Biosemiotics deal with the study of signs and meanings in living entities. Constructivism considers human knowledge as internally constructed by sense making rather than passively reflecting a pre-existing reality. Consequently, a constructivist perspective on biosemiotics leads to look at an internal active construction of meaning in living entities from basic life to humans. That subject is addressed with an existing tool: the Meaning Generator System (MGS) which is a system submitted to an internal constraint related to the nature of the (...) agent containing it (biological or artificial). Simple organisms generate meanings to satisfy a “stay alive” constraint. More complex living entities manage meaningful representations with more elaborated constraints. The generated meanings are used by the agents to implement actions aimed at satisfying the constraints. The actions can be physical, biological or mental and take place in the agent or in its environment. The case of human agency is introduced with meaningful representations that may have allowed our ancestors to become self-conscious by representing themselves as existing entities. This paper proposes to use the MGS as a thread to address the above items linking biosemiotics to constructivism with relations to normativity, agency and autonomy. Possible continuations are introduced. (shrink)

The presentation proposes to complement an existing development on meaning generation for animals, humans and artificial agents by looking at what could have existed at pre-biotic times and what could be a post-human meaning generation. The core of the approach is based on an existing model for meaning generation: the Meaning Generator System (MGS). The MGS is part of an agent submitted to an internal constraint. The MGS generates a meaning when it receives information that has a connection with the (...) constraint. The generated meaning is used by the agent to implement an action (physical, biological or mental) aimed at satisfying the constraint. The action can be in or out the agent. The purpose of the presentation is to widen the MGS approach in order to reach a coverage for information, constraint and meaning from a pre-biotic level to a possible post-human one. We present the MGS for animals, humans and artificial agents with the corresponding constraints. We then look at what could have been a constraint at a pre-biotic far from thermodynamic equilibrium level. At the other end of the spectrum we look at a possible post-human status with an evolution of a ‘limit anxiety’ human constraint and also with AAs submitted to animal or human type constraints. Such approach links information science with physics, evolution, anthropology, semiotics and human mind. Continuations are proposed. (shrink)

One of the mains challenges of biosemiotics is ‘to attempt to naturalize biological meaning’ [Sharov & all 2015]. That challenge brings to look at a possible evolutionary thread for biosemiotics based on meaning generation for internal constraint satisfaction, starting with a pre-biotic entity emerging from a material universe. Such perspective complements and extends previous works that used a model of meaning generation for internal constraint satisfaction (the Meaning Generator System) [Menant 2003a, b; 2011]. We propose to look at such (...) an evolutionary thread for biosemiotics in three steps. The first step presents the proposed emergence of a pre-biotic entity as a far from thermodynamic equilibrium volume constrained to maintains its status [Menant 2015]. Such constraint dependence introduces natural links with teleology and with meaning generation. It also introduces perspectives for evolutionary origins of agency, self, and autonomy, coming in addition to other biosemiotic perspectives [Tønnessen, 2015]. The next step recalls the MGS as being a system approach linking the agent containing it to its environment and bringing to the agent a control from within. We apply the MGS to animal life. Relations with the Umwelt, with constructivism and with the Peircean triadic approach are highlighted. The last step of the thread brings the evolution of life up to humans where specificities related to human mind have to be taken into account. Among them is self-consciousness for which an existing evolutionary scenario introduces anxiety management as a foundational human constraint [Menant, 2014]. We link that scenario to the evolutionary thread because it introduces specific human constraints and is based on the evolution of meaningful representations. A conclusion summarizes the steps of the proposed evolutionary thread. More work is needed on that subject. Possible continuations are introduced. (shrink)

The relations between life and cogntion have been addressed through different perspectives [Stewart 1996, Boden 2001, Bourgine and Stewart 2004, van Duijn & all 2006, Di Paolo 2009]. We would like here to address that subject by relating life to cognition through a process of meaning generation. Life emerged on earth as a far from thermodynamic equilibrium performance that had to maintain herself. Life is charactertized by a ‘stay alive’ constraint that has to be satisfied (such constraint can be included (...) in the constraint of being able to maintain far from equilibrium thermodynamic conditions [Bickhard 2011]). The local ‘stay alive‘ constraint has to be satisfied in an environment containing elements potentially supportive or harmfull. A key activity for the living entity is to characterize these elements in terms of meaningfulness relatively to the ‘stay alive’ constraint. This process can be modeled with an existing tool where a system submitted to an internal constraint generates meaningful information characterizing elements of the environment: the Meaning Generator System (MGS) [Menant, 2003, 2014 a]. In a few words: when a system submitted to an internal constraint receives from the environment an information that has a connection with the constraint it generates a meaning usable for the implementation of an action satisfying the constraint.The generated meaning is the connection existing between the received information and the constraint. The MGS models this process and interfaces to the action implementation for constraint satisfaction The meaning is generated by and for the system. The MGS grounds meaning generation in constraint satisfaction and links the living entity to her environment in a relational process. A simple example is with a paramecium close to a drop of acid. The paramecium which is submitted to a ‘stay alive’ constraint will move away from the acid area. The received information ‘presence of acid’ generates the meaning ‘acid not compatible with the ‘stay alive’ constraint‘ which triggers the moving away action (that example is close to Varela’s bacteria swimming up a sugar gradient. What the MGS brings in addition is a modeling of the significance of the chemical gradient for the organism). The action implemented to satisfy the constraint modifies the environment and the received information, establishing an interactive process linking the living entity to her environment. During its evolution animal life has elaborated new constraints (like ‘live group life’) and new functions enriching meaning generation and action scenarios. As a result the build up of meaningful representations has improved the constraint satisfaction processes of animals, embedding them in their environments in relational and interactive terms [Menant, 2011]. Cognition can be defined by proposing that ‘a system is cognitive if and only if sensory inputs serve to trigger actions in a specific way, so as to satisfy a viability constraint’ [Bourgine, Stewart 2004]. Cognition can also be considered as exemplifying a ‘vital criterion of responsiveness’ [Boden, 2001 ]. Consequently the MGS can be positioned as an elementary and generic version of animal cognition. For animal life, meaning generation for internal constraint satisfaction links life and cognition in a relational and interactive process. Cognition for human life is more complex as new performances have to be taken into account like self-consciousness and free-will. Meaning generation at human level is a challenging subject as human constraints are not clearly understood [Menant, 2011]. Many research activities are in process looking for some understanding of human mind [Philpapers]. One area of investigation is an evolutionary approach to self-consciousness using meaning generation where anxiety limitation comes up as a generic human constraint [Menant, 2014 b]. Assuming that we can have clear enough an understanding of some human constraints, we can look at the MGS for partly extending to humans the link between life and cognition that has been established for animals. So overall, we can consider that the MGS approach makes available an evolutionary link between life and cognition for animals, and partly for humans. A characteristic of the proposed system approach to meaning generation is the possibility to use it for any type of agent, be it organic (with intrinsic constraints ) or artificial (with derived constraints). Such characterization of agents through meaning generation can be used to discriminate artificial itelligence from human intelligence (see the MGS usage to support Searle’s chinese room argument [Menant, 2013]). On a more general basis, the proposed system approach can positions the MGS as a simple model for an internal source of normativity. It’s usage as a simple building block allows a bottom-up modeling for normativity in the sensorimotor approach. The ‘stay alive’ constraint could also be taken as a starting point for an evolutionary grounding of sensorimotor norms ‘in the biological normativity of the agent as a whole’ [Di Paolo & all 2014]. The proposed presentation will develop the points summarized here above and position them relatively to the autopoietic and enactive approaches. Several possible continuations will also be highlighted. (shrink)

