Why War?

2021 ◽  
Author(s):  
Christopher Coker
Keyword(s):  
Artificial Intelligence ◽  
Animal Behavior ◽  
Gene Editing ◽  
Human Agency ◽  
Ways Of Thinking ◽  
Over Time ◽  
Scientific Advances

What are humanity’s biological origins? What are the mechanisms, including culture, that continue to drive it? What is the history that has allowed it to evolve over time? And what are its functions – how does it survive and thrive by exploiting the features that define us as a species? These are the four questions of the ‘Tinbergen Method’ for explaining animal behavior, developed by the prize-winning Dutch ethologist Nico Tinbergen. The book contends that applying this method to war – which is unique to humans – can help us better understand why conflict is so resilient. The author explores these four questions in both past and present, and looks at our post – human future, assessing how far scientific advances in gene- editing, robotics and AI systems will de- center human agency. From the ancient Greeks to Artificial Intelligence (AI)  the book is an exploration of humankind’s propensity to warfare and its behavioral underpinnings. What it offers are new ways of thinking about our species’ unique and deadly preoccupation.

Eternal Today

2018 ◽  
Author(s):  
Jenni Myllykoski ◽  
Anniina Rantakari
Keyword(s):  
Real Time ◽  
Constitutive Relation ◽  
Human Agency ◽  
Fundamental Characteristic ◽  
Time Study ◽  
Software Company ◽  
Present Experience ◽  
Managerial Strategy ◽  
Over Time ◽  
Strategy Making

This chapter focuses on temporality in managerial strategy making. It adopts an ‘in-time’ view to examine strategy making as the fluidity of the present experience and draws on a longitudinal, real-time study in a small Finnish software company. It shows five manifestations of ‘in-time’ processuality in strategy making, and identifies a temporality paradox that arises from the engagement of managers with two contradictory times: constructed linear ‘over time’ and experienced, becoming ‘in time’. These findings lead to the re-evaluation of the nature of intention in strategy making, and the authors elaborate the constitutive relation between time as ‘the passage of nature’ and human agency. Consequently, they argue that temporality should not be treated merely as an objective background or a subjective managerial orientation, but as a fundamental characteristic of processuality that defines the dynamics of strategy making.

Robots as cognitive tools

2002 ◽  
Vol 1 (1) ◽  
pp. 125-143 ◽  
Author(s):  
Rolf Pfeifer
Keyword(s):  
Artificial Intelligence ◽  
Problem Solving ◽  
Main Tool ◽  
Human Cognition ◽  
Abstract Thinking ◽  
Cognitive Tools ◽  
Developmental Robotics ◽  
Information Theoretic ◽  
Natural Forms ◽  
Over Time

Artificial intelligence is by its very nature synthetic, its motto is “Understanding by building”. In the early days of artificial intelligence the focus was on abstract thinking and problem solving. These phenomena could be naturally mapped onto algorithms, which is why originally AI was considered to be part of computer science and the tool was computer programming. Over time, it turned out that this view was too limited to understand natural forms of intelligence and that embodiment must be taken into account. As a consequence the focus changed to systems that are able to autonomously interact with their environment and the main tool became the robot. The “developmental robotics” approach incorporates the major implications of embodiment with regard to what has been and can potentially be learned about human cognition by employing robots as cognitive tools. The use of “robots as cognitive tools” is illustrated in a number of case studies by discussing the major implications of embodiment, which are of a dynamical and information theoretic nature.

scholarly journals Empathet(H)Ics: Intersubjectivity, Interobjectivity, and (Non)Human Storytellers in Colum Mccann’s Let The Great World Spin

2021 ◽  
Vol 7 (1) ◽  
pp. 205-225
Author(s):  
Ada Beleuță ◽  
Keyword(s):  
Social Cognition ◽  
Human Agency ◽  
Space Time ◽  
Terrorist Attacks ◽  
Bruno Latour ◽  
Cognitive Capacities ◽  
Inflection Points ◽  
Social Theories ◽  
Over Time

