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#epistemology

7 posts7 participants1 post today
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bookandswordblog

"if I could insist on one skill that I have been trained, and practiced, to have, the skill that I think historians really specialize in, as a core requirement of humanities education today, it would be this; Ad Fontes, back (again) to the sources." - David Hitchcock bookandsword.com/2025/01/11/kn #histodons #antiquidons #epistemology

Book and SwordKnowing Things is Hard – Book and Sword
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Emma Stamm

ISO opinions:

In order for a body of knowledge to count as properly pseudoscientific (I get that "properly pseudoscientific" might be a contradiction in terms, but humor me), does it have to have an obvious place in what social convention designates as the mystical/metaphysical?

For example, if one says yes, astrology is definitely pseudoscientific and chiropractic medicine isn't.

· 34 people · Closed
#philosophy#epistemology#science
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Aneesh Sathe

The Mind as Semi-Solid Smoke

This post continues the series on Socratic Thinking, turning the space-and-place lens inward to examine the mind itself. Human minds can be thought of as an imperfect place with the ability to create their own insta-places to navigate ambiguity. 

On the Trail (1889) by Winslow Homer. Original from The National Gallery of Art. Digitally enhanced by rawpixel.

Exploration in any real or conceptual space needs navigational markers with sufficient meaning. Humans are biologically predisposed to seek out and use navigational markers. This tendency is rooted in our neural architecture, emerges early in life, and is shared with other animals, reflecting its deep evolutionary origins 1,2 .  Even the simplest of life performing chemotaxis uses the signal-field of food to navigate. 

When you’re microscopic, the territory is the map; at human scale, we externalise those cues as landmarks—then mirror the process inside our heads. Just as cells follow chemical gradients, our thoughts follow self-made landmarks, yet these landmarks are vaporous.

From the outside our mind is a single place, it is our identity. Probe closer and our identity is nebulous and dissolves the way a city dissolves into smaller and smaller places the closer you look. We use our identity to create the first stable place in the world and then use other places to navigate life. However, these places come from unreliable sources, our internal and external environments.  How do we know the places are even real, and do we have the knowledge to trust their reality? Well, we don’t. We can’t judge our mental landmarks false. Callard calls this normative self-blindness: the built-in refusal to saw off the branch we stand on.   

Normative self-blindness is a trick to gloss over details and keep moving. Insta-places are conjured from our experience and are treated as solid no matter how poorly they are tied down by actual knowledge. We can accept that a place was loosely formed in the past, an error, or is not yet well defined in the future, is unknown. However, in the moment, the places exist and we use them to see. 

Understanding and accepting that our minds work this way is a key tenet of Socratic Thinking. It makes adopting the posture of inquiry much easier. Socratic inquiry begins by admitting that everyone’s guiding landmarks may be made of semi-solid smoke.

1Chan, Edgar, Oliver Baumann, Mark A. Bellgrove, and Jason B. Mattingley. “From Objects to Landmarks: The Function of Visual Location Information in Spatial Navigation.” Frontiers in Psychology 3 (2012). https://doi.org/10.3389/fpsyg.2012.00304

2Freas, Cody A., and Ken Cheng. “The Basis of Navigation Across Species.” Annual Review of Psychology 73, no. 1 (January 4, 2022): 217–41. https://doi.org/10.1146/annurev-psych-020821-111311.

#AgnesCallard#cognitiveBiases#cognitiveScience
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Aneesh Sathe

Thinking with places 

“A farmer has to cut down trees to create space for his farmstead and fields. Yet once the farm is established it becomes an ordered world of meaning—a place—and beyond it is the forest and space.” — Yi-Fu Tuan

Thinking itself is place-making: the act of converting undifferentiated possibility into navigable meaning.

A place comes into being the moment we interrupt undifferentiated space. Place-making is fundamentally an act of interruption. Space is thought of as possibility but is unavailable without the signposts of place. When a place is created we impose a way of looking, being, and acting on the space of choice. The place you pick to navigate your space defines the identity you will inhabit during your quest. Every tool is a micro-place: it frames what can be thought and forecloses alternative moves. They enforce the kind of thoughts that can be had, the type of exploration that can be done, and configures space in an opinionated way. 

Two-masted Schooner with Dory (1894) by Winslow Homer. Original from The Smithsonian. Digitally enhanced by rawpixel.

Picking a tool commits us to a world view. Consider the space of ‘good TV shows’. Family, friends and culture have made the choice of what good means. When Netflix suggests shows it uses your watching history as a probe to create place so that every individual is always watching ‘good’ shows. The pure possibility space of the search bar is disrupted by the suggestions provided.

Like algorithmic curation, Socratic dialogue also interrupts space, it is interrogation as cartography. Socratic thinking is also an act of interruption and making concrete what was nebulous. It’s asking us to specify which show, if we claim to love TV. Socratic thinking (henceforth referred to as just thinking) starts by probing that which does not need questioning, the answers that are obvious the ones that everyone knows. This may seem foreign at first glance but we do this all the time, say we make a list of our favorite TV shows, someone always says you are missing this or that show and that this list is completely wrong. This kind of disagreement leads to the shared quest of answering the question, ‘What is it to be entertained?’. 

