Page 441 - Deep Learning

424 Notes to Pages 146–153

Weber and Perkins (1992). I do not know of any study of the tendency to run over
deadlines. The bad fit between creatives and bureaucratic organizations is prover-
bial and supported by case studies of innovations in business; see, e.g., Smith and
Alexander (1999).
30. See Wiley (1998) for a laboratory demonstration of this.
31. See Chapter 3, Note 17, regarding the relation between intelligence and
creativity.
32. Barron and Harrington (1981), Feist (1999) and Selby, Shaw and Houtz (2005)
have reviewed the relation between personality and creativity. Dacey and Lennon
(1998, Chap. 5), list 10 character traits of creative individuals that have support
in research: tolerance of ambiguity, “stimulus freedom” (the ability to restructure
one’s perceptions), “functional freedom” (the ability to use common objects in
new ways), flexibility, risk taking, preference for disorder, delay of gratification,
freedom from sex-role stereotyping, perseverance and courage. Other authors
have proposed related but somewhat different lists (Wolfradt & Pretz, 2001).
Interestingly, Csikszentmihalyi (1997, Chap. 3), has argued that it is a mistake
to look for extreme values on such dimensions. Instead, creative individuals are
characterized by the fact that they combine opposites. They combine high levels
of energy with habits of quietude and rest, (moderately) high IQ with naivité,
playfulness with discipline, fantasy with realism, extroversion with introversion,
humility with pride, the masculine with the feminine, rebelliousness with mas-
tery of tradition, passionate commitment with objectivity and suffering with joy.
33. Caprara and Cervone (2000) and Cervone (2004, 2005).
34. In 1979, J. W. Getzels could accurately complain that “there is hardly any system-
atic work on problem finding” (Getzels, 1979, p. 167). A decade and a half later,
Runco (1994) published a series of papers on the topic. The concept has since
become accepted as a crucial component of creative work (Jay & Perkins, 1997).
There is still no consensus of what makes a good problem finder, but the ques-
tion is the subject of research all over the world; see, e.g., Lee and Cho (2007),
Ramirez (2002) and Suwa (2003).
35. Wild (1992, pp. 123–124).
36. See Chapter 3, Note 35.
37. John-Steiner (2000). The literature on collective cognition is huge. A particularly
relevant strand of work consists of so-called network studies; see, e.g., Cowan
and Jonard (2003), Schilling and Phelps (2007) and Uzzi and Spiro (2005).
38. Baldwin (2001).
39. Broude (1994).
40. Crane (2002).
41. Buderi (1996).
42. Examples abound in the history of technology. The need for a valve that delivers
air at the right pressure from moment to moment during diving has already been
mentioned (Cousteau, 1953, pp. 8–20). Finding the right filament for the elec-
trical lightbulb held up Edison’s development of a system for electrical light in
homes for years (Baldwin, 2001).
43. Rhodes (1989).
44. Margolis (1987, 1993).