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Science of Intelligence: Methodology of the synthetic approach (SynthMeth)

Lupe

Methodology of the synthetic approach (Cluster of excellence "Science of Intelligence" (SCIoI), funded between 2019-2025)

Project description

The “Methodology of the Synthetic Approach” (SynthMeth) project is part of the “Science of Intelligence” Cluster of Excellence (SCIoI). SCIoI is an interdisciplinary research cluster concerned with intelligence in humans, animals, and artificial agents. SCIoI fosters the collaboration of scientists from different disciplines. The cluster aims to discover general principles of intelligence through the investigation of (inter)actions of both biological and synthetic actors in different experimental settings, such as humans interacting with humanoid robots or fish interacting with artificial fish. SCIoI central methodological procedure is the so-called “synthetic approach”. The synthetic approach is the attempt to utilize research into biological intelligence to build synthetic artifacts such as robots or computer programs and then use these artifacts as tools for intelligence research. The assumption is that the building of synthetic artifacts provides a fuller understanding of intelligence.

The SynthMeth project’s objective is to study the epistemological opportunities and limitations of the synthetic approach to intelligence research. SCIoI’s methodology of using synthetic artifacts as tools to investigate intelligent behaviors of biological agents, and vice versa, raises novel epistemological questions. What kind of knowledge about intelligent behaviors of biological agents can we obtain from synthetic artifacts that are designed to reproduce these behaviors? Under which conditions and for which purposes can we treat synthetic artifacts as functional equivalents of biological agents? What can we learn about intelligent behaviors from hybrid experimental settings in which artificial agents interact with biological counterparts? In sum, how do synthetic artifacts support and limit the exploration, validation, and stabilization of knowledge in interdisciplinary research? In order to answer these questions, SynthMeth conducts ethnographic research and collects data about the SCIoI projects. A further aim of the SynthMeth project is to feed back its insights into the internal SCIoI discussion, enabling projects to take advantage of our findings.

Project team:
Prof. Dr. Sabine Ammon
Prof. Dr. Ingo Schulz-Schaeffer
Dr. Ole Pütz
Martina Vortel
Kevin Wiggert

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