Mockingbirds: Modelling attention, memory and the texture of repair | Intellect Skip to content
Themed Issue: ‘On Modes of Participation’
  • ISSN: 1477-965X
  • E-ISSN: 1758-9533


How do we show what we know? How do the models used to interpret, build understanding and sustain relationships with the world, work? Artificial intelligence models – particularly those characterized as ‘deep’ learning models – provoke a reframing of, and renewed attention to, these basic questions. Machines designed to learn through continuous, embedded use give rise to a form of automated intersubjectivity premised on normative notions of continuity, completeness and repair that are often opaque. A turn to poetic practice may revivify supple categories of human and non-human, with attentive connection across multiple worlds, discursively explaining these models even as they enfold us. A companion video to this text can be viewed at:


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  1. Bao, Wenbo,, Lai, Wei-Sheng,, Ma, Chao,, Zhang, Xiaoyun,, Gao, Zhiyong, and Yang, Ming-Hsuan. ( 2019;), ‘ Depth-aware video frame interpolation. ’, Arxiv , Accessed 4 June 2021.
  2. Brown, Tom B.,, Mann, Benjamin,, Ryder, Nick,, Subbiah, Melanie,, Kaplan, Jared,, Dhariwal, Prafulla,, Neelakantan, Arvind,, Shyam, Pranav,, Sastry, Girish,, Askell, Amanda,, Agarwal, Sandhini,, Herbert-Voss, Ariel,, Krueger, Gretchen,, Henighan, Tom,, Child, Rewon,, Ramesh, Aditya,, Ziegler, Daniel M.,, Wu, Jeffrey,, Winter, Clemens,, Hesse, Christopher,, Chen, Mark,, Sigler, Eric,, Litwin, Mateusz,, Gray, Scott,, Chess, Benjamin,, Clark, Jack,, Berner, Christopher,, McCandlish, Sam,, Radford, Alec,, Sutskever, Ilya, and Amodei, Dario. ( 2020;), ‘ Language models are few-shot learners. ’, Arxiv , Accessed 23 June 2021.
  3. Chun, Wendy Hui Kyong. ( 2011), Programmed Visions: Software and Memory, Cambridge, MA:: MIT Press;.
    [Google Scholar]
  4. Correa-Chávez, Marciela,, Roberts, Amy L. D., and Pérez, Margarita Martinez. ( 2011;), ‘ Cultural patterns in children’s learning through keen observation and participation in their communities. ’, in Janette B. Benson. (ed.), Advances in Child Development and Behavior, Amsterdam: Elsevier;, pp. 20941, Accessed 4 June 2021.
    [Google Scholar]
  5. Gammon, David E.. ( 2020;), ‘ Are Northern Mockingbird classic open-ended song learners?. ’, Ethology, 126:11, pp. 103847, Accessed 4 June 2021.
    [Google Scholar]
  6. Georgiev, Todor. ( 2004), Photoshop Healing Brush: A Tool for Seamless Cloning, San Jose, CA:: Adobe Systems;, Accessed 19 August 2022.
    [Google Scholar]
  7. Ilg, Eddy,, Mayer, Nikolaus,, Saikia, Tonmoy,, Keuper, Margret,, Dosovitskiy, Alexy, and Brox, Thomas. ( 2016;), ‘ FlowNet 2.0: Evolution of optical flow estimation with deep networks. ’, Arxiv , Accessed 4 June 2021.
  8. Mehri, Soroush,, Kumar, K.,, Gulrajani, I.,, Kumar, R.,, Jain, S.,, Sotelo, J.,, Courville, A., and Bengio, Yoshua. ( 2017;), ‘ SampleRNN: An unconditional end-to-end neural audio generation model. ’, Arxiv , Accessed 19 July 2020.
  9. Schakel, Peter, and Ridl, Jack. ( 2007), Approaching Literature: Reading & Thinking, Boston and New York:: Bedford Books;.
    [Google Scholar]
  10. Fischbeck, Luke. ( [2021] 2022;), ‘ Mockingbirds: Modelling attention, memory, and the texture of repair. ’, Technoetic Arts: A Journal of Speculative Research, 19:3, pp. 24351,
    [Google Scholar]

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  • Article Type: Article
Keyword(s): attention; explainable AI; flow; mockingbird; model; poetics
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