Leveraging the Potentials of Dedicated Collaborative Interactive Learning: Conceptual Foundations to Overcome Uncertainty by Human-Machine Collaboration

10 Pages Posted: 13 Feb 2018 Last revised: 18 Mar 2018

See all articles by Adrian Calma

Adrian Calma

University of Kassel - Intelligent Embedded Systems

Sarah Oeste-Reiß

University of Kassel - Information Systems

Bernhard Sick

Independent

J. M. Leimeister

University of St. Gallen; University of Kassel - Information Systems

Date Written: January 1, 2018

Abstract

When a learning system learns from data that was previously assigned to categories, we say that the learning system learns in a supervised way. By “supervised”, we mean that a higher entity, for example a human, has arranged the data into categories. Fully categorizing the data is cost intensive and time consuming. Moreover, the categories (labels) provided by humans might be subject to uncertainty, as humans are prone to error. This is where dedicate collaborative interactive learning (D-CIL) comes together: The learning system can decide from which data it learns, copes with uncertainty regarding the categories, and does not require a fully labeled dataset. Against this background, we create the foundations of two central challenges in this early development stage of D-CIL: task complexity and uncertainty. We present an approach to “crowdsourcing traffic sign labels with self-assessment” that will support leveraging the potentials of D-CIL.

Keywords: Collaborative Interactive Learning, Uncertainty, Human-Machine Collaboration, Crowdsourcing

Suggested Citation

Calma, Adrian and Oeste-Reiß, Sarah and Sick, Bernhard and Leimeister, Jan Marco, Leveraging the Potentials of Dedicated Collaborative Interactive Learning: Conceptual Foundations to Overcome Uncertainty by Human-Machine Collaboration (January 1, 2018). Available at SSRN: https://ssrn.com/abstract=3116094 or http://dx.doi.org/10.2139/ssrn.3116094

Adrian Calma

University of Kassel - Intelligent Embedded Systems ( email )

Wilhelmshöher Allee 73
Kassel, 34121
Germany

Sarah Oeste-Reiß

University of Kassel - Information Systems ( email )

Pfannkuchstraße 1
No Address Available, DE 34121
Germany

Bernhard Sick

Independent ( email )

No Address Available
United States

Jan Marco Leimeister (Contact Author)

University of St. Gallen ( email )

Varnbuelstr. 14
Saint Gallen, St. Gallen CH-9000
Switzerland

University of Kassel - Information Systems ( email )

Nora-Platiel 4
Kassel, 34127
Germany

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