Biology seems to present local and transitory regularities rather than immutable laws. To account for these historically constituted regularities and to distinguish them from mathematical invariants, Montévil and Mossio (Journal of Theoretical Biology 372:179–191, 2015) have proposed to speak of constraints. In this article we analyse the causal power of these constraints in the evolution of biodiversity, i.e., their positivity, but also the modality of their action on the directions taken by evolution. We argue that to fully account (...) for the causal power of these constraints on evolution, they must be thought of in terms of normativity. In this way, we want to highlight two characteristics of the evolutionary constraints. The first, already emphasised as reported by Gould (The structure of evolutionary theory, Harvard University Press, 2002), is that these constraints are both produced by and producing biological evolution and that this circular causation creates true novelties. The second is that this specific causality, which generates unpredictability in evolution, stems not only from the historicity of biological constraints, but also from their internalisation through the practices of living beings. (shrink)

A growing number of linguistic attempts to explain how languages change use cultural-evolutionary models involving selection or drift. Developmental constraints and biases, which take center stage in evolutionary developmental biology or evo-devo, seem to be absent within this framework, even though linguistics is home to numerous notions of constraint. In this paper, we show how these evo-devo concepts could be applied to linguistic change and why they should. This requires some conceptual groundwork, due to important differences between (...) linguistic and biotic evolution. In biological evolution, development generates the organism's variable traits on which selection and drift act. In linguistic evolution by analogy, we say development generates the linguistic variants on which selection and drift can act. “Linguistic development” then picks out how individual speakers produce and comprehend language. It involves much more than just learning. Using this broad notion of development, we distinguish between different types of bias that could operate in the processes of linguistic innovation and transmission, which correspond to genetic mutation and biological reproduction, respectively. Having thus sharpened our conceptual toolbox, we then reanalyze two well-documented cases of linguistic change and show that, in both these cases, linguists have only considered Neo-Darwinian evolutionary explanations, falsely deploying an exclusive disjunction of selection and drift. We show that there is at least a third relevant alternative in these examples, namely developmental constraint or bias in the sense we explicate here. (shrink)

This chapter critically analyzes evolutionary epistemology as a theoretical framework for the study of science as a historical and cultural phenomenon. As spelled out by Campbell in the 1970s, evolutionary epistemology has an ambitious goal: it aims at understanding the complex relations between bio- logical evolution, especially the biological evolution of human cognition, and the cultural evolution of scientific knowledge. It eventually aims at forming an integrated causal theory of the evolution of science, starting with the evo- lution (...) of human cognition. In this chapter, the author considers Campbell’s project and specifies why it is still today a worthwhile project for explain- ing the evolution of science as a specific case of cultural evolution. But he also criticizes Campbell’s evolutionary epistemology for assuming that blind variation and selective retention are the processes through which science evolves. This assumption, the author argues, is at odds with much of what we know about scientific cognition and the history of science. He advocates (1) dropping the methodological constraint of looking for processes of blind variation and selective retention at the expense of other constructive processes and mechanisms of knowledge production; but (2) retaining the integrative point of evolutionary epistemology, which implies taking seriously the results of evolutionary psychology; and (3) retaining the populational framework for explaining the history of science, which means questioning why some scientific beliefs and practices eventually spread and stabilize in a scientific community. We end up with an updated research program for evolutionary epistemology, which faces new challenges. (shrink)

Many have expected that understanding the evolution of norms should, in some way, bear on our first-order normative outlook: How norms evolve should shape which norms we accept. But recent philosophy has not done much to shore up this expectation. Most existing discussions of evolution and norms either jump headlong into the is/ought gap or else target meta-ethical issues, such as the objectivity of norms. My aim in this paper is to sketch a different way in which evolutionary considerations (...) can feed into normative thinking—focusing on stability. I will discuss two forms of argument that utilize information about social stability drawn from evolutionary models, and employs it to assess claims in political philosophy. One such argument treats stability as feature of social states that may be taken into account alongside other features. The other uses stability as a constraint on the realization of social ideals, via a version of the ought-implies-can maxim. These forms of argument are not new; indeed they have a history going back at least to early modern philosophy. But their marriage with evolutionary information is relatively recent, has a significantly novel character, and has received little attention in recent moral and political philosophy. (shrink)

Can a human society be constrained in such a way that self-organization will thereafter tend to produce outcomes that advance the goals of the society? Such a society would be self-organizing in the sense that individuals who pursue only their own interests would none-the-less act in the interests of the society as a whole, irrespective of any intention to do so. The paper sketches an agent-based model that identifies the conditions that must be met if such a self-organizing society is (...) to emerge. The model draws heavily on an understanding of how self-organizing societies have emerged repeatedly during the evolution of life on Earth. The model demonstrates that the key enabling requirement for a self-organizing society is ‘consequence-capture’. Broadly this means that all agents in the society must capture sufficient of the beneficial consequences of their actions for the goals of the society. ‘Consequence-capture’ can be organized in a society by appropriate management that suppresses free riders and supports pro-social actions. In human societies these constraints include institutions such as systems of governance and social norms. If a self-organizing society is to emerge, consequence-capture must apply to all agents in the society, including those involved in the establishment and adaptation of institutions. If this is achieved, the result will be a fully self-organizing society in which the interests of all agents are aligned with the interests of the society as a whole. (shrink)

It is pretty obvious to most of us that self-consciousness is a product of evolution. But its nature is unknown. We propose here a scenario addressing a possible evolutionary nature of self-consciousness covering the segment linking pre-human primates to humans. The scenario is based on evolutions of representations and of inter-subjectivity that could have taken place within the minds of our pre-human ancestors . We begin by situating self-consciousness relatively to other aspects of human consciousness. With the help of (...) anthropology, we date a possible starting point of our scenario at a time when our non self-conscious pre-human ancestors were able to build meaningful representations and were capable of inter-subjectivity, like are our today modern apes. As the proposed scenario is based on an evolution of representations, we recall an existing model for meaningful representations based on the generation of meaningful information by systems submitted to internal constraints. This model allows us to define representations of conspecifics and auto-representations that we assume as having been present in the minds of our pre-human ancestors. The next step of the scenario is to consider an evolution of inter-subjectivity towards identification with conspecifics that could have led to a merger of the auto-representation with the representations of conspecifics in the minds of our ancestors. Such a merger brought the auto-representation to become about an entity existing in the environment, as were the representations of conspecifics. We consider that such identification with conspecifics has introduced in the mind of our ancestors an elementary and embryonic sense of being an existing entity that we name ‘ancestral self-consciousness’. The same process has also imposed to our ancestors an identification with suffering or endangered conspecifics which has produced an important anxiety increase that could have blocked the evolutionary process. We propose that the performances developed by our ancestors to manage that anxiety increase have also generated significant evolutionary advantages that have helped the development of ancestral self-consciousness and favored its evolution toward our full-fledged self-consciousness. It is also proposed that some pre-human primates have avoided the anxiety increase by finding a niche where evolutionary advantages were not necessary. This may have led to our today apes. The contribution of anxiety to the proposed scenario brings to position anxiety management as having guided the evolution of self-consciousness and as still being a key player in our today human minds. Regarding philosophy of mind, possible links between phenomenal consciousness and the proposed nature of self-consciousness are introduced. The conclusion presents a summary of the points addressed here. Possible continuations are highlighted as related to human mind, to anxiety management and to artificial intelligence. (shrink)

Mayr’s proximate–ultimate distinction has received renewed interest in recent years. Here we discuss its role in arguments about the relevance of developmental to evolutionary biology. We show that two recent critiques of the proximate–ultimate distinction fail to explain why developmental processes in particular should be of interest to evolutionary biologists. We trace these failures to a common problem: both critiques take the proximate–ultimate distinction to neglect specific causal interactions in nature. We argue that this is implausible, and that (...) the distinction should instead be understood in the context of explanatory abstractions in complete causal models of evolutionary change. Once the debate is reframed in this way, the proximate–ultimate distinction’s role in arguments against the theoretical significance of evo-devo is seen to rely on a generally implicit premise: that the variation produced by development is abundant, small and undirected. We show that a “lean version” of the proximate–ultimate distinction can be maintained even when this isotropy assumption does not hold. Finally, we connect these considerations to biological practice. We show that the investigation of developmental constraints in evolutionary transitions has long relied on a methodology which foregrounds the explanatory role of developmental processes. It is, however, entirely compatible with the lean version of the proximate–ultimate distinction. (shrink)

