Araştırma Makalesi
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Geleneksel Latin kaligrafi ve tipografi sanatının yapay zekâ çağındaki dönüşümü: Estetik, uygulama ve gelecek perspektifleri

Yıl 2025, Cilt: 15 Sayı: 4, 2014 - 2038, 30.12.2025
https://doi.org/10.30783/nevsosbilen.1752027

Öz

Öz: Bu çalışma, yapay zekâ teknolojilerinin geleneksel Latin kaligrafi ve tipografi disiplinleri üzerindeki üç boyutlu etkisini (estetik, metodolojik ve gelecek perspektifleri) sistematik olarak incelemeyi amaçlamaktadır. Yapay zekâ destekli dijital tipografi ve Latin kaligrafisi arasındaki hibrit yaratıcılık süreçlerini, algoritmik estetik perspektifiyle analiz eden bu araştırma, nitel yöntemle yürütülmüştür. Çalışmada, 15. yüzyıldan günümüze uzanan tarihsel örnekler ile yapay zekâ destekli tasarım araçları (Calligrapher AI, Fontjoy, Adobe Firefly) tarafından üretilen 150+ dijital eser, karşılaştırmalı içerik analizine tabi tutulmuştur. Araştırma bulguları üç temel sonucu ortaya koymaktadır: Birincisi, algoritmik tasarımın hız ve çeşitlilik avantajlarına rağmen, insan elinin yaratıcı dokunuşunu yansıtmada sınırlı kaldığı; özellikle harf anatomisi ve kompozisyonel dengede estetik kayıplar gözlendiği tespit edilmiştir (Elgammal et al., 2017). İkincisi, yapay zekâ destekli üretim süreçlerinin, geleneksel tekniklerin demokratikleşmesini sağlarken, kültürel bağlam aktarımında yetersiz kaldığı gözlemlenmiştir (Davis et al., 2021). Üçüncüsü, metaverse ve NFT uygulamalarında kaligrafinin yeni bir dijital değer kazanmasına rağmen, orijinallik ve etik sorunların belirginleştiği ortaya çıkmıştır (Lupton, 2022). Çalışma, teknoloji ve geleneğin sinerjik bütünleşmesi için kritik bir kuramsal çerçeve önermektedir: İnsan-yapay zekâ işbirliğine dayalı "hibrit yaratıcılık" modeli. Bu model, estetik değerlerin korunması ile teknolojik yeniliğin entegrasyonunu dengelemeyi hedeflemektedir.

Etik Beyan

Bu araştırmanın hazırlanması sürecinde bilimsel etik ilkelere titizlikle uyulmuştur. Çalışmada kullanılan tüm veri, belge ve materyaller akademik dürüstlük çerçevesinde elde edilmiş olup, herhangi bir şekilde tahrif edilmemiş veya çarpıtılmamıştır.