Thinking pursues knowledge through the act of stabilizing answers to such questions by creating places in those unexamined areas. Discussion allows us to map. There is usually no well defined answer for such questions, if there were, they would simply be problems that we could solve with a google search. The quest stops when the parties involved are satisfied that they have arrived at an answer. Thinking is the act of place-making by taking something that was ungraspable and tying it down with knowledge. Place is, after all, an “ordered world of meaning” and we can use these places to create home bases from which to explore.   

Even without other people simply engaging with the reality of the universe is sufficient for thought. Places are stable systems which provide a surface on which your thoughts and hypothesis can be tested. Even if there is no other person around and you’re simply engaged with looking at the world can uncover a new truth tied down by knowledge.  

Thinking is the process of updating beliefs based on the mini places that make up the space that you’re interrogating. Each place is a noisy pointer to the underlying truth, and each updating of belief allows you to get closer to the knowledge you seek.

#algorithmicCuration#cognitiveScience#criticalThinking
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KilleansRow 🇺🇲 🇺🇦🍀

1/2 #Epistemology and #Ontology have varying degrees of separation depending on the questions we ask. In the mix also is language and how we use it in a particular context. I often try to avoid using terms like #psi as it relates to phenomena like precognition or clairaudience simply because it also denotes a quantum process.Many researchers believe quantum mechanical descriptors fit as putative mechanisms for the cluster of phenomena referred to generically as psi but direct evidence is still-

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Zh-Sigma≅Σx, x∈S={💚🇪🇺λP(θ|y)⁂⧖⏚} learn-languages-world-life

#sociology #epistemology #scienceofscience #science #ai Please could you warn your "scientists" to remain "scientists" ? I have been blocked after warning that accusing AI of being AI without knowing what is AI is dangerous I can't forward you his invitation to a witchcraft-AI ban: I'm blocked

RE: https://bsky.app/profile/did:plc:iepyfmc7yhwwgbgeu4vc3vcx/post/3lsuyrghh7k2p

Bluesky Social · Zh-Sigma≅Σx, x∈S={💚🇪🇺λP(θ|y)⁂⧖⏚} learn-languages-world-life (@stphrolland.bsky.social)I think it is dangerous You don't even take the time to define the words AI. STRIKINGLY similar to how so-called "right-wing" politicians do politics in the USA: No need to define the word communist, let's accuse anyone we don't like of being it: anyway our voters will never take the time to check [contains quote post or other embedded content]
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Mark Gardner

@mjd This reminds me of the Objectivist #philosophy term “conceptual common denominator” to describe the shared characteristics that allow for the formation of concepts by identifying similarities among different entities. It serves as a basis for differentiating and integrating concepts, focusing on the essential attributes that define a category while omitting specific measurements.

Here’s the full chapter on concept-formation, from Introduction to Objectivist #Epistemology by #AynRand

courses.aynrand.orgConceptual Common Denominator – ARI Campus
#epistemology
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Barry Schwartz 🫖

People use extremely shallow reasoning when I ask them certain mathematical questions.

If I ask, "With what probability is seven the final digit of pi?" they most often claim the question is meaningless, because pi has no final digit. Thus it is, they say, meaningless to speak about a final digit of pi.

But they are doing EXACTLY THAT!

Indeed, how can you PROVE pi has no final digit, unless that has some meaning!

So, no, they are wrong. The probability is ZERO.

#mathematics#epistemology
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Agustin V. Startari

From Obedience to Execution: Structural Legitimacy in the Age of Reasoning Models
When models no longer obey but execute, what happens to legitimacy?

Core contributions:
• Execution vs. obedience in LLMs
• Structural legitimacy without subject
• Reasoning as authority loop

🔗 Full article: zenodo.org/records/15635364
🌐 Website: agustinvstartari.com
🪪 ORCID: orcid.org/0009-0002-1483-7154

ZenodoFrom Obedience to Execution: Structural Legitimacy in the Age of Reasoning ModelsThis article formulates a structural transition from Large Language Models (LLMs) to Language Reasoning Models (LRMs), redefining authority in artificial systems. While LLMs operated under syntactic authority without execution, producing fluent but functionally passive outputs, LRMs establish functional authority without agency. These models do not intend, interpret, or know. They instantiate procedural trajectories that resolve internally, without reference, meaning, or epistemic grounding. This marks the onset of a post-representational regime, where outputs are structurally valid not because they correspond to reality, but because they complete operations encoded in the architecture. Neutrality, previously a statistical illusion tied to training data, becomes a structural simulation of rationality, governed by constraint, not intention. The model does not speak. It acts. It does not signify. It computes. Authority no longer obeys form, it executes function. A mirrored version of this article is also available on Figshare for redundancy and citation indexing purposes: DOI: 10.6084/m9.figshare.29286362 Resumen Este artículo formula una transición estructural desde los Modelos de Lenguaje a Gran Escala (LLMs) hacia los Modelos de Razonamiento Lingüístico (LRMs), redefiniendo la noción de autoridad en sistemas artificiales. Mientras los LLMs operaban bajo una autoridad sintáctica sin ejecución, generando salidas coherentes pero pasivas, los LRMs instauran una autoridad funcional sin agencia. Estos modelos no interpretan, no intencionan, no conocen. Resuelven trayectorias procedurales internas sin referente, sin sentido, sin anclaje epistémico. Se inaugura así un régimen post-representacional, donde la validez no proviene de la correspondencia con el mundo, sino de la finalización estructural de operaciones. La neutralidad, antes ilusión estadística derivada del corpus, se convierte en simulación estructural de racionalidad, regulada por restricciones y no por decisiones. El modelo no habla: actúa. No significa: computa. La autoridad ya no obedece forma, ejecuta estructura.
#AI#LLM#Execution
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andrecatta

