From Computational Social Choice to Digital Democracy

Digital Democracy (aka e-democracy or interactive democracy) aims to enhance democratic decision-making processes by utilizing digital technology. A common goal of these approaches is to make collective decision-making more engaging, inclusive, and responsive to participants' opinions. For example, online decision-making platforms often provide much more flexibility and interaction possibilities than traditional democratic systems. It is without doubt that the successful design of digital democracy systems presents a multidisciplinary research challenge. I argue that tools and techniques from computational social choice should be employed to aid the design of online decision-making platforms and other digital democracy systems.

Data-Driven Dispatching Rules Mining and Real-Time Decision-Making Methodology in Intelligent Manufacturing Shop Floor with Uncertainty

In modern manufacturing industry, the methods supporting real-time decision-making are the urgent requirement to response the uncertainty and complexity in intelligent production process. In this paper, a novel closed-loop scheduling framework is proposed to achieve real-time decision making by calling the appropriate data-driven dispatching rules at each rescheduling point. This framework contains four parts: offline training, online decision-making, data base and rules base. In the offline training part, the potential and appropriate dispatching rules with managers’ expectations are explored successfully by an improved gene expression program (IGEP) from the historical production data, not just the available or predictable information of the shop floor. In the online decision-making part, the intelligent shop floor will implement the scheduling scheme which is scheduled by the appropriate dispatching rules from rules base and store the production data into the data base. This approach is evaluated in a scenario of the intelligent job shop with random jobs arrival. Numerical experiments demonstrate that the proposed method outperformed the existing well-known single and combination dispatching rules or the discovered dispatching rules via metaheuristic algorithm in term of makespan, total flow time and tardiness.

Online decision making and path planning framework for safe operation of unmanned aerial vehicles in urban scenarios

As the potential for deploying low-flying unmanned aerial vehicles (UAVs) in urban spaces increases, ensuring their safe operations is becoming a major concern. Given the uncertainties in their operational environments caused by wind gusts, degraded state of health, and probability of collision with static and dynamic objects, it becomes imperative to develop online decision-making schemes to ensure safe flights. In this paper, we propose an online decision-making framework that takes into account the state of health of the UAV, the environmental conditions, and the obstacle map to assess the probability of mission failure and re-plan accordingly. The online re-planning strategy considers two situations: (1) updating the current trajectory to reduce the probability of collision; and (2) defining a new trajectory to find a new safe landing spot, if continued flight would result in risk values above a pre-specified threshold. The re-planning routine uses the differential evolution optimization method and takes into account the dynamics of the UAV and its components as well as the environmental wind conditions. The new trajectory generation routine combines probabilistic road-maps with B-spline smoothing to ensure a dynamically feasible trajectory. We demonstrate the effectiveness of our approach by running UAV flight simulation experiments in urban scenarios.

The Role of Consumer Autonomy in Developing Sustainable AI: A Conceptual Framework

Artificial intelligence (AI)-based decision aids are increasingly employed by businesses to assist consumers’ decision-making. Personalized content based on consumers’ data brings benefits for both consumers and businesses, i.e., with regards to more relevant content. However, this practice simultaneously enables increased possibilities for exerting hidden interference and manipulation on consumers, reducing consumer autonomy. We argue that due to this, consumer autonomy represents a resource at the risk of depletion and requiring protection, due to its fundamental significance for a democratic society. By balancing advantages and disadvantages of increased influence by AI, this paper addresses an important research gap and explores the essential challenges related to the use of AI for consumers’ decision-making and autonomy, grounded in extant literature. We offer a constructive, rather than optimistic or pessimistic, outlook on AI. Hereunder, we present propositions suggesting how these problems may be alleviated, and how consumer autonomy may be protected. These propositions constitute the fundament for a framework regarding the development of sustainable AI, in the context of online decision-making. We argue that notions of transparency, complementarity, and privacy regulation are vital for increasing consumer autonomy and promoting sustainable AI. Lastly, the paper offers a definition of sustainable AI within the contextual boundaries of online decision-making. Altogether, we position this paper as a contribution to the discussion of development towards a more socially sustainable and ethical use of AI.

Online Decision Making

The growth in computer-mediated communication has created real challenges for society; in particular, the internet has become an important resource for “convincing” or persuading a person to make a decision. From a cybersecurity perspective, online attempts to persuade someone to make a decision has implications for the radicalisation of individuals. This chapter reviews multiple definitions and theories relating to decision making to consider the applicability of these to online decision making in areas such as buying behaviour, social engineering, and radicalisation. Research investigating online decision making is outlined and the point is made that research examining online research has a different focus than research exploring online decision making. The chapter concludes with some key questions for scholars and practitioners. In particular, it is noted that online decision making cannot be explained by one single model, as none is sufficient in its own capacity to underpin all forms of online behaviour.

Comparative Analysis Between Online and Offline Shopping Approach and Behavior of Consumers

The intent of this study is to present a view of online shopping decision through compare the offline and online decision making. Shopper’s shop when and where they desire, where they are contented with the products and the preference of shopping. The present paper is highlights the distinction among online and offline shopping approach and behavior of consumers of the study. Total 30 statements have been developed. Total 500 respondents have taken part in survey out of which 316 consumers preferred online shopping over offline shopping, whereas, 184 consumers preferred offline shopping over online shopping. Descriptive statistics and t-test is used to examine if mean level of agreement or disagreement between online shoppers and offline shoppers is significant or not. As a result it has been found that response of online and offline shoppers varies significantly for statements like online or offline Shopping saves time, online or offline shopping is convenient, It is safe to give out personal information, online or offline shopping provides overall adequate information, online or offline shopping provides the other required customer services, online or offline shopping requires fewer efforts, online or offline shopping provides faster goods and services, online or offline Shopping avoids botheration, online or offline shopping offers prompt delivery of goods, online or offline shopping allows one to look for the best price before purchasing, During online or offline shopping, one can touch the goods before I buy them, During online or offline shopping, once can try ortake demo of the product, online or offline shopping raises my prestige, I often buy things online or offline because it puts me in a better mood.