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Spread sheet for reading selection Links to an external site.

Meeting 1 (Block 1: Overview of the domain of computational creativity)

@inproceedings{Colton2012c,
    author = {S. Colton and G. A. Wiggins},
    booktitle = {Proc. European Conf. Artificial Intelligence},
    pages = {21--26},
    title = {Computational creativity: The final frontier?},
    year = {2012}}

Chapters 1 & 4 of @book{Zylinska2020m,
    author = {J. Zylinska},
    publisher = {Open Humanities Press},
    title = {AI Art: Machine Visions and Warped Dreams},
    year = {2020}}

@article{Esling2020a,
    author = {P. Esling and N. Devis},
    journal = {arXiv},
    title = {Creativity in the era of artificial intelligence.},
    year = {2020}}

Meeting 2 (Block 1: Overview of the domain of computational creativity)

@inbook{Benjamin1969a,
    author = {W. Benjamin},
    chapter = {The Work of Art in the Age of Mechanical Reproduction},
    editor = {H. Arendt},
    publisher = {Schocken Books},
    title = {Illuminations},
    year = {1969}}

@article{Jordanous2016g,
    author = {A. Jordanous},
    journal = {Connection Science},
    number = {2},
    pages = {194--216},
    title = {Four PPPPerspectives on computational creativity in theory and in practice},
    volume = {28},
    year = {2016}}

@inbook{Lamarque2010a,
    author = {P. Lamarque},
    chapter = {Imitating Style},
    publisher = {Oxford University Press},
    title = {Work and Object: Explorations in the Metaphysics of Art Work and Object: Explorations in the Metaphysics of Art},
    year = {2010}}

@article{Lamarque2010x,
    author = {P. Lamarque},
    journal = {J. Aesthetics and Art Criticism},
    number = {3},
    pages = {205--214},
    title = {The Uselessness of Art},
    volume = {68},
    year = {2010}}

@article{Lamb2018a,
    author = {C. Lamb and D. G. Brown and C. L. A. Clarke},
    journal = {ACM Computing Surveys},
    number = {2},
    pages = {1--34},
    title = {Evaluating Computational Creativity: An Interdisciplinary Tutorial},
    volume = {51},
    year = {2018}}

@inproceedings{Pease2011a,
    author = {A. Pease and S. Colton},
    booktitle = {Proc. AISB Symp. Musical Creativity},
    title = {On impact and evaluation in computational creativity: A discussion of the {Turing Test} and an alternative proposal},
    year = {2011}}

@inproceedings{Remy2020a,
    author = {C. Remy and L. M. Vermeulen and J. Frich and M. M. Biskjaer and P. Dalsgaard},
    booktitle = {Proc. AMC Designing Interactive Systems Conf.},
    pages = {457--476},
    title = {Evaluating Creativity Support Tools in HCI Research},
    year = {2020}}

@inproceedings{Colton2020a,
    author = {S. Colton and A. Pease and C. Guckelsberger and J. McCormack and T. Llano},
    booktitle = {Proc. Int. Conf. Comp. Creativity},
    title = {On the Machine Condition and its Creative Expression},
    year = {2020}}

@article{Wingstrom2022a,
    author = {R. Wingstr{\"o}m and H. Hautala and R. Lundman},
    journal = {Creativity Research Journal},
    title = {Redefining Creativity in the Era of AI? Perspectives of Computer Scientists and New Media Artists},
    year = {2022}}

@article{Mitchell2021a,
    author = {M. Mitchell},
    journal = {arXiv},
    title = {Why AI is Harder Than We Think},
    year = {2021}}

Meeting 3 (Block 1: Overview of the domain of computational creativity)

@article{Lamb2018a,
    author = {C. Lamb and D. G. Brown and C. L. A. Clarke},
    journal = {ACM Computing Surveys},
    number = {2},
    pages = {1--34},
    title = {Evaluating Computational Creativity: An Interdisciplinary Tutorial},
    volume = {51},
    year = {2018}}

Meeting 4 (Block 2: Creative practices with artificial intelligence)

