The Clockwork Penguin

Daniel Binns is a media theorist and filmmaker tinkering with the weird edges of technology, storytelling, and screen culture. He is the author of Material Media-Making in the Digital Age and currently writes about posthuman poetics, glitchy machines, and speculative media worlds.

Tag: pedagogy

  • Conjuring to a brief

    Generated by me with Leonardo.Ai.

    This semester I’m running a Media studio called ‘Augmenting Creativity’. The basic goal is to develop best practices for working with generative AI tools not just in creative workflows, but as part of university assignments, academic research, and in everyday routines. My motivation or philosophy for this studio is that so much attention is being focused on the outputs of tools like Midjourney and Leonardo.Ai (as well as outputs from textbots like ChatGPT); what I guess I’m interested in is exploring more precisely where in workflows, jobs, and daily life that these tools might actually be helpful.

    In class last week we held a Leonardo.Ai hackathon, inspired by one of the workshops that was run at the Re/Framing AI event I convened a month or so ago. Leonardo.Ai generously donated some credits for students to play around with the platform. Students were given a brief around what they should try to generate:

    • an AI Self-Portrait (using text only; no image guidance!)
    • three images to envision the studio as a whole (one conceptual, a poster, and a social media tile)
    • three square icons to represent one task in their daily workflow (home, work, or study-related)

    For the Hackathon proper, students were only able to adjust the text prompt and the Preset Style; all other controls had to remain unchanged, including the Model (Phoenix), Generation Mode (Fast), Prompt Enhance (off), and all others.

    Students were curious and excited, but also faced some challenges straight away with the underlying mechanics of image generators; they had to play around with word choice in prompts to get close to desired results. The biases and constraints of the Phoenix model quickly became apparent as the students tested its limitations. For some students this was more cosmetic, such as requesting that Leonardo.Ai generate a face with no jewelry or facial hair. This produced mixed results, in that sometimes explicitly negative prompts seemed to encourage the model to produce what wasn’t wanted. Other students encountered difficulties around race or gender presentation: the model struggles a lot with nuances in race, e.g. mixed-race or specific racial subsets, and also often depicts sexualised presentations of female-presenting people (male-presenting too, but much less frequently).

    This session last week proved a solid test of Leonardo.Ai’s utility and capacity in generating assets and content (we sent some general feedback to Leonardo.Ai on platform useability and potential for improvement), but also was useful for figuring out how and where the students might use the tool in their forthcoming creative projects.

    This week we’ve spent a little time on the status of AI imagery as art, some of the ethical considerations around generative AI, and where some of the supposed impacts of these tools may most keenly be felt. In class this morning, the students were challenged to deliver lightning talks on recent AI news, developing their presentation and media analysis skills. From here, we move a little more deeply into where creativity lies in the AI process, and how human/machine collaboration might produce innovative content. The best bit, as always, will be seeing where the students go with these ideas and concepts.

  • Priorities

    I am lucky to have a job that I love. But in the eighteen months of settling into full-time academia, I seem to have lost sight of the ‘love’ and become fixated on the ‘job’. A weird thing has happened in recent weeks, in that I’ve tried to become more focused on what is actually important about my work — and what feels the most rewarding.

    There are two main strands to the workload of an academic at my level: teaching and research. Research covers the writing and publication of scholarly work — be it journal articles, book chapters, conference presentations, monographs. Teaching is what it says on the tin.

    In 2011, mid-PhD, I took my first class at Western Sydney University (then UWS). It was a boring compulsory course, but I caught the bug, and have loved teaching ever since. With the transition to full-time employment, I’ve always tried to have time for my students, time to sink into my pedagogy, but that time has always felt sapped by other commitments. I say felt, because I’ve realised that the sapping of time has only occurred because I’ve let it.

    This semester, I’ve turned a corner. The most important commitments I have, during semester time, are my students. Everything else is secondary. To be clear, I don’t think the time I spend on teaching or research will change this semester (I have a book chapter to finish, a presentation to write, and a monograph to approve all by September). Rather what has changed is where my head is at most of the time: ensuring my students are, if not blissfully happy, then at least reasonably clear about what I’m trying to teach them, and the experience I would — ideally — like them to have.