Measuring the Uncanny Valley Effect
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Arkes HR (1991) Costs and benefits of judgment errors: implications for debiasing. Psychol Bull 110(3):486–498. doi: 10.1037/0033-2909.110.3.486
Bartneck C, Kulić D, Croft E, Zoghbi S (2009) Measurement instruments for the anthropomorphism, animacy, likeability, perceived intelligence, and perceived safety of robots. Int J Soc Robot 1(1):71–81. doi: 10.1007/s12369-008-0001-3
Becker-Asano C, Ogawa K, Nishio S, Ishiguro H (2010) Exploring the uncanny valley with Geminoid HI-1 in a real-world application. In: Blashki K (ed) Proceedings of IADIS International Conference Interfaces and Human Computer Interaction. IADIS Press, Lisbon, Portugal, pp 121–128
Bentler PM (1969) Semantic space is (approximately) bipolar. J Psychol 71(1):33–40. doi: 10.1080/00223980.1969.10543067
Bentler PM (1990) Comparative fit indexes in structural models. Psychol Bull 170(2):238–246. doi: 10.1037/0033-2909.107.2.238
Burleigh TJ, Schoenherr JR (2015) A reappraisal of the uncanny valley: categorical perception or frequency-based sensitization? Front Psychol 5(1488):1–19. doi: 10.3389/fpsyg.2014.01488
Chattopadhyay D, MacDorman KF (2016) Familiar faces rendered strange: Why inconsistent realism drives characters into the uncanny valley. J Vis, 16(11):7, 1–25
Cheetham M, Pavlovic I, Jordan N, Suter P, Jäncke L (2013) Category processing and the human likeness dimension of the uncanny valley hypothesis: eye-tracking data. Front Psychol 4(108):1–12. doi: 10.3389/fpsyg.2013.00108
Cheetham M, Suter P, Jäncke L (2011) The human likeness dimension of the “uncanny valley hypothesis”: behavioral and functional MRI findings. Front Hum Neurosci 5(125):1–14. doi: 10.3389/fnhum.2011.00126
Chin WW, Todd PA (1995) On the use, usefulness, and ease of use of structural equation modeling in MIS research: a note of caution. MIS Q 19(2):237–246. doi: 10.2307/249690
Dunning D, Johnson K, Ehrlinger J, Kruger J (2003) Why people fail to recognize their own incompetence. Curr Dir Psychol Sci 12(3):83–87. doi: 10.1111/1467-8721.01235
Feldman NH, Griffiths TL, Morgan JL (2009) The influence of categories on perception: explaining the perceptual magnet effect as optimal statistical inference. Psychol Rev 116(4):752–782. doi: 10.1037/a0017196
Fox CR, Clemen RT (2005) Subjective probability assessment in decision analysis: partition dependence and bias toward the ignorance prior. Manag Sci 51(9):1417–1432. doi: 10.1287/mnsc.1050.0409
Gärling T (1976) A multidimensional scaling and semantic differential technique study of the perception of environmental settings. Scand J Psychol 17(1):323–332. doi: 10.1111/j.1467-9450.1976.tb00248.x
Gefen D, Straub D, Boudreau M (2000) Structural equation modeling and regression: guidelines for research practice. Commun Assoc Inf Syst 4(7):1–79
Gerbing DW, Hamilton JG (1996) Viability of exploratory factor analysis as a precursor to confirmatory factor analysis. Struct Equ Model 3(1):62–72. doi: 10.1080/10705519609540030
Goetz J, Kiesler S, Powers A (2003) Matching robot appearance and behavior to tasks to improve human-robot cooperation. In: Proceedings of the 12th IEEE International Workshop on Robot and Human Interactive Communication. IEEE Press, Piscataway, pp 55–60. doi: 10.1109/ROMAN.2003.1251796
Hanson D (2005) Expanding the aesthetic possibilities for humanoid robots. In: Proceedings of the views of the uncanny valley workshop. IEEE-RAS International Conference on Humanoid Robots. December 5, Tsukuba, Japan
Harnad S (1987) Category induction and representation. In: Harnad S (ed) Categorical perception: the groundwork of cognition. Cambridge University Press, New York, pp 535–565
Hashimoto T, Nakane H, Kobayashi H (2013) Android patient robot simulating depressed patients for diagnosis training of psychiatric trainees. In: Proceedings of the Second IEEE International Conference on Robot, Vision and Signal Processing. IEEE Press, Piscataway, pp 247–252. doi: 10.1109/RVSP.2013.63
