Nir Fresco | Ben Gurion University of the Negev (original) (raw)

Papers by Nir Fresco

Cognitive Science, 2024

How are new Bayesian hypotheses generated within the framework of predictive processing? This exp... more How are new Bayesian hypotheses generated within the framework of predictive processing? This explanatory framework purports to provide a unified, systematic explanation of cognition by appealing to Bayes rule and hierarchical Bayesian machinery alone. Given that the generation of new hypotheses is fundamental to Bayesian inference, the predictive processing framework faces an important challenge in this regard. By examining several cognitive-level and neurobiological architecture-inspired models of hypothesis generation, we argue that there is an essential difference between the two types of models. Cognitive-level models do not specify how they can be implemented in brains and include structures and assumptions that are external to the predictive processing framework. By contrast, neurobiological architecture-inspired models, which aim to resemble brain processes better, fail to explain important capacities of cognition, such as categorisation and few-shot learning. The ('scaling-up') challenge for proponents of predictive processing is to explain the relationship between these two types of models using only the theoretical and conceptual machinery of Bayesian inference.

Psychonomic Bulletin & Review

Automaticity is still ill-understood, and its relation to habit formation and skill acquisition i... more Automaticity is still ill-understood, and its relation to habit formation and skill acquisition is highly debated. Recently, the principle of caching has been advanced as a potentially promising avenue for studying automaticity. It is roughly understood as a means of storing direct input-output associations in a manner that supports instant lookup. We raise various concerns that should be addressed before the theoretical progress afforded by this principle can be evaluated. Is caching merely a metaphor for computer caching or is it a computational model that can be used to derive testable predictions? How do the short-term and long-term effects of automaticity relate to the distinction between working memory and long-term memory? Does caching apply to stimulus-response associations—as already suggested by Logan’s instance theory—or to algorithms, too? How much experience is required for caching and how does caching depend on the task’s type? What is the relation between control processes and caching as these pertain to the possible suppression of automatic processes? Dealing with these questions will arguably also advance our understanding of automaticity.

Biology and Philosophy

Computational physical systems may exhibit indeterminacy of computation (IC). Their identified ph... more Computational physical systems may exhibit indeterminacy of computation (IC). Their identified physical dynamics may not suffice to select a unique computational profile. We consider this phenomenon from the point of view of cognitive science and examine how computational profiles of cognitive systems are identified and justified in practice, in the light of IC. To that end, we look at the literature on the underdetermination of theory by evidence (UTE) and argue that the same devices that can be successfully employed to confirm physical hypotheses can also be used to rationally single out computational profiles, notwithstanding IC.

Studies in Applied Philosophy, Epistemology and Rational Ethics, 2014

Synthese, 2021

Do the dynamics of a physical system determine what function the system computes? Except in speci... more Do the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question 'What does a particular neural system do?' is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon lends some support to the idea that a single neural structure may perform multiple cognitive functions, each subserved by a different computation. We provide an overarching conceptual framework in order to further the philosophical debate on the nature of computational indeterminacy and computational explanation.

American Philosophical Quarterly, 2020

The idea that the brain is an information processing system raises some challenging questions abo... more The idea that the brain is an information processing system raises some challenging questions about whether information exists independently of brains. Answering these questions is relevant for clarifying the theoretical foundations of the sciences of mind and brain, but also for appropriately interpreting and evaluating the evidence about how brains—and other biological systems—work. This article claims that (1) informational descriptions in the sciences of mind and brain can be genuinely explanatory, despite assuming a mind-dependent notion of information; and (2) that Popperian objectivity is sufficient for the explanatory role that information often plays in these sciences. Hierarchical predictive processing, which has become a central theoretical paradigm for neurobehavioural research, is used as a case study for supporting these two claims.

The British Journal for Philosophy of Science

Is the mathematical function being computed by a given physical system determined by the system’s... more Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with reference to the debate over realism about physical computation and computationalism. A welcome exception is Dewhurst’s ([2018]) recent analysis of computational individuation under the mechanistic framework. He rejects the idea of appealing to semantic properties for determining the computational identity of a physical system. But Dewhurst seems to be too quick to pay the price of giving up the notion of computational equivalence. We aim to show that the mechanist need not pay this price. The mechanistic framework can, in principle, preserve the idea of computational equivalence even between two different enough kinds of physical systems, say, electrical and hydraulic ones.

