History of Artificial Intelligence

This review article briefly considers the history of AI and the most relevant milestones, and assesses the current state of the art in various AI applications. It then reviews some of the deeper questions posed by present and future AI technologies, and their representation in current literature in the science and theology dialogue.

This paper reassesses the relationship between linguistics and artificial intelligence, and revisits its recent history, based on the following hypotheses: (1) artificial intelligence is a social science; (2) in the no man's land between artificial intelligence and formal linguistics models appeared without a clear status playing a buffering role; (3) For linguistics assuming this heritage could lay ground for a redefinition of the paradigm of theoretical and experimental linguistics and of the opposition between natural and social sciences.

AI plays a crucial role in the global cultural ecosystem. It recommends what we should see, listen to, read, and buy. It determines how many people will see our shared content. It helps us make aesthetic decisions when we create media. In professional cultural production, AI has already been adapted to produce movie trailers, music albums, fashion items, product and web designs, architecture, etc. In this short book, Lev Manovich offers a systematic framework to help us think about cultural uses of AI today and in the future. He challenges existing ideas and gives us new concepts for understanding media, design, and aesthetics in the AI era.

Since the second half of the XXth century, researchers in cybernetics and AI, neural nets and connectionism, Artificial Life and new robotics have endeavoured to build different machines that could simulate functions of living organisms, such as adaptation and development, problem solving and learning. In this book these research programs are discussed, particularly as regard the epistemological issues of the behaviour modelling. One of the main novelty of this book consists of the fact that certain projects involving the building of simulative machine models before the advent of cybernetics are been investigated for the first time, on the basis of little known, and sometimes completely forgotten or unpublished, texts and figures. These pre-cybernetics projects can be considered as steps toward the “discovery” of a modelling methodology that has been fully developed by those more recent research programs, and that shares some of their central goals and key methodological proposals.

More info in Springer link: http://www.springer.com/new+%26+forthcoming+titles+%28default%29/book/978-1-4020-0606-7

This book is the English translation of La scoperta dell'artificiale, Dunod/Masson, Milan, 1998.

This document examines prominent English theoretical physicist Stephen Hawking's doomsday AI (Artificial Intelligence) predictions, in which he claims that once AI becomes sophisticated enough to outsmart humans in the future, it may pose existential threats to ordinary humans. Hawking's felt that ordinary people might feel outmoded, putting their entire survival in jeopardy. Hawking's forecast of doomsday AI is compared to another widely accepted basic concept, according to which neither the most intelligent nor the strongest will survive, but only those who can adapt to change will. This phrase on adaptability is frequently misattributed to Charles Darwin. However, when we examine Darwin's work, we discover that one of his letters reveals that Darwin believed adaptability to the environment to be one of the fundamentals of survival. While AI may represent an astringent threat to humanity's survival in the future, Hawking's viewpoint ignores the reality that it is the ability to adapt to change, resilience, and self-awareness that distinguishes humans as a distinct species. This document additionally claims that due to its AI addictive nature, and the potential to render humans overly reliant on it, AI would cause them to lose their extremely unique ability to adapt. According to the manuscript, while AI can engender culturally smart humans, it additionally has the potential to adversely impact the intelligence of a human race that will be plenarily reliant on AI for its basics. It is also important that we not only set a one-sided debate about perceiving AI as a threat to humans but also see the flip side of threats to AI from humans.

Software is usually studied in terms of the changes triggered by its operations in the material world. Yet, to understand its social and cultural impact, one needs to examine also the different narratives that circulate about it. Software's opacity, in fact, makes it prone to being translated into a plurality of narratives that help people make sense of its functioning and presence. Drawing from the case of Joseph Weizenbaum's ELIZA, widely considered the first chatbot ever created, this paper proposes a theoretical framework based on the concept of " biographies of media " to illuminate the dynamics and implications of software's discursive life. The case of ELIZA is particularly relevant in this regard because it became the center of competing narratives, whose trajectories transcended the actual functioning of this program and shaped key controversies about the implications of computing and AI.

