Subjectivity, Bayesianism, and causality
نویسنده
چکیده
Bayesian probability theory is one of the most successful frameworks to model reasoning under uncertainty. Its defining property is the interpretation of probabilities as degrees of belief in propositions about the state of the world relative to an inquiring subject. This essay examines the notion of subjectivity by drawing parallels between Lacanian theory and Bayesian probability theory, and concludes that the latter must be enriched with causal interventions to model agency. The central contribution of this work is an abstract model of the subject that accommodates causal interventions in a measuretheoretic formalisation that is more general than causal graphs. This formalisation is obtained through a game-theoretic Ansatz based on modelling the inside and outside of the subject as an extended game with imperfect information between two players. Finally, I illustrate the expressiveness of this model with an example of causal induction.
منابع مشابه
Connecting Consciousness to Physical Causality: Abhinavagupta’s Phenomenology of Subjectivity and Tononi’s Integrated Information Theory
This article demonstrates remarkably similar methods for linking mind and body to address the “hard problem” in the work of 11th-century Indian philosopher Abhinavagupta with a currently prominent neuroscienctific theory, Tononi’s Integrated Information Theory 3.0. Both Abhinavagupta and Tononi and Christof Koch hinge their theories on the identity of phenomenal subjective experience with causa...
متن کاملCausality and subjectivity in discourse: The meaning and use of causal connectives in spontaneous conversation, chat interactions and written text
Many languages of the world have connectives to express causal rela tions at the discourse level. Often, language users systematically prefer one lexi cal item (because) over another (even highly similar) one (since) to express a causal relationship. Such choices provide a window on speakers’ cognitive cate gorizations, and have been modeled in previous work in terms of subjectivity. However...
متن کاملBayesianism and Information
Bayesianism is a theory of inductive inference that makes use of the mathematical theory of probability. Bayesians usually hold that the relevant probabilities should be interpreted in terms of rational degrees of belief. This still leaves much scope for disagreement, since there is no consensus about what norms govern rational degrees of belief. In this chapter, we first provide an introductio...
متن کاملCentre for Philosophy of Natural and Social Science Causality: Metaphysics and Methods
How ought we learn causal relationships? While Popper advocated a hypothetico-deductive logic of causal discovery, inductive accounts are currently in vogue. Many inductive approaches depend on the causal Markov condition as a fundamental assumption. This condition, I maintain, is not universally valid, though it is justifiable as a default assumption. In which case the results of the inductive...
متن کاملResponsible subjects and discourse causality. How mental spaces and perspective help identifying subjectivity in Dutch backward causal connectives
The Basic Communicative Spaces Network (BCSN – Sanders et al., 2009) accounts for crucial semantic–pragmatic characteristics of causal relations expressed by frequently used Dutch causal connectives. BCSN integrates subjectivity theory, domain theory, and mental spaces theory to explain their linguistic categorization. Starting with the original three-way classification of content, epistemic, a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Pattern Recognition Letters
دوره 64 شماره
صفحات -
تاریخ انتشار 2015