This paper outlines a critique of the use of the genetic variance–covariance matrix (G), one of the central concepts in the modern study of natural selection and evolution. Specifically, I argue that for both conceptual and empirical reasons, studies of G cannot be used to elucidate so-called constraints on natural selection, nor can they be employed to detect or to measure past selection in natural populations – contrary to what assumed by most practicing biologists. I suggest that the search (...) for a general solution to the difficult problem of identifying causal structures given observed correlation’s has led evolutionary quantitative geneticists to substitute statistical modeling for the more difficult, but much more valuable, job of teasing apart the many possible causes underlying the action of natural selection. Hence, the entire evolutionary quantitative genetics research program may be in need of a fundamental reconsideration of its goals and how they correspond to the array of mathematical and experimental techniques normally employed by its practitioners. (shrink)

It is pretty obvious that language and human consciousness entertain tight relations. We could not really be conscious of ourselves without the possibility to say “I” or “me”. And language is a key contributor in our capability to identify ourselves as conscious entities existing in the environment. But the relations linking language and consciousness are complex and difficult to analyze. Evolutionary origins of language are unknown as no fossil traces have been left by our ancestors. Sciences of consciousness however (...) begin to make available some possible evolutionary scenarios about the nature of human consciousness. We want here to propose a link between language and consciousness by using such an evolutionary scenario and also introduce the usage of a systemic approach to meaning generation. In the first part of the presentation we will use an existing scenario about the evolutionary nature of self-consciousness where the development of language has a role (1). We will highlight this role in order to identify language and self-consciousness as inter-dependant in their nature through a possible common evolutionary origin. Self-consciousness and language could then be considered as tightly inter-dependant through a common build up of human nature during evolution. The scenario presents an evolutionary nature of self-consciousness as resulting of the capability for pre-human primates to identify with their conspecifics (1, 2). The conspecifics are represented as existing in the environment, and such identification brought our pre-human ancestors to consider themselves as also existing in the environment. The scenario takes this event as being a first step for a conscious self-representation within pre-human primates, which progressively evolved toward our today human consciousness (3). But such identification with conspecifics was not for free at times of survival of the fittest. Identifying with conspecifics meant for our pre-human ancestor to also identify with their sufferings or encountered dangers. These came in addition to the dangers or sufferings naturally encountered and created a significant anxiety increase (1). The resulting level of anxiety had to be limited. One possibility for that was to develop psychological or physical tools that could have reduced the risks of occurrences and developments of such dangers and sufferings. Among these tools is the performance of language which can induce significant evolutionary advantages. We will propose a first scheme about how these evolutionary advantages could have reduced the dangers and sufferings encountered by our pre-human ancestors. We will also show how the development of language produced by itself a positive feedback on the development of inter-subjectivity in the evolutionary scenario, and so participated directly to the development of human consciousness. Other evolutionary advantages have existed like the development of imitation and synergy through experience (4). Language played a role there also, and has to be taken into account. The second part of the presentation will propose the usage of an existing systemic approach to meaning generation in terms of constraints satisfaction (5, 6). Constraints for pre-human primates, ranging from a basic “stay alive” to highly elaborated “limit anxiety”, were source of multiple meaning generations in which language has played (and still plays) a key role. Several continuations will be proposed linked to the here above thread on a co-evolutions of language and human consciousness, as based on the evolutionary scenario. (shrink)

Humans are cognitive entities. Our ongoing interactions with the environment are threaded with creations and usages of meaningful information. Animal life is also populated with meaningful information related to survival constraints. Information managed by artificial agents can also be considered as having meanings, as derived from the designer. Such perspective brings us to propose an evolutionary approach to cognition based on meaningful information management. We use a systemic tool, the Meaning Generator System (MGS), and apply it consecutively to (...) animals, humans and artificial agents [1, 2]. The MGS receives information from its environment and compares it with its constraint. The generated meaning is the connection existing between the received information and the constraint. It triggers an action aimed at satisfying the constraint. The action modifies the environment and the generated meaning. Meaning generation links agents to their environments. The MGS is a system: a set of elements linked by a set of relations. Any system submitted to a constraint and capable of receiving information can lead to a MGS. Animals, humans and robots are agents containing MGSs dealing with different constraints. Similar MGSs carrying different constraints will generate different meanings. Cognition is system dependent. Contrary to approaches on meaning generation based on psychology or linguistics, the MGS approach is not based on human mind. We want to avoid the circularity of taking human mind as a starting point. Free will and self-consciousness participate to the management of human meanings. They do not exist for animals or robots. Staying alive is a constraint that we share with animals. Robots ignore that constraint. We first use the MGS for animals with “stay alive” and “group life” constraints. The analysis of meaning and cognition in animals is however limited by our un-complete understanding of the nature of life (the question of final causes). Extending the analysis of meaning generation and cognition to humans is complex and has some true limitations as the nature of human mind is a mystery for today science and philosophy. The natures of our feelings, free will or self-consciousness are unknown. Approaches to identify human constraints are however possible, where the MGS can highlight some openings [3, 4]. Modeling meaning management in artificial agents is rather straightforward with the MGS. We, the designers, know the agents and the constraints. The derived nature of constraints, meaning and cognition is however to be highlighted. We define a meaningful representation of an item for an agent as being the networks of meanings relative to the item for the agent, with the action scenarios involving the item. Such meaningful representations embed the agents in their environments and are far from the GOFAI type of representations. Cognition, meanings and representations exist by and for the agents. We finish by summarizing the points presented here and highlight possible continuations . [1] “Information and Meaning” [2] “Introduction to a systemic theory of meaning” [3] “Computation on Information, Meaning and Representations. An Evolutionary Approach” [4] “Proposal for a shared evolutionary nature of language and consciousness”. (shrink)

Variation, adaptation, heredity and fitness, constraints and affordances, speciation, and extinction form the building blocks of the (Neo-)Darwinian research program, and several of these have been called “Darwinian principles.” Here, we suggest that caution should be taken in calling these principles Darwinian because of the important role played by reticulate evolutionary mechanisms and processes in also bringing about these phenomena. Reticulate mechanisms and processes include symbiosis, symbiogenesis, lateral gene transfer, infective heredity mediated by genetic and organismal mobility, and (...) hybridization. Because the “Darwinian principles” are brought about by both vertical and reticulate evolutionary mechanisms and processes, they should be understood as foundational for a more pluralistic theory of evolution, one that surpasses the classic scope of the Modern and the Neo-Darwinian Synthesis. Reticulate evolution moreover demonstrates that what conventional (Neo-)Darwinian theories treat as intra-species features of evolution frequently involve reticulate interactions between organisms from very different taxonomic categories. Variation, adaptation, heredity and fitness, constraints and affordances, speciation, and extinction therefore cannot be understood as “traits” or “properties” of genes, organisms, species, or ecosystems because the phenomena are irreducible to specific units and levels of an evolutionary hierarchy. Instead, these general principles of evolution need to be understood as common goods that come about through interactions between different units and levels of evolutionary hierarchies, and they are exherent rather than inherent properties of individuals. (shrink)

Background: One of the all-time questions in evolutionary biology regards the evolution of organismal shapes, and in particular why certain forms appear repeatedly in the history of life, others only seldom and still others not at all. Recent research in this field has deployed the conceptual framework of constraints and natural selection as measured by quantitative genetic methods. Scope: In this paper I argue that quantitative genetics can by necessity only provide us with useful statistical sum- maries that (...) may lead researchers to formulate testable causal hypotheses, but that any inferential attempt beyond this is unreasonable. Instead, I suggest that thinking in terms of coordinates in phenotypic spaces, and approaching the problem using a variety of empirical methods (seeking a consilience of evidence), is more likely to lead to solid inferences regarding the causal basis of the historical patterns that make up most of the data available on phenotypic evolution. (shrink)

