Workshop on Cognitive
Theories of Science and of Religion
March 31, 2:00-6:00
Sherwood Room, Levering
Hall
Reception to Follow
Schedule:
2:00 p.m.-3:10 p.m.
“The Process of Conceptual Change
3:10 p.m.-4:20 p.m.
“Engineering Models: Model-based problem solving in biomedical
engineering
4:20 p.m. -5:30 p.m.
Dan Sperber
(
5:30 p.m. -6:00p.m.
General Discussion
6:00 p.m.
Reception
The Process of
Conceptual Change
Many cognitive scientists accept Fodor's argument for strong continuity of
conceptual representations throughout development on both historical and
ontogenetic time scales. The argument: all learning reduces to
hypothesis testing, and one can't test a hypothesis one cannot represent.
Therefore, learning cannot result in new representational resources.
Meeting this challenge has two parts, descriptive and explanatory.
Descriptively, one must characterize what kinds of discontinuities occur
during development. Explanatorily, one must sketch a learning mechanism
that underlies these discontinuities. In this paper, I take on both
challenges.
Nancy J. Nersessian
Georgia Institute of Technology
Engineering
Models: Model-based problem solving in biomedical engineering
Engineering
and experimenting with in vitro model-systems is a signature
investigative practice of much research in biomedical engineering. In a
six-year ethnographic study of two university research laboratories, one in
tissue engineering and one in neural engineering, we have observed that the
central components of the model-systems are physical “devices” – custom
technology designed and constructed within the laboratories. Devices are not
stable technologies, but are designed, constructed, and re-designed in the
course of research with respect to problems encountered and changes in
understanding. The devices provide sites of simulation where in vitro models
are used to screen and control selected aspects of in vivo phenomena
that the researchers want to understand, and in the neural engineering lab in
silico models are added
to the mix. The devices also provide sites where cognitive, social, and
cultural dimensions of practice interlock.
Researchers
refer to their practice of engineering models as “putting a thought into the
bench top and seeing if it works.” These instantiated thought experiments
(model-base simulations) can involve open-ended exploration, hypothesis testing
or generation, explanation, and prediction. In this talk I examine a year-long
episode in the neural engineering lab where the cross-breeding of two
engineered models – one computational and one physical – that involved the
interaction of three researchers led to a significant conceptual innovation and
subsequent engineering innovations. Investigations of such model-based
problem-solving practices now used widely across engineering and the sciences
provide novel considerations for cognitive science theories, which are based
largely on studies of mundane cognition; in this case, of analogy and of
distributed cognition.
Institut Jean Nicod
Templeton Lecture IV
Religion and science: an old comparison in a new
epidemiological perspective
Thinking of religious phenomena in epidemiological terms, as a mesh of causal
chains where mental and environmental events alternate, we can identify causal
factors that weigh not globally on religions, but locally on every micro-event
in the propagation of religious ideas and practices. Approaching science
from the same epidemiological point of view, the causal factors we can identify
both in the cognitive mechanisms and in the social interactions involved
determine quite a different dynamics. Are the differences such as to make the
comparison an ill-framed exercise? Does the epidemiological perspective throw
any light on the historical and current relationships between religion and
science?