Companion robots: the hallucinatory danger of human-robot interactions

The advent of the so-called Companion Robots is raising many ethical concerns among scholars and in the public opinion. Focusing mainly on robots caring for the elderly, in this paper we analyze these concerns to distinguish which are directly ascribable to robotic, and which are instead preexistent. One of these is the “deception objection”, namely the ethical unacceptability of deceiving the user about the simulated nature of the robot’s behaviors. We argue on the inconsistency of this charge, as today formulated. After that, we underline the risk, for human-robot interaction, to become a hallucinatory relation where the human would subjectify the robot in a dynamic of meaning-overload. Finally, we analyze the definition of “quasi-other” relating to the notion of “uncanny”. The goal of this paper is to argue that the main concern about Companion Robots is the simulation of a human-like interaction in the absence of an autonomous robotic horizon of meaning. In addition, that absence could lead the human to build a hallucinatory reality based on the relation with the robot

Distributed Processes, Distributed Cognizers and Collaborative Cognition

Cognition is thinking; it feels like something to think, and only those who can feel can think. There are also things that thinkers can do. We know neither how thinkers can think nor how they are able do what they can do. We are waiting for cognitive science to discover how. Cognitive science does this by testing hypotheses about what processes can generate what doing (“know-how”) This is called the Turing Test. It cannot test whether a process can generate feeling, hence thinking -- only whether it can generate doing. The processes that generate thinking and know-how are “distributed” within the heads of thinkers, but not across thinkers’ heads. Hence there is no such thing as distributed cognition, only collaborative cognition. Email and the Web have spawned a new form of collaborative cognition that draws upon individual brains’ real-time interactive potential in ways that were not possible in oral, written or print interactions

Distributed Processes, Distributed Cognizers and Collaborative Cognition

Cognition is thinking; it feels like something to think, and only those who can feel can think. There are also things that thinkers can do. We know neither how thinkers can think nor how they are able do what they can do. We are waiting for cognitive science to discover how. Cognitive science does this by testing hypotheses about what processes can generate what doing (“know-how”) This is called the Turing Test. It cannot test whether a process can generate feeling, hence thinking -- only whether it can generate doing. The processes that generate thinking and know-how are “distributed” within the heads of thinkers, but not across thinkers’ heads. Hence there is no such thing as distributed cognition, only collaborative cognition. Email and the Web have spawned a new form of collaborative cognition that draws upon individual brains’ real-time interactive potential in ways that were not possible in oral, written or print interactions

Bruno Latour

This slender, quirky, and intriguing book collects three pièces d'occasion that collectively extend the argument against the fetishism of facts so memorably advanced in Bruno Latour's We Have Never Been Modern (1993 [1991]). The first piece is a translation of a 1996 pamphlet that Latour wrote about an internship with an ethnopsychiatric practice at the Centre Devereux in Paris. The second republishes the introduction (coauthored by Peter Weibel) to the catalogue of the 2002 exhibition Iconoclash, which Latour co-curated, at the Zentrum für Kunst und Medientechnologie in Karlsruhe, Germany. The third selection was published in 2005 in the volume Science, Religion, and the Human Experience (Oxford), edited by James D. Proctor

The Initiation of the Beautiful Uncanny

In recent years, there has been a movement in arts and one of the interests was in the uncanny where it was relating to surrealism. Previous artwork has addressed the Freudian uncanny concept as an unfamiliar, frightened emotion that is negatively disturbing. However, the concept of Nicholas Royal that uncanny can be strangely beautiful has opened up a new sight that been followed in this thesis. The artwork and art exhibition on fine art are mostly descriptive on creating acceptable uncanny artwork with a sense of beauty. To address the uncanny differently than what used to be and shed the light into the site of beauty to respond, a practice-based research has been carried out to highlight that uncanny can be perceived as beautiful in art. The fundamental aim of this research is to characterise a clear understanding of uncanny beauty. The three research exhibitions of this work were targeting the understanding of what I call“ beautiful uncanny”, as there is a reflective process in the relationship between the imagination of beauty with the uncanny feelings in a body of visual work. In the light of previous literature, related artwork and my understanding, a creation of human figures, hybrid with insects, through sculpture, based on photography have supported the theory of uncanny as being beautiful with further validation based on testing the responses of the viewers who attend the research exhibitions. The qualitative research has been used in this study to conduct the data of the questionnaire and semi-structured interview. The findings of the study have revealed that the importance of classifying uncanny as being beautiful without any rejection is to establish an artwork that increases attraction and curiosity toward knowledge through understanding the actual feelings of the presented artwork. Therefore, that has proposed an original contribution to the knowledge of the perspective of "The Beautiful Uncanny”

