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AI-generated Images: Investigating the Aesthetic, Educational, and the Socio-technical Impact of Synthography

Project
The proposed research aims to explore the epistemological, aesthetic, socio-semiotic, technical and
educational implications of "synthographies," a term referring to images generated through Text-toImage (TTI) technologies such as DALL·E and Stable Diffusion. Conducted by an interdisciplinary
team, this project will delve into the theoretical premises of AI-generated images and the
consequences of the transition from past methods of image creation to generative AI. This study will
examine the hybrid nature of AI-generated images, which blend autographic and allographic
elements, analyzing their impact on visual literacy. In particular, it will focus on the ways
synthography accelerates the erosion of the documental value of images thereby undercutting
authenticity and reliability of visual media, and raising questions regarding artistic authorship and the
artistic value of AI practices.
- What comprehensive theoretical framework can be established to define and understand AIgenerated images?
- How does the epistemological shift driven by TTI technologies transform the creation and
perception of images?
- How do TTI technologies influence the erosion of the documental value of images?
- What are the implications of integrating TTI technologies into education for enhancing visual
literacy?
- What are the potential technological advancements, socio-cultural implications, and limitations of
current TTI tools?
- How do synthographies impact global visual culture?
With the advent of advanced AI technologies, the process of image creation is undergoing a
profound transformation. The launch of DALL·E by OpenAI in January 2021 marked a significant
milestone, allowing users to create images from textual descriptions. This capability has sparked
extensive debate and reflection on the nature of these new forms of imagery. This project aims to
provide the theoretical and practical framework for understanding the aesthetic, educational, sociosemiotic, and technical implications of synthography, images generated through TTI. The main
challenge is to explicate how AI-generated images influence traditional notions of authorship,
creativity, and the documental value of images. This challenge will be addressed by taking an
interdisciplinary approach, combining resources and methods from aesthetics (art theory, visual
culture), education (curriculum studies, digital literacy), and engineering (AI technology, image
analysis). Current studies focus on the technological capabilities of TTI. By contrast, this project
broadens the investigating and refocuses on the subjective reception of AI-generated images and its
social, cognitive and educational impact, thereby covering a significant lacuna. Attention to the
subjective, social and cognitive implications of AI-images is expected to highlight under-explored
resources for enhancing visual literacy, fostering creative expression, and developing educational
frameworks that integrate AI technologies effectively.
  • Overview
  • Skills
  • Research Outputs

Overview

Contributor (4)

MANERA LORENZO   Scientific Manager  
MONTANARI FEDERICO   Participant  
PUGNAGHI Antonella   Participant  
SANGINETO Enver   Participant  

Representatives

MARIN EMANUELA   Administrative  

Leading department

Department of Education and Humanities   Principale  

Term type

FAR 2024 Progetti interdisciplinari - Linea UNIMORE

Financier

Università degli Studi di MODENA e REGGIO EMILIA
Funding Organization

Partner

Università degli Studi di MODENA e REGGIO EMILIA

Total Contribution (assigned) University (EUR)

60,000€

Date/time interval

December 2, 2024 - December 1, 2026

Project duration

24 months

Skills

Concepts (3)


SH5_8 - Metaphysics, philosophical anthropology; aesthetics - (2024)

Goal 4: Quality education

Settore PHIL-04/A - Estetica

Research Outputs

Research outputs (6)

Deepfakes as Image-ideograms. From Realism to Symbolic Currency 
EMERGINGSERIES JOURNAL
2025
Academic Article
Open Access
From the represenationalist stance to conceptual blending in AI-generated images 
ITINERA
2025
Academic Article
Open Access
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Text-to-image technologies. The Aesthetic implications of AI-generated images. 
ITINERA
2024
Academic Article
Open Access
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Postfazione 
LUCA SOSSELLA
2026
Chapter
Synthographies in the Classroom. Enhancing Visual Literacy with AI in ECEC and Primary Education 
WILEY
2025
Chapter
SYNTHOGRAPHIES. THE AESTHETIC AND EDUCATIONAL CHALLENGES POSED BY AI GENERATED IMAGES 
ASSOCIAZIONE “PER SCUOLA DEMOCRATICA”
2025
Conference Paper
Open Access
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