Today on YouTube I published a recent interview of me by James Ellias on causality, induction, and probability. (James published a different interview of me, on a narrower subject, a few weeks ago on his Inductica channel.) See the interview and description below.

How do we build knowledge from the evidence of the senses—and how can we know not only what we know, but how well we know it?

In this conversation with James Ellias, I discuss part of the epistemology developed in my book A Validation of Knowledge: A New, Objective Theory of Axioms, Causality, Meaning, Propositions, Mathematics, and Induction. James and I discuss the philosophical basis of causality, the validation of induction, and the role of probability in measuring the reliability of our conclusions.

The discussion begins with knowledge of existence and consciousness and with my argument that causality is known most directly in reality’s action on consciousness. From there we consider how we identify entities, why recognition of entities is not itself on the same epistemological level as sensory evidence, and how our knowledge of causality can be extended to causal relations among entities.

We then turn to induction. What justifies treating past instances as evidence for future ones? I argue that the mere passage from past to future introduces no new causal factor: time is not an entity acting on things. The relevant question is whether the causal conditions applicable to past instances also apply to the future instance.

Probability then becomes part of the epistemological issue: not merely whether we know a conclusion, but how reliably we know it in a given context. We discuss Bayesian reasoning and my proposed philosophical basis for assigning a prior probability to causality; nonparametric predictive inference; the work of Harold Jeffreys, Bruce Hill, and Frank Coolen; Ayn Rand’s identification of characteristics as ranges of measurement; Peter Gärdenfors’s related use of convexity; and the use of causal integration to increase the reliability of inductive conclusions.

In summary, the argument presented in the video proceeds as follows:

– The fact that existence causes our consciousness of it teaches us that causality exists.

– Our ability to perceive entities teaches us that causality is regular.

– Induction gives us a probability calculus to validate causality more broadly and to measure our ability to predict specific causal relations.

A Validation of Knowledge

The complete argument is developed step by step in my book. An interview necessarily skips many intermediate steps on which the conclusions depend, so viewers who want to evaluate the theory seriously are encouraged to read the book:

The book presents an epistemology of how to take the evidence of the senses and form concepts, statements, sequences of statements, and a corpus of knowledge that is true, organized, readily applicable to new situations, and conducive to the discovery of new knowledge.

In the book, I draw heavily from Ayn Rand’s theory of concepts as presented in her book, Introduction to Objectivist Epistemology, but I depart from her epistemology—especially as explicated by leading exponents of her philosophy—in important ways. Areas of departure include the perception of entities and the role of probability theory in epistemology.

My book is primarily for a specialized readership—familiar with epistemological ideas and with Ayn Rand’s theory of concepts in particular. The last third of the book uses probability theory and mathematics somewhat beyond basic calculus, but less mathematical explanations are also included to make the general ideas accessible to lay readers.

My 2009 Philosophy of Science article

A portion of my probabilistic theory of induction was published in my 2009 article, “Past Longevity as Evidence for the Future,” in Philosophy of Science. The article applies nonparametric predictive inference to the question of how past observations provide evidence for future ones. The book presents the much broader epistemological foundation within which that work belongs.

Article:
https://www.jstor.org/stable/10.1086/599273

Chapters

0:00 Why write A Validation of Knowledge?
2:54 Existence and consciousness
10:32 The “rejoice of consciousness”: knowing causality directly
14:41 Sensory evidence and the identification of entities
34:19 How do we know—and how well?
35:31 Hume, time, and the move from past to future
42:11 Probability as an epistemological measure
48:02 A philosophical basis for Bayesian priors
53:42 Nonparametric predictive inference
1:05:36 Characteristics as ranges of measurement
1:10:20 Convexity and inductive inference
1:21:06 Aircraft safety, probability, and context
1:35:53 Integration, causes, and increasing certainty
1:38:20 Closing

More

My website:
https://www.ronpisaturo.com/

James Ellias’s Inductica channel:
https://www.youtube.com/@Inductica/videos

A related earlier conversation with James:
https://www.youtube.com/watch?v=ZXPsGD_-aPw

#Epistemology #Induction #PhilosophyOfScience