University of Kwazulu-Natal

Ai Information Literacy The Computational Philosophy Lab

Bonisiwe Shabane
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ai information literacy the computational philosophy lab

Our informational environment has been revolutionized since the advent of the Internet, and is increasingly influenced by (classificatory and generative) AI. We are interested in empowering people through education to engage with information critically and constructively. We have investigated the psychology and pedagogy of critical reasoning, and built the Logic Calculator and the Digital Diploma; engaged in knowledge exchange with an AI-powered EdTech start up LearnerShape; and used information design... We are also computationally investigating human questions and answers in online fora to improve prompt engineering. A video of the CPL/FDM event on ‘AI Fluency and Prompt Power: Building a Smarter Workforce’ is available: here. Data and theory visualizations, including animations, offer a clear and engaging way to present academic research that might otherwise seem dry.

This initiative focuses on creating new methods to communicate key findings from AI and Information Literacy research at the Computational Philosophy Lab (CPL) at Northeastern University London. The CPL conducts research in areas such as information sharing through computer simulations, automated proof construction for scientific discovery and education, and mapping AI ethics through co-authorship and citation network analysis. Key projects include PolyGraphs (information sharing simulations), Consilient Reasoning (automating proofs), and the Network Analysis of the AI Ethics Field. The CPL is the UK’s first dedicated academic unit for computationally-enabled and AI-enhanced philosophy. It acts as a hub in London connecting the broader Northeastern University network with European partners. The lab supports collaborations that produce research relevant to academics, policymakers, practitioners, and civil society.

The CPL’s work is a valuable resource for those interested in the intersections of AI, philosophy, and information science. For professionals seeking to deepen their expertise in AI applications and ethics, exploring dedicated AI courses can be beneficial. Explore relevant offerings at Complete AI Training. The AI Literacy Lab is an interdisciplinary community of educators and researchers dedicated to exploring how generative AI is reshaping higher education. We investigate the implications of AI for teaching, learning, and scholarly inquiry, with a strong focus on equity, creativity, and critical engagement.As part of our mission to foster collaborative innovation, we’ve established the Human-AI... This initiative supports networking, knowledge-sharing, and co-creation around generative AI, particularly within the context of higher education.Our work centres on understanding how generative AI can be thoughtfully and ethically integrated into academic practice, not...

If you would like more information about HACKER or would like to join our network, please contact Dr Douglas Eacersall. For questions about this website, please contact Dr Lynette Pretorius. Sign up to receive an email when new AI literacy content is published. We don’t spam! Read our privacy policy for more info. Check your inbox or spam folder to confirm your subscription.

Republished from lynette.pretorius.com. Original post by Lynette Pretorius. I have recently developed and delivered a masterclass about how you can develop your AI literacy in your writing and research practice. This included a series of examples from my own experiences. I thought I’d provide a summary of this masterclass in a blog post so that everyone can benefit from my experiences. Artificial intelligence (AI) has been present in society for several years and refers to technologies which can perform tasks that used to require human intelligence.

This includes, for example, computer grammar-checking software, autocomplete or autocorrect functions on our mobile phone keyboards, or navigation applications which can direct a person to a particular place. Recently, however, there has been a significant advancement in AI research with the development of generative AI technologies. Generative AI refers to technologies which can perform tasks that require creativity. In other words, these generative AI technologies use computer-based networks to create new content based on what they have previously learnt. These types of artistic creations have previously been thought to be the domain of only human intelligence and, consequently, the introduction of generative AI has been hailed as a “game-changer” for society.I am using... The AIs I use most frequently include Google’s built-in generative AI in email, chat, Google Docs etc.

which learns from your writing to suggest likely responses. I also use Grammarly Pro to help me identify errors in my students’ writing, allowing me more time to give constructive feedback about their writing, rather than trying to find examples. This is super time-saving, particularly given how many student emails I get and the number of assignments and thesis chapters I read! I also frequently use a customised version of Chat GPT 4, which I trained to do things the way I would like them to be done. This includes responding in a specific tone and style, reporting information in specific ways, and doing qualitative data analysis. Finally, I use Leonardo AI and DALL-E to generate images, Otter AI to help me transcribe some of my research, Research Rabbit to help me locate useful literature on a topic, and AILYZE to...

