Designing Human-Centered Collective Intelligence

Human-Centered Collective Intelligence (HCCI) is an emergent research area that seeks to bring together major research areas like machine learning, statistical modeling, information retrieval, market research, and software engineering to address challenges pertaining to deriving intelligent insights and solutions through the collaboration of several intelligent sensors, devices and data sources. An archetypal contextual CI scenario might be concerned with deriving affect-driven intelligence through multimodal emotion detection sources in a bid to determine the likability of one movie trailer over another. On the other hand, the key tenets to designing robust and evolutionary software and infrastructure architecture models to address cross-cutting quality concerns is of keen interest in the “Cloud” age of today. Some of the key quality concerns of interest in CI scenarios span the gamut of security and privacy, scalability, performance, fault-tolerance, and reliability. I present recent advances in CI system design with a focus on highlighting optimal solutions for the aforementioned cross-cutting concerns. I also describe a number of design challenges and a framework that I have determined to be critical to designing CI systems. With inspiration from machine learning, computational advertising, ubiquitous computing, and sociable robotics, this literature incorporates theories and concepts from various viewpoints to empower the collective intelligence engine, ZOEI, to discover affective state and emotional intent across multiple mediums. The discerned affective state is used in recommender systems among others to support content personalization. I dive into the design of optimal architectures that allow humans and intelligent systems to work collectively to solve complex problems. I present an evaluation of various studies that leverage the ZOEI framework to design collective intelligence

Journey of Artificial Intelligence Frontier: A Comprehensive Overview

The field of Artificial Intelligence AI is a transformational force with limitless promise in the age of fast technological growth This paper sets out on a thorough tour through the frontiers of AI providing a detailed understanding of its complex environment Starting with a historical context followed by the development of AI seeing its beginnings and growth On this journey fundamental ideas are explored looking at things like Machine Learning Neural Networks and Natural Language Processing Taking center stage are ethical issues and societal repercussions emphasising the significance of responsible AI application This voyage comes to a close by looking ahead to AI s potential for human-AI collaboration ground-breaking discoveries and the difficult obstacles that lie ahead This provides with a well-informed view on AI s past present and the unexplored regions it promises to explore by thoroughly navigating this terrai

【研究分野別】シーズ集 [英語版]

[英語版

A theoretical and practical approach to a persuasive agent model for change behaviour in oral care and hygiene

There is an increased use of the persuasive agent in behaviour change interventions due to the agent‘s features of sociable, reactive, autonomy, and proactive. However, many interventions have been unsuccessful, particularly in the domain of oral care. The psychological reactance has been identified as one of the major reasons for these unsuccessful behaviour change interventions. This study proposes a formal persuasive agent model that leads to psychological reactance reduction in order to achieve an improved behaviour change intervention in oral care and hygiene. Agent-based simulation methodology is adopted for the development of the proposed model. Evaluation of the model was conducted in two phases that include verification and validation. The verification process involves simulation trace and stability analysis. On the other hand, the validation was carried out using user-centred approach by developing an agent-based application based on belief-desire-intention architecture. This study contributes an agent model which is made up of interrelated cognitive and behavioural factors. Furthermore, the simulation traces provide some insights on the interactions among the identified factors in order to comprehend their roles in behaviour change intervention. The simulation result showed that as time increases, the psychological reactance decreases towards zero. Similarly, the model validation result showed that the percentage of respondents‘ who experienced psychological reactance towards behaviour change in oral care and hygiene was reduced from 100 percent to 3 percent. The contribution made in this thesis would enable agent application and behaviour change intervention designers to make scientific reasoning and predictions. Likewise, it provides a guideline for software designers on the development of agent-based applications that may not have psychological reactance

Department of Computer Science Activity 1998-2004

This report summarizes much of the research and teaching activity of the Department of Computer Science at Dartmouth College between late 1998 and late 2004. The material for this report was collected as part of the final report for NSF Institutional Infrastructure award EIA-9802068, which funded equipment and technical staff during that six-year period. This equipment and staff supported essentially all of the department\u27s research activity during that period

