Our research

Exploring the Uncanny Valley consists of several interrelated research projects directed by Karl F. MacDorman at the Indiana University School of Informatics. The projects share a common interest in understanding human perception of forms of varying human likeness. The purpose of this website is to provide visitors with information about Exploring the Uncanny Valley projects and to administer experiments to those who volunteer to participate in them. One starting point for this research is Masahiro Mori's hypothesis that very humanlike robots risk appearing creepy.

You are encouraged to read the information on this website before registering to participate in the experiments. Registration is simple, requiring only your email address, gender, birth year, nationality at birth, and years of education. Once you have registered, you may select an experiment immediately. Before starting the experiment, you will first need to read and agree to the consent form. At the end of the experiment, you will get to see how your results compare to averages for previous participants.

The Uncanny Valley

In 1970 Masahiro Mori proposed the uncanny valley: a relation between human perception of robots and their degree of human likeness. Mori observed that as robots are built to look more humanlike, they appear more familiar and one might suppose that this trend would continue until they became indistinguishable from human beings. However, Mori argued that near-humanlike robots would appear strange or creepy, and this dip in familiarity he termed bukimi no tani, which has been popularly translated as the uncanny valley. According to Mori, movement amplifies the relation between human likeness and familiarity.


Mori, Masahiro (1970). Bukimi no tani [the uncanny valley] (K. F. MacDorman & T. Minato, Trans.). Energy, 7(4), 33-35.

Also see macdorman.com writings > uncanny valley.


Implicit association about human and machine speech and male and female speech

Researchers: Wade J. Mitchell, Karl F. MacDorman

The implicit association test (IAT) measures differential associations of two concepts with an attribute. Measurement is implicit, based on time-on-task performance. Performance is faster if a more strongly associated attribute-concept pair has the same response key than if a less strongly associated attribute-concept pair does. The IAT is intended to measure automatic evaluations that may differ from self-reported preferences. To the extent that these preferences are exclusively subconscious, their causes are not available to introspection. The IAT was developed by Anthony G. Greenwald (University of Washington), Mahzarin Banaji (Harvard University), and their colleagues.


Greenwald, A.G., McGhee, D.E., & Schwartz, L K. (1998). Measuring individual differences in implicit cognition: The implicit association test. Journal of Personality and Social Psychology, 74(6), 1464-1480.

Banaji, M. R. (2001). Implicit attitudes can be measured. In H. L. Roediger, III, J. S. Nairne, I. Neath, & A. Surprenant (Eds.), The nature of remembering: Essays in honor of Robert G. Crowder, pp. 117-150. Washington, DC: American Psychological Association.

Also see projectimplicit.net

Comparing subliminal, threshold, and conscious evaluations of human face images

Researchers: Himalaya Patel, Karl F. MacDorman


Perception of facial proportions

Researchers: Robert D. Green, Sandosh Vasudevan, Karl F. MacDorman

The uncanny valley hypothesis predicts increased sensitivity to human norms in figures approaching human likeness. An entity may seem uncanny or eerie because it violates norms related to appearance, movement quality, or contingency during interaction. In considering appearance, presumably, people should be more sensitive to deviations from perceptual norms in humanlike entities. The purpose of this study is to determine whether human beings vary in their sensitivity to the facial proportions of people, robots, and humanlike characters. It specifically considers what facial proportions are ideal and what ranges are acceptable with respect to a figure's degree of human likeness.


Etcoff, N. L. (1999). Survival of the prettiest: The science of beauty. Doubleday, New York.

Implicit association about robots and people

Researchers: Sandosh Vasudevan, Karl F. MacDorman

This website was created by Sandosh Vasudevan, Karl F. MacDorman, and their collaborators.
Copyright (c) 2006, Sandosh Vasudevan and Karl F. MacDorman. All rights reserved.