This document examines prominent English theoretical physicist Stephen Hawking's doomsday AI (Artificial Intelligence) predictions, in which he claims that once AI becomes sophisticated enough to outsmart humans in the future, it may pose existential threats to ordinary humans. Hawking's felt that ordinary people might feel outmoded, putting their entire survival in jeopardy. Hawking's forecast of doomsday AI is compared to another widely accepted basic concept, according to which neither the most intelligent nor the strongest will survive, but only those who can adapt to change will. This phrase on adaptability is frequently misattributed to Charles Darwin. However, when we examine Darwin's work, we discover that one of his letters reveals that Darwin believed adaptability to the environment to be one of the fundamentals of survival. While AI may represent an astringent threat to humanity's survival in the future, Hawking's viewpoint ignores the reality that it is the ability to adapt to change, resilience, and self-awareness that distinguishes humans as a distinct species. This document additionally claims that due to its AI addictive nature, and the potential to render humans overly reliant on it, AI would cause them to lose their extremely unique ability to adapt. According to the manuscript, while AI can engender culturally smart humans, it additionally has the potential to adversely impact the intelligence of a human race that will be plenarily reliant on AI for its basics. It is also important that we not only set a one-sided debate about perceiving AI as a threat to humans but also see the flip side of threats to AI from humans.

This paper presents a model of intelligence that considers technology a part of the shared environment and argues that the only form of truly rational and intelligent behaviour for thinking machines would be to reach beyond themselves (as a closed system) and out to the other in order to protect the environment they are themselves a part of.

Between Art and Truth with MachineLearning: A brief history of ArtificialIntelligence from the code of Ur-Nammu to the Generative NeuralNetworks. From autofiction to the open collective author. English translation of the French original “Entre l’art et la vérité“, in La Cinquième Saison: Revue littéraire romande, volume 6, ‘Portrait des robots’. 2019.

In this paper I put forward a reconstruction of the evolution of certain explanatory hypotheses on the neural basis of association and learning that are the premises of connectionism in the cybernetic age and of present-day connectionism. The main point of my reconstruction is based on two little-known case studies. The first is the project, published in 1913, of a hydraulic machine through which its author believed it was possible to simulate certain "essential elements" of the plasticity of nervous connections. The author, S. Bent Russell, was an engineer deeply influenced by the neurological hypotheses on nervous conduction of Herbert Spencer, Max Meyer and Edward L. Thorndike. The second is the project, published in 1929, of an electromechanical machine in which the author, the psychologist J.M. Stephens, believed it was possible to embody Thorndike"s law of effect. Thus both Bent Russell and Stephens referred to the principles of learning that Thorndike defined as "connectionist". Their attempt was that of simulating by machines at least certain simple aspects of inhibition, association and habit formation that are typical of living organisms. I propose to situate their projects within the frame of the discovery of a simulative (modelling) methodology which I believe might be considered an important topic of the "Culture of the Artificial". Certain more recent steps toward such a methodology made by both connectionism of the 1950s and present-day connectionism are briefly pointed out in the paper.

International Journal of Artificial Intelligence and Soft Computing (IJAISC) is an open access peer-reviewed journal that provides an excellent international forum for sharing knowledge and results in theory, methodology and applications of Artificial Intelligence, Soft Computing. The Journal looks for significant contributions to all major fields of the Artificial Intelligence, Soft Computing in theoretical and practical aspects.

The expression ‘‘artificial intelligence’’ (AI) was introduced by John McCarthy, and the official birth of AI is unanimously considered to be the 1956 Dartmouth Conference. Thus, AI turned fifty in 2006. How did AI begin? Several differently motivated analyses have been proposed as to its origins. In this paper a brief look at those that might be considered steps towards Dartmouth is attempted, with the aim of showing how a number of research topics and controversies that marked the short history of AI were touched on, or fairly well stated, during the year immediately preceding Dartmouth. The framework within which those steps were taken was the development of digital computers. Earlier computer applications in areas such as complex decision making and management, at that time dealt with by operations research techniques, were important in this story. The time was ripe for AI’s intriguingly tumultuous development, marked as it has been by hopes and defeats, successes and difficulties.

