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Related papers: Falsification and consciousness

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The spread of disinformation (maliciously spread false information) in online social networks has become an important problem in today's society. Disinformation's spread is facilitated by the fact that individuals often accept false…

Physics and Society · Physics 2025-04-15 Corbit R. Sampson , Juan G. Restrepo

Beliefs are not facts, but they are factive - they feel like facts. This property is what can make misinformation dangerous. Being able to deliberately navigate through a landscape of often conflicting factive statements is difficult when…

Human-Computer Interaction · Computer Science 2019-07-12 Philip Feldman , Aaron Dant , Wayne Lutters

There currently exists a gap between the theories proposed by the probability and uncertainty and the needs of Artificial Intelligence research. These theories primarily address the needs of expert systems, using knowledge structures which…

Artificial Intelligence · Computer Science 2013-04-12 Brian Falkenhainer

A long noted difficulty when assessing the reliability (or calibration) of forecasting systems is that reliability, in general, is a hypothesis not about a finite dimensional parameter but about an entire functional relationship. A…

Data Analysis, Statistics and Probability · Physics 2020-12-09 Jochen Bröcker

The no-supervenience theorem limits the capacity of physicalist theories to provide a comprehensive account of human consciousness. The proof of the theorem is difficult to formalize because it relies on both alethic and epistemic notions…

Neurons and Cognition · Quantitative Biology 2024-11-13 Cathy M Reason

Interpretability research takes counterfactual theories of causality for granted. Most causal methods rely on counterfactual interventions to inputs or the activations of particular model components, followed by observations of the change…

Machine Learning · Computer Science 2024-07-08 Aaron Mueller

This paper is a shortened version of the full paper that was published in the journal Frontiers of Psychology in May 2022. In recent decades, the scientific study of consciousness has significantly increased our understanding of this…

Neurons and Cognition · Quantitative Biology 2025-02-21 Nir Lahav , Zachariah A. Neemeh

Transparency is a fundamental requirement for decision making systems when these should be deployed in the real world. It is usually achieved by providing explanations of the system's behavior. A prominent and intuitive type of explanations…

Machine Learning · Computer Science 2021-07-23 André Artelt , Valerie Vaquet , Riza Velioglu , Fabian Hinder , Johannes Brinkrolf , Malte Schilling , Barbara Hammer

If we take the subjective character of consciousness seriously, consciousness becomes a matter of "being" rather than "doing". Because "doing" can be dissociated from "being", functional criteria alone are insufficient to decide whether a…

Neurons and Cognition · Quantitative Biology 2021-02-10 Larissa Albantakis , Giulio Tononi

In this paper the theory of flexibly-bounded rationality which is an extension to the theory of bounded rationality is revisited. Rational decision making involves using information which is almost always imperfect and incomplete together…

Artificial Intelligence · Computer Science 2013-06-11 Tshilidzi Marwala

Evaluating artificial systems for signs of consciousness is increasingly becoming a pressing concern, and a rigorous psychometric measurement framework may be of crucial importance in evaluating large language models in this regard. Most…

Neurons and Cognition · Quantitative Biology 2023-09-08 Igor Ševo

The quest for a scientific description of consciousness has given rise to new theoretical and empirical paradigms for the investigation of phenomenological contents as well as clinical disorders of consciousness. An outstanding challenge in…

Neurons and Cognition · Quantitative Biology 2018-01-12 Xerxes D. Arsiwalla , Paul Verschure

Probability theory, epistemically interpreted, provides an excellent, if not the best available account of inductive reasoning. This is so because there are general and definite rules for the change of subjective probabilities through…

Artificial Intelligence · Computer Science 2013-04-10 Wolfgang Spohn

For obtaining causal inferences that are objective, and therefore have the best chance of revealing scientific truths, carefully designed and executed randomized experiments are generally considered to be the gold standard. Observational…

Applications · Statistics 2008-11-12 Donald B. Rubin

Counterfactual explanations are widely used to interpret machine learning predictions by identifying minimal changes to input features that would alter a model's decision. However, most existing counterfactual methods have not been tested…

Machine Learning · Computer Science 2026-02-03 Leonidas Christodoulou , Chang Sun

Established frameworks to understand problems with reproducibility in science begin with the relationship between our understanding of the prior probability of a claim and the statistical certainty that should be demanded of it, and explore…

Other Statistics · Statistics 2022-05-30 Maria Chikina , Wesley Pegden

In science and medicine, model interpretations may be reported as discoveries of natural phenomena or used to guide patient treatments. In such high-stakes tasks, false discoveries may lead investigators astray. These applications would…

Machine Learning · Statistics 2020-08-18 Collin Burns , Jesse Thomason , Wesley Tansey

A knowledge system S describing a part of real world does in general not contain complete information. Reasoning with incomplete information is prone to errors since any belief derived from S may be false in the present state of the world.…

Artificial Intelligence · Computer Science 2011-05-20 Eliezer L. Lozinskii

The evolution of the human mind through natural selection mandates that our conscious experiences are causally potent in order to leave a tangible impact upon the surrounding physical world. Any attempt to construct a functional theory of…

Neurons and Cognition · Quantitative Biology 2024-05-10 Danko D. Georgiev

As causal ground truth is incredibly rare, causal discovery algorithms are commonly only evaluated on simulated data. This is concerning, given that simulations reflect preconceptions about generating processes regarding noise…