The moral panic that was initiated at the start of 2023 with the advent of Chat GPT caused debates in higher education. Some people insisted that generative AI would encourage students to cheat, thereby posing a significant risk to academic integrity. Others, however, advocated that the use of generative AI could make education more accessible to those who are traditionally marginalised and help students in their learning. I came to believe that the ability to use generative AI would be a core skill in the future, but that AI literacy would be essential. This led me to publish a paper where I defined AI literacy as: AI literacy is understanding “how to communicate effectively and collaboratively with generative AI technologies, as well as evaluate the trustworthiness of the results obtained”.

To conduct philosophical research using computational methods; and to reflect critically and constructively on the nature, uses, and societal impacts of artificial intelligence. We will be the UK’s first and premier centre for computationally-enabled and AI-enhanced philosophy. Serving as a London hub for related work within the broader Northeastern University network, and acting as an institutional bridge to Europe, we will collaborate with partners to deliver impactful research for policy-makers, practitioners,... This form is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply. Brian Ball is Professor of Philosophy at Northeastern University London. His research concerns the philosophy of AI and cognitive science – broadly construed so as to include mind and language, as well as the theory of knowledge.

His computational philosophy project, PolyGraphs, has been supported by the Royal Society and others; and he received a Talent Development Award from the British Academy for the follow-up Human and Network Sciences. He is widely published and in 2016 his ‘Knowledge, Safety, and Questions’ won the Philosophy South international essay prize. A member of Steering Group for the 695th Lord Mayor of London’s Ethical AI Initiative, he has acted as a consultant for the British Computer Society. He is a DISKAH Fellow during 2025-26, working on Digital Research Infrastructure and High Performance Computing to support Arts and Humanities research. David Peter Wallis Freeborn is Assistant Professor in Philosophy at Northeastern University, London. He works on the philosophy of AI, social and formal epistemology, philosophy of science, and philosophy of physics.

He began his research career as a particle physicist at the University of Oxford, conducting research at CERN, and receiving a PhD from University College London in 2016. He also holds an MSc in the Philosophy of Science from the London School of Economics and attained a second PhD in the Philosophy of Science from the University of California, Irvine in 2023. He is interested in both scientifically-informed-philosophy and philosophically-informed-science. His research focuses on artificial intelligence, Bayesian formal and social epistemology, the philosophy of physics, computational modelling, and network theory. Alice Helliwell is an Assistant Professor in Philosophy at Northeastern University London. Alice’s research is focussed on AI art and computational creativity.

She is particularly interested in developing theories of machine creativity, the interaction between art and AI, and the aesthetics of AI images. Alice holds an MA(Hons) in philosophy and psychology from the University of Edinburgh, and an MA in History and philosophy of art from the University of Kent, having received a Paris Scholarship to study... Alice went on to gain her PhD from the University of Kent, receiving a Vice Chancellor’s Scholarship. Alice’s PhD project, titled “Art-ificial: The Philosophy of AI Art” explored AI creativity and the capacity of AI systems to create art. She taught throughout her PhD and joined NU London (then New College of the Humanities) in 2021. Alice was Associate Director, then Interim Director of the Doctoral Research School at NU London from 2023-24.

Alice is involved in several active research projects, including collaborative projects on the landscape of AI ethics, AI in the creative industries, and AI arts and the human body. In summer 2025, Alice undertook a Visiting Fellow at the Centre for Philosophy and AI Research (PAIR) at Friedrich-Alexander-Universität. Her project will research “The Praise Gap: AI Responsibility Beyond Accountability”. Partially supported by a NULab Seedling Grant. Data and theory visualizations (including animations) are extremely powerful in communicating otherwise dry academic research. This project seeks to develop novel ways of communicating key findings emerging from AI & Information Literacy research currently being conducted under the auspices of Computational Philosophy Lab (CPL) at NU London.