Tracing some of the inflection points in our conceptualization of empathy, social cognition, intersubjective understanding, and social theories over time, this essay attempts to contextualize and give a possible explanation to the more radical changes determined by the so-called nonhuman turn. Drawing on the theories proposed by Steven Connor, Bill Brown, and Bruno Latour on the relations between human and nonhuman agents, the paper will argue for the inherent potential of things to both exceed the limits of human agency and cognitive capacities (specifically, memory and intersubjective understanding) and foster their expansion. A reading of Colum McCann’s Let the Great World Spin (2009) will emphasize the importance of interobjectivity as a mechanism of augmenting empathy and intersubjective understanding. The polyphony of narrativized memories of loss, mourning, trauma – and even pre-trauma, in their construction of an alternative history to the 9/11 terrorist attacks, uses things to encode, store, and retrieve memories, as well as to facilitate (re)connections with others beyond boundaries of space, time, or death. Thus, the democratic force of storytelling returns to corroborate “a democracy extended to things” (Latour).

scholarly journals Strategy selection as rational metareasoning

2016 ◽  
Author(s):  
Falk Lieder ◽  
Tom Griffiths
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Cost Benefit ◽  
Human Reasoning ◽  
Strategy Selection ◽  
Heuristics And Biases ◽  
Rational Model ◽  
The Mind ◽  
Over Time ◽  
Human Rationality

Many contemporary accounts of human reasoning assume that the mind is equipped with multiple heuristics that could be deployed to perform a given task. This raises the question how the mind determines when to use which heuristic. To answer this question, we developed a rational model of strategy selection, based on the theory of rational metareasoning developed in the artificial intelligence literature. According to our model people learn to efficiently choose the strategy with the best cost-benefit tradeoff by learning a predictive model of each strategy’s performance. We found that our model can provide a unifying explanation for classic findings from domains ranging from decision-making to problem-solving and arithmetic by capturing the variability of people’s strategy choices, their dependence on task and context, and their development over time. Systematic model comparisons supported our theory, and four new experiments confirmed its distinctive predictions. Our findings suggest that people gradually learn to make increasingly more rational use of fallible heuristics. This perspective reconciles the two poles of the debate about human rationality by integrating heuristics and biases with learning and rationality.

scholarly journals Modeling Belief in Dynamic Systems, Part II: Revision and Update

1999 ◽  
Vol 10 ◽  
pp. 117-167 ◽  
Author(s):  
N. Friedman ◽  
J. Y. Halpern
Keyword(s):  
Artificial Intelligence ◽  
Belief Revision ◽  
Dynamic Systems ◽  
Belief Change ◽  
Companion Paper ◽  
Minimal Change ◽  
Special Cases ◽  
Epistemic Modalities ◽  
Over Time ◽  
New Framework

The study of belief change has been an active area in philosophy and AI. In recent years two special cases of belief change, belief revision and belief update, have been studied in detail. In a companion paper (Friedman & Halpern, 1997), we introduce a new framework to model belief change. This framework combines temporal and epistemic modalities with a notion of plausibility, allowing us to examine the change of beliefs over time. In this paper, we show how belief revision and belief update can be captured in our framework. This allows us to compare the assumptions made by each method, and to better understand the principles underlying them. In particular, it shows that Katsuno and Mendelzon's notion of belief update (Katsuno & Mendelzon, 1991a) depends on several strong assumptions that may limit its applicability in artificial intelligence. Finally, our analysis allow us to identify a notion of minimal change that underlies a broad range of belief change operations including revision and update.

scholarly journals On Crashing the Barrier of Meaning in Artificial Intelligence

AI Magazine ◽  
2020 ◽  
Vol 41 (2) ◽  
pp. 86-92 ◽  
Author(s):  
Melanie Mitchell
Keyword(s):  
Artificial Intelligence ◽  
Information Theory ◽  
Animal Behavior ◽  
Developmental Psychology ◽  
Living Systems ◽  
Santa Fe ◽  
Dawn Song ◽  
Artificial Intelligence Systems

In 1986, the mathematician and philosopher Gian-Carlo Rota wrote, “I wonder whether or when artificial intelligence will ever crash the barrier of meaning” (Rota 1986). Here, the phrase “barrier of meaning” refers to a belief about humans versus machines: Humans are able to actually understand the situations they encounter, whereas even the most advanced of today’s artificial intelligence systems do not yet have a humanlike understanding of the concepts that we are trying to teach them. This lack of understanding may underlie current limitations on the generality and reliability of modern artificial intelligence systems. In October 2018, the Santa Fe Institute held a three-day workshop, organized by Barbara Grosz, Dawn Song, and myself, called Artificial Intelligence and the Barrier of Meaning. Thirty participants from a diverse set of disciplines — artificial intelligence, robotics, cognitive and developmental psychology, animal behavior, information theory, and philosophy, among others — met to discuss questions related to the notion of understanding in living systems and the prospect for such understanding in machines. In the hope that the results of the workshop will be useful to the broader community, this article summarizes the main themes of discussion and highlights some of the ideas developed at the workshop.