Kaynakça

  • Adobe Inc. (2021). Zapf Intelligence project report (Corporate report). Adobe Creative Cloud.
  • Ambrose, G., & Harris, P. (2011). The fundamentals of typography (2nd ed.). AVA Publishing.
  • Arielli, E. (2022). AI-aesthetics and the anthropocentric myth of creativity. NODES, (1), 19–. https://philarchive.org/rec/ARIAAT-6
  • Boden, M. A. (2016). AI: Its nature and future. Oxford University Press.
  • Boden, M. A. (2018). Artificial intelligence and creativity: A contradiction in terms? In R. W. Clowes (Ed.), The Routledge handbook of philosophy of imagination (pp. 381–395). Routledge.
  • Boden, M. A. (2023). The creative mind: Myths and mechanisms (3rd ed.). Routledge.
  • Bringhurst, R. (2013). The elements of typographic style (4th ed.). Hartley & Marks Publishers.
  • Brown, T. (1990). Design thinking in practice. Harvard Design Review, 7(3), 12–.
  • Carter, R., Day, B., & Meggs, P. B. (2011). Typographic design: Form and communication (5th ed.). Wiley.
  • Choi, H., & Kim, S. (2019). Digital creativity and traditional arts: A cross-temporal study. Visual Communication Quarterly, 26(4), 214–.
  • Crouwel, W. (2012). Modernism in typography. Amsterdam University Press.
  • Davis, M., García, R., & Aranda, J. (2021). AI and the future of design: Artistic agency in algorithmic systems. Design Issues, 37(2), 47–. https://doi.org/10.1162/desi_a_00648
  • Demir, F. (2020). Modern Türkiye'de yazı sanatı ve eğitim politikaları. Eğitim ve Sanat Dergisi, 8(2), 120– . Drogin, M. (1980). Medieval calligraphy: Its history and technique. Dover Publications.
  • Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). CAN: Creative adversarial networks. In Proceedings of the International Conference on Computational Creativity (ICCC) (pp. 96–103).
  • Goodfellow, I., Bengio, Y., & Courville, A. (2012). Deep learning foundations. MIT Press.
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
  • Johnson, P. (2019). AI and the craft of design. Journal of Emerging Technologies, 6(2), 112–
  • Kara, A. (2017). Kaligrafi ve tipografi: Kültürel bağlamda bir inceleme. Sanat Tarihi Dergisi, 22(1), 45–.
  • Kim, J. (2020). Digital handwriting analysis and AI. Journal of Computational Design, 15(3), 34–.
  • Kim, J., & Park, S. (2023). Handwriting vs algorithm: Aesthetics of humanized design. International Journal of Design, 17(1), 77–.
  • Kipdemir, S., & Yılmaz, İ. (2022). Kaligrafi eğitimi ve grafik tasarıma etkisi. International Academic Social Resources Journal, 7(34), 103–. https://doi.org/10.29228/ASRJOURNAL.57384
  • Korkmaz, S. (2016). Kaligrafi ve dijital dönüşüm. Güzel Sanatlar Fakültesi Dergisi, 14(3), 89–.
  • Kumar, R., & Patel, A. (2020). Machine aesthetics and generative art. Journal of Digital Art Research, 5(2), 34–.
  • Lee, M. (2022). Reinforcement learning in aesthetic decision-making. AI Design Journal, 8(1), 56–.
  • Lupton, E. (2010). Thinking with type: A critical guide for designers, writers, editors, & students. Princeton Architectural Press.
  • Lupton, E. (2014). Type on screen: A critical guide for designers, writers, developers, and students. Princeton Architectural Press.
  • Lupton, E. (2017). Thinking with type (2nd rev. ed.). Princeton Architectural Press.
  • Manovich, L. (2013). Software takes command. Bloomsbury Academic.
  • Manovich, L., & Arielli, E. (2024). Artificial aesthetics. Manovich.net. https://manovich.net/index.php/projects/artificial-aesthetic
  • Martinez, D., & Lee, M. (2023). The poetics of machine v. Journal of Digital Humanities, 11(1), 33–.
  • McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, authenticity, authorship: Recombinant creativity in computational art and music. In Proceedings of the Tenth International Conference on Computational Creativity (ICCC 2019) (pp. 217–224).
  • Mediavilla, C. (2016). Calligraphy: From calligraphy to abstract painting. Princeton University Press.
  • Meggs, P. B., & Purvis, A. W. (2016). Meggs' history of graphic design (6th ed.). Wiley.
  • Müller-Brockmann, J. (1981). Grid systems in graphic design (4th ed.). Niggli.
  • Öztürk, M. (2018). Osmanlı'dan Cumhuriyet'e yazı sanatı ve Harf Devrimi. Ankara Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(2), 45–.
  • Wang, D., & Gupta, R. (2022). AI and design cognition: Trends and critiques. Journal of Creative Technologies, 14(2), 99–.
  • Wang, R. (2021). New perspectives on generative aesthetics. Media Arts Review, 15(1), 42–.
  • Zeki, S. (1999). Inner vision: An exploration of art and the brain. Oxford University Press.

