32,666 research outputs found
Human Computation and Convergence
Humans are the most effective integrators and producers of information,
directly and through the use of information-processing inventions. As these
inventions become increasingly sophisticated, the substantive role of humans in
processing information will tend toward capabilities that derive from our most
complex cognitive processes, e.g., abstraction, creativity, and applied world
knowledge. Through the advancement of human computation - methods that leverage
the respective strengths of humans and machines in distributed
information-processing systems - formerly discrete processes will combine
synergistically into increasingly integrated and complex information processing
systems. These new, collective systems will exhibit an unprecedented degree of
predictive accuracy in modeling physical and techno-social processes, and may
ultimately coalesce into a single unified predictive organism, with the
capacity to address societies most wicked problems and achieve planetary
homeostasis.Comment: Pre-publication draft of chapter. 24 pages, 3 figures; added
references to page 1 and 3, and corrected typ
Crowdsourcing as a way to access external knowledge for innovation
This paper focuses on âcrowdsourcingâ as a significant trend in the new paradigm of open innovation (Chesbrough 2006; Chesbrough & Appleyard 2007). Crowdsourcing conveys the idea of opening the R&D processes to âthe crowdâ through a web 2.0 infrastructure. Based on two cases studies of crowdsourcing webstartups (Wilogo and CrowdSpirit), the paper aims to build a framework to characterize and interpret the tension between value creation by a community and value capture by a private economic actor. Contributing to the discussions on âhybrid organizational formsâ in organizational studies (Bruce & Jordan 2007), the analysis examines how theses new models combine various forms of relationships and exchanges (market or non market). It describes how crowdsourcing conveys new patterns of control, incentives and co-ordination mechanisms.communautĂ© ; crowdsourcing ; innovation ; formes organisationnelles hybrides ; plateforme ; web 2.0
Prochlo: Strong Privacy for Analytics in the Crowd
The large-scale monitoring of computer users' software activities has become
commonplace, e.g., for application telemetry, error reporting, or demographic
profiling. This paper describes a principled systems architecture---Encode,
Shuffle, Analyze (ESA)---for performing such monitoring with high utility while
also protecting user privacy. The ESA design, and its Prochlo implementation,
are informed by our practical experiences with an existing, large deployment of
privacy-preserving software monitoring.
(cont.; see the paper
Mitigating Gender Bias in Machine Learning Data Sets
Artificial Intelligence has the capacity to amplify and perpetuate societal
biases and presents profound ethical implications for society. Gender bias has
been identified in the context of employment advertising and recruitment tools,
due to their reliance on underlying language processing and recommendation
algorithms. Attempts to address such issues have involved testing learned
associations, integrating concepts of fairness to machine learning and
performing more rigorous analysis of training data. Mitigating bias when
algorithms are trained on textual data is particularly challenging given the
complex way gender ideology is embedded in language. This paper proposes a
framework for the identification of gender bias in training data for machine
learning.The work draws upon gender theory and sociolinguistics to
systematically indicate levels of bias in textual training data and associated
neural word embedding models, thus highlighting pathways for both removing bias
from training data and critically assessing its impact.Comment: 10 pages, 5 figures, 5 Tables, Presented as Bias2020 workshop (as
part of the ECIR Conference) - http://bias.disim.univaq.i
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