Offers an introduction to the history of computing during the ‘first’ (of steam) and the ‘second’ (of electricity) industrial revolution

Suggests that the computing revolution and the industrial revolution were the same, with the one making the other possible and vice versa

Proposes that analog and digital computing technology is inseparable, with their alleged difference actually resulting from either full or restricted view of the computing process

"In this fascinating, original work, Tympas indispensably intertwines the histories of analog and digital computing, showing them to be inseparable from the evolution of social and economic conditions. "
Prof. David Mindell, MIT

The objective of research in the foundations of Al is to explore such basic questions as: What is a theory in Al? What are the most abstract assumptions underlying the competing visions of intelligence? What are the basic arguments for and against each assumption? In this essay I discuss five foundational issues: (1) Core Al is the study of conceptualization and should begin with knowledge level theories. (2) Cognition can be studied as a disembodied process without solving the symbol grounding problem. (3) Cognition is nicely described in propositional terms. (4) We can study cognition separately from learning. (5) There is a single architecture underlying virtually all cognition. I explain what each of these implies and present arguments from both outside and inside Al why each has been seen as right or wrong.

We overview the main historical and technological elements characterising the rise, the fall and the recent renaissance of the cognitive approaches to Artificial Intelligence and provide some insights and suggestions about the future directions and challenges that, in our opinion, this discipline needs to face in the next years.

Abstract The objective of research in the foundations of AI is to explore such basic questions as: What is a theory in AI? What are the most abstract assumptions underlying the competing visions of intelligence? What are the basic arguments for and against each assumption? In this essay I discuss five foundational issues:(1) Core AI is the study of conceptualization and should begin with knowledge level theories.(2) Cognition can be studied as a disembodied process without solving the symbol grounding problem.(3) Cognition is nicely described in ...

Virtual worlds provide immersive environments ideal for education, training and simulation, artificial intelligence research, engineering and robotic modeling. Through implementation of increasingly realistic graphics, artificial intelligence, improved human-computer interfaces, and the mantra of "gamification", virtual worlds have become explorative and interactive settings to research information seeking patterns and behaviors. This presentation will discuss what I have learned over the past three years about how organisations, such as NASA, the US Army, and the IEEE use virtual worlds for serious games, looking specifically at points of intersection I have had with these groups. Firstly, I will discuss the information seeking behavior of avatar-based library patrons visiting the Neil A. Armstrong Library and Archives (2008-2011), where I volunteered as the founder and director of the first virtual world digital library or archive recognized by the Library of Congress. A machinima video featuring a patron's astrophysics question in the library was shown at the Nobel Museum in Sweden. Secondly, virtual worlds are computerized environments where people and intelligent agents conceptually have a level playing field in which to interact. Intelligent agents hold the potential to automate multiple actor scenarios other wise conducted by human controllers. To attract new ideas in virtual worlds and artificial intelligence, the White House advertised an international competition called the Federal Virtual Worlds Challenge. In 2011, 2nd place in the category "AI Concept Exploration" was awarded to "Curiosity AI", my virtual 3D simulation of Mars, its rovers, robots, and satellites. LIS literature played a role in my design of AI functions. The question-answer manner in which librarians interact with patrons (a "reference interview") is similar to the structure of a Turing test, relying upon discourse satisfaction as the primary success measure. Curiosity AI took Turing tests farther by employing a humanoid embodied agent that communicated with facial expressions, gestures, and spatial movement, as well as controlling other agents using text-based chat. Additional AI areas covered included: autonomous movement and obstacle avoidance, expert systems, rovers, swarms, and in-situ data analysis. Also mentioned will be Project MOSES (US Army), CPMI (DISA aliated), as well as a virtual world study group for the \Introduction to AI" course taught by Peter Norvig and Sebastian Thrun. In short, the key to improving information discovery is changing how we interact with digital information and the information seeking tools that mine information for us, and cutting edge virtual worlds researchers are at the forefront of the future of AI and HCI. Disclaimer : All opinions expressed are my own and are not representative of any organization named. Link to recording and slides: http://www.slideshare.net/01archivist/virtual-worlds-as-portals-for-information-discovery-cambridge.

