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Marek McGann

@MarekMcGann.sciences.social.ap.brid.gy

Cognitive scientist, teacher, nerd. I do theoretical and philosophical work in enactive, ecological, and embodied cognitive science. I am also interested in scientific practice in psychology (and it's the Department of Psychology at MIC, Limerick that pa…

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 27/10/2025

@aeryn_thrace Is the post set to 'followers only'? That prevents boosts by anyone but you. Per this site (and screenshot): docs.joinmastodon.org/user/posting The only other thing that I can think of is that mastodon.social gets limited by other […] [Original post on sciences.social]

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

🫳 🎤

We and our students can choose not to use these technologies. Just like we have banned smoking from public spaces, we could foster that process of banning both by choosing to individually quit smoking and by demanding regulation of the tobacco industry. Hence, we can also choose to unshackle ourselves and others from harmful technology industry frames, products, and lifestyles.

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five principles to protect the human knowledge ecosystem 5/5

Responsibility precludes scientists from using AI products whose use is irresponsible, e.g. harmful to people, animals, and the environment, or otherwise in violation of legal guidelines (e.g. copyright, data privacy, labour laws, Butterick 2025; Cole 2025; Rijo 2025; Tafani 2024a). Minimizing harm is vital for both engineers (ACM Code 2018 Task Force 2018) and theoreticians (Guest 2024).

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five principles to protect the human knowledge ecosystem 5/5

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five preoccupied to protect the human ecosystem 4/5

Independence means that scientists ensure that their research is unbiased by AI companies agendas, and that any potential conflicts of interest are declared in publications and other public communications (this also follows from Honesty and Transparency; cf. Mohamed Abdalla and Moustafa Abdalla 2021; Atkin 2025; Forbes and Guest 2025; Knoester et al. 2025).

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five principles to protect the human knowledge ecosystem 3/5

Transparency requires that the AI technologies are open source and computationally reproducible.
Here we must recall the technology industry’s obfuscatory tactics: “the name of the current producer of ChatGPT. ‘OpenAI’ sounds like it is engaged in open science, but as we have now seen, ‘open’ never really means what you think it does.” (Mirowski 2023, p. 738; see also Dingemanse 2025; Hao 2025; Jackson 2024; Liesenfeld and Dingemanse 2024; Liesenfeld, Lopez, et al. 2023;
Maffulli 2023; Maris 2025; Nolan 2025; Solaiman 2023; Thorne 2009; Widder et al. 2024)

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five principles to protect the human knowledge ecosystem. 2/5

Scrupulousness demands, among other things, that scientists only use AI products whose functionality is well-specified and validated for its specific scientific usage (cf. Kwisthout 2024; Kwisthout andRenooij2025).Thisincludesterminologicalprecisionaboutwhatformalisms,models,and/or technologies are used (recall Figure 1) and rigorous argumentation to motivate why these technologies are appropriate for the scientific purposes at hand.

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five principles to protect the human knowledge ecosystem. 2/5

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Five principles to protect the ecosystem of human knowledge. 1/5 @tomstafford has argued that the infoglut we live in is like when densely populated cities made plagues more likely. We need to normalise new hygienic practices. @olivia et al set some out.

Honesty implies that we do not secretly use AI technologies without disclosure, and that one does not make unfounded claims about the presumed capabilities of AI technologies (this also follows from Responsibility; see example from MIT Economics 2025, where perhaps too little too late was done).

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

"But AI tools will be just like calculators..."

we ban calculators when teaching children addition and other basic arithmetic operations for a reason (cf. Lodge et al. 2023). Otherwise, they would not learn these arithmetic operations, and calculators do not help to understand the basic mathematical rules. For the same reasons, we also do not allow the use of spellcheck software for children learning to spell, or keyboard typing when learning to write by hand

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Students aren't generally looking to cheat, and most think LLM use should not be allowed in college education. Let's not allow salespeople to speak for them.

Technology companies are not shy of falsely claiming that students are lazy or lack writing skills. Such a mantra serves only to sell products — or coverupandexcuseoverworkingthembyourcolleagues—withnoreflectiononreality.We condemn those claims and reassert students’ agency vis-à-vis corporate control.

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Why higher ed teaching is hard, and always will be. But we don't do it because it is easy, and we are trusted to do it well because we have hard earned expertise in our fields. Let's not undervalue that, hey?

Students have always cheated. Bending and breaking the rules is human nature. And by the same token, educators are not police. We are not here to obsessively surveil our students — education is based on mutual trust. Therefore, our duty is to build mutually shared values with our students and colleagues.

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

It is vital that we don't overestimate our understanding of human cognition. Yes, there is reason to believe we have a better grasp of some things than when AI hype first appeared in the 1950s, but that better understanding is not clear, and almost certainly isn't on the basis of simple computation

Although we do not fully understand human thinking, this does not licence attributing thinking to whichever machine or technology, uncritically and through anthropomorphisation. Such arguments from ignorance lack all scientific rigour. The only argument from ignorance that science permits is caution, more research, and care as appropriate actions when something is truly unknown.

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

Sigh. Paging Sam Altman.

AI hype cycles appear to go hot and cold every few years, it is also rife with valuable teaching moments. For example, a news story like this would not be out of place in the present:

The Navy revealed the embryo of an electronic computer today that it expects will be able to walk, talk, see, write, reproduce itself and be conscious of its existence.
The New York Times (1958, n.p.)

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 07/09/2025

The more I learn about history, the more I understand how important learning about history is. This is doubly important in my own professional field. @olivia and colleagues driving home the point against the inevitability of AI reminding us of this.

When we engage with the public, we notice people think that AI, as a field or a technology, appeared on the scene in the last three years. And they experience confusion and even dissonance when they discover the field and the technologies have existed for decades, if not centuries or even millennia (Bloomfield 1987; Boden 2006; Bogost 2025; Guest 2025; Hamilton 1998; Mayor 2018). Such ahistoricism facilitates “the AI-hype cycles that have long been fuelled by extravagant claims that substitute fictionforscience.”(Heffernan, 2025,n.p. Duarte etal.2024).

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Marek McGann @marekmcgann.sciences.social.ap.brid.gy · 12/06/2024

What does musicking afford? Eric Clarke Online at Ecological Psychology doi-org.libraryproxy.mic.ul.ie/10.1… #EcologicalPsychology #Music #Performance #CognitiveScience

The concept of affordances continues to provoke debate in the wider ecological community, and more specifically within the study of music, where the term has started to make increasingly frequent appearances. The adoption of this powerful idea by a range of authors interested in the human engagement with music is not without its problems, stemming from different attitudes to what musicking (to use Christopher Small’s neologism) can be understood to afford. In this paper I consider some of those possibilities – ranging from the manifest affordances of physical instruments in the hands of suitably attuned players, to the social and empathic affordances of collective musicking – and raise questions about possibilities and limits.

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