Yıl 2025, Cilt: 15 Sayı: 4, 2014 - 2038, 30.12.2025
https://doi.org/10.30783/nevsosbilen.1752027

Öz

Kaynakça

  • Adobe Inc. (2021). Zapf Intelligence project report (Corporate report). Adobe Creative Cloud.
  • Ambrose, G., & Harris, P. (2011). The fundamentals of typography (2nd ed.). AVA Publishing.
  • Arielli, E. (2022). AI-aesthetics and the anthropocentric myth of creativity. NODES, (1), 19–. https://philarchive.org/rec/ARIAAT-6
  • Boden, M. A. (2016). AI: Its nature and future. Oxford University Press.
  • Boden, M. A. (2018). Artificial intelligence and creativity: A contradiction in terms? In R. W. Clowes (Ed.), The Routledge handbook of philosophy of imagination (pp. 381–395). Routledge.
  • Boden, M. A. (2023). The creative mind: Myths and mechanisms (3rd ed.). Routledge.
  • Bringhurst, R. (2013). The elements of typographic style (4th ed.). Hartley & Marks Publishers.
  • Brown, T. (1990). Design thinking in practice. Harvard Design Review, 7(3), 12–.
  • Carter, R., Day, B., & Meggs, P. B. (2011). Typographic design: Form and communication (5th ed.). Wiley.
  • Choi, H., & Kim, S. (2019). Digital creativity and traditional arts: A cross-temporal study. Visual Communication Quarterly, 26(4), 214–.
  • Crouwel, W. (2012). Modernism in typography. Amsterdam University Press.
  • Davis, M., García, R., & Aranda, J. (2021). AI and the future of design: Artistic agency in algorithmic systems. Design Issues, 37(2), 47–. https://doi.org/10.1162/desi_a_00648
  • Demir, F. (2020). Modern Türkiye'de yazı sanatı ve eğitim politikaları. Eğitim ve Sanat Dergisi, 8(2), 120– . Drogin, M. (1980). Medieval calligraphy: Its history and technique. Dover Publications.
  • Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). CAN: Creative adversarial networks. In Proceedings of the International Conference on Computational Creativity (ICCC) (pp. 96–103).
  • Goodfellow, I., Bengio, Y., & Courville, A. (2012). Deep learning foundations. MIT Press.
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
  • Johnson, P. (2019). AI and the craft of design. Journal of Emerging Technologies, 6(2), 112–
  • Kara, A. (2017). Kaligrafi ve tipografi: Kültürel bağlamda bir inceleme. Sanat Tarihi Dergisi, 22(1), 45–.
  • Kim, J. (2020). Digital handwriting analysis and AI. Journal of Computational Design, 15(3), 34–.
  • Kim, J., & Park, S. (2023). Handwriting vs algorithm: Aesthetics of humanized design. International Journal of Design, 17(1), 77–.
  • Kipdemir, S., & Yılmaz, İ. (2022). Kaligrafi eğitimi ve grafik tasarıma etkisi. International Academic Social Resources Journal, 7(34), 103–. https://doi.org/10.29228/ASRJOURNAL.57384
  • Korkmaz, S. (2016). Kaligrafi ve dijital dönüşüm. Güzel Sanatlar Fakültesi Dergisi, 14(3), 89–.
  • Kumar, R., & Patel, A. (2020). Machine aesthetics and generative art. Journal of Digital Art Research, 5(2), 34–.
  • Lee, M. (2022). Reinforcement learning in aesthetic decision-making. AI Design Journal, 8(1), 56–.
  • Lupton, E. (2010). Thinking with type: A critical guide for designers, writers, editors, & students. Princeton Architectural Press.
  • Lupton, E. (2014). Type on screen: A critical guide for designers, writers, developers, and students. Princeton Architectural Press.
  • Lupton, E. (2017). Thinking with type (2nd rev. ed.). Princeton Architectural Press.
  • Manovich, L. (2013). Software takes command. Bloomsbury Academic.
  • Manovich, L., & Arielli, E. (2024). Artificial aesthetics. Manovich.net. https://manovich.net/index.php/projects/artificial-aesthetic
  • Martinez, D., & Lee, M. (2023). The poetics of machine v. Journal of Digital Humanities, 11(1), 33–.
  • McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, authenticity, authorship: Recombinant creativity in computational art and music. In Proceedings of the Tenth International Conference on Computational Creativity (ICCC 2019) (pp. 217–224).
  • Mediavilla, C. (2016). Calligraphy: From calligraphy to abstract painting. Princeton University Press.
  • Meggs, P. B., & Purvis, A. W. (2016). Meggs' history of graphic design (6th ed.). Wiley.
  • Müller-Brockmann, J. (1981). Grid systems in graphic design (4th ed.). Niggli.
  • Öztürk, M. (2018). Osmanlı'dan Cumhuriyet'e yazı sanatı ve Harf Devrimi. Ankara Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(2), 45–.
  • Wang, D., & Gupta, R. (2022). AI and design cognition: Trends and critiques. Journal of Creative Technologies, 14(2), 99–.
  • Wang, R. (2021). New perspectives on generative aesthetics. Media Arts Review, 15(1), 42–.
  • Zeki, S. (1999). Inner vision: An exploration of art and the brain. Oxford University Press.

