scholarly journals Towards Artificial Argumentation

AI Magazine ◽  
2017 ◽  
Vol 38 (3) ◽  
pp. 25-36 ◽  
Author(s):  
Katie Atkinson ◽  
Pietro Baroni ◽  
Massimiliano Giacomin ◽  
Anthony Hunter ◽  
Henry Prakken ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Computational Models ◽  
Complex Task ◽  
Artificial Intelligence Research ◽  
Inconsistent Information ◽  
Recent Developments ◽  
The Way

The field of computational models of argument is emerging as an important aspect of artificial intelligence research. The reason for this is based on the recognition that if we are to develop robust intelligent systems, then it is imperative that they can handle incomplete and inconsistent information in a way that somehow emulates the way humans tackle such a complex task. And one of the key ways that humans do this is to use argumentation either internally, by evaluating arguments and counterarguments‚ or externally, by for instance entering into a discussion or debate where arguments are exchanged. As we report in this review, recent developments in the field are leading to technology for artificial argumentation, in the legal, medical, and e-government domains, and interesting tools for argument mining, for debating technologies, and for argumentation solvers are emerging.

A Liar’s Epistemology

Qui Parle ◽  
2021 ◽  
Vol 30 (1) ◽  
pp. 119-157
Author(s):  
Brett Zehner
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Large Scale ◽  
Computational Models ◽  
Nervous Activity ◽  
Bad Faith ◽  
Computer Scientists ◽  
Human Decision ◽  
Media Philosophy ◽  
Historical Accounts

Abstract This methodologically important essay aims to trace a genealogical account of Herbert Simon’s media philosophy and to contest the histories of artificial intelligence that overlook the organizational capacities of computational models. As Simon’s work demonstrates, humans’ subjection to large-scale organizations and divisions of labor is at the heart of artificial intelligence. As such, questions of procedures are key to understanding the power assumed by institutions wielding artificial intelligence. Most media-historical accounts of the development of contemporary artificial intelligence stem from the work of Warren S. McCulloch and Walter Pitts, especially the 1943 essay “A Logical Calculus of the Ideas Immanent in Nervous Activity.” Yet Simon’s revenge is perhaps that reinforcement learning systems adopt his prescriptive approach to algorithmic procedures. Computer scientists criticized Simon for the performative nature of his artificially intelligent systems, mainly for his positivism, but he defended his positivism based on his belief that symbolic computation could stand in for any reality and in fact shape that reality. Simon was not looking to actually re-create human intelligence; he was using coercion, bad faith, and fraud as tactical weapons in the reordering of human decision-making. Artificial intelligence was the perfect medium for his explorations.

Argument Structure Models and Visualization

2009 ◽  
pp. 75-82 ◽  
Author(s):  
Ephraim Nissan
Keyword(s):  
Artificial Intelligence ◽  
Argument Structure ◽  
Intelligent Systems ◽  
Computational Models ◽  
Ad Hoc ◽  
Wide Spectrum ◽  
Tutoring Systems ◽  
Computer Tools ◽  
Legal Evidence ◽  
Visualization Tools

In order to visualize argumentation, there exist tools from multimedia. The most advanced sides of computational modeling of arguments belong in models and tools upstream of visualization tools: the latter are an interface. Computer models of argumentation come in three categories: logic-based (highly theoretical), probablistic, and pragmatic ad hoc treatments. Theoretical formalisms of argumentation were developed by logicists within artificial intelligence (and were implemented and often can be reused outside the original applications), or then the formalisms are rooted in philosophers’ work. We cite some such work, but focus on tools that support argumentation visually. Argumentation turns out in a wide spectrum of everyday life situations, including professional ones. Computational models of argumentation have found application in tutoring systems, tools for marshalling legal evidence, and models of multiagent communication. Intelligent systems and other computer tools potentially stand to benefit as well. Multimedia are applied to argumentation (in visualization tools), and also are a promising field of application (in tutoring systems). The design of networks could potentially benefit, if communication is modeled using multiagent technology.