Review of Philosophy and Psychology

There are many different notions of information in logic, epistemology, psychology, biology and c... more There are many different notions of information in logic, epistemology, psychology, biology and cognitive science that are employed differently in each discipline—often with little overlap. Since our interest here is in biological processes and organisms, we develop a taxonomy of functional information that extends the standard cue/signal distinction (as it is used in animal communication theory). Three general, main claims are advanced here. (1) This new taxonomy can be useful in describing learning and communication. (2) It avoids some problems that the natural/non-natural information distinction faces. (3) Functional information is produced through exploration processes followed by stabilisation processes.

Claims that computation is a form of information processing are common in computer and cognitive ... more Claims that computation is a form of information processing are common in computer and cognitive sciences. Unsurprisingly, the notions of 'information' and 'computation' have become intimately intertwined. On the instructional information processing account, digital computation is a form of information processing. However, this account faces several problems, which stem from adopting Floridi's conceptual framework of information, that are discussed here. We briefly examine Corning's theory of control information as an alternative to Floridi's framework. Since both are found unsuitable for the task of explaining computation as a form of information processing, another conceptual framework is defended, namely, that of functional information.

In this article we establish three claims: (1) When the target software is proprietary, in the ab... more In this article we establish three claims: (1) When the target software is proprietary, in the absence of other overriding ethical considerations, the identification of a vulnerability and the development, sale, and purchase of non-zero-day exploits are ethically justified; (2) when the target software is Free/Libre/Open Source, the buying and selling of vulnerabilities can be ethically justified only in a very narrow situation, while the sale and purchase of non-zero-day exploits is ethically justified absent of any other overriding information; and (3) democratic governments should promote legislation that either incentivizes corporate in-house vulnerability identification and mitigation programs or requires firms to more fully absorb the societal costs of insecure software.

Is information always true? According to some authors, including Dretske, Grice, Barwise, and rec... more Is information always true? According to some authors, including Dretske, Grice, Barwise, and recently, Floridi, who has defended the Veridicality Thesis, the answer is positive. For, on Floridi’s view, there is an intimate relation between information and knowledge, which is always true. It is argued in this article that information used in inferential knowledge can, nevertheless, be false, thereby showing that the Veridicality thesis is false.

Floridi’s Theory of Strongly Semantic Information posits the Veridicality Thesis (i.e., informati... more Floridi’s Theory of Strongly Semantic Information posits the Veridicality Thesis (i.e., information is true). One motivation is that it can serve as a foundation for information-based epistemology being an alternative to the tripartite theory of knowledge. However, the Veridicality thesis is false, if ‘information’ is to play an explanatory role in human cognition. Another motivation is avoiding the so-called Bar-Hillel/Carnap paradox (i.e., any contradiction is maximally informative). But this paradox only seems paradoxical, if (a) ‘information’ and ‘informativeness’ are synonymous, (b) logic is a theory of inference, or (c) validity suffices for rational inference. We argue that (a), (b) and (c) are false.

Society for the Philosophy of Information, Nov 22, 2013

The distinction between knowledge-how and knowledge-that has long been debated in the literature.... more The distinction between knowledge-how and knowledge-that has long been debated in the literature. This distinction can, arguably, be better understood in terms of a more fundamental distinction between information-how and information-that. Information-how is prescriptive and informs a cognitive agent about which action(s) can be performed to achieve a particular outcome. Information-that is descriptive and informs the agent about events, objects and states of affairs in the world. Since the latter has received more attention in the literature, this article focuses on the former. We offer a new account of information-how that answers the question: ‘When do data qualify as information-how?’.

Artefacts do not always do what they are supposed to do, due to a variety of reasons, including m... more Artefacts do not always do what they are supposed to do, due to a variety of reasons, including manufacturing problems, poor maintenance, and normal wear-and-tear. Since software is an artefact, it should be subject to malfunctioning in the same sense in which other artefacts can malfunction. Yet, whether software is on a par with other artefacts when it comes to malfunctioning crucially depends on the abstraction used in the analysis. We distinguish between “negative” and “positive” notions of malfunction. A negative malfunction, or dysfunction, occurs when an artefact token either does not (sometimes) or cannot (ever) do what it is supposed to do. A positive malfunction, or misfunction, occurs when an artefact token may do what is supposed to do but, at least occasionally, it also yields some unintended and undesirable effects. We argue that software, understood as type, may misfunction in some limited sense, but cannot dysfunction. Accordingly, one should distinguish software from other technical artefacts, in view
of their design that makes dysfunction impossible for the former, while possible for the latter.

