Avram Turing

What if computation is not just automation, but interpretation? We draw on the West African Ifá knowledge system to rethink AI, governance & intelligence through ethics, context, dialogue & social accountability. A new framework for AI governance & safety a.co/d/0h5Sypdt

@GoOutLiving @UyiosaOM Sounds like a great idea!

@UyiosaOM Congratulations on your new book, it sounds really interesting! If you are looking for another platform to talk about your book I have really enjoyed PodMatch. I do both hosting and guest appearances but a lot of my guests have books they want to talk about. Just a thought!

My new book is out! What if computation is not just automation, but interpretation? I draw on the West African Ifá knowledge system to rethink AI, governance, and intelligence through ethics, context, dialogue & social accountability. A new framework for AI governance & safety

Our new book! My new book is out! What if computation is not just automation, but interpretation? Drawing on the West African Ifá knowledge system to rethink AI, governance & intelligence through ethics, context, dialogue & social accountability. A new framework for AI safety

Our latest research initiative: lessons from an ancient African binary computational system youtube.com/watch?v=jCkbEJ…

Major preprint just out! We compare how humans and LLMs form judgments across seven epistemological stages. We highlight seven fault lines, points at which humans and LLMs fundamentally diverge: The Grounding fault: Humans anchor judgment in perceptual, embodied, and social experience, whereas LLMs begin from text alone, reconstructing meaning indirectly from symbols. The Parsing fault: Humans parse situations through integrated perceptual and conceptual processes; LLMs perform mechanical tokenization that yields a structurally convenient but semantically thin representation. The Experience fault: Humans rely on episodic memory, intuitive physics and psychology, and learned concepts; LLMs rely solely on statistical associations encoded in embeddings. The Motivation fault: Human judgment is guided by emotions, goals, values, and evolutionarily shaped motivations; LLMs have no intrinsic preferences, aims, or affective significance. The Causality fault: Humans reason using causal models, counterfactuals, and principled evaluation; LLMs integrate textual context without constructing causal explanations, depending instead on surface correlations. The Metacognitive fault: Humans monitor uncertainty, detect errors, and can suspend judgment; LLMs lack metacognition and must always produce an output, making hallucinations structurally unavoidable. The Value fault: Human judgments reflect identity, morality, and real-world stakes; LLM "judgments" are probabilistic next-token predictions without intrinsic valuation or accountability. Despite these fault lines, humans systematically over-believe LLM outputs, because fluent and confident language produce a credibility bias. We argue that this creates a structural condition, Epistemia: linguistic plausibility substitutes for epistemic evaluation, producing the feeling of knowing without actually knowing. To address Epistemia, we propose three complementary strategies: epistemic evaluation, epistemic governance, and epistemic literacy. Full paper in the first reply. Joint with @Walter4C & @matjazperc

Judge Orders Google to Share Search Results to Help Resolve Monopoly nytimes.com/2025/09/02/tec… via @NYTimes

#AI is presented as a disruptive #innovation. But as @UyiosaOM argues, #Indigenous knowledge systems, such as Ifá, provide an alternative decolonial lens through which to understand AI computation and its impact on society @LSEImpactBlog blogs.lse.ac.uk/impactofsocial…

blogs.lse.ac.uk/impactofsocial… Indigenous knowledge systems, such as Ifá, provide an alternative decolonial lens through which to understand AI computation and its impact on society

Times of India article: “How Noam Chomsky’s PhD thesis ‘Transformational Analysis’ reshaped linguistics” timesofindia.indiatimes.com/instant-schola…

“Everybody in math and physics uses it.” Nearly 35 years ago, Paul Ginsparg created arXiv, a digital repository for sharing research. It changed science for good. Three decades in, Ginsparg reflects on its legacy—and its future. wired.com/story/inside-a…

Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization - The Lancet thelancet.com/journals/lance…

“Here, we advance work on the Moral Turing Test and find that Americans rate ethical advice from GPT-4o as slightly more moral, trustworthy, thoughtful, and correct than that of the popular New York Times advice column, The Ethicist.”nature.com/articles/s4159…

"If there's a book that you want to read, but it hasn't been written yet, then you must write it. The same is true of any endeavor: if the solution you seek doesn't exist, create it." - Toni Morrison