Perspectives on Ethics of AI

2020 ◽  
pp. 419-441
Author(s):  
Benjamin Kuipers
Keyword(s):  
Autonomous Vehicles ◽  
Intelligent Systems ◽  
Feedback Mechanism ◽  
Computational Approach ◽  
Human Society ◽  
Decision Point ◽  
Free Riders ◽  
Ethical Knowledge ◽  
Distributed Intelligent Systems ◽  
Lesser Evil

This chapter describes a computational view of the function of ethics in human society and discusses its application to three diverse examples. First, autonomous vehicles are individually embodied intelligent systems that act as members of society. The ethical knowledge needed by such an agent is not how to choose the lesser evil when confronted by a Deadly Dilemma, but how to recognize the upstream decision point that makes it possible to avoid the Deadly Dilemma entirely. Second, disembodied distributed intelligent systems like Google and Facebook provide valuable services while collecting, aggregating, and correlating vast amounts of information about individual users. With inadequate controls, these corporate systems can invade privacy and do substantial damage through either correct or incorrect inferences. Third, acceptance of the legitimacy of the society by its individual members depends on a general perception of fairness. Rage about unfairness can be directed at individual free-riders or at systematic inequality across the society. Ultimately, the promise of a computational approach to ethical knowledge is not simply ethics for computational devices such as robots. It also promises to help people understand the pragmatic value of ethics as a feedback mechanism that helps intelligent creatures, human and nonhuman, live together in thriving societies.

scholarly journals An affine invariant approach for dense wide baseline image matching

2016 ◽  
Vol 12 (12) ◽  
pp. 155014771668082
Author(s):  
Fanhuai Shi ◽  
Jian Gao ◽  
Xixia Huang
Keyword(s):  
Image Matching ◽  
Intelligent Systems ◽  
Region Growing ◽  
Low Rank ◽  
Affine Invariant ◽  
Affine Transformations ◽  
Visual Sensor ◽  
Dense Matching ◽  
Rank Matrix ◽  
Distributed Intelligent Systems

Visual sensor networks have emerged as an important class of sensor-based distributed intelligent systems, where image matching is one of the key technologies. This article presents an affine invariant method to produce dense correspondences between uncalibrated wide baseline images. Under affine transformations, both point location and its neighborhood texture are changed between views, so dense matching becomes a tough task. The proposed approach tends to solve this problem within a sparse-to-dense framework. The contribution of this article is in threefolds. First, a strategy of reliable sparse matching is proposed, which starts from affine invariant features extraction and matching and then these initial matches are utilized as spatial prior to produce more sparse matches. Second, match propagation from sparse feature points to its neighboring pixels is conducted in the way of region growing in an affine invariant framework. Third, the unmatched points are handled by low-rank matrix recovery technique. Comparison experiments of the proposed method versus existing ones show a significant improvement in the presence of large affine deformations.

scholarly journals Long-Term Adaptivity in Distributed Intelligent Systems: Study of ViaBots in a Simulated Environment

Robotics ◽  
2019 ◽  
Vol 8 (2) ◽  
pp. 25
Author(s):  
Arturs Ardavs ◽  
Mara Pudane ◽  
Egons Lavendelis ◽  
Agris Nikitenko
Keyword(s):  
Organization Theory ◽  
Intelligent Systems ◽  
Autonomous Robots ◽  
Autonomous Agent ◽  
Systems Model ◽  
Simulated Environment ◽  
Multi Agent ◽  
Distributed Intelligent Systems ◽  
Viable System

This paper proposes a long-term adaptive distributed intelligent systems model which combines an organization theory and multi-agent paradigm—ViaBots. Currently, the need for adaptivity in autonomous intelligent systems becomes crucial due to the increase in the complexity and diversity of the tasks that autonomous robots are employed for. To deal with the design complexity of such systems within the ViaBots model, each part of the modeled system is designed as an autonomous agent and the entire model, as a multi-agent system. Based on the viable system model, which is widely used to ensure viability, (i.e., long-term autonomy of organizations), the ViaBots model defines the necessary roles a system must fulfill to be capable to adapt both to changes in its environment (like changes in the task) and changes within the system itself (like availability of a particular robot). Along with static role assignments, ViaBots propose a mechanism for role transition from one agent to another as one of the key elements of long term adaptivity. The model has been validated in a simulated environment using an example of a conveyor system. The simulated model enabled the multi-robot system to adapt to the quantity and characteristics of the available robots, as well as to the changes in the parts to be processed by the system.