The management of meaningful information by biological entities is at the core of biosemiotics [Hoffmeyer 2010]. Intentionality, the ‘aboutness’ of mental states, is a key driver in philosophy of mind. Philosophers have been reluctant to use intentionality for non human animals. Some biologists have been in favor of it. J. Hoffmeyer has been using evolutionary intentionality and Peircean semiotics to discuss a biosemiotic approach to the problem of intentionality [Hoffmeyer 1996, 2012]. Also, recent philosophical studies are bringing new openings (...) on the subject of biological intentionality.[Asma 2014]. What we propose here is to use an existing system approach to meaning generation to introduce a link between biosemiotics and bio-intentionality at basic life level in an evolutionary perspective. Meanings do not exist by themselves. They have to be generated for a given reason by a defined entity. A system approach to meaning generation based on constraint satisfaction has been developped to that end: the Meaning Generator System (MGS) [Menant 2003a]. It has been used for biosemiotics in an evolutionary perspective [Menant 2003b, 2011]. To look at relating biosemiotics to intentionality through meaning genaration we recall the system structure of the MGS with the agent that contains it. Meaning generation and agent interfacing with environment make available components for the groundings of the generated meaning in terms of data, data processing, interfacing and constraint [Menant, 2011]. These groundings of the meaning can be in or out the agent containing the MGS. They display what the generated meaning is about. For basic life the ‘aboutness’ of the generated meaning relies on a ‘stay alive’ constraint that has to be satisfied (others constraints, like ‘live group life’, are to be introduced through the evolution of life). Such ‘aboutness’ of a generated meaning within basic life can be associated to an elementary biological intentionality, to a ‘bio-intentionality’. As biosemiotics deals with meaning management by biological entities, the relations introduced by the MGS between meaning generation and bio-intentionality introduce a link between biosemiotics and bio-intentionality for basic life. We present and develop that link. Besides making available a model usable for bio-intentionality, the proposed approach may also provide an entry point to the concept of intentionality without having to take into account human specificities like self-consciousness. It should also be noted that the approach takes life as a given and that the‘stay alive’ constraint brings in a teleological component. Such presentation of bio-intentionality calls for other developments and continuations. Some will be introduced. (shrink)

Understanding computation as “a process of the dynamic change of information” brings to look at the different types of computation and information. Computation of information does not exist alone by itself but is to be considered as part of a system that uses it for some given purpose. Information can be meaningless like a thunderstorm noise, it can be meaningful like an alert signal, or like the representation of a desired food. A thunderstorm noise participates to the generation of meaningful (...) information about coming rain. An alert signal has a meaning as allowing a safety constraint to be satisfied. The representation of a desired food participates to the satisfaction of some metabolic constraints for the organism. Computations on information and representations will be different in nature and in complexity as the systems that link them have different constraints to satisfy. Animals have survival constraints to satisfy. Humans have many specific constraints coming in addition. And computers will compute what the designer and programmer ask for. We propose to analyze the different relations between information, meaning and representation by taking an evolutionary approach on the systems that link them. Such a bottom-up approach allows starting with simple organisms and avoids an implicit focus on humans, which is the most complex and difficult case. To make available a common background usable for the many different cases, we use a systemic tool that defines the generation of meaningful information by and for a system submitted to a constraint [Menant, 2003]. This systemic tool allows to position information, meaning and representations for systems relatively to environmental entities in an evolutionary perspective. We begin by positioning the notions of information, meaning and representation and recall the characteristics of the Meaning Generator System (MGS) that link a system submitted to a constraint to its environment. We then use the MGS for animals and highlight the network nature of the interrelated meanings about an entity of the environment. This brings us to define the representation of an item for an agent as being the network of meanings relative to the item for the agent. Such meaningful representations embed the agents in their environments and are far from the Good Old Fashion Artificial Intelligence type ones. The MGS approach is then used for humans with a limitation resulting of the unknown nature of human consciousness. Application of the MGS to artificial systems brings to look for compatibilities with different levels of Artificial Intelligence (AI) like embodied-situated AI, the Guidance Theory of Representations, and enactive AI. Concerns relative to different types of autonomy and organic or artificial constraints are highlighted. We finish by summarizing the points addressed and by proposing some continuations. (shrink)

The incidence of chronic non-communicable diseases (NCDs) such as diabetes, hypertension, cancers and cardiovascular diseases in Ghana has created a new mix of healthcare challenge for the country.

Meanings are present everywhere in our environment and within ourselves. But these meanings do not exist by themselves. They are associated to information and have to be created, to be generated by agents. The Meaning Generator System (MGS) has been developed on a system approach to model meaning generation in agents following an evolutionary perspective. The agents can be natural or artificial. The MGS generates meaningful information (a meaning) when it receives information that has a connection with an internal (...) constraint to which the agent is submitted. The generated meaning is to be used by the agent to implement actions aimed at satisfying the constraint. We propose here to highlight some characteristics of the MGS that could be related to items of philosophy of information. (shrink)

The nature of human mind has been an open question for more than 2000 years and it is still today a mystery. There has been during the last 30 years a renewed interest from science and philosophy on that subject. Among the existing research domains is neurophilosophy, an interdisciplinary study of neuroscience and philosophy looking at neuronal aspects of access consciousness, of phenomenal consciousness and at functional aspects of consciousness. We propose here to look if self-consciousness could have a place (...) in neurophilosophy by using an existing evolutionary scenario that can introduce possible links between neural processing and some aspects of self-consciousness. The scenario is about an evolutionary nature of self-consciousness where evolutions of inter-subjectivity and meaningful representations may have led our ancestors to identify with their conspecifics. The scenario proposes that this process has brought our pre-human ancestors to represent themselves as existing entities like the conspecifics they identified with were represented. Such a representation of oneself as an existing entity may have created an elementary version of self-consciousness that we name “ancestral self-consciousness”. But identification with suffering or endangered conspecifics has also produced an important anxiety increase. To limit that anxiety our ancestors have developed mental states and behaviors like caring, imitation communication and simulation. These performances have introduced evolutionary advantages leading to an evolutionary engine that has favored the development of ancestral self-consciousness toward our human self-consciousness. We begin by presenting a model for the generation of meaningful information based on a system submitted to an internal constraint (the Meaning Generator System). We use that model to introduce meaningful representations as networks of meaningful information. We then present the evolutionary scenario for self-consciousness that uses meaningful representations and the performance of inter-subjectivity. The scenario leads to propose two links between self-consciousness and neural processes: mirror-neurons as neural introduction to inter-subjectivity and self-consciousness as neural computation on meaningful representations. Possible continuations are highlighted. (shrink)

In his Target Article, Terrence Deacon develops simple models that assist in understanding the role of RNA in the origins of life. However, his models fail to adequately represent an important evolutionary dynamic. Central to this dynamic is the selection that impinges on RNA molecules in the context of their association with proto-metabolisms. This selection shapes the role of RNA in the emergence of life. When this evolutionary dynamic is appropriately taken into account, it predicts a role for (...) RNA that is consistent with the Managed-Metabolism Hypothesis about the origins of life, and inconsistent with Deacon’s account. (shrink)

This paper delves into the character concept as applied to reproduction. Our argument is that the prevailing functional-adaptationist perspective falls short in explaining the evolution of reproductive traits, and we propose an alternative organismal-relational approach that incorporates the developmental and interactive aspects of reproduction. To begin, we define the functional individuation of reproductive traits as evolutionary strategies aimed at enhancing fitness, and we demonstrate how this perspective influences the classification of reproductive characters and modes, the comprehension of shared traits (...) as resulting from conflicts of evolutionary interest between individuals, and the explanation of reproductive diversity. After outlining the shortcomings of this framework, we introduce an organismal-relational approach grounded in evolutionary developmental studies of reproduction. This view provides a revised classification for reproductive characters and modes and offers a new understanding of interorganismal traits that takes into account their inherently relational nature. Lastly, we present the research agenda that emerges from this approach, which addresses the core explanatory gaps left by the adaptationist perspective, including the explanation of reproductive homologies and homoplasies, the developmental constraints associated with the evolution of reproductive modes, and the evolvability of reproductive characters. (shrink)