The transformation of traditional latin calligraphy and typography art in the age of AI: Aesthetics, practice, and future perspectives

Yıl 2025, Cilt: 15 Sayı: 4, 2014 - 2038, 30.12.2025
https://doi.org/10.30783/nevsosbilen.1752027

Öz

Abstract: This study aims to systematically examine the three-dimensional impact of artificial intelligence technologies on traditional Latin calligraphy and typography disciplines (aesthetic, methodological, and future perspectives). Analyzing the hybrid creative processes between AI-supported digital typography and Latin calligraphy from an algorithmic aesthetic perspective, this research was conducted using qualitative methods. In the study, historical examples spanning from the 15th century to the present day, along with over 150 digital works produced by artificial intelligence-supported design tools (Calligrapher AI, Fontjoy, Adobe Firefly), were subjected to comparative content analysis. The research findings reveal three main results: First, despite the advantages of speed and diversity in algorithmic design, it was found to be limited in reflecting the creative touch of the human hand; in particular, aesthetic losses were observed in letter anatomy and compositional balance (Elgammal et al., 2017). Second, it was observed that AI-supported production processes democratize traditional techniques but fall short in terms of cultural context transfer (Davis et al., 2021). Thirdly, despite calligraphy gaining new digital value in metaverse and NFT applications, issues of originality and ethics have become apparent (Lupton, 2022). The study proposes a critical theoretical framework for the synergistic integration of work, technology, and tradition: a model of “hybrid creativity” based on human-artificial intelligence collaboration. This model aims to balance the preservation of aesthetic values with the integration of technological innovation.

