Thinking Machines Research Articles

Auro Lecci’s Algorithmic Art: Toward the Computer as a Thinking Machine

Abstract This paper analyzes Italian artist Auro Lecci’s contribution to pioneering media art, beginning with his paintings and ending with his computer artworks (1969–1972). As the author suggests, Lecci’s paintings were already characterized by an algorithmic method that the artist went on to develop in his computer-generated works. The paper first discusses the plotter drawings Lecci created at the Computing Center of the University of Pisa (CNUCE), and then focuses on his last computer art project, made at the University of Massachusetts in Amherst, to suggest connections between Lecci’s work and artificial intelligence.

Memory as a Universal Thinking Machine

The present article is designed to reassess the intrinsic values of using memory in the process of language acquisition and language learning, with a focus on the four skills – reading, writing, listening, and speaking – as the building blocks in achieving the best communication goals. According to researchers like Mary Carruthers, Janine Rider, or Lambert Schenkel, there are people who possess a retentive memory, and others who excel in the power of memory. One way or another, memory gives us the ability that generates knowledge, and, by the same token, enables us to speak, read, and write effectively and logically. The sustaining pillars of this monumental edifice are, as touted by medieval thinkers, the concept of memory as a universal thinking machine, as well as (according to more recent researchers) the power of working memory, which can work wonders when we know how to hold and manipulate knowledge. The study of memory from a historical perspective and reflected in world literature can give us an exhaustive frame of reference and the benefits that result in turning accumulated knowledge into accumulated learning.

Что мешает нам создать Общий искусственный интеллект? Одна старая стена и один старый спор

The goal set by A. Turing – the creation of a thinking machine – is one of the most important scientific problems that has not yet been solved. The modern frontier in this area is the creation of Artificial General Intelligence (AGI). Modern researchers are looking for different ways to solve this challenging task. In their search, many scholars point out that attempts to use exclusive lin­guistic communication to solve this problem are not enough. The authors of this article analyze a wide range of research and compare it with well-known re­search in the field of language and consciousness, which became known as the “Zagorsky experiment”. Such a comparison of the latest achievements in the field of AI and an analysis of one of the most breakthrough achievements of neuroscience in the rehabilitation of deaf-blind-mute children is being done for the first time in the literature known to us. Based on the experience of the “Zagorsk experiment”, the article concludes that sensory interaction with the outside world is a necessary condition for the creation of AGI. A vision of vari­ous forms of interaction between the machine and the surrounding world is pro­posed: from verbal to non-verbal, from virtual to physical and otherwise. These forms become the basis for the introduction of a new concept of techno-umwelt. Machine transitions from various techno-umwelts can serve as the basis for cre­ating an AGI that has the ability to act as good or better than a human in a vari­ety of environments.

Is Human Being Computable, or Anthropology of Artificial Intelligence. Methodological Aspect

The article analyzes the anthropological paradigms of the mainstream approaches to AI development. The article concludes that the principle of computability (quantifiability) first introduced in the early stages of AI development (namely by A.Turing) is still paramount. The article showcases the way this principle is rooted in what Heidegger described as treating humans and the state of being itself as a consumable and ultimately destructible commodity. One tries to quantify the state of being in order to consume it. As a consequence, humanity approaches the creation of a “thinking machine” as an exercise in self-imitation. The article highlights the deficiencies of creating AI via copying human patterns. The article also suggests a viable alternative — a mediatory method, developed by culturally-historical psychology. The latter perceives the thought process not as a brain activity but as a objective act, mediated through sings and speech. This way of thinking leads to a new strategy of AI development — as a smart helping hand for humans. This, however, requires an overhaul in medical, educational, governmental and many other social practices. The author concludes that any AI development is bound to start with a social engineering process, renovating the principles, governing day to day lives. This is why the development of AI is not a purely technological task. Is affects a deeper level of human existence, unfit to be interpreted in numerical terms.