This includes research in information sharing via computer simulations (project: PolyGraphs), automating proof construction for the purposes of scientific discovery and education (project: Consilient Reasoning), and mapping AI ethics co-authorship and citation networks (project:... The CPL is the UK’s first and premier academic research unit for computationally-enabled and AI-enhanced philosophy. Serving as a London hub for related work within the broader Northeastern University network, and acting as an institutional bridge to Europe, the CPL fosters collaborations with partners to deliver impactful research for academics,... Its four main areas of research are: AI Ethics, AI Creativity, AI & Information Literacy and Philosophical Simulations. To learn more, visit the Computational Philosophy Lab’s website. Ball, B., Koliousis, A.

(2023) Training philosopher engineers for better AI. AI & Soc 38, 861–868. https://doi.org/10.1007/s00146-022-01535-7 AI is transforming human cultures and societies at a rapid pace; yet the AI ethics landscape is cross-sectoral, interdisciplinary, and highly complex. We are using computational methods (e.g. natural language processing, graph computing) to map topics, trends, and networks within the various disciplinary academic literatures, amongst policy-makers, and in the communities of practice beyond, to identify knowledge gaps, and deliver embedded research...

Creativity is central to the arts and sciences – and even to the human condition. The question of whether, and if so how, AI can achieve it is crucial for understanding ourselves and our AI futures – a matter we have discussed in TEDx talks. Working alongside creative practitioners, we are exploring the role of AI in scientific discovery (via neural, symbolic and neuro-symbolic modelling), the aesthetics of AI artworks, whether LLMs can understand and make genuinely creative use... Our informational environment has been revolutionized since the advent of the Internet, and is increasingly influenced by (classificatory and generative) AI. We are interested in empowering people through education to engage with information critically and constructively. We have investigated the psychology and pedagogy of critical reasoning, and built the Logic Calculator and the Digital Diploma; engaged in knowledge exchange with an AI-powered EdTech start up LearnerShape; and used information design...

We are also computationally investigating human questions and answers in online fora to improve prompt engineering…. Simulation is a common technique in the natural and social sciences. It is less common (though not unheard of) in the humanities. We have developed and are exploiting the PolyGraphs simulation framework to conduct philosophical research surrounding the nature of rational opinion formation (in individuals and groups), the effectiveness of various information processing strategies under adverse... Our Python code is scalable, allowing us to explore large datasets on realistic networks (e.g. on the National Internet Observatory, or through access enabled under the EU’s Digital Services Act); and it is built to enable machine learning, on the deep graph learning library….

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Our Informational Environment Has Been Revolutionized Since The Advent Of

Our informational environment has been revolutionized since the advent of the Internet, and is increasingly influenced by (classificatory and generative) AI. We are interested in empowering people through education to engage with information critically and constructively. We have investigated the psychology and pedagogy of critical reasoning, and built the Logic Calculator and the Digital Diploma;...

This Initiative Focuses On Creating New Methods To Communicate Key

This initiative focuses on creating new methods to communicate key findings from AI and Information Literacy research at the Computational Philosophy Lab (CPL) at Northeastern University London. The CPL conducts research in areas such as information sharing through computer simulations, automated proof construction for scientific discovery and education, and mapping AI ethics through co-authorship...

The CPL’s Work Is A Valuable Resource For Those Interested

The CPL’s work is a valuable resource for those interested in the intersections of AI, philosophy, and information science. For professionals seeking to deepen their expertise in AI applications and ethics, exploring dedicated AI courses can be beneficial. Explore relevant offerings at Complete AI Training. The AI Literacy Lab is an interdisciplinary community of educators and researchers dedicate...

If You Would Like More Information About HACKER Or Would

If you would like more information about HACKER or would like to join our network, please contact Dr Douglas Eacersall. For questions about this website, please contact Dr Lynette Pretorius. Sign up to receive an email when new AI literacy content is published. We don’t spam! Read our privacy policy for more info. Check your inbox or spam folder to confirm your subscription.

Republished From Lynette.pretorius.com. Original Post By Lynette Pretorius. I Have

Republished from lynette.pretorius.com. Original post by Lynette Pretorius. I have recently developed and delivered a masterclass about how you can develop your AI literacy in your writing and research practice. This included a series of examples from my own experiences. I thought I’d provide a summary of this masterclass in a blog post so that everyone can benefit from my experiences. Artificial ...