Distributed Intelligent Systems

2009 ◽  
Author(s):  
Abdellah Bedrouni ◽  
Ranjeev Mittu ◽  
A. Boukhtouta ◽  
Jean Berger
Keyword(s):  
Intelligent Systems ◽  
Distributed Intelligent Systems

scholarly journals The Good, the Bad, and the Ethical Implications of Bridging Blockchain and Multi-Agent Systems

Information ◽  
2019 ◽  
Vol 10 (12) ◽  
pp. 363 ◽  
Author(s):  
Davide Calvaresi ◽  
Jean-Paul Calbimonte ◽  
Alevtina Dubovitskaya ◽  
Valerio Mattioli ◽  
Jean-Gabriel Piguet ◽  
...  
Keyword(s):  
Intelligent Systems ◽  
Early Stage ◽  
Multi Agent Systems ◽  
Agent Systems ◽  
Ethical Implications ◽  
Blockchain Technology ◽  
Development Framework ◽  
Multi Agent ◽  
Distributed Intelligent Systems ◽  
Similar Solutions

The agent based approach is a well established methodology to model distributed intelligent systems. Multi-Agent Systems (MAS) are increasingly employed in applications dealing with safety and information critical tasks (e.g., in eHealth, financial, and energy domains). Therefore, transparency and the trustworthiness of the agents and their behaviors must be enforced. For example, employing reputation based mechanisms can promote the development of trust. Nevertheless, besides recent early stage studies, the existing methods and systems are still unable to guarantee the desired accountability and transparency adequately. In line with the recent trends, we advocate that combining blockchain technology (BCT) and MAS can achieve the distribution of the trust, removing the need for trusted third parties (TTP), potential single points of failure. This paper elaborates on the notions of trust, BCT, MAS, and their integration. Furthermore, to attain a trusted environment, this manuscript details the design and implementation of a system reconciling MAS (based on the Java Agent DEvelopment Framework (JADE)) and BTC (based on Hyperledger Fabric). In particular, the agents’ interactions, computation, tracking the reputation, and possible policies for disagreement-management are implemented via smart contracts and stored on an immutable distributed ledger. The results obtained by the presented system and similar solutions are also discussed. Finally, ethical implications (i.e., opportunities and challenges) are elaborated before concluding the paper.

Special Issue on Computational Cybernetics

2005 ◽  
Vol 9 (4) ◽  
pp. 345-345
Author(s):  
Wilfried Elmenreich ◽  
◽  
Imre J. Rudas ◽  
Keyword(s):  
Control Theory ◽  
Intelligent Systems ◽  
Adaptive Systems ◽  
Communication Theory ◽  
Social Systems ◽  
Feedback Mechanism ◽  
Wide Field ◽  
Automatic Control Systems ◽  
Review Cycle ◽  
The One

This issue contains selected papers from the International IEEE Conference on Computational Cybernetics that took place in Vienna 2004 in Austria at the Vienna University of Technology. Computational Cybernetics is the synergetic integration of Cybernetics and Computational Intelligence techniques. Cybernetics was defined by Wiener as "the science of control and communication, in the animal and the machine". The word "cybernetics" itself stems from the Greek "kybernetes" that means pilot or governor. While the roots of cybernetics go back to the time when James Watt equipped his steam engine with a Governor, that is a simple feedback mechanism for regulation of steam flow, the computational component was a child of the 20th century with the rise of information processing machines. The science of cybernetics and the science of computer science have in common, that both infiltrated many fields of application such as mathematics, telecommunication, regulated engines, living systems/medicine, social systems, and economical systems. Thus, on the one hand, the science of computational cybernetics encompasses a wide field, like the comparative study of automatic control systems, mechanical, biological (living), social and economical systems, communication theory, signal processing, information technology, control theory, the theory of adaptive systems, and the theory of complex systems (game theory, operational research). On the other hand, this research allows for finding common roots and common behavior among this broad field. This dichotomy between a broad overarching topic and the focus on computational cybernetics establishes the basis for interesting talks and discussions between scientists of different disciplines. We have selected 11 papers from the conference covering the fields of system design and modeling, neural networks, control theory, robotics and pattern recognition, which resemble the great variety of computational cybernetics. After the conference, each of these papers has undergone another peer review cycle in which the papers had been improved in order to fit this journal's topic and quality. It is our hope that the papers in this issue will inspire and help our readers in the development of advanced intelligent systems at the service of mankind.

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