viewpoints viewpoints

V Vdoi:10.1145/2160718.2160731 Abraham Bernstein, Mark Klein, and Thomas W. Malone Viewpoint Programming the Global Considering how we can improve our understanding and utilization of the emerging human- constituting the global brain.

ew ways of combining networked humans and computers—whether they are called collective intel- ligence, social computing, Nor various other terms—are already extremely important and likely to become truly transformative in do- mains from education and industry to government and the arts. These systems are now routinely able to solve problems that would have been unthinkably difficult only a few short years ago, combining the commu- nication and number-crunching ca- pabilities of computer systems with the creativity and high-level cognitive capabilities of people. And all this is supercharged by the emergent gen- erativity and robust evaluation that can come from the many eyes of large crowds of people. As the scale, scope, and connectivity of these human- computer networks increase, we be- lieve it will become increasingly useful to view all the people and computers on our planet as constituting a kind of “global brain.” We still only poorly understand, however, how to “program” this global brain. We have some stunning success stories (such as Wikipedia, Google), but most applications still fail, or re- point, we will consider this challenge, What Makes the Global quire a long series of trial-and-error re- exploring the nature of these differ- Brain Different? finements, for reasons we only poorly ences as well as issuing a call to arms There are already literally hundreds understand. Because people are in- describing open research challenges of compelling examples of the global volved, programming the global brain that need to be met in order to more brain at work, collectively representing

tration by John H er s ey by tration is deeply different from programming fully exploit the enormous potential of the contributions of many millions of us 3,10 I ll traditional computers. In this View- the global brain. people and computers. These range

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from systems where individuals per- unique challenges (and opportunities)? form simple micro-tasks (http://mturk. We believe a fundamental requirement com) to where they compete to solve Because people is developing powerful new program- complex engineering problems (http:// are involved, ming metaphors that more accurately innocentive.com). Some systems har- reflect the ways people and computers ness the “wisdom of crowds” in con- programming the can work together in the global brain. texts that range from “citizen science”4 global brain is For instance, today’s innovative collec- (http://fold.it, http://galaxyzoo.org) tive systems embody a set to predicting box office performance deeply different of common design patterns,8 includ- (http://hsx.com). Open idea ecologies from programming ing collections (where people create (where crowds of people share, recom- independent items, such as YouTube bine, and refine each other’s creative traditional computers. videos), collaborations (where people outputs) have produced remarkable create interdependent items, such as results for everything from videos Linux modules), and various kinds of (http://youtube.com) and encyclope- group and individual decisions (such as dias (http://wikipedia.org) to software voting, averaging, social networks, and (Linux). Systems have been developed markets). These design patterns, in that look for individual task-focused ally highly deterministic and limited turn, can be embodied in various pro- “geniuses” (http://marketocracy.com) in diversity because a relatively small gramming metaphors, such as: or, conversely, datamine the activ- range of software is typically replicated ˲˲ An idea ecology: The global brain ity traces of millions of users across millions of computers. People, can host a constant ferment of idea (Google’s search engine). While these by contrast, are prone to a bewilder- generation, mutation, recombination, systems