Humans versus AI: whether and why we prefer human-created compared to AI-created artwork

[1]  Robert C. Seamans,et al.  Art-ificial Intelligence: The Effect of AI Disclosure on Evaluations of Creative Content , 2023, SSRN Electronic Journal.

[2]  Emily S. Cross,et al.  The computer, A choreographer? Aesthetic responses to randomly-generated dance choreography by a computer , 2022, Heliyon.

[3]  A. Chatterjee.  Art in an age of artificial intelligence , 2022, Frontiers in Psychology.

[4]  Amy M. Belfi,et al.  AI composer bias: Listeners like music less when they think it was composed by an AI. , 2022, Journal of experimental psychology. Applied.

[5]  F. Babiloni,et al.  Investigating the negative bias towards artificial intelligence: Effects of prior assignment of AI-authorship on the aesthetic appreciation of abstract paintings , 2022, Comput. Hum. Behav..

[6]  A. Schepman,et al.  The General Attitudes towards Artificial Intelligence Scale (GAAIS): Confirmatory Validation and Associations with Personality, Corporate Distrust, and General Trust , 2022, Int. J. Hum. Comput. Interact..

[7]  Diyi Yang,et al.  Will AI Console Me when I Lose my Pet? Understanding Perceptions of AI-Mediated Email Writing , 2022, CHI.

[8]  Simone Natale,et al.  The Lovelace effect: Perceptions of creativity in machines , 2022, New Media & Society.

[9]  Emily S. Cross,et al.  Value attributed to text-based archives generated by artificial intelligence , 2022, Royal Society Open Science.

[10]  Katrin Fischer,et al.  Human, I wrote a song for you: An experiment testing the influence of machines' attributes on the AI-composed music evaluation , 2022, Comput. Hum. Behav..

[11]  J. Devin McAuley,et al.  What Drives Narrative Engagement With Music? , 2021, Music Perception.

[12]  Elz.e Sigut.e Mikalonyt.e,et al.  Can Artificial Intelligence Make Art? , 2021, SSRN Electronic Journal.

[13]  Harsha Gangadharbatla.  The Role of AI Attribution Knowledge in the Evaluation of Artwork , 2021, Empirical Studies of the Arts.

[14]  Yi Mou,et al.  Using Machine Learning to Learn Machines: A Cross-Cultural Study of Users’ Responses to Machine-Generated Artworks , 2020, Journal of Broadcasting & Electronic Media.

[15]  Nils Köbis,et al.  Artificial intelligence versus Maya Angelou: Experimental evidence that people cannot differentiate AI-generated from human-written poetry , 2020, Comput. Hum. Behav..

[16]  Khalil Israfilzade.  WHAT S IN A NAME EXPERIMENT ON THE AESTHETIC JUDGMENTS OF ART PRODUCED BY ARTIFICIAL INTELLIGENCE , 2020 .

[17]  Yi Mou,et al.  Investigating American and Chinese Subjects' explicit and implicit perceptions of AI-Generated artistic work , 2020, Comput. Hum. Behav..

[18]  A. Schepman,et al.  Initial validation of the general attitudes towards Artificial Intelligence Scale , 2020, Computers in Human Behavior Reports.

[19]  J. Devin McAuley,et al.  What the music said: narrative listening across cultures , 2019, Palgrave Communications.

[20]  M. Hogg,et al.  Liking for abstract and representational art: National identity as an art appreciation heuristic. , 2019 .

[21]  Joo-Wha Hong,et al.  Artificial Intelligence, Artists, and Art , 2019, ACM Trans. Multim. Comput. Commun. Appl..

[22]  Jonathan A. Fugelsang,et al.  Bullshit Makes the Art Grow Profounder , 2019, SSRN Electronic Journal.

[23]  The Cambridge Handbook of Creativity , 2019 .

[24]  Ahmed Elgammal,et al.  Art, Creativity, and the Potential of Artificial Intelligence , 2019, Arts.

[25]  M. Karwowski,et al.  Exploring creative mindsets: Variable and person-centered approaches. , 2019, Psychology of Aesthetics, Creativity, and the Arts.

[26]  Teresa M. Amabile,et al.  ? + ? = creativity. , 2018, Public health nursing.

[27]  J. Wagemans,et al.  Putting the art in artificial: Aesthetic responses to computer-generated art. , 2017 .

[28]  A. Sherman,et al.  What Is Art Good For? The Socio-Epistemic Value of Art , 2017, Front. Hum. Neurosci..

[29]  H. Leder,et al.  Move me, astonish me… delight my eyes and brain: The Vienna Integrated Model of top-down and bottom-up processes in Art Perception (VIMAP) and corresponding affective, evaluative, and neurophysiological correlates. , 2017, Physics of life reviews.

[30]  Duane E. Lundy,et al.  It’s Tough To Be a Critic , 2017 .

[31]  Marinela Rusu.  2. Empathy and Communication through Art , 2017 .

[32]  Richard W. Hass,et al.  Disentangling creative mindsets from creative self-efficacy and creative identity: Do people hold fixed and growth theories of creativity , 2016 .

[33]  Linda Krug,et al.  Toronto Empathy Questionnaire , 2016 .

[34]  A. Chatterjee,et al.  Annals of the New York Academy of Sciences Neuroscience of Aesthetics , 2022 .

[35]  Jonathan A. Fugelsang,et al.  On the reception and detection of pseudo-profound bullshit , 2015, Judgment and Decision Making.

[36]  Jan R. Landwehr,et al.  A Dual-Process Perspective on Fluency-Based Aesthetics , 2015, Personality and social psychology review : an official journal of the Society for Personality and Social Psychology, Inc.

[37]  Amy Ione,et al.  The Aesthetic Brain: How We Evolved to Desire Beauty and Enjoy Art , 2015, Leonardo.

[38]  D. Berlyne.  Conflict, arousal, and curiosity , 2014 .

[39]  M. Freeman.  Transmedia Critical| Advertising the Yellow Brick Road: Historicizing the Industrial Emergence of Transmedia Storytelling , 2014 .

[40]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[41]  R. McCrae,et al.  Openness to Experience , 2014, Encyclopedia of Evolutionary Psychological Science.

[42]  Wolfgang Tschacher,et al.  Is This Art? An Experimental Study on Visitors’ Judgement of Contemporary Art , 2014 .

[43]  Guillermo Campitelli,et al.  Does the cognitive reflection test measure cognitive reflection? A mathematical modeling approach , 2014, Memory & cognition.

[44]  Keith E. Stanovich,et al.  Assessing miserly information processing: An expansion of the Cognitive Reflection Test , 2014 .

[45]  M. Karwowski.  Creative mindsets: Measurement, correlates, consequences. , 2014 .

[46]  Scott Barry Kaufman,et al.  Opening up Openness to Experience: A Four-Factor Model and Relations to Creative Achievement in the Arts and Sciences. , 2013 .

[47]  Karen B. Schloss,et al.  Visual aesthetics and human preference. , 2013, Annual review of psychology.

[48]  Paul Bloom,et al.  Art and authenticity: the importance of originals in judgments of value. , 2012, Journal of experimental psychology. General.

[49]  Joe Pulizzi,et al.  The Rise of Storytelling as the New Marketing , 2012 .

[50]  G. Carrus,et al.  The Automatic Aesthetic Evaluation of Different Art and Architectural Styles , 2011 .

[51]  Elizabeth-Anne L. Wilson,et al.  Affect and Artificial Intelligence , 2010 .

[52]  Oliver J. Hulme,et al.  Modulation of aesthetic value by semantic context: An fMRI study , 2009, NeuroImage.

[53]  R. N. Spreng,et al.  The Toronto Empathy Questionnaire: Scale Development and Initial Validation of a Factor-Analytic Solution to Multiple Empathy Measures , 2009, Journal of personality assessment.

[54]  J. O'Doherty,et al.  Marketing actions can modulate neural representations of experienced pleasantness , 2008, Proceedings of the National Academy of Sciences.