Apocalypse Now!: From Freud, Through Lacan, to Stiegler’s Psychoanalytic ‘Survival Project

The objective of this article is to explore the value of psychoanalysis in the early twenty-first century through reference to Freud, Lacan, and Stiegler’s work on computational madness. In the first section of the article I consider the original objectives of psychoanalysis through reference to what I call Freud’s ‘normalisation project’, before exploring the critique of this discourse concerned with the defence of oedipal law through a discussion of the post-modern ‘individualisation project’ set out by Deleuze and Guattari and others. Tracking the development of ‘the individualisation project’ in history, I consider its connections with the cybernetic theories of Wiener and Shannon in the psycho-cyber-utopianism of the 1990s, before moving on to consider the other side of the psychoanalytic-cybernetic interaction through a discussion of Jacques Lacan’s rereading of Freud’s Beyond the Pleasure Principle in the second section of the article. In reading Lacan’s seminar on Freudian drive in terms of the cybernetic repression of death, I set up the conclusion to the article which involves a discussion of Bernard Stiegler’s ‘survival project’ that relies on a recognition of the limit of death in order to produce human significance and oppose the madness of our contemporary computational reality

Robot Heavens and Robot Dreams: Ultimate Reality in A.I. and Other Recent Films

Numerous recent films understand ultimate reality to be multi-layered. This article examines the various formulas films use to express this idea, such as heaven, dreams, technology, temporal loops and altered mental states, while also exploring the various religious and philosophical traditions on which these ultimate reality films draw. Next, I suggest a postmodern framework as a way of accounting for the ubiquity of the reality theme across filmic genres and I argue that film is a unique medium for expressing this epistemology. Finally, I turn to an extensive analysis of A.I. as a case study of a postmodern, multivalent ultimate reality film and illuminate nine possible endings that combine myth, religion, Freud and Jung with themes of technology and ontological identity

Cognition as management of meaningful information. Proposal for an evolutionary approach.