Kaynakça

  • Adobe Inc. (2021). Zapf Intelligence project report (Corporate report). Adobe Creative Cloud.
  • Ambrose, G., & Harris, P. (2011). The fundamentals of typography (2nd ed.). AVA Publishing.
  • Arielli, E. (2022). AI-aesthetics and the anthropocentric myth of creativity. NODES, (1), 19–. https://philarchive.org/rec/ARIAAT-6
  • Boden, M. A. (2016). AI: Its nature and future. Oxford University Press.
  • Boden, M. A. (2018). Artificial intelligence and creativity: A contradiction in terms? In R. W. Clowes (Ed.), The Routledge handbook of philosophy of imagination (pp. 381–395). Routledge.
  • Boden, M. A. (2023). The creative mind: Myths and mechanisms (3rd ed.). Routledge.
  • Bringhurst, R. (2013). The elements of typographic style (4th ed.). Hartley & Marks Publishers.
  • Brown, T. (1990). Design thinking in practice. Harvard Design Review, 7(3), 12–.
  • Carter, R., Day, B., & Meggs, P. B. (2011). Typographic design: Form and communication (5th ed.). Wiley.
  • Choi, H., & Kim, S. (2019). Digital creativity and traditional arts: A cross-temporal study. Visual Communication Quarterly, 26(4), 214–.
  • Crouwel, W. (2012). Modernism in typography. Amsterdam University Press.
  • Davis, M., García, R., & Aranda, J. (2021). AI and the future of design: Artistic agency in algorithmic systems. Design Issues, 37(2), 47–. https://doi.org/10.1162/desi_a_00648
  • Demir, F. (2020). Modern Türkiye'de yazı sanatı ve eğitim politikaları. Eğitim ve Sanat Dergisi, 8(2), 120– . Drogin, M. (1980). Medieval calligraphy: Its history and technique. Dover Publications.
  • Elgammal, A., Liu, B., Elhoseiny, M., & Mazzone, M. (2017). CAN: Creative adversarial networks. In Proceedings of the International Conference on Computational Creativity (ICCC) (pp. 96–103).
  • Goodfellow, I., Bengio, Y., & Courville, A. (2012). Deep learning foundations. MIT Press.
  • Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep learning. MIT Press.
  • Johnson, P. (2019). AI and the craft of design. Journal of Emerging Technologies, 6(2), 112–
  • Kara, A. (2017). Kaligrafi ve tipografi: Kültürel bağlamda bir inceleme. Sanat Tarihi Dergisi, 22(1), 45–.
  • Kim, J. (2020). Digital handwriting analysis and AI. Journal of Computational Design, 15(3), 34–.
  • Kim, J., & Park, S. (2023). Handwriting vs algorithm: Aesthetics of humanized design. International Journal of Design, 17(1), 77–.
  • Kipdemir, S., & Yılmaz, İ. (2022). Kaligrafi eğitimi ve grafik tasarıma etkisi. International Academic Social Resources Journal, 7(34), 103–. https://doi.org/10.29228/ASRJOURNAL.57384
  • Korkmaz, S. (2016). Kaligrafi ve dijital dönüşüm. Güzel Sanatlar Fakültesi Dergisi, 14(3), 89–.
  • Kumar, R., & Patel, A. (2020). Machine aesthetics and generative art. Journal of Digital Art Research, 5(2), 34–.
  • Lee, M. (2022). Reinforcement learning in aesthetic decision-making. AI Design Journal, 8(1), 56–.
  • Lupton, E. (2010). Thinking with type: A critical guide for designers, writers, editors, & students. Princeton Architectural Press.
  • Lupton, E. (2014). Type on screen: A critical guide for designers, writers, developers, and students. Princeton Architectural Press.
  • Lupton, E. (2017). Thinking with type (2nd rev. ed.). Princeton Architectural Press.
  • Manovich, L. (2013). Software takes command. Bloomsbury Academic.
  • Manovich, L., & Arielli, E. (2024). Artificial aesthetics. Manovich.net. https://manovich.net/index.php/projects/artificial-aesthetic
  • Martinez, D., & Lee, M. (2023). The poetics of machine v. Journal of Digital Humanities, 11(1), 33–.
  • McCormack, J., Gifford, T., & Hutchings, P. (2019). Autonomy, authenticity, authorship: Recombinant creativity in computational art and music. In Proceedings of the Tenth International Conference on Computational Creativity (ICCC 2019) (pp. 217–224).
  • Mediavilla, C. (2016). Calligraphy: From calligraphy to abstract painting. Princeton University Press.
  • Meggs, P. B., & Purvis, A. W. (2016). Meggs' history of graphic design (6th ed.). Wiley.
  • Müller-Brockmann, J. (1981). Grid systems in graphic design (4th ed.). Niggli.
  • Öztürk, M. (2018). Osmanlı'dan Cumhuriyet'e yazı sanatı ve Harf Devrimi. Ankara Üniversitesi Sosyal Bilimler Enstitüsü Dergisi, 25(2), 45–.
  • Wang, D., & Gupta, R. (2022). AI and design cognition: Trends and critiques. Journal of Creative Technologies, 14(2), 99–.
  • Wang, R. (2021). New perspectives on generative aesthetics. Media Arts Review, 15(1), 42–.
  • Zeki, S. (1999). Inner vision: An exploration of art and the brain. Oxford University Press.
Toplam 38 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Güzel Sanatlar
Bölüm Araştırma Makalesi
Yazarlar

Serdar Kipdemir 0000-0002-6969-6670

Gönderilme Tarihi 27 Temmuz 2025
Kabul Tarihi 9 Aralık 2025
Yayımlanma Tarihi 30 Aralık 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 15 Sayı: 4

Kaynak Göster

APA Kipdemir, S. (2025). Geleneksel Latin kaligrafi ve tipografi sanatının yapay zekâ çağındaki dönüşümü: Estetik, uygulama ve gelecek perspektifleri. Nevşehir Hacı Bektaş Veli Üniversitesi SBE Dergisi, 15(4), 2014-2038. https://doi.org/10.30783/nevsosbilen.1752027