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VisioTracker, an Innovative Automated Approach to Oculomotor Analysis

VisioTracker, an Innovative Automated Approach to Oculomotor Analysis

Published on: October 12, 2011

Machine vision situations: Tracing distributed agency.

Marianne Gunderson¹, Ragnhild Solberg², Linda Kronman¹

¹Department of Linguistic, Literary and Aesthetic Studies, University of Bergen, Bergen, 5020, Norway.

Open Research Europe

|April 24, 2024

Summary

This study introduces the "machine vision situation" to analyze how machine vision technologies influence creative works. This method reveals complex interactions between human and non-human actors in distributed agency.

Keywords:

agency art digital humanities games machine vision science fiction

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Area of Science:

Science and Technology Studies
Digital Humanities
Media Studies

Background:

Traditional analyses of agency in creative works often overlook the intricate roles of technology.
Machine vision technologies are increasingly integrated into creative processes, necessitating new analytical frameworks.

Purpose of the Study:

To propose and validate a novel analytical method, the "machine vision situation," for examining agency in heterogeneous assemblages.
To explore the complex entanglements between human and non-human actors facilitated by machine vision in creative works.

Main Methods:

Introduction of the "machine vision situation" as a unit of analysis.
Application of the method to diverse creative works: narratives, digital games, and artworks.
Grounded in an interdisciplinary theoretical framework.

Main Results:

Identified specific moments where machine vision technologies actively participate in events, beyond being mere tools or protagonists.
Revealed key aspects of distributed agency, highlighting overlooked complexities and entanglements.
Demonstrated the flexibility of the "machine vision situation" for both quantitative and qualitative research.

Conclusions:

The "machine vision situation" offers a valuable and flexible method for tracing distributed agency in human-technology interactions.
This approach enhances understanding of agency in creative works and other contexts involving human and non-human actors.