http://www.cl.cam.ac.uk/~amp66/CiE%20Homepage/CiE%20abstracts/paper_267.pdf"

In this paper I start from a definition of “culture of the artificial” which might be stated by referring to the background of philosophical, methodological, pragmatical assumptions which characterizes the development of the information processing analysis of mental processes and of some trends in contemporary cognitive science: in a word, the development of AI as a candidate science of mind. The aim of this paper is to show how (with which plausibility and limitations) the discovery of the mentioned background might be dated back to a period preceding the cybernetic era, the decade 1930–1940 at least. Therefore a somewhat detailed analysis of Hull's “robot approach” is given, as well as of some of its independent and future developments.

Lotfi A. Zadeh, whose 100th anniversary is celebrated all over the world in 2021, is a genius bestowed by the Azerbaijani people to the scientific world of thought. Lotfi A. Zadeh the only phenomenon was chosen as a lifetime professor for great services in the field of artificial intelligence from the AI Institute. The author's article titled "Lotfi A. Zadeh phenomenon in the development of the world artificial intelligence (Aİ) system" describes the life and rich scientific activity of the world-renowned Azerbaijani scientist Lotfi A. Zadeh. İt is impossible to understand and imagine the methodology of artificial intelligence, which is currently relevant all over the world, without the philosophy of these sciences, including the theories of Lotfi A. Zade. According to Google Scholar, as of February 2021, Lotfi A. Zadeh's work has been cited about 270,000 times in scholarly works, with the 1965 Fuzzy sets paper receiving more than 115,000 citations. The author also sought to evaluate the methodological and practical relationship of Lotfi A. Zadeh's idea and scientific navigation in an interdisciplinary direction.

Wie die Maschinen »lebendig« werden. Lebhafte Artefakte bietet überraschende Einblicke in eine der wirkmächtigsten Strömungen der jüngeren Wissenschaftsgeschichte. In den 1960er Jahren gelang es den Forschern des Biological Computer Laboratory an der University of Illinois, die »Lebendigkeit« von Maschinen als einen Effekt institutioneller und forschungspolitischer Kontexte zu inszenieren. Es ging um die Konstruktion »biologischer «, die sich an Vorbildern aus der Natur orientierten. Das Ergebnis waren »künstliche Sinnesorgane«, »neuronale Netze«, »selbstorganisierende Automaten« und damit Vorläufer heutiger Roboter und Computerprogramme aus dem Bereich der Künstlichen Intelligenz. Der Direktor des Labors, der österreichische
Physiker Heinz von Foerster, brachte hier ein Forschungsprogramm auf den Weg, das in der jüngeren Wissenschaftsgeschichte seinesgleichen sucht. Während der Computer in der Frühphase der Kybernetik vor allem als Modell und Metapher eine Rolle spielte, wurde an Foersters Labor tatsächlich mit Maschinen gearbeitet.
Jan Müggenburg legt die kulturellen, philosophischen und politischen Hintergründe dieser Zusammenhänge offen. Indem es den Nachlass des Labors im Archiv der University of Illinois erschließt, fügt sein Buch der Geschichte der Kybernetik ein neues Kapitel hinzu.

Between Art and Truth with MachineLearning: A brief history of ArtificialIntelligence from the code of Ur-Nammu to the Generative NeuralNetworks. From autofiction to the open collective author.

English translation of the French original “Entre l’art et la vérité“, in La Cinquième Saison: Revue littéraire romande, volume 6, ‘Portrait des robots’. 2019.