cover an enormous range of ing and inconsistent variety of idiosyn- and selection, analogous to biological approaches, it has become clear from cratic deviations from rational and ac- evolution. In this context, program- these experiences that programming curate performance. The global brain, ming consists of soliciting collections the global brain is different from pro- therefore, calls for a radically more of items and specifying a fitness func- gramming traditional computers in capable quality assurance oriented to- tion for choosing among them. Inter- some fundamental ways. Some of the ward the particular kinds of errors that esting examples of this include the most important differences include: occur with human participants. Fortu- MATLAB open programming contests ˲˲ Motivational diversity: People, un- nately, the global brain also provides (for software) and YouTube (for videos). like current computational systems, access, at least currently, to a huge hu- ˲˲ A web of dependencies: Many im- are self-interested and therefore re- man “cognitive surplus,”11 so that, for portant problems (such as product, quire appropriate incentives—any- instance, quality mechanisms based process, and policy definition) can be thing from money, fame, and fun to on previously unthinkable levels of re- viewed as collaborations, where mul- altruism and community—to perform dundancy have become practical.10 tiple diverse agents try to solve inter- tasks. These incentives have to be These attributes lead, in turn, to dependent pieces of a larger problem. carefully designed, moreover, to avoid the possibility of new, and potentially The global brain can detect when con- people gaming the system or causing troubling, forms of . Crowds flicts appear between sub-solutions, as outright damage. In some cases, one of people, when engaged in solving well as guide agents toward a globally may even use their motivation to do interdependent problems, can evince consistent result. In this context, pro- one task to accomplish another, as in emergent behaviors that range from gramming includes defining the task reCAPTCHA, where people OCR docu- groupthink (where decision-makers decomposition and specifying ways ments as a side effect of passing a hu- converge prematurely on a small sub- of managing the interdependencies man versus bot test.12 set of the solution space) to balkaniza- among sub-problems. Early examples ˲˲ Cognitive diversity: In most com- tion (where decision-makers divide of this include virtual mockups such as puter systems we deal with a limited into intransigent competing cliques) the digital pre-assembly system Boeing range of diversity—in terms of mem- to chaotic dynamics (for example, used in the design of the 777 aircraft. ory, speed, and device access. People, stock market bubbles and crashes). ˲˲ An intellectual supply chain: For by contrast, vary across many dimen- While emergence is, of course, not some problems, we can view the global sions in the kinds of tasks they can do unique to the global brain, it is prob- brain as a supply chain, where a se- well, and their individual strengths ably made much more challenging by quence of tasks and flows are only incompletely understood at the unprecedented combination of mi- among people and machines can be best. This implies qualitative differ- crosecond computer and communica- specified in advance. In this context, ences in how (and how well) we can ex- tions speeds, globe-scale interdepen- programming can be defined in terms pect to match tasks and resources in a dencies, and human diversity. already familiar to computer scien- global brain context. tists as processes and dataflows. Inter- ˲˲ Error diversity: With traditional The Need for New esting examples of this idea include computers, we worry much more about Programming Metaphors the Turkit6 and Crowdforge5 systems, outright failure than other kinds of How, then, can we effectively program which have been applied to such tasks errors. And the other errors are usu- a global brain, characterized as it is by as writing and editing articles.