Phenotypic integration refers to the study of complex patterns of covariation among functionally related traits in a given organism. It has been investigated throughout the 20th century, but has only recently risen to the forefront of evolutionary ecological research. In this essay, I identify the reasons for this late flourishing of studies on integration, and discuss some of the major areas of current endeavour: the interplay of adaptation and constraints, the genetic and molecular bases of integration, the role (...) of phenotypic plasticity, macroevolutionary studies of integration, and statistical and conceptual issues in the study of the evolution of complex phenotypes. I then conclude with a brief discussion of what I see as the major future directions of research on phenotypic integration and how they relate to our more general quest for the understanding of phenotypic evolution within the neo-Darwinian framework. I suggest that studying integration provides a particularly stimulating and truly interdisciplinary convergence of researchers from fields as disparate as molecular genetics, developmental biology, evolutionary ecology, palaeontology and even philosophy of science. (shrink)

Evolutionary debunking arguments abound, but it is widely assumed that they do not arise for our perceptual beliefs about midsized objects, insofar as the adaptive value of our object beliefs cannot be explained without reference to the objects themselves. I argue that this is a mistake. Just as with moral beliefs, the adaptive value of our object beliefs can be explained without assuming that the beliefs are accurate. I then explore the prospects for other sorts of vindications of our (...) object beliefs—which involve “bootstrapping” from our experiences as of midsized objects—and I defend bootstrapping maneuvers against a variety of objections. Finally, I argue for an explanatory constraint on legitimate bootstrapping and show how some attempts to respond to debunking arguments run afoul of the constraint. (shrink)

Few metaphors in biology are more enduring than the idea of Adaptive Landscapes, originally proposed by Sewall Wright (1932) as a way to visually present to an audience of typically non- mathematically savvy biologists his ideas about the relative role of natural selection and genetic drift in the course of evolution. The metaphor, how- ever, was born troubled, not the least reason for which is the fact that Wright presented different diagrams in his original paper that simply can- not refer (...) to the same concept and are therefore hard to reconcile with each other (Pigliucci 2008). For instance, in some usages, the landscape’s non- fitness axes represent combinations of individual genotypes (which cannot sensibly be aligned on a linear axis, and accordingly were drawn by Wright as polyhedrons of increasing dimensionality). In other usages, however, the points on the diagram represent allele or genotypic frequencies, and so are actually populations, not individuals (and these can indeed be coherently represented along continuous axes). (shrink)

Pere Alberch played a pivotal role in shaping the field of evolutionary developmental biology during the 1980s and 1990s. Whereas initially his contributions were sidelined by the empirical advancements of the molecular revolution in developmental and evolutionary biology, his theoretical insights have left a lasting impact on the discipline. This article provides a comprehensive review of the legacy and evolvability of Alberch's ideas in contemporary evo-devo, which included the study of morphogenesis as the proper level of developmental causation, (...) the interplay between developmental constraints and natural selection, the epistemic role of teratologies, the origin of evolutionary novelties and the concept of evolvability. (shrink)

The article proposes to further develop the ideas of the Extended Evolutionary Synthesis by including into evolutionary research an analysis of phenomena that occur above the organismal level. We demonstrate that the current Extended Synthesis is focused more on individual traits (genetically or non-genetically inherited) and less on community system traits (synergetic/organizational traits) that characterize transgenerational biological, ecological, social, and cultural systems. In this regard, we will consider various communities that are made up of interacting populations, and for (...) which the individual members can belong to the same or to different species. Examples of communities include biofilms, ant colonies, symbiotic associations resulting in holobiont formation, and human societies. The proposed model of evolution at the level of communities revises classic theorizing on the major transitions in evolution by analyzing the interplay between community/social traits and individual traits, and how this brings forth ideas of top-down regulations of bottom-up evolutionary processes (collaboration of downward and upward causation). The work demonstrates that such interplay also includes reticulate interactions and reticulate causation. In this regard, we exemplify how community systems provide various non-genetic ‘scaffoldings’, ‘constraints’, and ‘affordances’ for individual and sociocultural evolutionary development. Such research complements prevailing models that focus on the vertical transmission of heritable information, from parent to offspring, with research that instead focusses on horizontal, oblique and even reverse information transmission, going from offspring to parent. We call this reversed information transfer the ‘offspring effect’ to contrast it from the ‘parental effect’. We argue that the proposed approach to inheritance is effective for modelling cumulative and distributed developmental process and for explaining the biological origins and evolution of language. (shrink)

This dissertation examines the psychology of moral judgment and its implications for normative ethics and metaethics. Recent empirical findings in moral psychology, such as the impact of emotions, intuitions, and situational factors on moral judgments, have sparked a debate about whether ordinary moral judgments are systematically error-prone. Some philosophers, such as Peter Singer and Joshua Greene, argue that these findings challenge the reliability of moral intuitions and support more "reasoned", consequentialist approaches over deontological ones. The first part of the dissertation (...) reviews these provocative findings and the philosophical reactions to them, which often invoke the notion of 'moral relevance' - the idea that some factors shaping moral judgments are morally irrelevant. The second part develops a psychological account of moral relevance, drawing on theories of the moral domain, the role of emotions, and models of moral cognition. This account reveals the complex interplay of intuitive and reasoned processes in generating impressions of moral relevance. The final part reevaluates the philosophical discussions in light of this psychological understanding. It contends that the evolutionary background of moral intuitions does not necessarily render them inadequate, and that both deontological and consequentialist judgments likely depend on evolved intuitions to a significant degree. Furthermore, the tendency to dismiss certain influences on moral judgment as irrelevant can itself be explained psychologically. Considering the psychological account presented, mind-independent accounts of morality become less plausible. The dissertation concludes that while empirical moral psychology reveals important constraints on normative theorizing, it does not decisively favor consequentialism over deontology. To assess the significance of empirical-scientific findings for ethics, a nuanced understanding of the origins of moral judgments is nevertheless indispensable. (shrink)

Three decades after Chalmers named it, the ‘hard problem’ remains. I suggest a parsimonious solution. Biological dynamic systems interact according to simple rules (while the environment provides simple constraints) and thus self-organize to become a new, more complex dynamic system at the next level. This spiral repeats several times generating a hierarchy of levels. A leap to the next level is frequently creative and surprising. From ants, themselves self-organized according to physical/chemical laws, may emerge an ant colony self-organized according (...) to eusocial laws. A dynamic system need not be material. A living language (immaterial) is a complex adaptive system. Body/brain are material but the next level of complexity, a psychological dynamic system, a thought, feeling, image or ideal, is less material. From several psychological dynamic systems emerges the next level, narrative (immaterial), and from multiple narratives emerges personality. Concrete evidence explains how an early narrative emerges from body-and-brain. Evidence also shows that personality emerges from narrative. Even an objective narrative captures subjectivity since the teller’s choice of content is subjective. I argue that the ‘stream-of-consciousness’ story (movie) you are currently telling yourself (watching) is your conscious experience, ‘what it is like’ for you to be conscious. Adriana Cavarero’s arguments support this. Each level of a hierarchy of dynamic systems must necessarily be homeostatic, at that level. McDowell et al. (2023: submitted, in revision) reported evidence that a dream (a narrative) supports personality homeostatically. Perhaps the evolutionary advantage of conscious experience, also a narrative, has always been that it too supports personality homeostatically. Personality and body/brain, a chimera of symbiotic life-forms, constitute interactionist duality. (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, while the production (...) of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