@article{Ramesh2022a,
    author = {A. Ramesh and P. Dhariwal and A. Nichol and C. Chu and M. Chen},
    journal = {arXiv},
    number = {arXiv:2204.06125},
    title = {Hierarchical Text-Conditional Image Generation with CLIP Latents},
    year = {2022}}

@article{Rombach2022a,
    author = {R. Rombach and A. Blattmann and D. Lorenz and P. Esser and B. Ommer},
    journal = {arXiv},
    number = {arXiv:2112.10752},
    title = {High-Resolution Image Synthesis with Latent Diffusion Models},
    year = {2022}}

Birger's presentation: Stable Diffusion Generative AI.pdf Download Stable Diffusion Generative AI.pdf 

Meeting 5 (Block 2: Creative practices with artificial intelligence)


@article{Vaswani2017,
    author = {Ashish Vaswani and Noam Shazeer and Niki Parmar and Jakob Uszkoreit and Llion Jones and Aidan N. Gomez and Lukasz Kaiser and Illia Polosukhin},
    journal = {ArXiv e-prints},
    title = {Attention Is All You Need},
    year = {2017}}

@article{Brown2020,
    author = {Brown, Tom B. and Mann, Benjamin and Ryder, Nick and Subbiah, Melanie and Kaplan, Jared and Dhariwal, Prafulla and Neelakantan, Arvind and Shyam, Pranav and Sastry, Girish and Askell, Amanda and Agarwal, Sandhini and Herbert-Voss, Ariel and Krueger, Gretchen and Henighan, Tom and Child, Rewon and Ramesh, Aditya and Ziegler, Daniel M. and Wu, Jeffrey and Winter, Clemens and Hesse, Christopher and Chen, Mark and Sigler, Eric and Litwin, Mateusz and Gray, Scott and Chess, Benjamin and Clark, Jack and Berner, Christopher and McCandlish, Sam and Radford, Alec and Sutskever, Ilya and Amodei, Dario},
    journal = {arXiv},
    title = {Language Models are Few-Shot Learners},
    volume = {10.48550/ARXIV.2005.14165},
    year = {2020}}

Meeting 6 (Block 2: Creative practices with artificial intelligence)

@article{dhariwal2020jukebox,
  title={Jukebox: A generative model for music},
  author={Dhariwal, Prafulla and Jun, Heewoo and Payne, Christine and Kim, Jong Wook and Radford, Alec and Sutskever, Ilya},
  journal={arXiv preprint arXiv:2005.00341},
  year={2020}
}

@inproceedings{knotts2020survey,
  title={A survey on the uptake of Music AI Software},
  author={Knotts, Shelly and Collins, Nick},
  booktitle={Proceedings of the International Conference on New Interfaces for Musical Expression},
  pages={499--504},
  year={2020}
}

@article{Sturm2018a,
author = {B. L. Sturm and O. Ben-Tal and \'U. Monaghan and N. Collins and D. Herremans and E. Chew and G. Hadjeres and E. Deruty and F. Pachet},
journal = {J. New Music Research},
number = {1},
pages = {36-55},
title = {Machine Learning Research that Matters for Music Creation: A Case Study},
volume = {48},
year = {2018}}

@inproceedings{Colton2016a,
author = {S. Colton and M. T. Llano and R. Hepworth and J. Charnley and C. V. Gale and A. Baron and F. Pachet and P. Roy and P. Gerv\'as and N. Collins and B. L. Sturm and T. Weyde and D. Wolff and J. R. Lloyd},
booktitle = {Proc. Int. Conf. Comp. Creativity},
title = {The {B}eyond the {F}ence Musical and {C}omputer {S}ays {S}how Documentary},
year = {2016}}

@article{Jordanous2016a,
author = {A. Jordanous},
journal = {Connection Science},
number = {4},
pages = {350-386},
title = {Has computational creativity successfully made it {``Beyond the Fence''} in musical theatre?},
volume = {29},
year = {2017}}

@article{Roads1985a,
author = {C. Roads},
journal = {Computing Surveys},
number = {2},
pages = {163-190},
title = {Research in music and artificial intelligence},
volume = {17},
year = {1985}}