[55]  V. Gallese,et al.  Motion, emotion and empathy in esthetic experience , 2007, Trends in Cognitive Sciences.

[56]  Robert R. McCrae,et al.  Aesthetic Chills as a Universal Marker of Openness to Experience , 2007 .

[57]  P. Silvia.  Cognitive Appraisals and Interest in Visual Art: Exploring an Appraisal Theory of Aesthetic Emotions , 2005 .

[58]  H. Leder,et al.  A model of aesthetic appreciation and aesthetic judgments. , 2004, British journal of psychology.

[59]  Samuel M. McClure,et al.  Neural Correlates of Behavioral Preference for Culturally Familiar Drinks , 2004, Neuron.

[60]  Ira J. Roseman,et al.  Appraisals cause experienced emotions: Experimental evidence , 2004 .

[61]  Gregory J. Feist,et al.  Openness to Experience, Non-Conformity, and the Preference for Abstract Art , 2004 .

[62]  Carol A. Mockros.  The development of aesthetic experience and judgement , 1993 .

[63]  N. Kettlewell,et al.  The Effect of Subject Matter and Degree of Realism on Aesthetic Preferences for Paintings , 1990 .

[64]  G. Cupchik,et al.  Individual differences as predictors of preference in visual art , 1985 .

[65]  T. M. Amabile.  Social psychology of creativity: A consensual assessment technique. , 1982 .

[66]  D. Berlyne,et al.  The perception of collative properties in visual stimuli. , 1979, Scandinavian journal of psychology.

[67]  M. Bornstein.  Qualities of color vision in infancy. , 1975, Journal of experimental child psychology.

[68]  D. Berlyne.  Behaviourism? Cognitive theory? Humanistic psychology? To Hull with them all. , 1975 .

[69]  D. Berlyne.  Aesthetics and psychobiology , 1975 .

[70]  R. H. Knapp,et al.  Preferences for abstract and representational art. , 1963, The Journal of social psychology.

[71]  J. D. Trainor-McKinnon.  Brain, Beauty, and Art: Essays Bringing Neuroaesthetics into Focus, edited by Anjan Chatterjee and Eileen R. Cardillo , 2023, Teaching Philosophy.

[72]  J. Mueller,et al.  Consensual Assessment , 2020, Encyclopedia of Creativity.

[73]  Karl K. Jeffries,et al.  A scattered CAT: A critical evaluation of the consensual assessment technique for creativity research. , 2019, Psychology of Aesthetics, Creativity, and the Arts.

[74]  J. Bittner,et al.  Cognitive Research : Principles and Implications , 2017 .

[75]  Roger E. Beaty,et al.  Openness to experience and awe in response to nature and music: Personality and profound aesthetic experiences. , 2015 .

[76]  D. Moffat,et al.  An investigation into people’s bias against computational creativity in music composition , 2006 .

[77]  Justin Kruger,et al.  The Effort Heuristic , 2004 .

[78]  Hilde van der Togt,et al.  Publisher's Note , 2003, J. Netw. Comput. Appl..

[79]  C. Douglas.  Painting by Numbers: Komar and Melamid's Scientific Guide to Art. Ed. JoAnn Wypijewski. New York: Farrar Straus Giroux, 1997. 205 pp. Appendix. Plates. $50.00, hard bound. , 2000 .

[80]  Vitaly Komar,et al.  Painting by numbers : Komar and Melamid's scientific guide to art , 1999 .

[81]  Ellen Winner,et al.  Perceiving What Paintings Express , 1984 .

[82]  Ellen Winner,et al.  Invented Worlds: The Psychology of the Arts , 1982 .

[83]  S. Frederick.  Journal of Economic Perspectives—Volume 19, Number 4—Fall 2005—Pages 25–42 Cognitive Reflection and Decision Making , 2022 .

[84]  Harun Zulić.  HOW AI CAN CHANGE/ IMPROVE/INFLUENCE MUSIC COMPOSITION, PERFORMANCE AND EDUCATION: THREE CASE STUDIES , 2022 .