The question ‘What is computation?’ might seem a trivial one to many, but this is far from being ... more The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of an observer choosing to view it as such. According to one view, which we dub bold anti-realist pancomputationalism, every physical object (can be said to) computes every computer program. According to another, more modest view, some computational systems can be ascribed multiple computational descriptions. We argue that the first view is misguided, and that the second view need not entail observer-relativity of computation. At least to a large extent, computation is an objective phenomenon. Construed as a form of information processing, we argue that information-processing considerations determine what type of computation takes place in physical systems.

Synthese, May 2014

What is nontrivial digital computation? It is the processing of discrete data through discrete st... more What is nontrivial digital computation? It is the processing of discrete data through discrete state transitions in accordance with finite instructional information. The motivation for our account is that many previous attempts to answer this question are inadequate, and also that this account accords with the common intuition that digital computation is a type of information processing. We use the notion of reachability in a graph to defend this characterization in memory-based systems and underscore the importance of instructional information for digital computation. We argue that our account evaluates positively against adequacy criteria for accounts of computation.

Mnds & Machines, Feb 2014

There has been an ongoing conflict regarding whether reality is fundamentally digital or analogue... more There has been an ongoing conflict regarding whether reality is fundamentally digital or analogue. Recently, Floridi has argued that this dichotomy is misapplied. For any attempt to analyse noumenal reality independently of any level of abstraction at which the analysis is conducted is mistaken. In the pars destruens of this paper, we argue that Floridi does not establish that it is only levels of abstraction that are analogue or digital, rather than noumenal reality. In the pars construens of this paper, we reject a classification of noumenal reality as a deterministic discrete computational system. We show, based on considerations from classical physics, why a deterministic computational view of the universe faces problems (e.g., a reversible computational universe cannot be strictly deterministic).

The phenomenon of digital computation is explained (often differently) in computer science, compu... more The phenomenon of digital computation is explained (often differently) in computer science, computer engineering and more broadly in cognitive science. Although the semantics and implications of malfunctions have received attention in the philosophy of biology and philosophy of technology, errors in computational systems remain of interest only to computer science. Miscomputation has not gotten the philosophical attention it deserves. Our paper fills this gap by offering a taxonomy of miscomputations. This taxonomy is underpinned by a conceptual analysis of the design and implementation of conventional computational systems at various levels of abstraction. It shows that ‘malfunction’ as it is typically used in the philosophy of artefacts only represents one type of miscomputation.

Cognitive Science, 2024

How are new Bayesian hypotheses generated within the framework of predictive processing? This exp... more How are new Bayesian hypotheses generated within the framework of predictive processing? This explanatory framework purports to provide a unified, systematic explanation of cognition by appealing to Bayes rule and hierarchical Bayesian machinery alone. Given that the generation of new hypotheses is fundamental to Bayesian inference, the predictive processing framework faces an important challenge in this regard. By examining several cognitive-level and neurobiological architecture-inspired models of hypothesis generation, we argue that there is an essential difference between the two types of models. Cognitive-level models do not specify how they can be implemented in brains and include structures and assumptions that are external to the predictive processing framework. By contrast, neurobiological architecture-inspired models, which aim to resemble brain processes better, fail to explain important capacities of cognition, such as categorisation and few-shot learning. The ('scaling-up') challenge for proponents of predictive processing is to explain the relationship between these two types of models using only the theoretical and conceptual machinery of Bayesian inference.

Psychonomic Bulletin & Review

Automaticity is still ill-understood, and its relation to habit formation and skill acquisition i... more Automaticity is still ill-understood, and its relation to habit formation and skill acquisition is highly debated. Recently, the principle of caching has been advanced as a potentially promising avenue for studying automaticity. It is roughly understood as a means of storing direct input-output associations in a manner that supports instant lookup. We raise various concerns that should be addressed before the theoretical progress afforded by this principle can be evaluated. Is caching merely a metaphor for computer caching or is it a computational model that can be used to derive testable predictions? How do the short-term and long-term effects of automaticity relate to the distinction between working memory and long-term memory? Does caching apply to stimulus-response associations—as already suggested by Logan’s instance theory—or to algorithms, too? How much experience is required for caching and how does caching depend on the task’s type? What is the relation between control processes and caching as these pertain to the possible suppression of automatic processes? Dealing with these questions will arguably also advance our understanding of automaticity.

