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  1. Theories of Artificial Intelligence—Meta-Theoretical considerations.Pei Wang - 2012 - In Pei Wang & Ben Goertzel (eds.), Theoretical Foundations of Artificial General Intelligence. Springer. pp. 305--323.
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  • Theoretical Foundations of Artificial General Intelligence.Pei Wang & Ben Goertzel (eds.) - 2012 - Springer.
    Pei Wang, Ben Goertzel. [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [ 18] [19] [20] [21] [22] [23] [24] [25] [26] [27] Bach, J. (2009). Principles ofSynthetic Intelligence PSI: An Architecture ofMotivated Cognition (Oxford University Press,  ...
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  • Artificial Intelligence: A Modern Approach.Stuart Jonathan Russell & Peter Norvig (eds.) - 1995 - Prentice-Hall.
    Artificial Intelligence: A Modern Approach, 3e offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Number one in its field, this textbook is ideal for one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. Dr. Peter Norvig, contributing Artificial Intelligence author and Professor Sebastian Thrun, a Pearson author are offering a free online course at Stanford University on artificial intelligence. According to an article in The New York Times, the course on artificial intelligence is (...)
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  • Artificial intelligence as law. [REVIEW]Bart Verheij - 2020 - Artificial Intelligence and Law 28 (2):181-206.
    Information technology is so ubiquitous and AI’s progress so inspiring that also legal professionals experience its benefits and have high expectations. At the same time, the powers of AI have been rising so strongly that it is no longer obvious that AI applications (whether in the law or elsewhere) help promoting a good society; in fact they are sometimes harmful. Hence many argue that safeguards are needed for AI to be trustworthy, social, responsible, humane, ethical. In short: AI should be (...)
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  • Reading agendas between the lines, an exercise.Giovanni Sileno, Alexander Boer & Tom van Engers - 2017 - Artificial Intelligence and Law 25 (1):89-106.
    This work presents elements for an alternative operationalization of monitoring and diagnosis of multi-agent systems, developed in the context of compliance checking. In contrast to traditional accounts of model-based diagnosis, and most proposals concerning non-compliance, our method does not consider any commitment towards the individual unit of agency. Identity is considered to be mostly an attribute to assign responsibility, and not as the only referent to a source of intentionality. The proposed method requires as input a set of prototypical agent-roles (...)
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  • Black is the new orange: how to determine AI liability.Paulo Henrique Padovan, Clarice Marinho Martins & Chris Reed - 2023 - Artificial Intelligence and Law 31 (1):133-167.
    Autonomous artificial intelligence (AI) systems can lead to unpredictable behavior causing loss or damage to individuals. Intricate questions must be resolved to establish how courts determine liability. Until recently, understanding the inner workings of “black boxes” has been exceedingly difficult; however, the use of Explainable Artificial Intelligence (XAI) would help simplify the complex problems that can occur with autonomous AI systems. In this context, this article seeks to provide technical explanations that can be given by XAI, and to show how (...)
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  • Symbiosis with artificial intelligence via the prism of law, robots, and society.Stamatis Karnouskos - 2021 - Artificial Intelligence and Law 30 (1):93-115.
    The rapid advances in Artificial Intelligence and Robotics will have a profound impact on society as they will interfere with the people and their interactions. Intelligent autonomous robots, independent if they are humanoid/anthropomorphic or not, will have a physical presence, make autonomous decisions, and interact with all stakeholders in the society, in yet unforeseen manners. The symbiosis with such sophisticated robots may lead to a fundamental civilizational shift, with far-reaching effects as philosophical, legal, and societal questions on consciousness, citizenship, rights, (...)
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  • Administrative due process when using automated decision-making in public administration: some notes from a Finnish perspective.Markku Suksi - 2020 - Artificial Intelligence and Law 29 (1):87-110.
    Various due process provisions designed for use by civil servants in administrative decision-making may become redundant when automated decision-making is taken into use in public administration. Problems with mechanisms of good government, responsibility and liability for automated decisions and the rule of law require attention of the law-maker in adapting legal provisions to this new form of decision-making. Although the general data protection regulation of the European Union is important in acknowledging automated decision-making, most of the legal safeguards within administrative (...)
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  • Detecting tax evasion: a co-evolutionary approach.Erik Hemberg, Jacob Rosen, Geoff Warner, Sanith Wijesinghe & Una-May O’Reilly - 2016 - Artificial Intelligence and Law 24 (2):149-182.
    We present an algorithm that can anticipate tax evasion by modeling the co-evolution of tax schemes with auditing policies. Malicious tax non-compliance, or evasion, accounts for billions of lost revenue each year. Unfortunately when tax administrators change the tax laws or auditing procedures to eliminate known fraudulent schemes another potentially more profitable scheme takes it place. Modeling both the tax schemes and auditing policies within a single framework can therefore provide major advantages. In particular we can explore the likely forms (...)
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  • Knowledge-based artificial neural networks.Geoffrey G. Towell & Jude W. Shavlik - 1994 - Artificial Intelligence 70 (1-2):119-165.
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