The Turing Test (TT), the Chinese Room Argument (CRA), and the Symbol Grounding Problem (SGP) are about the question “can machines think?” We propose to look at these approaches to Artificial Intelligence (AI) by showing that they all address the possibility for Artificial Agents (AAs) to generate meaningful information (meanings) as we humans do. The initial question about thinking machines is then reformulated into “can AAs generate meanings like humans do?” We correspondingly present the TT, the CRA and the SGP (...) as being about generation of human-like meanings. We model and address such possibility by using the Meaning Generator System (MGS) where a system submitted to an internal constraint generates a meaning in order to satisfy the constraint. The system approach of the MGS allows comparing meaning generations in animals, humans and AAs. The comparison shows that in order to have AAs capable of generating human-like meanings, we need the AAs to carry human constraints. And transferring human constraints to AAs raises concerns coming from the unknown natures of life and human mind which are at the root of human constraints. Implications for the TT, the CRA and the SGP are highlighted. It is shown that designing AAs capable of thinking like humans needs an understanding about the natures of life and human mind that we do not have today. Following an evolutionary approach, we propose as a first entry point an investigation about the possibility for extending a “stay alive” constraint into AAs. Ethical concerns are raised from the relations between human constraints and human values. Continuations are proposed. (This paper is an extended version of the proceedings of an AISB/IACAP 2012 presentation). (shrink)

Information and meaning are present everywhere around us and within ourselves. Specific studies have been implemented to link information and meaning (Linguistic, Biosemiotic, Psychology, Psychiatry, Cognition, Artificial Intelligence... ). No general coverage is available for the notion of meaning. We propose to complement this lack by a system approach to meaning generation in an evolutionary background. That short paper is a summary of the system approach where a Meaning Generator System (MGS) based on internal constraint satisfaction has been introduced. (...) The MGS can be used for animals (with “stay alive” related constraints), for humans (with “look for happiness” type constraints) and for artificial agents with programmed constraints. Definitions for agency and autonomy are made available based on internal constraint satisfaction. Usage of the MGS with the Turing Test shows why today computers cannot think like humans do. The MGS also allows to introduces evolutionary scenarios for cognition, intentionality and self-consciousness, with an entry point to a human specific anxiety. Continuations are proposed. (shrink)

The notions of information, representation and enaction entertain historical and complex relations with cognition. Historical relations because representational structures belong to the central hypothesis of cognitive sciences. Complex relations because cognitive sciences apply the notion of representation to animals, humans and robots, and also because the enactive approach tends to disregard the GOFAI type of representations. In this wide horizon of relations, we propose to look at a systemic approach that could bring up a common denominator for information and representations (...) in the build up of cognition, and also keep a link with the enactive approach. Our purpose is to show that systems submitted to constraints can generate meaningful information to maintain their natures, and consequently build up meaningful representations that have some compatibility with the enactive approach. Such a systemic approach to the notion of meaningful information could then make available a link between enaction and meaningful representations. The first part of the presentation is about reminding that cognition does not exist per se, but is related to the system that builds it. We look at cognition as constituted by dynamic meaningful representations built up by systems that have constraints to satisfy in their environments. Cognition is considered here at the level of the system that builds it and uses it in order to maintain its nature in its environment. Such a systemic approach fits with evolution. Organisms build representations to cope with survival constraints (frogs build representations of moving black dots in order to satisfy food constraints). Humans build representations and cognition to satisfy constraints that are conscious and unconscious. Artificial systems can use representations and cognition to run activities related to constraints implemented by the designers or coming from the environment (a goal to reach being considered as a constraint to satisfy). In the second part of the presentation we define what are a meaningful information and a representation for a system submitted to a constraint in its environment, and we link these to the enactive approach. We define a meaningful information (a meaning) as an information generated by a system submitted to a constraint when it receives an external information that has a connection with the constraint. The meaning is precisely that connection. The meaning belongs to the interactions that link the system to its environment. The function of the meaning is to participate to the determination of an action that will be implemented in order to satisfy the constraint. (Menant, 2003). The satisfaction of the constraint goes with maintaining the nature of the system in its environment. A Meaning Generator System (MGS) is defined correspondingly. It is a building block for higher level systems. We present some characteristics of the MGS (groundings of a meaning, domain of efficiency and transfer of meanings, networking of meanings, evolutionary usage). The MGS approach is close to a simplified version of the Peircean triadic theory of signs (Menant, 2003, 2005 ). We define the representation of an item for a system as being the dynamic set of meaningful information corresponding to the item for the system in its environments (an elementary representation being made of a single meaningful information). These representations link the system to its environment by their meaningful components related to the nature of the system. These representations are different from the GOFAI ones. The possibilities for linking these notions of meaning and representation with the enactive approach come from the structure of the MGS: the need for an action is the cause of the meaning generation by and for the system. The action on the environment is for the system to maintain its nature (its identity). The MGS links together the generation of meaningful representations, the nature of the system, and the interactions with the environment. This can be considered as close to enacting a world by meaning generation (Di Paolo and all 2007), and to the enactive concept of sense making (De Jaegher, Di Paolo 2007). We propose that basing the definition of a representation on the notion of meaningful information generated by a system submitted to a constraint can open a way for making the notion of representation compatible with the enactive approach. In the third part of the presentation, we consider some cases of meaningful information and representations for organisms and for robots. Regarding organisms, the MGS can be used in an evolutionary context by looking at the evolution of the systems and of the constraints. Purpose is to modelize the generation of meanings and of representations in order to make available a tool usable for different levels of evolution, as evolution has a place in cognitive sciences (Proust, 2007). Constraints for basic life are survival constraints (individual and species). Group life constraints are also to be considered. Reaching the level of humans in evolution brings in new constraints that cannot be clearly identified as they have to take into account human consciousness which is today a mystery (the “hard problem”). On an evolutionary standpoint, human constraints come in addition to the ones existing for non human organisms. We can make some hypothesis on the nature of human constraints (Maslow pyramid based constraints, anxiety limitation…). For robots, the MGS is initially based on the design of the robot. The meaning generated within a robot is initially derived from the constraints implemented by the designer and from the environment. But some non calculable or non predictable evolutions of the robot can introduce meanings that look proper to the robot. This last point can be linked to the notion of autonomy in robots. In such examples, the dynamic management of meanings thru the MGSs in their environments keeps the link with the enactive approach. We finish the presentation by summarising the points addressed and by proposing several continuations. (shrink)

How micro- and macroevolutionary evolutionary processes produce phenotypic change is without question one of the most intriguing and perplexing issues facing evolutionary biologists. We believe that roadblocks to progress lie A) in the underestimation of the role of the environment, and in particular, that of the interaction of genotypes with environmental factors, and B) in the continuing lack of incorporation of development into the evolutionary synthesis. We propose the integration of genetic, environmental and developmental perspectives on the (...) evolution of the phenotype in the form of the concept of the developmental reaction norm (DRN) The DRN represents the set of multivariate ontogenies that can be produced by a single genotype when it is exposed to environmental variation. It encompasses: 1) the processes that alter the phenotype throughout the ontogenetic trajectory, 2) the recognition that different aspects of the phenotype are (and must be) correlated and 3) the ability of a genotype to produce phenotypes in different environments. This perspective necessitates the explicit study of character expression during development, the evaluation of associations between pairs or groups of characters (e.g., multivariate allometries), and the exploration of reaction norms and phenotypic plasticity. We explicitly extend the concept of the DRN to encompass adjustments made in response to changes in the internal environment as well. Thus, ‘typical’ developmental sequences (e.g., cell fate determination) and plastic responses are simply manifestations of different scales of ‘environmental’ effects along a continuum. We present: (1) a brief conceptual review of three fundamental aspects of the generation and evolution of phenotypes: the changes in the trajectories describing growth and differentiation (ontogeny), the multivariate relationships among characters (allometry), and the effect of the environment (plasticity); (2) a discussion of how these components are merged in the concept of the developmental reaction norm; and (3) a reaction norm perspective of major determinants of phenotypes: epigenesis, selection and constraint. (shrink)

