more intelligence than a very smart individual or a few individuals, but this network is better at solving problems and working on things that the brain pushes to its limits to do. Surowiecki cites four conditions that govern the ability of the network to succeed. He lists diversity of opinion (we would say cognitive diversity); independence of members from one another; decentralization; and a good method for aggregating opinions.
We are cautioned however, in the classic work by Charles Mackay, Extraordinary Popular Delusions and the Madness of Crowds by Charles Mackay (1841): "Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one." So what is different? Global interconnectivity and the self-editing of the group. Merely collecting and amassing data will not, by itself, make us smarter; it will only make us dumber. What will be critical will be our ability to stitch together this data.
CI’s use as a “peace technology,” even as a diplomatic tool, could pave paths for conflict avoidance. Enlisting cross-cultural actors in common projects for common goals could lead to greater cooperation among disparate groups, even states, in broad environments.
It may well even lead us to approach those global, complex problems that Rischard, Ghani and Lockhart outline in their books. Here are some examples of CI:
People who need problems solved can easily access large online groups that can contribute time, energy and insight to solving problems, a phenomenon that’s becoming known as “crowdsourcing.” People in these groups seem willing to share their resources and ideas with others in exchange for both economic and non-economic (i.e. reputational or altruistic) goods, even when such sharing may prevent them from attaining even larger goods. InnoCentive connects anonymous “seekers” and their problems with over 160,000 anonymous “solvers” who try to find solution. Anonymity means that only a solution’s merit, not the parties’ backgrounds, comes into play. InnoCentive offloads seekers’ risk while eliminating barriers to entry for a large number of willing, often highly motivated solvers. InnoCentive relieves seekers of the risk of high or uncertain R&D expenditures while solvers (160,000 and counting) absorb that risk in exchange for a posted award. In doing so, InnoCentive accesses a labor pool much larger than that of most private companies, and to date has found solutions to roughly 300 of 800 posted problems. While 40 percent of InnoCentive solvers hold Ph.D.s, they tend not to discover solutions in their area of expertise. Some solvers completely lack formal training in the problem areas they choose.
In large contests, particularly those with binary outcomes such as the winner-take-all contests of the Iowa Electronic Markets (IEM), the ability of the crowd to predict election winners is quite remarkable. The IEM (http://www.biz.uiowa.edu/iem/) are a University of Iowa project that creates markets based on U.S. presidential and other political contests; traders use real money to buy and sell shares based on who they believe will win and lose, and by how much. Trading is halted shortly before Election Day and payouts are made based on the election’s winners and losers. The IEM involves educated guesses that are made serious by the injection of traders’ own funds, for which the university has a regulatory waiver. The IEM is intended as a teaching tool rather than a real-life stock or commodities market, with participation capped at $500.
Collective Forecasting, especially as practiced by Dr. Jane McGonigal of the Institute for the Future, involves alternate reality games in which people are given a scenario and live it locally, regularly feeding data back into a common portal to be combined and reissued globally. Occurring over weeks or months, this type of iterative process might yield insights that are not easily available or are unobtainable through traditional means.
Richard O'Neill
In the past two decades we have seen a democratizing of the tools of production (the PC); lowered costs of consumption (the Internet); and the ability to connect consumers to interesting niche products and elevate those goods (Google, YouTube, FaceBook); along with the key phenomenon of user-generated content (Wikipedia). This shifts the power balance in remarkable ways from institutions to individuals. Peers end up trusting peers more as peers convey authenticity; “ants have megaphones”. Institutions cannot control the conversation; at best they might influence it.
James Surowiecki, in The Wisdom of Crowds, maintains that a network of people not only has more intelligence than a very smart individual or a few individuals, but this network is better at solving problems and working on things that the brain pushes to its limits to do. Surowiecki cites four conditions that govern the ability of the network to succeed. He lists diversity of opinion (we would say cognitive diversity); independence of members from one another; decentralization; and a good method for aggregating opinions.
We are cautioned however, in the classic work by Charles Mackay, Extraordinary Popular Delusions and the Madness of Crowds by Charles Mackay (1841): "Men, it has been well said, think in herds; it will be seen that they go mad in herds, while they only recover their senses slowly, and one by one." So what is different? Global interconnectivity and the self-editing of the group. Merely collecting and amassing data will not, by itself, make us smarter; it will only make us dumber. What will be critical will be our ability to stitch together this data.
CI’s use as a “peace technology,” even as a diplomatic tool, could pave paths for conflict avoidance. Enlisting cross-cultural actors in common projects for common goals could lead to greater cooperation among disparate groups, even states, in broad environments.
It may well even lead us to approach those global, complex problems that Rischard, Ghani and Lockhart outline in their books. Here are some examples of CI:
People who need problems solved can easily access large online groups that can contribute time, energy and insight to solving problems, a phenomenon that’s becoming known as “crowdsourcing.” People in these groups seem willing to share their resources and ideas with others in exchange for both economic and non-economic (i.e. reputational or altruistic) goods, even when such sharing may prevent them from attaining even larger goods. InnoCentive connects anonymous “seekers” and their problems with over 160,000 anonymous “solvers” who try to find solution. Anonymity means that only a solution’s merit, not the parties’ backgrounds, comes into play. InnoCentive offloads seekers’ risk while eliminating barriers to entry for a large number of willing, often highly motivated solvers. InnoCentive relieves seekers of the risk of high or uncertain R&D expenditures while solvers (160,000 and counting) absorb that risk in exchange for a posted award. In doing so, InnoCentive accesses a labor pool much larger than that of most private companies, and to date has found solutions to roughly 300 of 800 posted problems. While 40 percent of InnoCentive solvers hold Ph.D.s, they tend not to discover solutions in their area of expertise. Some solvers completely lack formal training in the problem areas they choose.
In large contests, particularly those with binary outcomes such as the winner-take-all contests of the Iowa Electronic Markets (IEM), the ability of the crowd to predict election winners is quite remarkable. The IEM (http://www.biz.uiowa.edu/iem/) are a University of Iowa project that creates markets based on U.S. presidential and other political contests; traders use real money to buy and sell shares based on who they believe will win and lose, and by how much. Trading is halted shortly before Election Day and payouts are made based on the election’s winners and losers. The IEM involves educated guesses that are made serious by the injection of traders’ own funds, for which the university has a regulatory waiver. The IEM is intended as a teaching tool rather than a real-life stock or commodities market, with participation capped at $500.
Collective Forecasting, especially as practiced by Dr. Jane McGonigal of the Institute for the Future, involves alternate reality games in which people are given a scenario and live it locally, regularly feeding data back into a common portal to be combined and reissued globally. Occurring over weeks or months, this type of iterative process might yield insights that are not easily available or are unobtainable through traditional means.
Richard O'Neill
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