Predicting consumers’ intention to purchase fully autonomous driving systems : which factors drive acceptance?

This study aimed to find which factors influence consumers’ intention to purchase a fully autonomous driving system in the future and which perceived product characteristics influence the purchase intention and how. Therefore, an extension of the acceptance model of Driver Assistant Systems by Arndt (2011) is presented. It integrates perceived product characteristics specific to autonomous driving technology, to investigate which factors determine the acceptance of fully autonomous driving systems. The proposed model was empirically tested based on primary data collected in Germany. Exploratory and confirmatory factor analyses were performed to assess the reliability and validity of the measurement model. Further, structural equation modeling was used to evaluate the causal relationships. The findings indicated that Attitude toward buying, Subjective Norm and the perceived product characteristics Efficiency, Trust in Safety and Eco-Friendliness significantly influenced individuals’ behavioral intention to purchase driverless technology. The variables perceived Comfort, Image and Driving Enjoyment were not found to have a significant effect on behavioral intention. Attitude and Subjective Norm had the most significant influence. A somewhat surprising finding was that Subjective Norm not only had a direct effect on Behavioral Intention, as suggest by the theory of reasoned action and theory of planned behavior, but also on Attitude

Artificial morality: Making of the artificial moral agents

Abstract: Artificial Morality is a new, emerging interdisciplinary field that centres around the idea of creating artificial moral agents, or AMAs, by implementing moral competence in artificial systems. AMAs are ought to be autonomous agents capable of socially correct judgements and ethically functional behaviour. This request for moral machines comes from the changes in everyday practice, where artificial systems are being frequently used in a variety of situations from home help and elderly care purposes to banking and court algorithms. It is therefore important to create reliable and responsible machines based on the same ethical principles that society demands from people. New challenges in creating such agents appear. There are philosophical questions about a machine’s potential to be an agent, or mora l agent, in the first place. Then comes the problem of social acceptance of such machines, regardless of their theoretic agency status. As a result of efforts to resolve this problem, there are insinuations of needed additional psychological (emotional and cogn itive) competence in cold moral machines. What makes this endeavour of developing AMAs even harder is the complexity of the technical, engineering aspect of their creation. Implementation approaches such as top- down, bottom-up and hybrid approach aim to find the best way of developing fully moral agents, but they encounter their own problems throughout this effort

The Current State of Normative Agent-Based Systems

Recent years have seen an increase in the application of ideas from the social sciences to computational systems. Nowhere has this been more pronounced than in the domain of multiagent systems. Because multiagent systems are composed of multiple individual agents interacting with each other many parallels can be drawn to human and animal societies. One of the main challenges currently faced in multiagent systems research is that of social control. In particular, how can open multiagent systems be configured and organized given their constantly changing structure? One leading solution is to employ the use of social norms. In human societies, social norms are essential to regulation, coordination, and cooperation. The current trend of thinking is that these same principles can be applied to agent societies, of which multiagent systems are one type. In this article, we provide an introduction to and present a holistic viewpoint of the state of normative computing (computational solutions that employ ideas based on social norms.) To accomplish this, we (1) introduce social norms and their application to agent-based systems; (2) identify and describe a normative process abstracted from the existing research; and (3) discuss future directions for research in normative multiagent computing. The intent of this paper is to introduce new researchers to the ideas that underlie normative computing and survey the existing state of the art, as well as provide direction for future research.Norms, Normative Agents, Agents, Agent-Based System, Agent-Based Simulation, Agent-Based Modeling

Theory of the Arbitration Process

A sensor fusion method for state estimation of a flexible industrial robot is developed. By measuring the acceleration at the end-effector, the accuracy of the arm angular position, as well as the estimated position of the end-effector are improved. The problem is formulated in a Bayesian estimation framework and two solutions are proposed; the extended Kalman filter and the particle filter. In a simulation study on a realistic flexible industrial robot, the angular position performance is shown to be close to the fundamental Cramér-Rao lower bound. The technique is also verified in experiments on an ABB robot, where the dynamic performance of the position for the end-effector is significantly improved.Vinnova Excellence Center LINK-SICSSF project Collaborative Localizatio

Development of a Future Orientation Model in Emerging Adulthood in Hungary

Social and economic sustainability of countries globally largely depend on how well educational structures are capable of empowering future generations with skills and competencies to become autonomous and active citizens. Such competency is future planning, which is vital in the identity formation of youth in their developmental phase of emerging adulthood. The article below attempts to elaborate a predictive model of future orientation based on current and future norms, future interest and concern. The model was tested on a sample population of business school students (N=217) in their emerging adulthood. Norm acceptance ranking proved to be different for present and future times. Amongst a number of contextual variables shaping the formation of future plans concern has been found to hold the strongest predictive power

Responsible Autonomy

As intelligent systems are increasingly making decisions that directly affect society, perhaps the most important upcoming research direction in AI is to rethink the ethical implications of their actions. Means are needed to integrate moral, societal and legal values with technological developments in AI, both during the design process as well as part of the deliberation algorithms employed by these systems. In this paper, we describe leading ethics theories and propose alternative ways to ensure ethical behavior by artificial systems. Given that ethics are dependent on the socio-cultural context and are often only implicit in deliberation processes, methodologies are needed to elicit the values held by designers and stakeholders, and to make these explicit leading to better understanding and trust on artificial autonomous systems.Comment: IJCAI2017 (International Joint Conference on Artificial Intelligence

Liapunov Exponents and the Reversibility of Molecular Dynamics Algorithms

We study the phenomenon of lack of reversibility in molecular dynamics algorithms for the case of Wilson's lattice QCD. We demonstrate that the classical equations of motion that are employed in these algorithms are chaotic in nature. The leading Liapunov exponent is determined in a range of coupling parameters. We give a quantitative estimate of the consequences of the breakdown of reversibility due to round-off errors.Comment: Latex2e file, 4 figures, 19 page