Robots, Replicants, and Surrogates

2021 ◽  
pp. 84-111
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Science Fiction ◽  
Intelligent Systems ◽  
New World ◽  
Attitudes And Perceptions ◽  
The World ◽  
Recent Developments ◽  
Brave New World ◽  
And Robotics

The human brain is an extraordinary machine. Its ability to process information and adapt to circumstances by reprogramming itself is unparalleled, and it remains the best source of inspiration for recent developments in artificial intelligence. This has given rise to machine learning, intelligent systems, and robotics. Robots and AI might right now still seem the reserve of blockbuster science fiction movies and documentaries, but it's no doubt the world is changing. This chapter explores the origins, attitudes, and perceptions of robotics and the multiple types of robots that exist today. Perhaps most importantly, it focuses on ethical and societal concerns over the question: Are we heading for a brave new world or a science fiction horror-show where AI and robots displace or, perhaps more worryingly, replace humans?

Computational models and empirical constraints

1978 ◽  
Vol 1 (1) ◽  
pp. 91-99 ◽  
Author(s):  
Zenon W. Pylyshyn
Keyword(s):  
Artificial Intelligence ◽  
Computational Models ◽  
Task Demands ◽  
Top Down ◽  
Artificial Intelligence Research ◽  
Cognitive Simulation ◽  
Functional Models ◽  
Complex Program ◽  
Computational Systems ◽  
Made In

AbstractIt is argued that the traditional distinction between artificial intelligence and cognitive simulation amounts to little more than a difference in style of research - a different ordering in goal priorities and different methodological allegiances. Both enterprises are constrained by empirical considerations and both are directed at understanding classes of tasks that are defined by essentially psychological criteria. Because of the different ordering of priorities, however, they occasionally take somewhat different stands on such issues as the power/generality trade-off and on the relevance of the sort of data collected in experimental psychology laboratories.Computational systems are more than a tool for checking the consistency and completeness of theoretical ideas. They are ways of empirically exploring the adequacy of methods and of discovering task demands. For psychologists, computational systems should be viewed as functional models quite independent of (and likely not reducible to) neurophysiological systems, and cast at a level of abstraction appropriate for capturing cognitive generalizations. As model objects, however, they do present a serious problem of interpretation and communication since the task of extracting the relevant theoretical principles from a large complex program may be formidable.Methodologies for validating computer programs as cognitive models are briefly described. These may be classified as intermediate state, relative complexity, and component analysis methods. Compared with the constraints imposed by criteria such as sufficiency, breadth, and extendability, these experimentally based methods are relatively weak and may be most useful after some top-down progress is made in the understanding of methods sufficient for relevant tasks - such as may be forthcoming from artificial intelligence research.

Deep new: The shifting narratives of artificial intelligence from Deep Blue to AlphaGo

2019 ◽  
Vol 25 (4) ◽  
pp. 627-642 ◽  
Author(s):  
Paolo Bory
Keyword(s):  
Artificial Intelligence ◽  
New York ◽  
Intelligent Systems ◽  
Secondary Sources ◽  
South Korean ◽  
Deep Blue ◽  
The Media ◽  
The One ◽  
World Champion ◽  
The Way

The article compares two key events that marked the narratives around the emergence of artificial intelligence (AI) in two different time frames: the game series between the Russian world champion Garry Kasparov and the IBM supercomputer Deep Blue held in New York in 1997, and the Go game series between the South Korean champion Lee Sedol and DeepMind’s AI AlphaGo held in Seoul in 2016. Relying on a corpus of primary and secondary sources such as newspapers and specialized magazines, biographic books, the live broadcasts and the main documentaries reporting the challenges, the article investigates the way in which IBM and Google DeepMind used the human–machine competition to narrate the emergence of a new, deeper, form of AI. On the one hand, the Kasparov–Deep Blue match was presented by broadcasting media and IBM itself as a conflictual and competitive form of struggle between human kind and a hardware-based, obscure and humanlike player. While on the other hand, the social and symbolic message promoted by DeepMind and the media conveyed a cooperative and fruitful interaction with a new software-based, transparent and un-humanlike form of AI. The analysis of the case studies reveals how AI companies mix narrative tropes, gaming and spectacle in order to promote the newness and the main features of their products. In particular, recent narratives of AI based on human feelings and values such as beauty and trust can shape the way in which the presence of intelligent systems is accepted and integrated in everyday life.

scholarly journals Hume’s guillotine and intelligent technologies

2021 ◽  
Author(s):  
Pertti Saariluoma
Keyword(s):  
Artificial Intelligence ◽  
Information Processing ◽  
Social Influence ◽  
David Hume ◽  
Intelligent Systems ◽  
Fundamental Problem ◽  
Human Mind ◽  
The Way