Artificial Intelligence in Computer Networks : Role of AI in Network Security

Artificial Intelligence (AI) in computer networks has been emerging for the last decade, there are revolutionary inventions that have created automation and digitalization in the fields of the Internet. The layout of computer networks works in layers of topologies with the help of AI, a virtual layer of software has been added that runs predictive algorithms of Artificial Neural Networks (ANNs) with the help of Machine Learning (ML) and Deep Learning (DL). This thesis describes the relation between AI algorithms and duplication of human cognitive behavior in emerging technologies. The advantages of AI in computer networks include automation, digitalization, Internet of Things (IoT), centralization of data, etc. At the same time, the biggest disadvantage is the ethical violation of privacy and the security of data. It is further discussed in the thesis that Artificial Intelligence uses many security protocols, including Next-Generation Firewalls, to prevent security violations. The Software Network Analysis (SNA) and Software Defined Networks (SDN) play an important role in Artificial Intelligence in computer Networks. This thesis aims to analyze the relationship between the development of AI algorithms and the duplication of the human cognitive behavior in various emerging technologies. Software Network Analysis (SNA) and Software Defined Networks (SDN) are critical components of computer network artificial intelligence. The purpose of this dissertation is to investigate the relationship between AI algorithms and network security. The thesis analyzes 2 main aspects, the role of Artificial Intelligence in Computer Networks and how Artificial Intelligence is helping in securing computer networks to deal with the modern network threats. Security today has become one of the main concerns, everyday a production networks receives arounds thousands of attacks of different scales, and proper network security measures are not configured and taken, a lot can be compromised. Network virtualization, Cloud Computing, has seen exponentially growth in few past years, because of the trend of less human interaction, and minimizing of doing repeated tasks over and over. Data in today’s world is now more important than it has been in decades earlier, this is because today everything is moving towards digitalization, proper Information Security policies are derived and implemented all over the world to ensure the protection of Data. Europe has its own General Data Protection Regulation (GDPR) which ensures that every company who deals with data is to implement certain measures to ensure the data is protected which also involves implementing the right network security measures so that the right people have the access to the sensitive information. This thesis covers the overall impact of Artificial Intelligence in Computer Networks and Network Security

Horizon 2020-funded security research projects with dual-use potential: An overview (2014-2018)

The analysis carried out in this report facilitates the identification of dual-use research topics and projects funded under Horizon 2020 that have a dual-use civilian/military potential, the results of which could be applied both by security and defence stakeholders (including industry). In this way, it could support the future security and defence research programmes in their attempt of avoiding duplication of investments and promoting synergies.JRC.E.7-Knowledge for Security and Migratio

Adaptive Financial Regulation and RegTech: A Concept Article on Realistic Protection for Victims of Bank Failures

Frustrated by the seeming inability of regulators and prosecutors to hold bank executives to account for losses inflicted by their companies before, during, and since the financial crisis of 2008, some scholars have suggested that private-attorney-general suits such as class action and shareholder derivative suits might achieve better results. While a few isolated suits might be successful in cases where there is provable fraud, such remedies are no general panacea for preventing large-scale bank-inflicted losses. Large losses are nearly always the result of unforeseeable or suddenly changing economic conditions, poor business judgment, or inadequate regulatory supervision—usually a combination of all three. Yet regulators face an increasingly complex task in supervising modern financial institutions. This Article explains how the challenge has become so difficult. It argues for preserving regulatory discretion rather than reducing it through formal congressional direction. The Article also asserts that regulators have to develop their own sophisticated methods of automated supervision. Although also not a panacea, the development of “RegTech” solutions will help clear away volumes of work that understaffed and underfunded regulators cannot keep up with. RegTech will not eliminate policy considerations, nor will it render regulatory decisions noncontroversial. Nevertheless, a sophisticated deployment of RegTech should help focus regulatory discretion and public-policy debate on the elements of regulation where choices really matter