Robert J Laubacher

Biographic Data

ID9569571
NAMERobert J Laubacher
GIVEN NAMESRobert J
FAMILY NAMELaubacher
SIGNATURELAUBACHER R J
AFFILIATIONSMassachusetts Institute of Technology
ORCID0000-0002-4645-1590
VERIFIEDYes
TOTAL WORKS4
TOTAL CITATIONS0
WORKS AS AUTHOR4
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2023
LATEST PUBLICATION YEAR2026
H-INDEX0

  • The Crowd Without People

    Open AccessFabian Probost, Manfred Schoch et al.ARTICLEGroup Decision and Negotiation2026

    Large Language Models (LLMs) are transforming the innovation process by scaling ideation and creativity. This yields the challenge of evaluating the growing flood of ideas. In simpler contexts, tasks with clear criteria and well-defined outcome possibilities, where human evaluators are also a bottleneck, LLM systems are already being used as a scalable and cheap alternative. In this study, we assess whether LLMs and LLM agents can be used as eval…

  • Idea Evaluation for Solutions to Specialized Problems

    Open AccessHenner Gimpel, Robert J Laubacher et al.ARTICLEGroup Decision and Negotiation2025

    Complex problems such as climate change pose severe challenges to societies worldwide. To overcome these challenges, digital innovation contests have emerged as a promising tool for idea generation. However, assessing idea quality in innovation contests is becoming increasingly problematic in domains where specialized knowledge is needed. Traditionally, expert juries are responsible for idea evaluation in such contests. However, experts are a sub…

  • Advancing Content Synthesis in Macro-Task Crowdsourcing Facilitation Leveraging Natural Language Processing

    Open AccessHenner Gimpel, Robert J Laubacher et al.ARTICLEGroup Decision and Negotiation2024

    Macro-task crowdsourcing presents a promising approach to address wicked problems like climate change by leveraging the collective efforts of a diverse crowd. Such macro-task crowdsourcing requires facilitation. However, in the facilitation process, traditionally aggregating and synthesizing text contributions from the crowd is labor-intensive, demanding expertise and time from facilitators. Recent advancements in large language models (LLMs) hav…

  • Towards Artificial Intelligence Augmenting Facilitation

    Open AccessHenner Gimpel, Vanessa Graf-Seyfried et al.ARTICLEGroup Decision and Negotiation2023

    Crowdsourcing holds great potential: macro-task crowdsourcing can, for example, contribute to work addressing climate change. Macro-task crowdsourcing aims to use the wisdom of a crowd to tackle non-trivial tasks such as wicked problems. However, macro-task crowdsourcing is labor-intensive and complex to facilitate, which limits its efficiency, effectiveness, and use. Technological advancements in artificial intelligence (AI) might overcome these…