AbstractEmerging intelligent society shall change the way people are organised around their work and consequently also as a society. One approach to investigating intelligent systems and their social influence is information processing. Intelligence is information processing. However, factual and ethical information are different. Facts concern true vs. false, while ethics is about what should be done. David Hume recognised a fundamental problem in this respect, which is that facts can be used to derive values. His answer was negative, which is critical for developing intelligent ethical technologies. Hume’s problem is not crucial when values can be assigned to technologies, i.e. weak ethical artificial intelligence (AI), but it is hard when we speak of strong ethical AI, which should generate values from facts. However, this paper argues that Hume’s aporia is grounded on a mistaken juxtaposition of emotions and cognition. In the human mind, all experiences are based on the cooperation of emotions and cognitions. Therefore, Hume’s guillotine is not a real obstacle, but it is possible to use stronger forms of ethical AI to develop new ethics for intelligent society.

scholarly journals A Survey on Artificial Intelligence in Malware as Next-Generation Threats

MENDEL ◽  
2019 ◽  
Vol 25 (2) ◽  
pp. 27-34 ◽  
Author(s):  
Cong Truong Thanh ◽  
Ivan Zelinka
Keyword(s):  
Artificial Intelligence ◽  
Swarm Intelligence ◽  
Next Generation ◽  
Digital Space ◽  
Transformative Potential ◽  
Recent Developments ◽  
Malicious Program ◽  
The Way

Recent developments in Artificial intelligence (AI) have a vast transformative potential for both cybersecurity defenders and cybercriminals. Anti-malware solutions adopt intelligent techniques to detect and prevent threats to the digital space. In contrast, cybercriminals are aware of the new prospects too and will probably try to use it in their activities. This survey aims at providing an overview on the way artificial intelligence can be used to power a malicious program that is: intelligent evasion techniques, autonomous malware, AI against itself, and applying bio-inspired computation and swarm intelligence.

Recent developments in the study of cognitive processing of emotionally arousing words

2015 ◽  
Vol 2 (1) ◽  
pp. 129-149
Author(s):  
Mauricio Iza ◽  
Jesús Ezquerro
Keyword(s):  
Artificial Intelligence ◽  
Social Interactions ◽  
Cognitive Processing ◽  
Mirror Neurons ◽  
Computational Models ◽  
Current Trends ◽  
Recent Developments ◽  
The Common ◽  
Computational Models Of Emotion

Research on the interaction between emotion, cognition and language in the field of Artificial Intelligence has become particularly active along the last years. Lots of computational models of emotion have been developed. There are accounts stressing the role of canonical and mirror neurons as underlying the use of nouns and verbs. At the same time, neuropsychology is developing new approaches for modeling language, emotion and cognition inspired on the insights gained from robotics. The current landscape is thus a promising collaboration between several approaches: Social Psychology, Neuropsychology, Artificial Intelligence (mainly embodied), and even Philosophy, so that each field provides useful cues for the common goal of understanding social interactions (including the interactions with machines).The aim of this paper is to analyze and asses the current trends in psychology and neuroscience for studying the mechanisms of the neurocomputational cognitive-affective architecture related to the conceptualization and use of language.

scholarly journals Gaps between the digits

2019 ◽  
Vol 25 (1) ◽  
pp. 56-70
Author(s):  
Romi Ron Morrison
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
Turning Point ◽  
Computational Power ◽  
Black Feminists ◽  
The World ◽  
Ways Of Being ◽  
Human Fluid ◽  
Critical Site ◽  
The Way

Abstract Artificially intelligent systems (ai) are increasingly becoming the ubiquitous, unseen arbiters of our social, civic and familial lives. Ever increasing computational power, combined with almost limitless data, has led to a turning point in the way artificial intelligence assists, judges, and cares for humans. In the wake of such power we must ask ourselves what it is that we are making inherently unknowable as the world becomes more predictable, managed, and discrete. Building on the work of black feminists Sylvia Wynter and Hortense Spillers, I perform a reading of the “flesh”. I aim to hint towards a different field of relations and a knowledge politic premised on unknowability and the radical potential of the subjugated to foster new imaginaries of the human fluid enough to weather instability. This piece troubles the boundaries inscribed between things. Settled in the flesh of blackness, we are reminded of the ways that blackness floods the landscape of productive reason while holding outlier ways of being beyond Western Man. This paper seeks to return to the pulse found within the flesh as a critical site for thinking through alternate ways of being, within the messiness, the unstable, the precarious; finding life born of transition, the pulse within discord.

Sign in / Sign up

Export Citation Format

Share Document