Humans are cognitive entities. Our behaviors and ongoing interactions with the environment are\ud threaded with creations and usages of meaningful information, be they conscious or unconscious.\ud Animal life is also populated with meaningful information related to the survival of the individual\ud and of the species. The meaningfulness of information managed by artificial agents can also be\ud considered as a reality once we accept that the meanings managed by an artificial agent are\ud derived from what we, the cognitive designers, have built the agent for.\ud This rapid overview brings to consider that cognition, in terms of management of meaningful\ud information, can be looked at as a reality for animal, humans and robots. But it is pretty clear\ud that the corresponding meanings will be very different in nature and content. Free will and selfconsciousness\ud are key drivers in the management of human meanings, but they do not exist for\ud animals or robots. Also, staying alive is a constraint that we share with animals. Robots do not\ud carry that constraint.\ud Such differences in meaningful information and cognition for animal, humans and robots could\ud bring us to believe that the analysis of cognitions for these three types of agents has to be done\ud separately. But if we agree that humans are the result of the evolution of life and that robots are a\ud product of human activities, we can then look at addressing the possibility for an evolutionary\ud approach at cognition based on meaningful information management. A bottom-up path would\ud begin by meaning management within basic living entities, then climb up the ladder of evolution\ud up to us humans, and continue with artificial agents.\ud This is what we propose to present here: address an evolutionary approach for cognition, based\ud on meaning management using a simple systemic tool.\ud We use for that an existing systemic approach on meaning generation where a system submitted\ud to a constraint generates a meaningful information (a meaning) that will initiate an action in order\ud to satisfy the constraint [1,2]. The action can be physical, mental or other.\ud This systemic approach defines a Meaning Generator System (MGS). The simplicity of the MGS\ud makes it available as a building block for meaning management in animals, humans and robots.\ud Contrary to approaches on meaning generation in psychology or linguistics, the MGS approach is\ud not based on human mind. To avoid circularity, an evolutionary approach has to be careful not to\ud include components of human mind in the starting point.\ud The MGS receives information from its environment and compares it with its constraint. The\ud generated meaning is the connection existing between the received information and the\ud constraint. The generated meaning is to trigger an action aimed at satisfying the constraint. The\ud action will modify the environment, and so the generated meaning. Meaning generation links\ud agents to their environments in a dynamic mode. The MGS approach is triadic, Peircean type.\ud The systemic approach allows wide usage of the MGS: a system is a set of elements linked by a\ud set of relations. Any system submitted to a constraint and capable of receiving information from\ud its environment can lead to a MGS. Meaning generation can be applied to many cases, assuming\ud we identify clearly enough the systems and the constraints. Animals, humans and robots are then\ud agents containing MGSs. Similar MGSs carrying different constraints will generate different\ud meanings. Cognition is system dependent.\ud We first apply the MGS approach to animals with “stay alive” and “group life” constraints. Such\ud constraints can bring to model many cases of meaning generation and actions in the organic\ud world. However, it is to be highlighted that even if the functions and characteristics of life are well\ud known, the nature of life is not really understood. Final causes are difficult to integrate in our\ud today science. So analyzing meaning and cognition in living entities will have to take into account\ud our limited understanding about the nature of life. Ongoing research on concepts like autopoiesis\ud could bring a better understanding about the nature of life [3].\ud We next address meaning generation for humans. The case is the most difficult as the nature of\ud human mind is a mystery for today science and philosophy. The natures of our feelings, free will\ud or self-consciousness are unknown. Human constraints, meanings and cognition are difficult to\ud define. Any usage of the MGS approach for humans will have to take into account the limitations\ud that result from the unknown nature of human mind.\ud We will however present some possible approaches to identify human constraints where the MGS\ud brings some openings in an evolutionary approach [4, 5]. But it is clear that the better human\ud mind will be understood, the more we will be in a position to address meaning management and\ud cognition for humans. Ongoing research activities relative to the nature of human mind cover\ud many scientific and philosophical domains [6].\ud The case of meaning management and cognition in artificial agents is rather straightforward with\ud the MGS approach as we, the designers, know the agents and the constraints. In addition, our\ud evolutionary approach brings to position notions like artificial constraints, meaning and autonomy\ud as derived from their animal or human source.\ud We next highlight that cognition as management of meaningful information by agents goes\ud beyond information and needs to address representations which belong to the central hypothesis\ud of cognitive sciences.\ud We define the meaningful representation of an item for an agent as being the networks of\ud meanings relative to the item for the agent, with the action scenarios involving the item.\ud Such meaningful representations embed the agents in their environments and are far from the\ud GOFAI type ones [4]. Meanings, representations and cognition exist by and for the agents.\ud We finish by summarizing the points presented and highlight some possible continuations.\ud [1] C. Menant "Information and Meaning" http://cogprints.org/3694/\ud [2] C. Menant “Introduction to a Systemic Theory of Meaning” (short paper)\ud http://crmenant.free.fr/ResUK/MGS.pdf\ud [3] A. Weber and F. Varela “Life after Kant: Natural purposes and the autopoietic foundations of\ud biological individuality”. Phenomenology and the Cognitive Sciences 1: 97–125, 2002.\ud [4] C. Menant "Computation on Information, Meaning and Representations. An Evolutionary\ud Approach" http://www.idt.mdh.se/ECAP-2005/INFOCOMPBOOK/CHAPTERS/10-Menant.pdf\ud http://crmenant.free.fr/2009BookChapter/C.Menant.211009\ud [5] C. Menant "Proposal for a shared evolutionary nature of language and consciousness"\ud http://cogprints.org/7067/\ud [6] Philpapers “philosophy of mind” http://philpapers.org/browse/philosophy-of-min