Biology and Philosophy

Computational physical systems may exhibit indeterminacy of computation (IC). Their identified ph... more Computational physical systems may exhibit indeterminacy of computation (IC). Their identified physical dynamics may not suffice to select a unique computational profile. We consider this phenomenon from the point of view of cognitive science and examine how computational profiles of cognitive systems are identified and justified in practice, in the light of IC. To that end, we look at the literature on the underdetermination of theory by evidence (UTE) and argue that the same devices that can be successfully employed to confirm physical hypotheses can also be used to rationally single out computational profiles, notwithstanding IC.

Studies in Applied Philosophy, Epistemology and Rational Ethics, 2014

Synthese, 2021

Do the dynamics of a physical system determine what function the system computes? Except in speci... more Do the dynamics of a physical system determine what function the system computes? Except in special cases, the answer is no: it is often indeterminate what function a given physical system computes. Accordingly, care should be taken when the question 'What does a particular neural system do?' is answered by hypothesising that the system computes a particular function. The phenomenon of the indeterminacy of computation has important implications for the development of computational explanations of biological systems. Additionally, the phenomenon lends some support to the idea that a single neural structure may perform multiple cognitive functions, each subserved by a different computation. We provide an overarching conceptual framework in order to further the philosophical debate on the nature of computational indeterminacy and computational explanation.

American Philosophical Quarterly, 2020

The idea that the brain is an information processing system raises some challenging questions abo... more The idea that the brain is an information processing system raises some challenging questions about whether information exists independently of brains. Answering these questions is relevant for clarifying the theoretical foundations of the sciences of mind and brain, but also for appropriately interpreting and evaluating the evidence about how brains—and other biological systems—work. This article claims that (1) informational descriptions in the sciences of mind and brain can be genuinely explanatory, despite assuming a mind-dependent notion of information; and (2) that Popperian objectivity is sufficient for the explanatory role that information often plays in these sciences. Hierarchical predictive processing, which has become a central theoretical paradigm for neurobehavioural research, is used as a case study for supporting these two claims.

The British Journal for Philosophy of Science

Is the mathematical function being computed by a given physical system determined by the system’s... more Is the mathematical function being computed by a given physical system determined by the system’s dynamics? This question is at the heart of the indeterminacy of computation phenomenon (Fresco et al. [unpublished]). A paradigmatic example is a conventional electrical AND-gate that is often said to compute conjunction, but it can just as well be used to compute disjunction. Despite the pervasiveness of this phenomenon in physical computational systems, it has been discussed in the philosophical literature only indirectly, mostly with reference to the debate over realism about physical computation and computationalism. A welcome exception is Dewhurst’s ([2018]) recent analysis of computational individuation under the mechanistic framework. He rejects the idea of appealing to semantic properties for determining the computational identity of a physical system. But Dewhurst seems to be too quick to pay the price of giving up the notion of computational equivalence. We aim to show that the mechanist need not pay this price. The mechanistic framework can, in principle, preserve the idea of computational equivalence even between two different enough kinds of physical systems, say, electrical and hydraulic ones.

Review of Philosophy and Psychology

There are many different notions of information in logic, epistemology, psychology, biology and c... more There are many different notions of information in logic, epistemology, psychology, biology and cognitive science that are employed differently in each discipline—often with little overlap. Since our interest here is in biological processes and organisms, we develop a taxonomy of functional information that extends the standard cue/signal distinction (as it is used in animal communication theory). Three general, main claims are advanced here. (1) This new taxonomy can be useful in describing learning and communication. (2) It avoids some problems that the natural/non-natural information distinction faces. (3) Functional information is produced through exploration processes followed by stabilisation processes.