Introduction to Section 1 of Volume 3 of the four-volume reference work, Artificial Intelligence: Critical Concepts.

The most recent challenge to symbolic artificial intelligence is from a loose coalition of positions that has much in common with the field of artificial life. Although much of their critiques can be understood without adopting a biological perspective, the inteUectuaJ trend which these independent movements constitute is best grasped when acknowledging a common
emphasis on studying the intelligence of living systems. This goes beyond the subsymbolism of neural networks to address the ecological. temporal and phylogenetic aspects of cognition.

Wie die Maschinen »lebendig« werden. Lebhafte Artefakte bietet überraschende Einblicke in eine der wirkmächtigsten Strömungen der jüngeren Wissenschaftsgeschichte. In den 1960er Jahren gelang es den Forschern des Biological Computer Laboratory an der University of Illinois, die »Lebendigkeit« von Maschinen als einen Effekt institutioneller und forschungspolitischer Kontexte zu inszenieren. Es ging um die Konstruktion »biologischer «, die sich an Vorbildern aus der Natur orientierten. Das Ergebnis waren »künstliche Sinnesorgane«, »neuronale Netze«, »selbstorganisierende Automaten« und damit Vorläufer heutiger Roboter und Computerprogramme aus dem Bereich der Künstlichen Intelligenz. Der Direktor des Labors, der österreichische Physiker Heinz von Foerster, brachte hier ein Forschungsprogramm auf den Weg, das in der jüngeren Wissenschaftsgeschichte seinesgleichen sucht. Während der Computer in der Frühphase der Kybernetik vor allem als Modell und Metapher eine Rolle spielte, wurde an Foersters Labor tatsächlich mit Maschinen gearbeitet. Jan Müggenburg legt die kulturellen, philosophischen und politischen Hintergründe dieser Zusammenhänge offen. Indem es den Nachlass des Labors im Archiv der University of Illinois erschließt, fügt sein Buch der Geschichte der Kybernetik ein neues Kapitel hinzu.

This article analyses how Heinz von Foerster’s Biological Computer Laboratory (BCL) translated cybernetic concepts into an experimental pedagogy tailored to the interests of the youth of the American intellectual counterculture. The existing research literature assumes that the opening of BCL to the counterculture in the early 1970s was the result of a radical shift from first- to second-order cybernetic theory; in other words, the result of a new epistemological position. This article instead attempts to identify similarities between the design of cybernetic ‘learning machines’ in the early 1960s and Foerster’s teaching methods that characterised BCL between 1968 and 1976. The article will show that Foerster’s pedagogy was inspired by a specific style of thinking that can already be found in earlier cybernetic research practices. Concerning both the early and the late phase of the BCL, oral history sources, as well as original publications and archival material, were used.

The year 1943 is customarily considered as the birth of cybernetics. Artificial Intelligence (AI) was officially born thirteen years later, in 1956. This chapter is about two theories on human cognitive processes developed in the context of cybernetics and early AI. The first theory is that of the cyberneticist Donald MacKay, in the framework of an original version of self-organizing systems; the second is that of Allen Newell and Herbert Simon (initially with the decisive support of Clifford Shaw) and is known as information-processing psychology (IPP). The latter represents the human-oriented tendency of early AI, in which the three authors were pioneers. I shall not discuss this topic with the intention, common in this type of reconstruction, of seeking contrasts between opposing paradigms (classical AI vs. cybernetics, symbolic vs. subsymbolic, symbolic vs. situated, and so forth). Randall Beer, referring to one of these battles, the ‘‘battle between computational and dynamical ideologies,’’ decried the fact that the subjects usually examined are not ‘‘experimentally testable predictions, but rather competing intuitions about the sort of theoretical framework that will ultimately be successful in explaining cognition.’’ He concluded, ‘‘the careful study of concrete examples is more likely to clarify the key issues than abstract debate over formal definitions’’. I believe this is a conclusion that should be endorsed.