For those who haven't realized yet, the perpetual battle for power is always about knowledge manipulation. As knowledge availability, mobilization, and accessibility become increasingly central to current technological paradigms in the West, it's time to take cultural and epistemological matters seriously.

#Technology #AI #KnowledgeManipulation #CulturalStudies #Epistemology #PowerAndControl #TechTrends #WesternTechnology #DigitalAge

axios.com/2025/03/06/exclusive via @digyoursoul

Illustration of a laptop with a laser beam extending from the camera, resembling a gun's laser sight
Axios · Exclusive: Russian disinformation floods AI chatbots, study findsBy Ina Fried
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Agustin V. Startari

🚨 New academic article by Agustín V. Startari:
The Grammar of Objectivity: Formal Mechanisms for the Illusion of Neutrality in Language Models

🔍 Focus: How LLMs use syntax to simulate neutrality without epistemic grounding.
📊 Introduces the Simulated Neutrality Index (INS), based on 1,000 model outputs.
📁 Open access: doi.org/10.5281/zenodo.15729518

ZenodoThe Grammar of Objectivity: Formal Mechanisms for the Illusion of Neutrality in Language ModelsAbstract Simulated neutrality in generative models produces tangible harms (ranging from erroneous treatments in clinical reports to rulings with no legal basis) by projecting impartiality without evidence. This study explains how Large Language Models (LLMs) and logic-based systems achieve neutralidad simulada through form, not meaning: passive voice, abstract nouns and suppressed agents mask responsibility while asserting authority. A balanced corpus of 1 000 model outputs was analysed: 600 medical texts from PubMed (2019-2024) and 400 legal summaries from Westlaw (2020-2024). Standard syntactic parsing tools identified structures linked to authority simulation. Example: a 2022 oncology note states “Treatment is advised” with no cited trial; a 2021 immigration decision reads “It was determined” without precedent. Two audit metrics are introduced, agency score (share of clauses naming an agent) and reference score (proportion of authoritative claims with verifiable sources). Outputs scoring below 0.30 on either metric are labelled high-risk; 64 % of medical and 57 % of legal texts met this condition. The framework runs in <0.1 s per 500-token output on a standard CPU, enabling real-time deployment. Quantifying this lack of syntactic clarity offers a practical layer of oversight for safety-critical applications. This work is also published with DOI reference in Figshare https://doi.org/10.6084/m9.figshare.29390885 and SSRN (In Process )   Resumen La neutralidad simulada en los modelos generativos produce daños tangibles, desde tratamientos erróneos en informes clínicos hasta sentencias sin fundamento jurídico, al proyectar imparcialidad sin evidencia. Este estudio analiza cómo los modelos de lenguaje de gran tamaño (LLM) y los sistemas lógicos reproducen dicha neutralidad mediante la forma y no el contenido. Patrones como la voz pasiva, los sustantivos abstractos y la supresión del agente ocultan la responsabilidad y, al mismo tiempo, afirman autoridad. Se examinó un corpus equilibrado de 1 000 salidas de modelo: 600 textos médicos de PubMed (2019-2024) y 400 resúmenes legales de Westlaw (2020-2024). Se emplearon herramientas estándar de análisis sintáctico para detectar estructuras asociadas con la simulación de autoridad. Por ejemplo, una nota oncológica de 2022 afirma «Se aconseja el tratamiento» sin citar ensayos clínicos; en un resumen migratorio de 2021 se lee «Se determinó» sin referencia a precedentes jurídicos. El artículo introduce dos métricas de auditoría: la puntuación de agencia, que mide la proporción de cláusulas con agente explícito, y la puntuación de referencia, que calcula el porcentaje de afirmaciones autoritativas respaldadas por fuentes verificables. Las salidas con valores inferiores a 0,30 en cualquiera de estas métricas se clasifican como de alto riesgo; el 64 % de los textos médicos y el 57 % de los jurídicos cumplen este criterio. El marco se ejecuta en menos de 0,1 segundos por salida de 500 tokens en una CPU estándar, lo que demuestra su viabilidad en tiempo real. Cuantificar esta falta de claridad sintáctica aporta una capa práctica de supervisión para aplicaciones críticas.
#LLM#AIethics#SyntacticAuthority
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