Transmission Mysteries: Art and Technophilia

Transmission Mysteries: Art and Technophilia

Artificial Intelligence: History and its Legal Framework in Indonesia

The purpose of this study is to addresses overview of AI and its use within Indonesian law. The discussion aims to be nuanced while also being understandable to those who do not have a technical background and to investigate AI's application relating to the formation of Indonesian laws. This study is a qualitative study. Indonesian regulations only apply to individuals and legal entities that are legally recognized legal subjects. AI is not intelligent in the sense of human cognition, nor intelligent thinking machines. AI is the ability to train computer how to do specific task. The role of the state in providing legal protection should be defined. This legal protection is required to provide legal certainty to the AI user community, both through AI-specific laws and regulations, as well as special institutions authorized to oversee the use of AI in Indonesia.

The Philosophising Machine – a Specification of the Turing Test

Block’s (The Philosophical Review, 90(1), 5–43 1981) anti-behaviourist attack of the Turing Test not only illustrates that the test is a non-sufficient criterion for attributing thought; I suggest that it also exemplifies the limiting case of the more general concern that a machine which has access to enormous amounts of data can pass the Turing Test by simple symbol-manipulation techniques. If the answers to a human interrogator are entailed by the machines’ data, the Turing Test offers no clear criterion to distinguish between a thinking machine and a machine that merely manipulates representations of words and sentences as it is found in contemporary Natural Language Processing models. This paper argues that properties about vagueness are accessible to any human-like thinker but do not normally display themselves in ordinary language use. Therefore, a machine that merely performs simple symbol manipulation from large amounts of previously acquired data – where this body of data does not contain facts about vagueness – will not be able to report on these properties. Conversely, a machine that has the capacity to think would be able to report on these properties. I argue that we can exploit this fact to establish a sufficient criterion of thought. The criterion is a specification of some of the questions that, as I explain, should be asked by the interrogator in a Turing Test situation.

A Constitution for the Anthropocene Body Politic Environment, Culture, and the Humanities in the Twenty-First Century

The following article is a slightly revised version of Serenella Iovino’s Keynote Address at the 2021 European Conference for the Humanities, jointly organised in Lisbon (5-7 May) by the UNESCO Social and Human Sciences Programme, the International Council for Philosophy and Human Sciences (CIPSH), and the Portuguese Foundation for Science and Technology (FCT). The theme of the Conference Section inaugurated by this lecture was “The Humanities in the Twenty-First Century”. By acknowledging the official approval of the BRIDGES Project on education for sustainability as a partner of the UNESCO Management of Social Transformation Program, Iovino evaluated the role of the Environmental Humanities in the agenda of the so-called ‘New Humanities’, paying special attention to their relevance during the COVID-19 pandemic. In this framework, Venice emerged both as a symbol and as a very concrete object of care, proving to be “a thinking machine” for contemporary natural-cultural dynamics, as Salvatore Settis has defined it. The lecture ended with the invitation to turn the current crisis into a constitutive moment for the ‘Anthropocene body politic’, namely, the earthly collective of agents and of processes, both human and nonhuman, natural and technological.

Machines Imitating Human Thinking Using Bayesian Learning and Bootstrap

In the field of cognitive science, much research has been conducted on the diverse applications of artificial intelligence (AI). One important area of study is machines imitating human thinking. Although there are various approaches to development of thinking machines, we assume that human thinking is not always optimal in this paper. Sometimes, humans are driven by emotions to make decisions that are not optimal. Recently, deep learning has been dominating most machine learning tasks in AI. In the area of optimal decisions involving AI, many traditional machine learning methods are rapidly being replaced by deep learning. Therefore, because of deep learning, we can expect the faster growth of AI technology such as AlphaGo in optimal decision-making. However, humans sometimes think and act not optimally but emotionally. In this paper, we propose a method for building thinking machines imitating humans using Bayesian decision theory and learning. Bayesian statistics involves a learning process based on prior and posterior aspects. The prior represents an initial belief in a specific domain. This is updated to posterior through the likelihood of observed data. The posterior refers to the updated belief based on observations. When the observed data are newly added, the current posterior is used as a new prior for the updated posterior. Bayesian learning such as this also provides an optimal decision; thus, this is not well-suited to the modeling of thinking machines. Therefore, we study a new Bayesian approach to developing thinking machines using Bayesian decision theory. In our research, we do not use a single optimal value expected by the posterior; instead, we generate random values from the last updated posterior to be used for thinking machines that imitate human thinking.

