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Current research in artificial intelligence has been primarily focused on machine learning as applied to specific computer and engineering problems. For example, facial recognition or malware detection. This aspect of artificial intelligence has seen numerous advances and continues to advance. Research regarding synthetic consciousness has not progressed on par with research into other sub domains of artificial intelligence. While there has been speculation regarding the eventuality of some level of consciousness being developed via artificial intelligence, no specific research modalities have been adequately developed. This paper focuses on two synthetic consciousness issues. The first issue is to provide a basis for developing synthetic consciousness. The second issue is outlining specific research modalities that have a significant probability of achieving synthetic consciousness. The premise of this paper is to outline how to most effectively create algorithmic systems that have a high probability of leading to the emergent property of consciousness. [ABSTRACT FROM AUTHOR]

Recently, there has been increased research on the topic of artificially intelligent programs having the capability of developing advanced systems that are presently used by governments and organizations to analyze highly complex structures across sectors in ways not possible with conventional information technology. While some AI is subject to rigid testing and ethical reviews, other applications raise questions as to what governance structures are in place to control the risks to humanity and long term harmful economic and social consequences. This paper raises awareness about how governments and private industry face an unprecedented challenge in managing these complex systems that include regulators, markets, and special interests that all play a role in influencing the development of AI in different contexts without a full appreciation of the impact of AI on human rights and other consequences. The research focuses on three primary areas: (1) How AI technologies have evolved; (2) What are the major ethical and human rights issues evolving from the use of AI in the public and business environment; and (3) how can we improve our frameworks and governance structure for AI regulation. Through empirical evidence this paper explores the legal implications including the rights and duties of the government and private industry in protecting against unlawful intrusions into people's lives, while at the same time advancing recommendations for accountability frameworks and regulations essential to ensure safety and security in advancing artificially intelligent systems. [ABSTRACT FROM AUTHOR]

Megaprojects are continuing to capture worldwide attention from India’s Smart Cities, to the $4.75 billion Hadron Collider at CERN, to the US $150 billion International Space Station, and Europe’s largest railway infrastructure project, Crossrail in London. The Organization for Economic Cooperation and Development (OECD) estimates global investment needs of $6.3 trillion per year from 2016-2030 (Mirabile, et al. 2017). To meet this growing demand, there has been a recent call, within the megaproject scholarship, for a better understanding of “what goes on in megaprojects – how they are managed and organized, from within, by the managers who are tasked with bringing them to fruition.” (Söderlund, et al. 2017). Studies about megaprojects have generally concentrated on the cost conflicts between the stakeholders and cost overrun issues (Adam et al., 2014; Flyvbjerg, 2017), however these have been superseded by more important issues in recent years such as project security, protecting the health and safety of its workers, project sustainability and value creation, and managing the impact of climate change and presently a global pandemic. All of these require a more agile approach to project management and a more sophisticated intelligence that can be generated through Algorithms that are used to generate artificially intelligent systems. Through an analysis of the AI and Project Management literature, ethnographic studies, and semi-structured interviews with project management professionals, this paper explores the growing use of Artificial Intelligence to manage megaprojects including the obligations of private industry, and the government as the guardian of the public interest, while at the same time exploring the technical, managerial and ethical considerations in the deployment of AI. [ABSTRACT FROM AUTHOR]

Companies invest vast amounts of time and resources into protecting themselves against outside invasion. However, employees and partners can deal as much damage from the inside. Whether from malice or negligence, the results can be equally as devastating. The focus of this study will be on discovering threats within a predefined synthetic dataset (The Insider Threat Test Dataset by Carnegie Mellon's Software Engineering Institute) using popular machine learning algorithms (Random Forest, K-Nearest Neighbour, and Multi-Layer Perceptron). A comparison of the performance of the three algorithms is provided as a first phase, using a 5-tuple flow-based data. The paper then proposes a novel approach where the detection algorithm includes psychometric analysis (based on the Big Five Personality Traits applied to hacker types) of the network users in addition to traditional features used for detection with machine learning. [ABSTRACT FROM AUTHOR]