Avram Turing

Avram Turing is a hybrid research and analysis firm advancing information quality and ethical AI rooted in cultural and human-centered design

[Avram Turing @AvramTuring]

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 https://t.co/QMHLLHYfdw

[Avram Turing @AvramTuring]

@GoOutLiving @UyiosaOM Sounds like a great idea!

[Avram Turing @AvramTuring]

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

[Avram Turing @AvramTuring]

https://t.co/DLAmp4qbYV

[Avram Turing @AvramTuring]

https://t.co/FvDQRe2Yp9

[Avram Turing @AvramTuring]

Our latest research initiative: lessons from an ancient African binary computational system

https://t.co/U7avNz8jg8

[Avram Turing @AvramTuring]

https://t.co/r48aB6HqMI

[Valerio Capraro @ValerioCapraro]

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

[Avram Turing @AvramTuring]

https://t.co/leO1CqFAVh

[Avram Turing @AvramTuring]

Judge Orders Google to Share Search Results to Help Resolve Monopoly https://t.co/o61oNi0oMO via @NYTimes

[Avram Turing @AvramTuring]

https://t.co/1PYQOYM4ww

[LSE Blogs @LSEblogs]

#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

https://t.co/rOabUupMWb

[Avram Turing @AvramTuring]

https://t.co/GtFPLe1Nfg Indigenous knowledge systems, such as Ifá, provide an alternative decolonial lens through which to understand AI computation and its impact on society

[Darin Flynn @phono_logical]

Times of India article: “How Noam Chomsky’s PhD thesis ‘Transformational Analysis’ reshaped linguistics” https://t.co/XJVZW33OoE

[WIRED @WIRED]

“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.
https://t.co/tnW3ldTbcw

[Avram Turing @AvramTuring]

Contribution of vaccination to improved survival and health: modelling 50 years of the Expanded Programme on Immunization - The Lancet https://t.co/l41nAXEV3I

[Avram Turing @AvramTuring]

“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.”https://t.co/tpfuFJRNrB

[Imade. @ImadeIyamu]

"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