Claims that computation is a form of information processing are common in computer and cognitive ... more Claims that computation is a form of information processing are common in computer and cognitive sciences. Unsurprisingly, the notions of 'information' and 'computation' have become intimately intertwined. On the instructional information processing account, digital computation is a form of information processing. However, this account faces several problems, which stem from adopting Floridi's conceptual framework of information, that are discussed here. We briefly examine Corning's theory of control information as an alternative to Floridi's framework. Since both are found unsuitable for the task of explaining computation as a form of information processing, another conceptual framework is defended, namely, that of functional information.

In this article we establish three claims: (1) When the target software is proprietary, in the ab... more In this article we establish three claims: (1) When the target software is proprietary, in the absence of other overriding ethical considerations, the identification of a vulnerability and the development, sale, and purchase of non-zero-day exploits are ethically justified; (2) when the target software is Free/Libre/Open Source, the buying and selling of vulnerabilities can be ethically justified only in a very narrow situation, while the sale and purchase of non-zero-day exploits is ethically justified absent of any other overriding information; and (3) democratic governments should promote legislation that either incentivizes corporate in-house vulnerability identification and mitigation programs or requires firms to more fully absorb the societal costs of insecure software.

Is information always true? According to some authors, including Dretske, Grice, Barwise, and rec... more Is information always true? According to some authors, including Dretske, Grice, Barwise, and recently, Floridi, who has defended the Veridicality Thesis, the answer is positive. For, on Floridi’s view, there is an intimate relation between information and knowledge, which is always true. It is argued in this article that information used in inferential knowledge can, nevertheless, be false, thereby showing that the Veridicality thesis is false.

Floridi’s Theory of Strongly Semantic Information posits the Veridicality Thesis (i.e., informati... more Floridi’s Theory of Strongly Semantic Information posits the Veridicality Thesis (i.e., information is true). One motivation is that it can serve as a foundation for information-based epistemology being an alternative to the tripartite theory of knowledge. However, the Veridicality thesis is false, if ‘information’ is to play an explanatory role in human cognition. Another motivation is avoiding the so-called Bar-Hillel/Carnap paradox (i.e., any contradiction is maximally informative). But this paradox only seems paradoxical, if (a) ‘information’ and ‘informativeness’ are synonymous, (b) logic is a theory of inference, or (c) validity suffices for rational inference. We argue that (a), (b) and (c) are false.

Society for the Philosophy of Information, Nov 22, 2013

The distinction between knowledge-how and knowledge-that has long been debated in the literature.... more The distinction between knowledge-how and knowledge-that has long been debated in the literature. This distinction can, arguably, be better understood in terms of a more fundamental distinction between information-how and information-that. Information-how is prescriptive and informs a cognitive agent about which action(s) can be performed to achieve a particular outcome. Information-that is descriptive and informs the agent about events, objects and states of affairs in the world. Since the latter has received more attention in the literature, this article focuses on the former. We offer a new account of information-how that answers the question: ‘When do data qualify as information-how?’.

Artefacts do not always do what they are supposed to do, due to a variety of reasons, including m... more Artefacts do not always do what they are supposed to do, due to a variety of reasons, including manufacturing problems, poor maintenance, and normal wear-and-tear. Since software is an artefact, it should be subject to malfunctioning in the same sense in which other artefacts can malfunction. Yet, whether software is on a par with other artefacts when it comes to malfunctioning crucially depends on the abstraction used in the analysis. We distinguish between “negative” and “positive” notions of malfunction. A negative malfunction, or dysfunction, occurs when an artefact token either does not (sometimes) or cannot (ever) do what it is supposed to do. A positive malfunction, or misfunction, occurs when an artefact token may do what is supposed to do but, at least occasionally, it also yields some unintended and undesirable effects. We argue that software, understood as type, may misfunction in some limited sense, but cannot dysfunction. Accordingly, one should distinguish software from other technical artefacts, in view
of their design that makes dysfunction impossible for the former, while possible for the latter.

The question ‘What is computation?’ might seem a trivial one to many, but this is far from being ... more The question ‘What is computation?’ might seem a trivial one to many, but this is far from being in consensus in philosophy of mind, cognitive science and even in physics. The lack of consensus leads to some interesting, yet contentious, claims, such as that cognition or even the universe is computational. Some have argued, though, that computation is a subjective phenomenon: whether or not a physical system is computational, and if so, which computation it performs, is entirely a matter of an observer choosing to view it as such. According to one view, which we dub bold anti-realist pancomputationalism, every physical object (can be said to) computes every computer program. According to another, more modest view, some computational systems can be ascribed multiple computational descriptions. We argue that the first view is misguided, and that the second view need not entail observer-relativity of computation. At least to a large extent, computation is an objective phenomenon. Construed as a form of information processing, we argue that information-processing considerations determine what type of computation takes place in physical systems.

