senseforsense

Senseforsense is a hypothetical interdisciplinary initiative focused on sensemaking and the interpretation of sensory information by humans and machines. The project examines how people and automated systems extract meaning from sensory inputs across modalities such as vision, audition, and touch, and how context, prior knowledge, and bias influence interpretation.

Origin and purpose: Senseforsense was proposed in 2018 by a loose network of researchers in cognitive science, design, and artificial intelligence who sought a common framework for evaluating sensemaking processes. The stated aim is to improve transparency, reliability, and accessibility in how sensory information is translated into knowledge.

Activities and resources: The initiative publishes open resources, including datasets, methodological templates, and case studies. It sponsors workshops and collaborates with universities and industry partners to develop tools for annotating and evaluating sensemaking tasks. It also promotes ethical considerations such as consent, bias mitigation, and accessibility in sensory data use.

Structure and governance: Senseforsense operates as a decentralized, community-led network with a rotating steering group and working teams focusing on research methods, data governance, and education. Decisions are typically made through collaborative discussion and consensus-building among participants from academia, industry, and civil society.

Impact and reception: Senseforsense is cited in discussions of human-centered AI and perceptual psychology as a conceptual model for interdisciplinary collaboration. It has been used in academic settings to illustrate issues of interpretability and bias in sensory data and to foster dialogue across disciplines.

See also: sensemaking; perceptual psychology; human-computer interaction; explainable AI; data ethics.