Research and Implementation of Machine Programming Based on Agile Thinking

With the rapid development of information, communication, network and computer, the field, depth and breadth of computer applications are also rapidly expanding. The traditional production methods, development techniques and development tools of software development are no longer suitable for the system software development with larger and larger scale and more complex structure. Facing the fast changing demand, how to develop software quickly and quickly has become an urgent problem. This paper takes the agile development methodology as the support point and the core idea, puts forward to adopt the agile development thought as the core, take IDE as the tool, take machine programming as the core technology, carries on the research to the agile thinking machine programming technology, carries on the development in Visual Studio, finally, realizes carries on the programming with the machine.

Artificial Intelligence and the Common Sense of Animals.

The problem of common sense remains a major obstacle to progress in artificial intelligence. Here, we argue that common sense in humans is founded on a set of basic capacities that are possessed by many other animals, capacities pertaining to the understanding of objects, space, and causality. The field of animal cognition has developed numerous experimental protocols for studying these capacities and, thanks to progress in deep reinforcement learning (RL), it is now possible to apply these methods directly to evaluate RL agents in 3D environments. Besides evaluation, the animal cognition literature offers a rich source of behavioural data, which can serve as inspiration for RL tasks and curricula.

Robot Ergonomics: A cognitive scenario of the new behavioral Objects

The research reviews the tremendous development of Ergonomics in the information era. As the traditional products design shifts to be interactive, Ergonomic science must be applied in new and diverse ways to suit the challenges of the near future. Here, there was a need to create a new concept that elevates Ergonomics applications and sciences to a new level of future product design — interactive and robotic — that is called Robot Ergonomics, which represents a new and innovative activity in measurement and verification systems. Modeling the behavior of robot - which is the most sophisticated and complex creative thinking machine - is considered as one of the most important factors in the user's understanding of the new interactive relationships. Therefore, the designer uses the scenario-style methodology to design a proactive work environment in order to improve the process of virtual interaction in advance, an approach that monitors current errors and predicts those that are expected in the future. In addition, the virtual interaction is based on achieving the central concepts of use and taking into account the physical appearances of the interaction environment by eliciting the scenario of Robot Ergonomics determinants, and therefore harmonizes the reaction rhythm. The designer then relies on the experts' scenario to simulate the emotional presence of the user and correct the concepts of interaction perception in a real way, which improves the quality of the realistic interaction by adding new design dimensions, as well as can be used within the interactive work situations.

BEHAVIORAL COMPONENTS IN RELATIONSHIPS OF ECONOMIC AGENTS (EXAMPLE OF THE UKRAINIAN CAR MARKET)

In neoclassical economics a concept of individual is seen as a logical thinking machine, which accurately analyzes all information received and, based on it, makes decisions that maximize his/her personal gain and minimize risks while achieving his/her goals. Such behavior of a person is called rational. Such concept serves as a source of neoclassicism for the construction of supply and demand models, operation of tax systems, business cycles, inflation etc. It was not accepted to pay attention to the psychology of decision-making, it was believed, that these transient, random factors pale against the grandeur of economic incentives. Psychologists are interested in solutions that are emotional, casual, pursued by some sort of cultural ideas, norms, rules, and may even be phobias, conversely economics is the science of rational behavior. The purpose of this paper is to identify and analyze the behavioral components and their influence on the interaction of economic agents in the commodity market. The study used methods of constructing a multivariate regression model, OLS, Student and Fisher criteria, statistical research, sociological surveys and expert opinion. Authors will analyze the behavioral aspects of market relationships on the example of used car market in Ukraine This paper provides several different situations and tested them with real market data to demonstrate that both buyers and sellers may not act rationally on the market, set prices, based on their personal beliefs, subjective and psychological factors and that must be considered when building economical models.