Ho C-C, MacDorman KF (2010) Revisiting the uncanny valley theory: developing and validating an alternative to the Godspeed indices. Comput Hum Behav 26(6):1508–1518. doi: 10.1016/j.chb.2010.05.015
Ho C-C, MacDorman KF, Pramono ZAD (2008) Human emotion and the uncanny valley: A GLM, MDS, and isomap analysis of robot video ratings. In: Proceedings of the Third ACM/IEEE International Conference on Human-Robot Interaction (pp. 169–176). ACM, New York. doi: 10.1145/1349822.1349845
Kätsyri J, Förger K, Mäkäräinen M, Takala T (2015) A review of empirical evidence on different uncanny valley hypotheses: support for perceptual mismatch as one road to the valley of eeriness. Front Psychol 6(390):1–16. doi: 10.3389/fpsyg.2015.00390
Kikutani M, Roberson D, Hanley JR (2010) Categorical perception for unfamiliar faces: the effect of covert and overt face learning. Psychol Sci 21(6):865–872. doi: 10.1177/0956797610371964
Kruger J, Dunning D (1999) Unskilled and unaware of it: how difficulties in recognizing one’s own incompetence lead to inflated self-assessments. J Personal Soc Psychol 77(6):1121–1134. doi: 10.1037/0022-3514.77.6.1121
Looser CE, Wheatley T (2010) The tipping point of animacy: how, when, and where we perceive life in a face. Psychol Sci 21(12):1854–1862. doi: 10.1177/0956797610388044
MacDorman KF, Chattopadhyay D (2016) Reducing consistency in human realism increases the uncanny valley effect; increasing category uncertainty does not. Cognition 146:190–205. doi: 10.1016/j.cognition.2015.09.019
MacDorman KF, Entezari SO (2015) Individual differences predict sensitivity to the uncanny valley. Interact Stud 16(2):141–172. doi: 10.1075/is.16.2.01mac
MacDorman KF, Green RD, Ho C-C, Koch C (2009) Too real for comfort: Uncanny responses to computer generated faces. Comput Hum Behav 25(3):695–710. doi: 10.1016/j.chb.2008.12.026
MacDorman KF, Ishiguro H (2006a) The uncanny advantage of using androids in social and cognitive science research. Interact Stud 7(3):297–337. doi: 10.1075/is.7.3.03mac
MacDorman KF, Ishiguro H (2006b) Opening Pandora’s uncanny box: reply to commentaries on the uncanny advantage of using androids in social and cognitive science research. Interact Stud 7(3):361–368. doi: 10.1075/is.7.3.10mac
MacDorman KF, Vasudevan SK, Ho C-C (2009) Does Japan really have robot mania? Comparing attitudes by implicit and explicit measures. AI Soc 23(4):485–510. doi: 10.1007/s00146-008-0181-2
Macrae CN, Bodenhausen GV (2000) Social cognition: thinking categorically about others. Annu Rev Psychol 51(1):93–120. doi: 10.1146/annurev.psych.51.1.93
Mangan BB (2015) The uncanny valley as fringe experience. Interact Stud 16(2):193–199. doi: 10.1075/is.16.2.05man
Mathur MB, Reichling DB (2016) Navigating a social world with robot partners: a quantitative cartography of the uncanny valley. Cognition 146:22–32. doi: 10.1016/j.cognition.2015.09.008
Meah LFS, Moore RK (2014) The uncanny valley: a focus on misaligned cues. In: Beetz M, Johnston B, Williams M-A (eds) Social robotics, LNAI, vol 8755. Springer, Cham, pp 256–265. doi: 10.1007/978-3-319-11973-1_26
Michalowski MP, Sabanovic S, Simmons R (2006) A spatial model of engagement for a social robot. In: Proceedings of the Ninth IEEE International Workshop on Advanced Motion Control. IEEE Press, Piscataway, pp 762–767. doi: 10.1109/AMC.2006.1631755
Misselhorn C (2009) Empathy with inanimate objects and the uncanny valley. Minds Mach 19(3):345–459. doi: 10.1007/s11023-009-9158-2
Mitchell WJ, Szerszen Sr, KA, Lu AS, Schermerhorn PW, Scheutz M, MacDorman KF (2011). A mismatch in the human realism of face and voice produces an uncanny valley. i-Perception, 2(1), 10–12. doi: 10.1068/i0415
Moore RK (2012) A Bayesian explanation of the ‘uncanny valley’ effect and related psychological phenomena. Sci Rep 2(864):1–5. doi: 10.1038/srep00864