Meeting 7 (Block 3: Principles of ethics and sustainability)

  • Agre, P. E. (1997). Lessons learned in trying to reform AI. Social science, technical systems, and cooperative work: Beyond the Great Divide, 131.
  • Flick, C., Worrall, K. (2022). The Ethics of Creative AI. In: Vear, C., Poltronieri, F. (eds) The Language of Creative AI. Springer Series on Cultural Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-10960-7_5
  • Hesmondhalgh, D., Campos Valverde, R., Kaye, D., & Li, Z. (2023). The Impact of Algorithmically Driven Recommendation Systems on Music Consumption and Production: A Literature Review. UK Centre for Data Ethics and Innovation Reports. (Comment: as this paper is quite long, you may choose to focus your reading and your presentation on sections that seem most relevant to you.)
  • Holzapfel, A., Sturm, B., & Coeckelbergh, M. (2018). Ethical dimensions of music information retrieval technology. Transactions of the International Society for Music Information Retrieval, 1(1), 44-55. 
  • Jobin, A., Ienca, M., & Vayena, E. (2019). The global landscape of AI ethics guidelines. Nature Machine Intelligence, 1(9), 389-399. 
  • Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2016). The ethics of algorithms: Mapping the debate. Big Data & Society, 3(2), 2053951716679679. 
  • Steen, M. (2015). Upon opening the black box and finding it full: Exploring the ethics in design practices. Science, Technology, & Human Values, 40(3), 389-420. 
  • Weidinger, L. et al. (2022). Taxonomy of Risks posed by Language Models. 2022 ACM Conference on Fairness, Accountability, and Transparency, 214–229. https://doi.org/10.1145/3531146.3533088

 Meeting 8 (Block 3: Principles of ethics and sustainability)

  • Anthony, L. F. W., Kanding, B., & Selvan, R. (2020). Carbontracker: Tracking and predicting the carbon footprint of training deep learning models. arXiv preprint arXiv:2007.03051. 
  • Emily M. Bender et al 2021. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 In Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency (FAccT '21). Association for Computing Machinery, New York, NY, USA, 610–623. https://doi.org/10.1145/3442188.3445922
  • Douwes, C., Esling, P., & Briot, J. P. (2021). Energy Consumption of Deep Generative Audio Models. arXiv preprint arXiv:2107.02621.  
  • Jääskeläinen, P., Pargman, D., & Holzapfel, A. (2022, June). On the environmental sustainability of Ai art (s). In Eighth Workshop on Computing within Limits. 
  • Schwartz, R., Dodge, J., Smith, N. A., & Etzioni, O. (2020). Green ai. Communications of the ACM, 63(12), 54-63. 
  • Strubell, E., Ganesh, A., & McCallum, A. (2020, April). Energy and policy considerations for modern deep learning research. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 34, No. 09, pp. 13693-13696). 

 Meeting 9 (Block 3: Principles of ethics and sustainability)

  • Texts for Political Ecology:
    • (Arrieta-Ibarra, I., Goff, L., Jiménez-Hernández, D., Lanier, J., & Weyl, E. G. (2018, May). Should we treat data as labor? Moving beyond" free". In aea Papers and Proceedings (Vol. 108, pp. 38-42).)
    • Crawford, Kate: Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence (Chapter 3)
    • (Daughtry, J. M. (2020). Did Music Cause the End of the World? Transposition. Musique et Sciences Sociales, Hors-série 2, Article Hors-série 2. https://doi.org/10.4000/transposition.5192
    • Kyle Devine: Decomposed: the political ecology of music, Chapter 1: Introduction: Political Ecology and Recorded Music
    • Hesmondhalgh, D., & Meier, L. M. (2018). What the digitalisation of music tells us about capitalism, culture and the power of the information technology sector. Information, Communication & Society, 21(11), 1555–1570.)
    • Holzapfel, A. (2023): Introducing Political Ecology of Creative-Ai. https://arxiv.org/abs/2301.10233
    • Nost & Colven (2022): Earth for AI: A Political Ecology of Data-Driven Climate Initiatives
  • Texts on legal aspects: