Empowering Partnership: Ethics in Context

This article aims to offer a general view of the work and the progress the Partnership and promotions team, placed at the core of the Globethics.net Foundation activities, has reached so far. Starting with a general view on its tasks and duties, Christine Housel opens the floor for the regional officers of the department to offer a personalized view and opinion on the relevant and pressing matters Globethics.net has to focus, or has focused on, locally. During this exposition, we will hear about the Partnership and promotion team’s commitment with students at all levels, its work to foster and nurture ethics in higher education on institutions worldwide, and the diversity and plurality held in itself, a clear embodiment of the pluralistic vocation of Globethics.net

Running With Mittens

The work described in the following thesis rests upon two underlying concepts: 1) Moments of meeting, a phrase borrowed from Cissna and Anderson (2002), have been creatively, spiritually, and emotionally transformative for me, and 2) These moments are particularly transformative when they are characterized by a deep sense of empathy, genuineness, and unconditional positive regard. Based on these two points, a body of work was created during the Masters of Fine Arts (MFA) program (Running with Mittens, Domesticity #1-#5 and the Mitten Knitter.) The rationale, inspiration, and methodological choices inherent in these works are described fully throughout this thesis. Upon final reflection of my artwork and the culminating MFA show, I clearly observe my attachment to the representational and my shift to valuing the abstract and conceptual. In the end, I believe that my place may be in the margins between conceptualization and traditional techniques

The Fourth Industrial Revolution’s Wave Crashes Upon the Shores of Accounting: The Value Metric for the Fourth Industrial Revolution

Financial Management / Faculty ReportAcquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsAlmost 30 years ago, Elliott (1992) shared several critical insights about the inadequacies of the field of accounting to account for radical changes in the ways businesses develop and execute strategy based on the fundamental opportunities that had come about due to information age technology. Accounting has remained virtually unchanged for over 500 years and society has now entered what Schwab (2015) referred to as the “Fourth Industrial Revolution” where technology advancements follow an exponential growth curve introduces a reality that combines technology across the physical, digital, and biological domains. The Fourth Industrial Revolution has the potential to change both public and private sector organizations, and society itself, however, the accounting practices are not positioned to take advantage of these changes. With this phenomenon in mind, this study seeks to address a gap in the literature that the current accounting practices are insufficient to meet the challenges of the Fourth Industrial Revolution as they do not provide a raw, non-monetized common unit of value, that can measure productivity on a ratio scale for non-profit organizations or at the sub-corporate level in for-profit organization. Through a discussion guided by the literature, this study seeks to generate a scholastic dialogue on how to address this problem.Approved for public release; distribution is unlimited

Cybersecurity, Artificial Intelligence, and Risk Management: Understanding Their Implementation in Military Systems Acquisitions

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThis research has the explicit goal of proposing a reusable, extensible, adaptable, and comprehensive advanced analytical modeling process to help the U.S. Navy in quantifying, modeling, valuing, and optimizing a set of nascent Artificial Intelligence and Machine Learning (AI/ML) applications in the aerospace, automotive and transportation industries and developing a framework with a hierarchy of functions by technology category and developing a unique-to-Navy-ship construct that, based on weighted criteria, scores the return on investment of developing naval AI/ML applications that enhance warfighting capabilities. This current research proposes to create a business case for making strategic decisions under uncertainty. Specifically, we will look at a portfolio of nascent artificial intelligence and machine learning applications, both at the PEO-SHIPS and extensible to the Navy Fleet. This portfolio of options approach to business case justification will provide tools to allow decision-makers to decide on the optimal flexible options to implement and allocate in different types of artificial intelligence and machine learning applications, subject to budget constraints, across multiple types of ships. The concept of the impact of innovative technology on productivity has applicability beyond the Department of Defense (DoD). Private industry can greatly benefit from the concepts and methodologies developed in this research to apply to the hiring and talent management of scientists, programmers, engineers, analysts, and senior executives in the workforce to increase innovation productivity.Approved for public release; distribution is unlimited

Cybersecurity, Artificial Intelligence, and Risk Management: Understanding Their Implementation in Military Systems Acquisitions

Excerpt from the Proceedings of the Nineteenth Annual Acquisition Research SymposiumThis research has the explicit goal of proposing a reusable, extensible, adaptable, and comprehensive advanced analytical modeling process to help the U.S. Navy in quantifying, modeling, valuing, and optimizing a set of nascent Artificial Intelligence and Machine Learning (AI/ML) applications in the aerospace, automotive and transportation industries and developing a framework with a hierarchy of functions by technology category and developing a unique-to-Navy-ship construct that, based on weighted criteria, scores the return on investment of developing naval AI/ML applications that enhance warfighting capabilities. This current research proposes to create a business case for making strategic decisions under uncertainty. Specifically, we will look at a portfolio of nascent artificial intelligence and machine learning applications, both at the PEO-SHIPS and extensible to the Navy Fleet. This portfolio of options approach to business case justification will provide tools to allow decision-makers to decide on the optimal flexible options to implement and allocate in different types of artificial intelligence and machine learning applications, subject to budget constraints, across multiple types of ships. The concept of the impact of innovative technology on productivity has applicability beyond the Department of Defense (DoD). Private industry can greatly benefit from the concepts and methodologies developed in this research to apply to the hiring and talent management of scientists, programmers, engineers, analysts, and senior executives in the workforce to increase innovation productivity.Approved for public release; distribution is unlimited

Is human resources management in the leading states being reinvented?

Reinventing government is an approach to public sector management theory that may be the most influential and significant in the past half century. It claims that the traditional government employment principles of fitness and merit can coexist with increased managerial discretion and greater employee independence. Reinvention also contends that flexibility and decentralization can be combined with a system that demands high levels of accountability and equity. Many of its recommendations for improving government are directed toward human resources management.The purpose of this study is to learn about the degree to which reinvention has penetrated selected state civil service systems. Its point of departure was to select several of reinvention's major endorsements, then investigate their implementation in states known for supporting progressive personnel practices. Related inquiries were made regarding the evolving role of the states' central personnel departments and the status of merit principles and oversight.Several recent nationwide surveys were used to identify states whose personnel systems are among the country's most progressive. Interviews were conducted with veteran personnel professionals who were selected based on their reputations for objectivity and professionalism. The findings from the research reveal that almost half of the selected reinvention recommendations have made very little progress in the past decade. However, the few that have been strongly embraced are among the most important

and Cost/Benefits Opportunities

Acquisition Research Program Sponsored Report SeriesSponsored Acquisition Research & Technical ReportsThe acquisition of artificial intelligence (AI) systems is a relatively new challenge for the U.S. Department of Defense (DoD). Given the potential for high-risk failures of AI system acquisitions, it is critical for the acquisition community to examine new analytical and decision-making approaches to managing the acquisition of these systems in addition to the existing approaches (i.e., Earned Value Management, or EVM). In addition, many of these systems reside in small start-up or relatively immature system development companies, further clouding the acquisition process due to their unique business processes when compared to the large defense contractors. This can lead to limited access to data, information, and processes that are required in the standard DoD acquisition approach (i.e., the 5000 series). The well-known recurring problems in acquiring information technology automation within the DoD will likely be exacerbated in acquiring complex and risky AI systems. Therefore, more robust, agile, and analytically driven acquisition methodologies will be required to help avoid costly disasters in acquiring these kinds of systems. This research provides a set of analytical tools for acquiring organically developed AI systems through a comparison and contrast of the proposed methodologies that will demonstrate when and how each method can be applied to improve the acquisitions lifecycle for AI systems, as well as provide additional insights and examples of how some of these methods can be applied. This research identifies, reviews, and proposes advanced quantitative, analytically based methods within the integrated risk management (IRM)) and knowledge value added (KVA) methodologies to complement the current EVM approach. This research examines whether the various methodologies—EVM, KVA, and IRM—could be used within the Defense Acquisition System (DAS) to improve the acquisition of AI. While this paper does not recommend one of these methodologies over the other, certain methodologies, specifically IRM, may be more beneficial when used throughout the entire acquisition process instead of within a portion of the system. Due to this complexity of AI system, this research looks at AI as a whole and not specific types of AI.Approved for public release; distribution is unlimited.Approved for public release; distribution is unlimited