scholarly journals Engineering Emotionally Intelligent Agents

2011 ◽  
pp. 99-117
Author(s):  
Penny Baillie ◽  
Mark Toleman ◽  
Dickson Lukose
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Agents ◽  
Emotional State ◽  
Psychological Theory ◽  
Emotional States ◽  
Changing Environment ◽  
Emotionally Intelligent ◽  
Over Time ◽  
The Way

Interacting with intelligence in an ever-changing environment calls for exceptional performances from artificial beings. One mechanism explored to produce intuitive-like behavior in artificial intelligence applications is emotion. This chapter examines the engineering of a mechanism that synthesizes and processes an artificial agent’s internal emotional states: the Affective Space. Through use of the affective space, an agent can predict the effect certain behaviors will have on its emotional state and, in turn, decide how to behave. Furthermore, an agent can use the emotions produced from its behavior to update its beliefs about particular entities and events. This chapter explores the psychological theory used to structure the affective space, the way in which the strength of emotional states can be diminished over time, how emotions influence an agent’s perception, and the way in which an agent can migrate from one emotional state to another.

Introduction

2013 ◽  
pp. 1-5
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Neural Networks ◽  
Computational Intelligence ◽  
Evolutionary Computing ◽  
Historical Background ◽  
Intelligent Computing ◽  
Biometric Security ◽  
Introductory Overview ◽  
Over Time

This chapter presents an introductory overview of the application of computational intelligence in biometrics. Starting with the historical background on artificial intelligence, the chapter proceeds to the evolutionary computing and neural networks. Evolutionary computing is an ability of a computer system to learn and evolve over time in a manner similar to humans. The chapter discusses swarm intelligence, which is an example of evolutionary computing, as well as chaotic neural network, which is another aspect of intelligent computing. At the end, special concentration is given to a particular application of computational intelligence—biometric security.

Origin of Cyber Warfare and How the Espionage Changed

2021 ◽  
pp. 145-153
Author(s):  
Maria Luisa Nardi
Keyword(s):  
Artificial Intelligence ◽  
International Relations ◽  
Technological Innovation ◽  
Digital Technology ◽  
New Technologies ◽  
Cyber Warfare ◽  
Individual Rights ◽  
Information Warfare ◽  
Political Field ◽  
Over Time

International politics is faced with new and vital issues, linked to aspects such as individual rights, the holding of democracy, the effects of worldwide policies, as well as the geopolitics of technology. The intertwining of technology and international relations is now a fact. Exploring the new and different political challenges posed by new technologies is a factor of transformation of the global society that influence on its actors. Today, an application of technological innovation, digital technology, and artificial intelligence is a steady political field. The focus of this work is to describe over time the notion of information warfare, which has matured and manifested into a form that has a colossal impact on how the contemporary wars are fought, but this has also resulted in the downgrading of strategic side of information warfare or cyber warfare to a decisive tactical force multiplier capable of turning the tides in war.

Removing the Constraints of Disability

2021 ◽  
pp. 205-219
Author(s):  
Wadad Kathy Tannous ◽  
Laney McGrew
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Neural Networks ◽  
Assistive Technologies ◽  
Vision Impairment ◽  
Cultural Participation ◽  
Smart Glasses ◽  
Control Computer ◽  
3D Printed ◽  
Over Time

One billion people globally live with disabilities that are physical, sensory, psychiatric, neurological, cognitive, or intellectual. Their disabilities are dynamic and can be temporary or permanent, singular or plural, from birth or developed, and can change over time. People with disabilities face barriers to economic, social, political, and cultural participation. Assistive technology, artificial intelligence, and broader technology can amplify their inclusion, participation, and independence. This chapter will highlight emerging and evolving technologies, rooted in machine learning and neural networks, which assist across different disabilities and seek to improve the user's sense of ability and independence. These include Seeing AI app, OXSIGHT, OrCam, Envision smart glasses, and Dot Watch for vision impairment; Ava app and cognitive hearing aid for hearing impairment; Liftware self-stabilising utensils for limited hand mobility; Eyegaze and Tobii – assistive technologies that allow users to control computer and smartphone screens with their eyes; and 3D printed prosthetics.

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