The collective intelligence genome

Malone, Thomas W.; Laubacher, Robert; Dellarocas, Chrysanthos

doi:10.1109/emr.2010.5559142

Cited by 296 publications

(382 citation statements)

References 1 publication

Supporting

Mentioning

343

Contrasting

Unclassified

Order By: Relevance

“…Further, they do not provide any explicit treatment of cognitive diversity in and between human actors [5] or abstractions for complex coordination patterns such as group decision procedures [2]. Finally, they assume that computation can be fully specified ex-ante.…”

Section: Background and Related Workmentioning

confidence: 99%

“…Malone et al [2] examined about 250 different HCSs and identified in the Collective Intelligence Genome the characteristics ("genes") that can be recombined to the basic building blocks ("genome") of human computation systems. Their conceptual classification framework suggests characterizing each building block by answering two pairs of questions.…”

Section: Background and Related Workmentioning

confidence: 99%

“…CrowdLang supports cross-platform workforce integration, the management of human computer latency, and incorporates abstractions for group decisions, contests, and collaborative interaction patterns as proposed by Malone et al [2]. CrowdLang also supports the management of arbitrary dependencies among tasks and workers, and not only asynchronous parallelization.…”

Section: Introductionmentioning

confidence: 99%

“…Wikipedia, Google, and other stunning success stories show that with the rapid growth of the World Wide Web and the advancements in communication technology, this concept of Division of Labor can also be applied to knowledge work [1,2]. These new modes of collaboration-whether they are called collective intelligence, human computation, crowdsourcing, or social computing 2 -are now able to routinely solve problems that would have been unthinkably difficult only a few years ago by interweaving the creativity and cognitive capabilities of networked humans and the efficiency and scalability of networked machines in processing large amounts of data [5].…”

Section: Introductionmentioning

confidence: 99%

“…To move from a culture of "Wizard of Oz" techniques, in which applications are the result of extensive trial-and-error refinements, a programming language has to support the recombination [6] of interaction patterns to systematically explore the design space of possible solutions. Recent research only partially addresses these challenges by providing programming frameworks and models [7][8][9] for massive parallel human computation, concepts for planning and controlling dependencies [10,11], and theoretical deductive analysis of emergent collective intelligence [2].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems

Minder

Bernstein

2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Human computation systems are often the result of extensive lengthy trial-and-error refinements. What we lack is an approach to systematically engineer solutions based on past successful patterns.In this paper we present the CrowdLang1 programming framework for engineering complex computation systems incorporating large crowds of networked humans and machines with a library of known interaction patterns. We evaluate CrowdLang by programming a German-to-English translation program incorporating machine translation and a monolingual crowd. The evaluation shows that CrowdLang is able to simply explore a large design space of possible problem-solving programs with the simple variation of the used abstractions. In an experiment involving 1918 different human actors, we show that the resulting translation program significantly outperforms a pure machine translation in terms of adequacy and fluency whilst translating more than 30 pages per hour and approximates the human-translated gold standard to 75%. Abstract. Human computation systems are often the result of extensive lengthy trial-and-error refinements. What we lack is an approach to systematically engineer solutions based on past successful patterns. In this paper we present the CrowdLang 1 programming framework for engineering complex computation systems incorporating large crowds of networked humans and machines with a library of known interaction patterns. We evaluate CrowdLang by programming a German-to-English translation program incorporating machine translation and a monolingual crowd. The evaluation shows that CrowdLang is able to simply explore a large design space of possible problem-solving programs with the simple variation of the used abstractions. In an experiment involving 1918 different human actors, we show that the resulting translation program significantly outperforms a pure machine translation in terms of adequacy and fluency whilst translating more than 30 pages per hour and approximates the human-translated gold standard to 75%.

show abstract

Section: Background and Related Workmentioning

confidence: 99%

Section: Background and Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems

Minder

Bernstein

2012

Lecture Notes in Computer Science

View full text Add to dashboard Cite

show abstract

Crowdsourcing and Human‐in‐the‐Loop forIoT

Ibáñez

Reeves

Simperl

2020

The Internet of Things

View full text Add to dashboard Cite

show abstract

Building responses to sustainable development challenges: A multistakeholder collaboration framework and application to climate change

2020

View full text Add to dashboard Cite

The affirmation of open innovation and collaborative systems is enabling unprecedented opportunities to create business value while facilitating multistakeholder conversation on sustainability issues. In particular, platform‐based models are emerging as organization archetypes able to facilitate cooperative dynamics among industrial actors, policy makers, academicians, scientists, and citizens. In this article, we use interdisciplinary business management and collaborative innovation literature to build the conceptual framework of a multisided platform as a collaboration environment gathering actors willing to define responses to sustainable development challenges. We present five dimensions or “genes,” that is, the focus and strategic intent or orientation of the platform (what), the participating sides, actors and groups (who), the actions, flows and coordination mechanisms (how), and the value drivers, benefits and externalities (why), and the rules regulating the affiliation and interaction processes (governance). We also present and discuss 30 subtopics or management items that are associated with the five dimensions defined. We then apply the conceptual model to analyze a case in the climate change endeavor and to show how competitive and cooperative dynamics can be virtuously integrated to provide individual‐ and company‐driven responses to a timely socioenvironmental issue. The article provides a new perspective on collaboration to enhance social development, and it offers theoretical and practitioner insights for a broad interdisciplinary audience including scholars, practitioners, business, and platform managers.

show abstract

The collective intelligence genome

Cited by 296 publications

References 1 publication

CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems

CrowdLang: A Programming Language for the Systematic Exploration of Human Computation Systems

Crowdsourcing and Human‐in‐the‐Loop forIoT

Building responses to sustainable development challenges: A multistakeholder collaboration framework and application to climate change

Contact Info

Product

Resources

About