Synthese, May 2014

What is nontrivial digital computation? It is the processing of discrete data through discrete st... more What is nontrivial digital computation? It is the processing of discrete data through discrete state transitions in accordance with finite instructional information. The motivation for our account is that many previous attempts to answer this question are inadequate, and also that this account accords with the common intuition that digital computation is a type of information processing. We use the notion of reachability in a graph to defend this characterization in memory-based systems and underscore the importance of instructional information for digital computation. We argue that our account evaluates positively against adequacy criteria for accounts of computation.

Mnds & Machines, Feb 2014

There has been an ongoing conflict regarding whether reality is fundamentally digital or analogue... more There has been an ongoing conflict regarding whether reality is fundamentally digital or analogue. Recently, Floridi has argued that this dichotomy is misapplied. For any attempt to analyse noumenal reality independently of any level of abstraction at which the analysis is conducted is mistaken. In the pars destruens of this paper, we argue that Floridi does not establish that it is only levels of abstraction that are analogue or digital, rather than noumenal reality. In the pars construens of this paper, we reject a classification of noumenal reality as a deterministic discrete computational system. We show, based on considerations from classical physics, why a deterministic computational view of the universe faces problems (e.g., a reversible computational universe cannot be strictly deterministic).

The phenomenon of digital computation is explained (often differently) in computer science, compu... more The phenomenon of digital computation is explained (often differently) in computer science, computer engineering and more broadly in cognitive science. Although the semantics and implications of malfunctions have received attention in the philosophy of biology and philosophy of technology, errors in computational systems remain of interest only to computer science. Miscomputation has not gotten the philosophical attention it deserves. Our paper fills this gap by offering a taxonomy of miscomputations. This taxonomy is underpinned by a conceptual analysis of the design and implementation of conventional computational systems at various levels of abstraction. It shows that ‘malfunction’ as it is typically used in the philosophy of artefacts only represents one type of miscomputation.

There are currently considerable confusion and disarray about just how we should view computation... more There are currently considerable confusion and disarray about just how we should view computationalism, connectionism and dynamicism as explanatory frameworks in cognitive science. A key source of this ongoing conflict among the central paradigms in cognitive science is an equivocation on the notion of computation simpliciter. ‘Computation’ is construed differently by computationalism, connectionism, dynamicism and computational neuroscience. I claim that these central paradigms, properly understood, can contribute to an integrative cognitive science. Yet, before this claim can be defended, a better understanding of ‘computation’ is required.
‘Digital computation’ is an ambiguous concept. It is not just the classical dichotomy between analogue and digital computation that is the basis for the equivocation on ‘computation’ simpliciter in cognitive science, but also the diversity of extant accounts of digital computation. What does it take for a physical system to perform digital computation? There are many answers to this question ranging from Turing machine computation, through the formal manipulation of symbols, the execution of algorithms and others, to strong pancomputationalism, according to which every physical system computes every Turing-computable function. Despite some overlap among them, extant accounts of concrete digital computation are intensionally and extensionally non- equivalent, thereby rendering ‘digital computation’ ambiguous.
The objective of this book is twofold. First, it is to promote a clearer understanding of concrete digital computation. Accordingly, the main underlying thesis of the book is that not only are extant accounts of concrete digital computation non-equivalent, but most of them are inadequate. In the course of examining several key accounts of concrete digital computation, I also propose the instructional information processing account, according to which nontrivial digital computation is the processing of discrete data in accordance with finite instructional information. The second objective is to establish the foundational role of computation in cognitive science whilst rejecting the extrinsically representational nature of computation proper.

This book introduces key topics in the philosophy of information, written by the PI research netw... more This book introduces key topics in the philosophy of information, written by the PI research network of the Society for the Philosophy of Information.

Beta version published 2012, first version published 2013.

This is a book note of Piccinini's "Physical Computation: a mechanistic account".