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citai.bsky.social
Artificial Intelligence Research Centre, CitAI.
@citai.bsky.social
1.1K followers 40 following 36 posts
We are an interdisciplinary team at City, University of London specialised in the intersection between the development of novel AI techniques, AGI, and XAI with a keen interest in its legal, ethical and social impact.
https://cit-ai.net/
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Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
Surprise, surprise. Here we go.

“The European Commission is proposing a pause to parts of its landmark artificial intelligence laws amid intense pressure from Big Tech companies and the US government.”

www.ft.com/content/af6c...
EU set to water down landmark AI act after Big Tech pressure
Commission proposes pauses to provisions in digital rule book
www.ft.com
November 7, 2025 at 2:03 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
irisvanrooij.bsky.social
✨ This is wonderful 🎬 🍿

Librebel on Youtube reads out our position paper:

Guest, O., Suarez, … & van Rooij, I. (2025). Against the Uncritical Adoption of 'AI' Technologies in Academia. Zenodo. doi.org/10.5281/zeno...

www.youtube.com/watch?v=cJNO... @olivia.science @marentierra.bsky.social
Against the Uncritical Adoption of AI Technologies in Academia by Guest et. al. (2025)
YouTube video by librebel
www.youtube.com
November 8, 2025 at 12:22 AM
Reposted by Artificial Intelligence Research Centre, CitAI.
irisvanrooij.bsky.social
“Ultimately, the collective strategy of AI companies threatens to deskill precisely those people who are essential for society to function(…) automation of knowledge and culture by private companies is a worrying prospect – conjuring dystopian and outright fascistic scenarios.” — @olivia.science
AI Is Hollowing Out Higher Education
Olivia Guest & Iris van Rooij urge teachers and scholars to reject tools that commodify learning, deskill students, and promote illiteracy.
www.project-syndicate.org
October 17, 2025 at 10:51 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
A quick summary for busy people:

We propose a mathematical framework for learning representations by extracting the algebra of transformations of worlds from the agent's perspective.
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www.sciencedirect.com/science/arti...
Algebras of actions in an agent's representations of the world
Learning efficient representations allows robust processing of data, data that can then be generalised across different tasks and domains, and it is t…
www.sciencedirect.com
September 11, 2025 at 5:40 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
olivia.science
Finally! 🤩 Our position piece: Against the Uncritical Adoption of 'AI' Technologies in Academia:
doi.org/10.5281/zeno...

We unpick the tech industry’s marketing, hype, & harm; and we argue for safeguarding higher education, critical
thinking, expertise, academic freedom, & scientific integrity.
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Abstract: Under the banner of progress, products have been uncritically adopted or even imposed on users — in past centuries with tobacco and combustion engines, and in the 21st with social media. For these collective blunders, we now regret our involvement or apathy as scientists, and society struggles to put the genie back in the bottle. Currently, we are similarly entangled with artificial intelligence (AI) technology. For example, software updates are rolled out seamlessly and non-consensually, Microsoft Office is bundled with chatbots, and we, our students, and our employers have had no say, as it is not considered a valid position to reject AI technologies in our teaching and research. This is why in June 2025, we co-authored an Open Letter calling on our employers to reverse and rethink their stance on uncritically adopting AI technologies. In this position piece, we expound on why universities must take their role seriously toa) counter the technology industry’s marketing, hype, and harm; and to b) safeguard higher education, critical thinking, expertise, academic freedom, and scientific integrity. We include pointers to relevant work to further inform our colleagues. Figure 1. A cartoon set theoretic view on various terms (see Table 1) used when discussing the superset AI (black outline, hatched background): LLMs are in orange; ANNs are in magenta; generative models are in blue; and finally, chatbots are in green. Where these intersect, the colours reflect that, e.g. generative adversarial network (GAN) and Boltzmann machine (BM) models are in the purple subset because they are both generative and ANNs. In the case of proprietary closed source models, e.g. OpenAI’s ChatGPT and Apple’s Siri, we cannot verify their implementation and so academics can only make educated guesses (cf. Dingemanse 2025). Undefined terms used above: BERT (Devlin et al. 2019); AlexNet (Krizhevsky et al. 2017); A.L.I.C.E. (Wallace 2009); ELIZA (Weizenbaum 1966); Jabberwacky (Twist 2003); linear discriminant analysis (LDA); quadratic discriminant analysis (QDA). Table 1. Below some of the typical terminological disarray is untangled. Importantly, none of these terms are orthogonal nor do they exclusively pick out the types of products we may wish to critique or proscribe. Protecting the Ecosystem of Human Knowledge: Five Principles
September 6, 2025 at 8:13 AM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
Some pictures of this enlightening event organised by @hcid.city and @citai.bsky.social
Pannel discussion A picture of a presenter delivering a talk Another presenter A keynote speaker
September 5, 2025 at 7:14 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
Available open access.