The notion of representation is at the foundation of cognitive sciences and is used in theories of mind and consciousness. Other notions like ‘embodiment’, 'intentionality‘, 'guidance theory' or ‘biosemantics’ have been associated to the notion of representation to introduce its functional aspect. We would like to propose here that a conception of 'usage related' representation eases its positioning in an evolutionary context, and opens new areas of investigation toward self-representation and self-consciousness. The subject is presented in five parts:Following an (...) overall presentation, the first part introduces a usage related representation as being an information managed by a system submitted to a constraint that has to be satisfied. We consider that such a system can generate a meaningful information by comparing its constraint to a received information (Menant 2003). We define a representation as being made of the received information and of the meaningful information. Such approach allows groundings in and out for the representation relatively to the system. The second part introduces the two types of representations we want to focus on for living organisms: representations of conspecifics and auto-representation, the latter being defined without using a notion of self-representation. Both types of representations have existed for our pre-human ancestors which can be compared to today great apes.In the third part, we use the performance of intersubjectivity as identified in group life with the presence of mirror neurons in the organisms. Mirror neurons have been discovered in the 90‘s (Rizzolatti & al.1996, Gallese & al.1996). The level of intersubjectivity that can be attributed to non human primates as related to mirror neurons is currently a subject of debate (Decety 2003). We consider that a limited intersubjectivity between pre-human primates made possible a merger of both types of representations. The fourth part proposes that such a merger of representations feeds the auto-representation with the meanings associated to the representations of conspecifics, namely the meanings associated to an entity perceived as existing in the environment. We propose that auto-representation carrying these new meanings makes up the first elements of self-representation. Intersubjectivity has allowed auto-representation to evolve into self-representation, avoiding the homunculus risk. The fifth part is a continuation to other presentations (Menant 2004, 2005) about possible evolution of self-representation into self-consciousness. We propose that identification with suffering or endangered conspecifics has increased anxiety, and that the tools used to limit this anxiety (development of empathy, imitation, language and group life) have provided a positive feedback on intersubjectivity and created an evolutionary engine for the organism. Other outcomes have also been possible. Such approach roots consciousness in emotions. The evolutionary scenario proposed here does not introduce explicitly the question of phenomenal consciousness (Block 1995). This question is to be addressed later with the help of this scenario.The conclusion lists the points introduced here with their possible continuations. (shrink)

We present a theory of human artistic experience and the neural mechanisms that mediate it. Any theory of art has to ideally have three components. The logic of art: whether there are universal rules or principles; The evolutionary rationale: why did these rules evolve and why do they have the form that they do; What is the brain circuitry involved? Our paper begins with a quest for artistic universals and proposes a list of ‘Eight laws of artistic experience’ -- (...) a set of heuristics that artists either consciously or unconsciously deploy to optimally titillate the visual areas of the brain. One of these principles is a psychological phenomenon called the peak shift effect: If a rat is rewarded for discriminating a rectangle from a square, it will respond even more vigorously to a rectangle that is longer and skinnier that the prototype. We suggest that this principle explains not only caricatures, but many other aspects of art. Example: An evocative sketch of a female nude may be one which selectively accentuates those feminine form-attributes that allow one to discriminate it from a male figure; a Boucher, a Van Gogh, or a Monet may be a caricature in ‘colour space’ rather than form space. Even abstract art may employ ‘supernormal’ stimuli to excite form areas in the brain more strongly than natural stimuli. Second, we suggest that grouping is a very basic principle. The different extrastriate visual areas may have evolved specifically to extract correlations in different domains , and discovering and linking multiple features into unitary clusters -- objects -- is facilitated and reinforced by direct connections from these areas to limbic structures. In general, when object-like entities are partially discerned at any stage in the visual hierarchy, messages are sent back to earlier stages to alert them to certain locations or features in order to look for additional evidence for the object . Finally, given constraints on allocation of attentional resources, art is most appealing if it produces heightened activity in a single dimension rather than redundant activation of multiple modules. This idea may help explain the effectiveness of outline drawings and sketches, the savant syndrome in autists, and the sudden emergence of artistic talent in fronto-temporal dementia. In addition to these three basic principles we propose five others, constituting a total of ‘eight laws of aesthetic experience’. (shrink)

Recently, various philosophers have argued that we can obtain knowledge via the imagination. In particular, it has been suggested that we can come to know concrete, empirical matters of everyday significance by appropriately imagining relevant scenarios. Arguments for this thesis come in two main varieties: black box reliability arguments and constraints-based arguments. We suggest that both strategies are unsuccessful. Against black-box arguments, we point to evidence from empirical psychology, question a central case-study, and raise concerns about a (claimed) (...) class='Hi'>evolutionary rationale for the imagination's reliability. Against the constraints-based account, we argue that to the extent that it works, this does not give rise to knowledge that is distinctively from the imagination. We conclude by suggesting that the imagination's role in raising possibilities, traditionally seen as part of the context of discovery, can in fact play a role in justification, including as a bulwark against certain sorts of skepticism. (shrink)

The concept of adaptation is pivotal to modern evolutionary thinking, but it has long been the subject of controversy, especially in respect of the relative roles of selection versus constraints in explaining the traits of organisms. This paper tackles a different problem for the concept of adaptation: its interpretation in light of multilevel selection theory. In particular, I arbitrate a dispute that has broken out between the proponents of rival perspectives on multilevel adaptations. Many experts now say that (...) multilevel and kin selection views are mathematically equivalent to one another—that the mathematical accounting of evolution can be carried out at any hierarchical level one chooses. But what does this formal equivalence imply - are they equivalent in other ways too? I show here that significant conceptual non-equivalence has survived: the two sides commit to different views regarding how much selection has to act at a level before we can call traits at that level adaptations; about whether policing mechanisms are adaptations, and about whether non-organisms can bear adaptations. (shrink)

Epistemological objections to moral realism allege that realism entails moral skepticism. Many philosophers have assumed that theistic moral realists can easily avoid such objections. In this article, I argue that things are not so easy: theists run the risk of violating an important constraint on replies to epistemological objections, according to which replies to such objections may not rely on substantive moral claims of a certain kind. Yet after presenting this challenge, I then argue that theists can meet it, successfully (...) replying to the objections without relying on the problematic kinds of substantive moral claims. Theists have a distinctive and plausible reply to epistemological objections to moral realism. (shrink)

Biological modalities, i.e., biologically possible, impossible, or necessary states of affairs have not received much attention from philosophers. Yet, it is widely agreed that there are biological constraints on physically possible states of affairs, such that not everything that is physically possible is also biologically possible, even if everything that is biologically possible is also physically possible. Furthermore, biologists use concepts that appear to be modal in nature, such as the concept of evolvability in evolutionary developmental biology, or (...) “evo-devo.” The present chapter investigates what kind of modality underlies the concept of evolvability. This concept tries to capture the capacity of an organism or a lineage to sustain genetic changes that enable it to evolve or to evolve adaptively. The basic idea of the proposed approach is to construe evolvability as a kind of accessibility in a modal space. The difficult part is to specify this modal space and the relevant accessibility relation. While there may not be a general way of defining such a relation, there exist model systems for which it is possible, e.g., evolving small RNAs. The modal space in such cases turns out to be quite distinct from those constructed by philosophers, e.g., David Lewis’s similarity metric for possible worlds. Even though the biological case examined here is quite special, attending to the way in which biological possibilities are modeled in this case harbors some general lessons about biological modalities, in particular their dependence on the explanatory goals of the models modeling modality. (shrink)