Mori M (2012) The uncanny valley. IEEE Robotics and Automation (trans: MacDorman KF, Kageki N) 19(2), 98–100 doi: 10.1109/MRA.2012.2192811 (Original work published in 1970)
Nomura T, Kanda T, Suzuki T, Kato K (2004) Psychology in human-robot communication: an attempt through investigation of negative attitudes and anxiety toward robots. In: Proceedings of the 13th IEEE International Workshop on Robot and Human Interactive Communication. IEEE Press, Piscataway, pp 35–40
Nomura T, Kanda T (2016) Rapport–expectation with a robot scale. Int J Soc Robot (8)1: 21–30. doi: 10.1007/s12369-015-0293-z
Prakash A, Rogers WA (2015) Why some humanoid faces are perceived more positively than others: effects of humanlikeness and task. Int J Soc Robot 7(2):309–0331. doi: 10.1007/s12369-014-0269-4
Pronin E (2007) Perception and misperception of bias in human judgment. Trends Cognit Sci 11(1):37–43. doi: 10.1016/j.tics.2006.11.001
Pronin E, Lin DY, Ross L (2002) The bias blind spot: perceptions of bias in self versus others. Personal Soc Psychol Bull 28(3):369–381. doi: 10.1177/0146167202286008
Ramey CH (2005) The uncanny valley of similarities concerning abortion, baldness, heaps of sand, and humanlike robots. In: Proceedings of the Views of the Uncanny Valley Workshop. IEEE-RAS International Conference on Humanoid Robots. December 5, Tsukuba, pp 8–13
Riek LD, Rabinowitch TC, Chakrabarti B, Robinson P (2009) Empathizing with robots: fellow feeling along the anthropomorphic spectrum. In: Proceedings of the Third International Conference on Affective Computing and Intelligent Interaction and Workshops. Amsterdam, pp 1–6, September 10–12. doi: 10.1109/ACII.2009.5349423
Rosenberg S, Nelson C, Vivekananthan P (1968) A multidimensional approach to the structure of personality impressions. J Personal Soc Psychol 97(4):283–294. doi: 10.1037/h0026086
Rugg G, McGeorge P (1997) The sorting techniques: a tutorial paper on card sorts, picture sorts and item sorts. Expert Syst 12(4):80–93. doi: 10.1111/1468-0394.00045
Seyama J, Nagayama RS (2007) The uncanny valley: the effect of realism on the impression of artificial human faces. Presence 16(4):337–351. doi: 10.1162/pres.16.4.337
ter Hofstede F, Audenaert A, Steenkamp J-BEM, Wedel M (1998) An investigation into the association pattern techniques as a quantitative approach to measuring means-end chains. Int J Res Mark 15(1):37–50. doi: 10.1016/S0167-8116(97)00029-3
Tondu B, Bardou N (2011) A new interpretation of Mori’s uncanny valley for future humanoid robots. Int J Robot Autom 26(3):337–348. doi: 10.2316/Journal.206.2011.3.206-3348
Turkle S (2007) Authenticity in the age of digital companions. Interact Stud 8(3):501–517. doi: 10.1075/is.8.3.11tur
Uekermann F, Herrmann A, Wentzel D, Landwehr JR (2008) The influence of stimulus ambiguity on category and attitude formation. Rev Manag Sci 4(1):33–52. doi: 10.1007/s11846-009-0034-5
van Schuur WH, Kiers HAL (1994) Why factor analysis often is the incorrect model for analyzing bipolar concepts and what model to use instead. Appl Psychol Meas 18(2):97–110. doi: 10.1177/014662169401800201
Vanden Abeele P (1992) A means-end study of dairy consumption motivation. Report for the European Commission, EC Regulation 1000/90–43 ST
Vlachos E, Scharfe H (2015) An open-ended approach to evaluating android faces. In: Proceedings of the 24th IEEE International Symposium on Robot and Human Interactive Communication. IEEE Press, Piscataway, pp 746–751
Walters M, Marcos S, Syrdal DS, Dautenhahn K (2013) An interactive game with a robot: People’s perceptions of robot faces and a gesture-based user interface. In: Proceedings of the Sixth International Conference on Advanced Computer-human Interactions. IARIA Press, Lisbon, Portugal, pp 123–128
Yamada Y, Kawabe T, Ihaya K (2013) Categorization difficulty is associated with negative evaluation in the “uncanny valley” phenomenon. Jpn Psychol Res 55(1):20–32. doi: 10.1111/j.1468-5884.2012.00538.x