Turing : l’incalculabilité et l’imprédictibilité

Turing : Uncalculability and Unpredictability. The objective of this paper is to highlight the co-presence, in Turing’s work, of two competing lines of research : one line the objective of which is to challenge the limits of calculability and then to consider the possibility of a thinking machine ; the other line, relying upon the non coincidence of determinism and predictability of dynamical systems, that leads to the irreducibility of a human brain to a “discrete-state machine”. The three oppositions discrete/continuous, logic/dynamics, and arithmetic/geometry make it possible to better understand the contradiction between these two lines of research, a contradiction which, in turn, commands a reassessment of the first of these three alternatives.

Currents of valuable conglomerates in the differences of human wishes: G. Deloz - F. Guattari

The article examines the role of value conglomerate currents in sections of willing machines inthe philosophy of G. Deleuze and F. Guattari. The movement and current of value conglomeratesthrough the person turned away from God is refined and formed. Accordingly, the essence of theconcepts introduced by the philosophers of the «wanting machine» and «body without organs»is clarified. It is noted that the specificity of the terminological apparatus of the collaborationof philosophers is built on the defined ontological plane of diversity and the dichotomouscontradiction of mental and schizoid judgments, where meaning loses the usual forms of logicand is replaced by singularities. The dichotomy of singularities was developed by G. Deleuzein the treatise «The Logic of Meaning», during the study of planes of meaning in the worksof L. Carroll. It is established that the desiring machine becomes the presentation of the basiccomponent of the person - as an organism, mental thinking and unconscious consumption. Havingthe constituent organs of activity, a person is unconsciously formed into a willing machine, thatis, a person moves at will, which is modeled in his instructions for using his own organism. It isnoted that the machine that desires is not just a symbiosis of spare parts, which can be noticed inthe philosophy of G. Deleuze and F. Guattari in the first place, but is a machine that constantlydesires, even when something sucks in itself. Desire pushes the machine to interconnect withother machines, so it becomes a slave of its own desires, and the range of these desires expandsand then narrows like a pendulum oscillation. The desires themselves are irresistible, so someof them are controlled by capitalism and psychiatry through the structure of a society of control,digitization and detritorialization. It is the machines that desire to do everything by the body, butit causes the body to suffer, because the body is already a concept of docking, levers, standards ofconnection, moral regulators of the superconscious. It is determined that the body without organscomes into conflict with the wanting machine, because the body searches for the cause of sufferingin the presence of organs, and therefore removes them, becomes sterile. However, philosopherspoint to the constant repetition of motions not only of the desiring machine, but also of the bodywithout organs: decipherment returns to digitization, the body being filled by the organs of desire.The processes of constant return are deteritized by capitalism. Value conglomerates themselvescombine into the horrible twin of God and the devil, good and evil. The minority replaces themajority. An example of the metamorphosis of a minority homosexual into the majority of LGBTpeople is given. It is stated that the most valuable conglomerates are embedded in the ontologicalmetamorphosis, not in the dualism of the pairs of good and evil. The values themselves are definedas the lines of cutting a person through the pendulum movements of the jacket of good and evil,and therefore, as such, they are not internal to the wanting machine. The model of movement ofthe flows of value conglomerates, which is represented as a continuous cutting of the lines of thegood and evil desires of passive thinking machines, driven into the judgment of the social systemby the method of psychoanalytic compulsion, is defined. In this model, the face of God is alwaysturned away from man, and the desire of man crosses God as if sewing him to his own judgment.