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˲˲ A collaborative deliberation: The vational elements, as well as scalable trol” perspective for organizing people global brain can also be used to enact task-to-resource matchmaking such to one oriented around cultivating and decision processes where people and as markets. These will be challenging coordinating7 societies made up of software systems select issues to con- problems because people (unlike hard- many diverse independent players. sider, enumerate and critique solution ware resources) are diverse in all the alternatives, and then choose some ways we have described. But providing A Call to Arms subset of these solutions. In this con- easy-to-use solutions for the problems We have attempted to identify some of text, programming can be viewed as of finding and motivating human par- the key challenges, opportunities, and defining the rules for identifying issues ticipants—rather than requiring each strategies involved in programming the and enumerating, critiquing, and se- system developer to solve this problem emerging global brain. Learning to do lecting solutions. individually—will greatly facilitate pro- this well is, perhaps, even more urgent ˲˲ A radically fluid virtual organiza- gramming the global brain. than many people realize. Our world is tion: Sometimes it is useful to view the Defining new programming lan- faced with both existential threats of global brain as a collection of evanes- guages. Conventional programming unprecedented seriousness (such as cent virtual organizations, which rap- languages are, out of necessity, fully the environment) and huge opportu- idly coalesce, perform, and disband prescriptive, describing the algo- nities (such as for scientific and social in light-speed open markets. In this rithms to be executed in exhaustive progress). We believe that our ability to context, programming includes iden- detail. Such languages are often not a face the threats and opportunities of tifying the task requirements and se- good match, however, for specifying the coming century will be profoundly lecting among the organizations that tasks with human participants. The affected by how well, and soon, we can are offering to perform the task. Inter- programming languages for the global master the art of programming our esting examples of this idea include brain will, therefore, need to support planet’s emerging global brain. odesk.com and elance.com. a “specificity frontier” of varying de- ˲˲ A multi-user game: Many tasks can grees of detail in task definition.2 One References 1. ahmad, S., Battle, A., and Kamvar, S. The be presented as a multi-user game, end of this frontier involves defining Jabberwocky programming environment for where useful outcomes are achieved programs that allocate highly specific structured social computing. UIST ‘11 (Santa Barbara, CA, Oct. 16–19, 2011). as a result, sometimes unintentional, micro-tasks to people and link them 2. bernstein, A. How can cooperative work tools support dynamic group processes? Bridging the of playing the game. In this context, into larger workflows. In the middle specificity frontier. In Proceedings of the International programming consists of specifying ground, we may use constraint-based Conference on Computer Supported Cooperative Work (CSCW 2000) 2000, ACM. the rules and incentives for game play. programs, which specify (for example, 3. doan, A., Ramakrishnan, R., and Halevy, A. Interesting examples of this include in a game setting) the goals as well as Crowdsourcing systems on the World-Wide Web. Commun. ACM 54, 4 (Apr. 2011), 86–96. fold.it and the Google Image Labeller. the limits on how they can be achieved, 4. hand, E. Citizen science: People power. Nature 466 Making such global brain program- but not how they should be achieved. (2010), 685–687. 5. kittur, A., Smus, B., and Kraut, R. Crowdforge: ming metaphors a reality will, in turn, At the far end of the specificity fron- Crowdsourcing complex work. In Proceedings of the require progress along several fronts: tier, programming may be limited to ACM Conference on Human Factors in Computing Systems (CHI ’11). ACM, New York (2011). Creating “social operating sys- simply stating incomplete goal speci- 6. little, G. et al. TurKit: Human computation tems.” An operating system, in the con- fications. Additionally, we need to ex- on mechanical turk. In Proceedings of the 23nd Annual ACM Symposium on User Interface Software and text of a single computer, manages the pand the range of abstractions such Technology (UIST ‘10). ACM, New York, 2010, 57–66. allocation of hardware and software programming languages offer. While 7. Malone, T.W. The Future of Work. Harvard Business School Press, Boston, MA, 2004. resources such as memory, CPU time, traditional programming languages 8. Malone, T.W., Laubacher, R., and Dellarocas, C. The genome. Sloan Management disk space, and input/output devices. incorporate constructs such as loops Review 51, 3 (Spring 2010), 21–31. A social operating system, in addition and recursion, a global brain program- 9. Minder, P. and Bernstein, A. CrowdLang—First steps towards programmable human computers for general to doing all these things, will also have ming language may also need to in- computation. In Proceedings of the 3rd Human to manage the mustering and alloca- corporate abstractions such as group Computation Workshop (HCOMP 2011), AAAI-Press. 10. Quinn, A.J. and Bederson, B.B. Human computation: tion of human resources to tasks. This decision processes, contests, and col- A survey and taxonomy of a growing field. In will require fast, robust infrastructures laborative steps.1,9 Proceedings of CHI 2011, (Vancouver, BC, Canada, May 7–12, 2011). for contracts, payments, or other moti- Promulgating new software engi- 11. Shirky, C. Cognitive Surplus: Creativity and Generosity neering skills. Programmers will need in a Connected Age. Penguin Press, New York, 2010. 12. von Ahn, L. et al. reCAPTCHA: Human-based to develop new mind-sets about, for character recognition via Web security measures. Making global brain example, such basic concepts as what Science 321 (2008), 1465–1468. a “program” is and what “testing” and Abraham Bernstein ([email protected]) is a professor metaphors a reality “debugging” mean. They will need to at the University of Zurich’s Department of Informatics become not just software architects and heads the Dynamic and Distributed Information will require progress Systems Group. and implementers, but also Mark Klein ([email protected]) is a principal research along several fronts. organizational or even societal archi- scientist at the MIT Center for Collective Intelligence in tects able to think systematically about Cambridge, MA. things like motivations, coalitions, Thomas W. Malone ([email protected]) is the director of the MIT Center for Collective Intelligence and the Patrick emergence, and so on. Perhaps most J. McGovern Professor of Management at the MIT Sloan fundamentally, they will need to transi- School of Management in Cambridge, MA. tion from a purely “command-and-con- Copyright held by author.

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