Social Computing; Human Computation; Crowdsourcing; CSCW (Computer Supported Cooperatie Work); Collective Intelligence; Human-Computer Interaction; Business Process Management; Group Decision Processes
Goncalves Jorge, Feldman Michael, Hu Subingqian, Kostakos Vassilis, Bernstein Abraham (2017), Task Routing and Assignment in Crowdsourcing based on Cognitive Abilities, in WWW 2017 Companion
, Perth, AustraliaACM press, Perth, Australia.
Lienk George, Lumbard Kevin, Conboy Kieran, Feller Joseph, George Jordana, Germonprez Matt, Goggins Sean, Jeske Debora, Kiely Gaye, Schuster Kirsten, Willis Matt (2017), Contemporary Issues of Open Data in Information Systems Research: Considerations and Recommendations, in Communications of the Association for Information Systems
, 41(25), 556-577.
De Boer Patrick, Bernstein Abraham (2017), Efficiently identifying a well-performing crowd process for a given problem, in 20th ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW 2017)
, Portland, OR.
De Boer Patrick, Bühler Marcel, Bernstein Abraham (2017), Expert estimates for feature relevance are imperfect, in The 4th IEEE International Conference on Data Science and Advanced Analytics
, Tokyo, Japan.
Feldmann Michaek, Anastasiu Cristian, Bernstein Abraham (2016), Towards Enabling Crowdsourced Collaborative Data Analysis, in Collective Intelligence (Abstracts)
, New York, USA.
De Boer Patrick, Bernstein Abraham (2016), PPLib: toward the automated generation of crowd computing programs using process recombination and auto-experimentation, in ACM Transactions on Intelligent Systems and Technology
, 7(4), 49.
Feldman Michael (2015), Massively Collaborative Complex Work — Exploring the Frontiers of Crowdsourcing, in Doctoral Consortium of the 36th International Conference on Information Systems (ICIS)
, Fort Worth, USAICIS, Auckland, DE.
De Boer Patrick, Bernstein Abraham (2015), PPLib: towards systematic crowd process design using recombination and auto-experimentation, in Collective Intelligence 2015 (Abstract)
, Santa Clara, CAself-publsihed by conference, Santa Clara, CA.
Feldman Michael, Bernstein Abraham (2014), Behavior-Based Quality Assurance in Crowdsourcing Markets Conference, in Human Computation & Crowdsourcing (HCOMP'14)
Feldman Michael, Bernstein Abraham (2014), Cognition-based Task Routing:Towards Highly-Effective Task-Assignments in Crowdsourcing Settings, in 35th International Conference on Information Systems (ICIS 2014)
, Auckland, New ZealandInternational Conference on Information Systems, ?.
Feldman Michael, Gao Shen, Novel Marc, Papaioannou Katerina, Bernstein Abraham (2014), SHAX: The Semantic Historical Archive eXplorer, in ISWC 2014 Posters & Demonstrations Track
, Riva del Garda, Italy.
Much of the prosperity gained by the industrialization of the economy in the 18th century arose from the increased productivity by dividing work into smaller tasks performed by more specialized workers. Wikipedia, Google and other stunning success stories show that with the rapid growth of the World Wide Web, this concept of “Division of Labour” can also be applied on knowledge work [6, 40]. Consequently, systems interweaving both the number-crunching capabilities and scalability of computer systems with the creativity and high-level cognitive capabilities of people are now routinely able to solve problems that would have been unthinkably difficult only a few years ago. As the scale, scope and connectivity of these human-computer networks increase, we believe it will become increasingly useful to view these systems as constituting a kind of “global brain” .Even though there are already literally hundreds of compelling examples of the global brain at work, our understanding of how to “program” the global brain is still poor because human computers are different from traditional computers due to the huge motivational, error and cognitive diversity within and between humans [6, 45]. In this project we intend to investigate problem-solving processes that are either to difficult or to expensive to solve by either pure machine or pure human crowds. As such, we aim to answer the following research questions:• How can we systematically program, cultivate, and coordinate the global brain whilst automatically adapting to the cognitive variance of human computation resources?• How can we support the seamless reuse of successful interaction patterns resulting in a systematic exploration of the whole design space?• How can we efficiently recruit, incentivize, and allocate human computers in human computation systems taking the requestor’s budget, time, and quality constraints into consideration?To harness the full potential of the global brain, we need new powerful programming metaphors that support the design and implementation of human computation systems, as well as general-purpose infrastructure to execute them. Specifically, to move from a culture of “wizard of oz”-techniques, in which applications are the result of extensive trial-and-error refinements, we propose to build the programming language and framework CrowdLang which will incorporate abstractions such as group decision processes, the CrowdRecombinator, a novel tool to support the engineering process of new human computation systems, and the social operating system CrowdOS which will manage the allocation of human resources to tasks as well as provide robust infrastructure for contracts and payments. We believe using these three components, human computation systems will become truly transformative in a variety of domains.The impact of the project is twofold. On the practical side these tools will help engineers and managers to adopt human computation systems in practice and, thus, will foster the transformation of the Swiss economy in the “age of hyperspecialization” . On the scientific side, our explorations are likely to advance the field by providing new insights about the interplay between human and machine computation, the longterm properties of those systems, and will foster more engineering-oriented approaches in the development process.