Book Review: "The Big Nine: How the Tech Titans & Their Thinking Machines Could Warp Humanity"

Book Review: "The Big Nine: How the Tech Titans & Their Thinking Machines Could Warp Humanity"

If Machines Want to Dream... Adam Wiśniewski-Snerg on Ethical Consequences of There Being No Substantial Distinction between Humans and Robots

Adam Wiśniewski-Snerg (1937-1995) was a Polish science fiction writer. In his novel Robot (1973), he made an attempt at a literary visualization of a machine acquiring human identity. In this article I would like to follow the ethical consequences of such situations in created literary worlds. It is worth remembering, however, that these artistic worlds often serve to test non-literary reality. In his novel, Wiśniewski-Snerg also dealt with the problem of human feelings (e.g. moral dilemmas) in a thinking machine, which is formed in the image and likeness of a human being. Such literary reflection is valuable, partly because it enters into an interesting dialogue with the work of Bruno Schulz (1892- 1942), one of the most important Polish writers of the 20th century. It is also one of the first attempts in Polish literature to address the issue of sentient machines, and is a kind of preview of contemporary dilemmas connected with the work on the creation of artificial intelligence. An example of such a dilemma is the issue of the sentient machine’s perception of the tasks imposed on it by the human-constructor. Perhaps it will start to experience them as a kind of unethical oppression. In Wiśniewski-Snerg’s writing this problem of is, of course, expressed in a metaphorical way.

The Postdigital Challenge of Critical Media Literacy

This article situates contemporary critical media literacy into a postdigital context. It examines recent advances in data literacy, with an accent to Big Data literacy and data bias, and expands them with insights from critical algorithm studies and the critical posthumanist perspective to education. The article briefly outlines differences between older software technologies and artificial intelligence (AI), and introduces associated concepts such as machine learning, neural networks, deep learning, and AI bias. Finally, it explores the complex interplay between Big Data and AI and teases out three urgent challenges for postdigital critical media literacy. (1) Critical media literacy needs to reinvent existing theories and practices for the postdigital context. (2) Reinvented theories and practices need to find a new balance between the technological aspects of data and AI literacy with the political aspects of data and AI literacy, and learn how to deal with non-predictability. (3) Critical media literacy needs to embrace the posthumanist challenge; we also need to start thinking what makes AIs literate and develop ways of raising literate thinking machines. In our postdigital age, critical media literacy has a crucial role in conceptualisation, development, and understanding of new forms of intelligence we would like to live with in the future.

Biological Faithfulness is Unnecessary for Machine Learning

Artificial intelligence (AI) is the ability of any device to take an input, like that of its environment, and work to achieve a desired output. Some advancements in AI have focused n replicating the human brain in machinery. This is being made possible by the human connectome project: an initiative to map all the connections between neurons within the brain. A full replication of the thinking brain would inherently create something that could be argued to be a thinking machine. However, it is more interesting to question whether a non-biologically faithful AI could be considered as a thinking machine. Under Turing’s definition of ‘thinking’, a machine which can be mistaken as human when responding in writing from a “black box,” where they can not be viewed, can be said to pass for thinking. Backpropagation is an error minimizing algorithm to program AI for feature detection with no biological counterpart which is prevalent in AI. The recent success of backpropagation demonstrates that biological faithfulness is not required for deep learning or ‘thought’ in a machine. Backpropagation has been used in medical imaging compression algorithms and in pharmacological modelling.

Can the Machine Understand: An Evidence Based Approach to the Chinese Room

The debate of a thinking machine continues on, especially in an era where machines are achieving tasks that we never thought possible. In this essay, I explore one of the most famous critiques of the thinking machine, Searle’s Chinese room, by breaking down his argument into two claims of varying scope. I then offer an alternative method to assess this argument, by employing a top down approach in contrast to Searles which seems to advance from the conclusion. I explore the current thinking on how the human brain may come to understand the world, as well as some of the aspects of these semantics. This is all in an effort to elucidate some the features necessary for machine understanding and to accurately assess whether a machine possesses them. I conclude that Searle may have been too quick to judge the abilities of computers, and that a claim that any digital computer cannot understand is much too strong.