www.sciencedirect.com/science/arti...
Algebras of actions in an agent's representations of the world
Learning efficient representations allows robust processing of data, data that can then be generalised across different tasks and domains, and it is t…
www.sciencedirect.com
August 21, 2025 at 3:41 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
I am pleased to announce that this paper has been accepted for publication in Artificial Intelligence (AIJ)! 😊

arxiv.org/abs/2310.01536
August 11, 2025 at 1:43 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
New version available. The readability of the paper has been greatly improved. Enjoy!
arxiv.org/abs/2310.01536
Algebras of actions in an agent's representations of the world
In this paper, we propose a framework to extract the algebra of the transformations of worlds from the perspective of an agent. As a starting point, we use our framework to reproduce the symmetry-base...
arxiv.org
July 29, 2025 at 9:30 AM
Reposted by Artificial Intelligence Research Centre, CitAI.
irisvanrooij.bsky.social
Did you all know that Margaret Boden founded the first School of Cognitive and Computing Sciences in 1987.

No?

Well, now you do 😌

Btw, listen to this great talk by her. I'll be adding this to the resources from our 1st year students in Intro to AI.

www.youtube.com/watch?v=wPRA...
Professor Margaret Boden - Human-level AI: Is it Looming or Illusory?
YouTube video by CSER Cambridge
www.youtube.com
September 1, 2024 at 7:21 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
Inaugural Lecture of the Margaret Boden Lecture series at the Leverhulme Centre for the Future of Intelligence

www.youtube.com/watch?v=zNr2...
The Margaret Boden Lecture - Lecture One by Professor Margaret Boden (Sussex)
YouTube video by Future of Intelligence
www.youtube.com
July 28, 2025 at 4:18 PM
citai.bsky.social
Sad news. RIP Maggie Boden.
Maggie was an AI pioneer and a truly interdisciplinary scholar, integrating in her work philosophy, psychology, and computer science -worth emphasising in an era of massive, data-hungry GenAI architectures.
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staff.sussex.ac.uk/news/article...
Obituary: Professor Maggie Boden
The University of Sussex mourns the loss of Professor Margaret (Maggie) Boden, a pioneering figure in cognitive science and artificial intelligence.
staff.sussex.ac.uk
July 28, 2025 at 3:57 PM
citai.bsky.social
comicsandai.org Comics & AI: Critical Prompts @comicsandai.org · Jul 24
Habemus programme! Full abstracts and bios to follow, but here's the listing of accepted speakers and their presentation titles: comicsandai.org/programme/  Join us on 4 September in London for a one-day multidisciplinary conference on the future of comics, technology, and creativity!
Programme
Evemt start: 9:00hrs. End: 18:30hrs followed by social.   The City St George’s Interaction Lab, The Centre for Human-Computer Interaction Design (HCID), and The Artificial Intelligence Researc…
comicsandai.org
July 24, 2025 at 2:51 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
comicsandai.org
You are invited to a one-day multidisciplinary conference on the future of comics, technology, and creativity. Abstracts (200 words) + bios (100 words) due: 10 July 2025. Don’t miss this opportunity to rethink comics and AI with a multidisciplinary community! #CFP: comicsandai.org #ComicsStudies
Comics & AI: Critical Prompts
A multidisciplinary conference on the future of comics, technology, and creativity
comicsandai.org
May 15, 2025 at 6:07 AM
citai.bsky.social
May 12, 2025 at 5:29 PM
citai.bsky.social
#CitAI_Seminars
Tuesday, 22-04 (Zoom, 16:00 BST) Marin Lujak Artificial Intelligence Research Group on
'Scalable, efficient and distributed multi-agent coordination of automated agricultural vehicle fleets'
If interested, pls get in touch with
the organisers.
More info cit-ai.net/seminars.html
CitAI-Seminars
Website of the Artificial Reseach Centre, CitAI. Seminars.
cit-ai.net
April 11, 2025 at 2:23 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
The EU has just announced a plan to establish Europe’s leadership in AI.
digital-strategy.ec.europa.eu/en/library/a...

