Humans Versus AI: Whether and Why We Prefer Human-Created Compared to AI-Created Artwork

With the recent proliferation of advanced artifcial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human-compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a “Human-created” or “AI-created” label to paintings actually created by AI, and then assessed participants’ judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labelled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Efort, and Time to create) intended to elucidate why people more-positively appraise Human-labelled artworks. The main fndings from Study 1 were replicated, with narrativity (Story) and perceived efort behind artworks (Efort) moderating the label efects (“Human-created” vs. “AI-created”), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes toward AI moderated label efects for more-communicative judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks relative to purportedly humancreated artwork, and suggest that knowledge of human engagement in the artistic process contributes positively to appraisals of art

Concert recording 2019-11-20

[Track 1]. Quatour pour saxophones. I. Gaiete Villageoise / F. & M. Jeanjean -- [Track 2]. Memory from Nepomuk\u27s dances / Marcelo Zarvos -- [Track 3]. Quatour pour saxophones. II. Doloroso III. Spirituoso / P.M. Dubois -- [Track 4]. Danza 2016 / Lucky Chops -- [Track 5]. Howler back / Zack Browning -- [Track 6]. Dusk / Steven Bryant -- [Track 7]. Oileain reel / Craig Richards

Quantitative differential proteomics of yeast extracellular matrix: there is more to it than meets the eye

Background: Saccharomyces cerevisiae multicellular communities are sustained by a scaffolding extracellular matrix, which provides spatial organization, and nutrient and water availability, and ensures group survival. According to this tissue-like biology, the yeast extracellular matrix (yECM) is analogous to the higher Eukaryotes counterpart for its polysaccharide and proteinaceous nature. Few works focused on yeast biofilms, identifying the flocculin Flo11 and several members of the HSP70 in the extracellular space. Molecular composition of the yECM, is therefore mostly unknown. The homologue of yeast Gup1 protein in high Eukaryotes (HHATL) acts as a regulator of Hedgehog signal secretion, therefore interfering in morphogenesis and cell-cell communication through the ECM, which mediates but is also regulated by this signalling pathway. In yeast, the deletion of GUP1 was associated with a vast number of diverse phenotypes including the cellular differentiation that accompanies biofilm formation. Methods: S. cerevisiae W303-1A wt strain and gup1Δ mutant were used as previously described to generate biofilmlike mats in YPDa from which the yECM proteome was extracted. The proteome from extracellular medium from batch liquid growing cultures was used as control for yECM-only secreted proteins. Proteins were separated by SDS-PAGE and 2DE. Identification was performed by HPLC, LC-MS/MS and MALDI-TOF/TOF. The protein expression comparison between the two strains was done by DIGE, and analysed by DeCyder Extended Data Analysis that included Principal Component Analysis and Hierarchical Cluster Analysis. Results: The proteome of S. cerevisiae yECM from biofilm-like mats was purified and analysed by Nano LC-MS/MS, 2D Difference Gel Electrophoresis (DIGE), and MALDI-TOF/TOF. Two strains were compared, wild type and the mutant defective in GUP1. As controls for the identification of the yECM-only proteins, the proteome from liquid batch cultures was also identified. Proteins were grouped into distinct functional classes, mostly Metabolism, Protein Fate/Remodelling and Cell Rescue and Defence mechanisms, standing out the presence of heat shock chaperones, metalloproteinases, broad signalling cross-talkers and other putative signalling proteins. The data has been deposited to the ProteomeXchange with identifier PXD001133.Conclusions: yECM, as the mammalian counterpart, emerges as highly proteinaceous. As in higher Eukaryotes ECM, numerous proteins that could allow dynamic remodelling, and signalling events to occur in/and via yECM were identified. Importantly, large sets of enzymes encompassing full antagonistic metabolic pathways, suggest that mats develop into two metabolically distinct populations, suggesting that either extensive moonlighting or actual metabolism occurs extracellularly. The gup1Δ showed abnormally loose ECM texture. Accordingly, the correspondent differences in proteome unveiled acetic and citric acid producing enzymes as putative players in structural integrity maintenance.This work was funded by the Marie Curie Initial Training Network GLYCOPHARM (PITN-GA-2012-317297), and by national funds from FCT I.P. through the strategic funding UID/BIA/04050/2013. Fábio Faria-Oliveira was supported by a PhD scholarship (SFRH/BD/45368/2008) from FCT (Fundação para a Ciência e a Tecnologia). We thank David Caceres and Montserrat MartinezGomariz from the Unidad de Proteómica, Universidad Complutense de Madrid – Parque Científico de Madrid, Spain for excellent technical assistance in the successful implementation of all proteomics procedures including peptide identification, and Joana Tulha from the CBMA, Universidade do Minho, Portugal, for helping with the SDS-PAGE experiments, and the tedious and laborious ECM extraction procedures. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium, via the PRIDE partner repository, with the dataset identifier PXD001133. We would like to thank the PRIDE team for all the help and support during the submission process.info:eu-repo/semantics/publishedVersio