This paper explores the evolution of consciousness and subjectivity through a biological framework for understanding the universe. It posits that functional patterns in biological systems mirror cosmic mathematical principles, defining our objective reality. Similar to wave and Fibonacci patterns in different physical phenomena, biological patterns are intrinsic to all things and can be quantified using Dedre Gentner’s approach to analogy. For example, Earth’s ocean currents and the melting and freezing of Antarctica resemble the circulatory system and heart, while the production (...) of music from instruments is analogous to ribosomal protein synthesis. Shelves, tables, and chairs function like cytosol by holding objects in space, and a coffee cup mirrors red blood cell distribution. These analogies reveal a universal order rooted in biology’s functional patterns, essential for shaping the emergence and evolution of life. The paper traces the development of consciousness from its rudimentary cellular states to complex human cognition, highlighting the role of biologically-patterned environments in driving evolutionary changes. Organisms that recognized and organized according to these patterns evolved as “pattern recognition engines” crucial for survival—thus, Life (survival) being the primary measure of consciousness. Humans advanced this capacity, gaining cognitive freedom by insulating themselves from environmental constraints, but faced increased subjectivity complexity. Consciousness, while inherently subjective and necessary for cognitive development, evolves in humans to understand objective reality and its biological nature, so to understand and navigate complexities of subjectivity. Ultimately, the paper asserts consciousness is the ability to recognize and adhere to life-sustaining patterns and principles. Successful adherence deems them worthy of continued existence, while failure leads to demise. Parallels with historical concepts like Atman and Brahman in Hinduism suggest ancient recognition of the correspondence between human and universal patterns. This ancient understanding, coupled with modern scientific evidence, reveals the interconnectedness and intrinsic biological nature of reality. (shrink)

Freedom is generated in at least two distinct ways: as the ability to avoid perceived dangers and pursue perceived goods, and even to pursue complicated plans in those directions, freedom evolves. But as a social and political matter, freedom seems more subject to human will. The best social institutions -- the kind that serve to encourage or constrain freedom of choice -- also appear to be evolutionary products in some sense. Can there be too much freedom? Of course there (...) can. No constraint at all would guarantee personal and social disaster. Individual activity can pose serious dangers to nature and to culture. But how may we ensure that the constraints we may chose to impose our ones that are good for us? What we need to do is to find, as consistently as possible with the necessity that human individuals be able to use their local perception of local opportunity in pursuit of their own interests, a framework that emerges out of human practice; we should take advantage of lessons learned about evolution: those strategies work that are in tune with the forces at work within the niche. In our attempts to solve social problems, we can't afford to take our eyes off the characteristics of the individuals that make up the social world we hope to change. And in my view, here as elsewhere, the smallest intervention is likely to be the best. (shrink)

Kant’s notorious remark about the impossibility of there ever being a Newton of a blade of grass has often been interpreted as a misguided pre-emptive strike against Darwin and evolutionary theories in general: 'It would be absurd for humans even to make such an attempt or to hope that there may yet arise a Newton who could make comprehensible even the generation of a blade of grass according to natural laws that no intention has ordered; rather, we must absolutely (...) deny this insight to human beings. (CPJ 5:400) My aim in this chapter is to re-evaluate this claim in the context of Kant’s account of organic generation and argue that, contrary to what is usually thought, it does leave room for the possibility of evolution. After spelling out the constraints Kant identifies for any scientific study of the history of living beings, I examine his theory of generation and draw its implications for biological heredity, species diversity, and the role played by environmental factors in organic development. On this basis, I conclude that first, evolution is a possible albeit far-fetched hypothesis for Kant; second, Darwin’s theory of natural selection would have turned a far-fetched possibility into a plausible candidate; and third, it would not have disposed of the need for teleology. This is why, I argue, Darwin could never have been a Newton of a blade of grass. (shrink)

If someone disagrees with my moral views, or more generally if I’m in a group of n people who all disagree with each other, but I don’t have any special evidence or basis for my epistemic superiority, then it’s at best a 1-in-n chance that my views are correct. The skeptical threat from disagreement is thus a kind of moral lottery, to adapt a similar metaphor from Sharon Street. Her own genealogical debunking argument, as I discuss, relies on a premise (...) of such disagreement among evolutionary counterparts. -/- In this paper, I resist the threat from disagreement by showing that, on some of the most influential and most attractive theories of content determination, the premise of moral disagreement cannot serve any skeptical or revisionary purposes. I examine and criticize attempts, made by Gilbert Harman and Sharon Street, to argue from disagreement to relativism by relying on a theory of content determination that involves a principle that, within certain constraints, maximizes the attribution to us of true beliefs. And I examine and criticize Robert Williams’s attempt to show there is moral disagreement by relying on a theory of content determination that involves a principle that instead maximizes the attribution to us of rationality. My overall aim is to defend commonsense moral realism via a careful look at the theory of content and concepts. (shrink)

Based on Kolchinsky and Wolpert’s work on the semantics of autonomous agents, I propose an application of Mathematical Logic and Probability to model cognitive processes. In this work, I will follow Bateson’s insights on the hierarchy of learning in complex organisms and formalize his idea of applying Russell’s Type Theory. Following Weaver’s three levels for the communication problem, I link the Kolchinsky–Wolpert model to Bateson’s insights, and I reach a semantic and conceptual hierarchy in living systems as an explicative model (...) of some adaptive constraints. Due to the generality of Kolchinsky and Wolpert’s hypotheses, I highlight some fundamental gaps between the results in current Artificial Intelligence and the semantic structures in human beings. In light of the consequences of my model, I conclude the paper by proposing a general definition of knowledge in probabilistic terms, overturning de Finetti’s Subjectivist Definition of Probability. (shrink)

This chapter proceeds in five steps. First, we will describe and justify the structure of the traditional system of species classification. Second, we will discuss three formal principles governing the development of taxonomies in general. It will emerge that, in addition to these formal principles, a division of living beings must meet certain empirical constraints. In the third section, we will show that the traditional division of living beings into species best meets these constraints. Fourth, we will argue (...) that a taxonomic system based on this notion of species provides a more natural alternative to the many arbitrary classifications that are possible. Hence, the traditional classificatory system is also the most natural one. Finally, we will discuss and reject an alternative account that suggests defining species solely with a view to their evolutionary history. We will argue that taxonomic trees do not depict hereditary connections but, rather, something else. (shrink)

Symmetry in biological and physical systems is a product of self-organization driven by evolutionary processes, or mechanical systems under constraints. Symmetry-based feature extraction or representation by neural networks may unravel the most informative contents in large image databases. Despite significant achievements of artificial intelligence in recognition and classification of regular patterns, the problem of uncertainty remains a major challenge in ambiguous data. In this study, we present an artificial neural network that detects symmetry uncertainty states in human observers. (...) To this end, we exploit a neural network metric in the output of a biologically inspired Self- Organizing Map Quantization Error (SOM-QE). Shape pairs with perfect geometry mirror symmetry but a non-homogenous appearance, caused by local variations in hue, saturation, or lightness within and/or across the shapes in a given pair produce, as shown here, a longer choice response time (RT) for “yes” responses relative to symmetry. These data are consistently mirrored by the variations in the SOM-QE from unsupervised neural network analysis of the same stimulus images. The neural network metric is thus capable of detecting and scaling human symmetry uncertainty in response to patterns. Such capacity is tightly linked to the metric’s proven selectivity to local contrast and color variations in large and highly complex image data. (shrink)

How to use a model organism to study phenotypic integration and constraints on evolution.

Allen Buchanan and Russel Powell’s The Evolution of Moral Progress (EMP) is likely to become a landmark. It adeptly builds on much of the recent empirical work, weaving it together with philosophical material drawn from a series of essays published by the two authors. EMP makes the case that moral progress is not only consistent with human psychology but—under some conditions—likely. At its heart is a careful, well-developed rebuttal to the idea that there are evolved constraints endogenous to human (...) minds that place significant limits on various forms of moral progress, especially on the spread and sustainability of inclusive values. The alternative picture they present acknowledges that evolutionary history has shaped how our minds produce behaviour, but emphasizes that the contexts in which they currently operate are just as pivotal. While safe and stable ecological and social circumstances are hospitable to cosmopolitanism and encouraging of inclusive values, dangerous and threatening circumstances are more favourable to parochialism, exclusivist values, and morally regressive outgroup hostility (also see Buchanan and Powell [2015], [2016], [2017]). Overall, EMP is a compelling, well-researched, and timely book. It articulates arguably the most persuasive naturalistic theory of moral progress to date, and lays the groundwork for important and impactful research. (shrink)