Five key points:

1. Creating a solid computing infrastructure: strengthening the network of AI Factories and establishing resource-efficient Gigafactories

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The AI Continent Action Plan
The European Union is committed and determined to become a global leader in Artificial Intelligence, a leading AI continent.
digital-strategy.ec.europa.eu
April 9, 2025 at 1:50 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
New preprint with @corinacatarau.bsky.social and
@ealonso.bsky.social from @citai.bsky.social:
A representational framework for learning and encoding structurally enriched trajectories in complex agent environments
arxiv.org/abs/2503.13194
A representational framework for learning and encoding structurally enriched trajectories in complex agent environments
The ability of artificial intelligence agents to make optimal decisions and generalise them to different domains and tasks is compromised in complex scenarios. One way to address this issue has focuse...
arxiv.org
March 18, 2025 at 2:52 PM
citai.bsky.social
AI in health security:

1- LLMs to speed up qualitative analysis in public health research.
2- AI to detect foodborne illness outbreaks.
3- AI to make public health guidance more consistent.
ukhsa.blog.gov.uk/2025/03/14/h...
How we are pioneering artificial intelligence applications in public health
The UK Health Security Agency (UKHSA) is harnessing the power of artificial intelligence (AI) to address health security challenges. Here are 3 examples of projects that demonstrate how we're using cu...
ukhsa.blog.gov.uk
March 14, 2025 at 2:16 PM
citai.bsky.social
Congratulations to Rich Sutton and Andrey Barto!
www.acm.org/media-center...
Andrew Barto and Richard Sutton are the recipients of the 2024 ACM A.M. Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning.
Andrew Barto and Richard Sutton are the recipients of the 2024 ACM A.M. Turing Award for developing the conceptual and algorithmic foundations of reinforcement learning. In a series of papers beginning in the 1980s, Barto and Sutton introduced the main ideas, constructed the mathematical foundations, and developed important algorithms for reinforcement learning—one of the most important approaches for creating intelligent systems.
www.acm.org
March 5, 2025 at 4:52 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
And the Turing Award 2025 goes to Sutton and Barto! Congrats!

www.wired.com/story/pionee...
Pioneers of Reinforcement Learning Win the Turing Award
Having machines learn from experience was once considered a dead end. It’s now critical to artificial intelligence, and work in the field has won two men the highest honor in computer science.
www.wired.com
March 5, 2025 at 4:47 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
New preprint from @citai.bsky.social and wonderful Julian @julian-jn.bsky.social
julian-jn.bsky.social Julian JN @julian-jn.bsky.social · Jan 30
1. 🧠Excited to share my published paper "Advancing the Biological Plausibility and Efficacy of Hebbian Convolutional Neural Networks" with @emp1.bsky.social. Available from: arxiv.org/abs/2501.17266
January 30, 2025 at 6:50 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
julian-jn.bsky.social
1. 🧠Excited to share my published paper "Advancing the Biological Plausibility and Efficacy of Hebbian Convolutional Neural Networks" with @emp1.bsky.social. Available from: arxiv.org/abs/2501.17266
January 30, 2025 at 6:07 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
emp1.bsky.social
An advance of a paper that will soon be available in ArXiv. All merit to my wonderful student @julian-jn.bsky.social !
I hope you enjoy it.

We present an optimal architecture that significantly enhances recent research aimed at integrating Hebbian learning with competition mechanisms and CNNs.
➡️
Advancing the Biological Plausibility and Efficacy of Hebbian Convolutional Neural Networks by Julian Jimenez-Nimo and Esther Mondragón The research presented in this paper advances the integration of Hebbian learning into Convolutional Neural Networks (CNNs) for image processing, systematically exploring different architectures to build an optimal configuration, adhering to biological tenability. Hebbian learning operates on local unsupervised neural information to form feature representations, providing an alternative to the popular but arguably biologically implausible and computationally intensive backpropagation learning algorithm. The suggested optimal architecture significantly enhances recent research aimed at integrating Hebbian learning with competition mechanisms and CNNs, expanding their representational capabilities by incorporating hard Winner-Takes-All (WTA) competition, Gaussian lateral inhibition mechanisms and Bienenstock–Cooper–Munro (BCM) learning rule in a single model. The resulting model achieved 76\% classification accuracy on CIFAR-10, rivalling its end-to-end backpropagation variant (77\%) and critically surpassing the state-of-the-art hard-WTA performance in CNNs of the same network depth (64.6\%) by 11.4\%. Moreover, results showed clear indications of sparse hierarchical learning through increasingly complex and abstract receptive fields. In summary, our implementation enhances both the performance and the generalisability of the learnt representations and constitutes a crucial step towards more biologically realistic artificial neural networks.
January 6, 2025 at 6:34 PM
Reposted by Artificial Intelligence Research Centre, CitAI.
devezer.bsky.social
Article fresh off the print (no paywall)! The tl;dr is in the quoted thread. We advance a measure of replication distance to capture differences btw an original study & its replications. We also discuss how statistics needs to go beyond ideal assumptions to serve science better.

#metasci #sts #stat
October 6, 2024 at 8:06 PM