Depression and Emotion Regulation Strategy Use Moderate Age-Related Attentional Positivity Bias

Data and code that was used for all analyses reported in the manuscript

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

With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human-compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a "Human-created" or "AI-created" label to paintings actually created by AI, and then assessed participants' judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labelled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate why people more-positively appraise Human-labelled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects ("Human-created" vs. "AI-created"), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes toward AI moderated label effects for more-communicative judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks relative to purportedly human-created artwork, and suggest that knowledge of human engagement in the artistic process contributes positively to appraisals of art

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

Abstract With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human-compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a “Human-created” or “AI-created” label to paintings actually created by AI, and then assessed participants’ judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labelled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate why people more-positively appraise Human-labelled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects (“Human-created” vs. “AI-created”), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes toward AI moderated label effects for more-communicative judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks relative to purportedly human-created artwork, and suggest that knowledge of human engagement in the artistic process contributes positively to appraisals of art

Does Human Creativity Matter in the Age of Generative AI?

As artificial intelligence (AI) continues to evolve, particularly in the context of generative art, a critical question emerges about the future role of human creativity: In the age of generative AI, does individual creative ability still matter? Here, we explored this question via an online, pre-registered study involving 375 participants who completed gold-standard divergent-thinking tasks and generated semantic wordsets for AI-art creation using an AI-art generator. We generated the resultant images from these participant-produced wordsets through DALL-E, and a group of trained raters independently assessed the images for general creativity. Findings revealed widespread positive correlations among the creativity tasks. Specifically, the semantic diversity of wordsets and performance on the gold-standard creativity tasks served as significant positive predictors for the creativity of the AI-generated images, indicating that individuals possessing greater divergent-thinking capabilities, and who generated more-creative word prompts for an art generator, produced more-creative AI-generated artwork. These results suggest that, despite the democratizing effect of AI-art generation, human creativity remains an important component in directing AI-produced creative outcomes like visual art. The implications of these findings are discussed in the context of creative industries and the science of creativity

Humans vs. AI: Whether and why we prefer human-created compared to AI-created artwork

With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human- compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a “Human-created” or “AI-created” label to paintings actually created by AI, and then assessed participants’ judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labeled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate why people more-positively appraise human-labeled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects (“Human-created” vs. “AI-created”), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes towards AI moderated label effects for more-abstract judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks, which suggests that human engagement in the artistic process contributes positively to our appraisals of art and that, on this basis, AI may not replace human creativity

Size‐Induced Ferroelectricity in Antiferroelectric Oxide Membranes

Despite extensive studies on size effects in ferroelectrics, how structures and properties evolve in antiferroelectrics with reduced dimensions still remains elusive. Given the enormous potential of utilizing antiferroelectrics for high-energy-density storage applications, understanding their size effects will provide key information for optimizing device performances at small scales. Here, the fundamental intrinsic size dependence of antiferroelectricity in lead-free NaNbO3 membranes is investigated. Via a wide range of experimental and theoretical approaches, an intriguing antiferroelectric-to-ferroelectric transition upon reducing membrane thickness is probed. This size effect leads to a ferroelectric single-phase below 40 nm, as well as a mixed-phase state with ferroelectric and antiferroelectric orders coexisting above this critical thickness. Furthermore, it is shown that the antiferroelectric and ferroelectric orders are electrically switchable. First-principle calculations further reveal that the observed transition is driven by the structural distortion arising from the membrane surface. This work provides direct experimental evidence for intrinsic size-driven scaling in antiferroelectrics and demonstrates enormous potential of utilizing size effects to drive emergent properties in environmentally benign lead-free oxides with the membrane platform