Towards An Integrated Framework for Artificial Intelligence Governance

Artificial intelligence (AI) is being developed and adopted by many organizations throughout the world. As the potential of AI is being leveraged, many opportunities are being realized and continue to emerge. However, potential issues need to be addressed (Wang and Siau, 2019), such as ethical and legal concerns (Siau and Wang, 2020), making an AI governance framework paramount (Wang and Siau, 2018; Chen et al., 2022). To address this need, we propose an integrated AI governance framework based on an analysis of existing AI frameworks from different regions of the world (i.e., United States, European Commission, Singapore, and Hong Kong). More specifically, we systematically analyzed these frameworks, juxtaposed the frameworks to identify similarities and differences, which allowed us to identify the core components of AI governance, and proposed an integrated framework for AI governance that adheres to the characteristics of analytic theory (Gregor, 2006). The proposed AI governance framework encompasses both Strategic as well as Tactical and Operational components. There is an overarching theme that crosses the Strategic, Tactical, and Operational components that we termed Stakeholder Communication, Interaction, and Engagement. The integrated framework can be utilized by practitioners as guidelines for their AI endeavors and it can also serve as a foundation to guide future AI governance research. Moving forward, we plan to conduct case studies on AI governance frameworks in organizations and study their impacts on AI success. Future research also includes extending our proposed AI governance framework and fine-tuning it to fit unique organizational characteristics or specific sectors of industry. REFERENCES Chen, J., Eschenbrenner, B., Nah, F., Siau, K., and Qian, Y. 2022. “Diffusion of AI Governance,” Proceedings of the Seventeenth Midwest Association for Information Systems Conference, Omaha, Nebraska, May 16-17. Gregor, S. 2006. “The Nature of Theory in Information Systems,” MIS Quarterly (30:3), pp. 611-642. Siau, K., and Wang, W. 2020. “Artificial Intelligence (AI) Ethics: Ethics of AI and Ethical AI,” Journal of Database Management (31:2), pp. 74-87. Wang, W., and Siau, K. 2019. “Artificial Intelligence, Machine Learning, Automation, Robotics, Future of Work, and Future of Humanity – A Review and Research Agenda,” Journal of Database Management, (30:1), pp. 61-79. Wang, W., and Siau, K. 2018. “Artificial Intelligence: A Study on Governance, Policies, and Regulations,” Thirteenth Annual Midwest Association for Information Systems Conference, St. Louis, Missouri, May 17-18

"Consciousness". Selected Bibliography 1970 - 2001

This is a bibliography of books and articles on consciousness in philosophy, cognitive science, and neuroscience over the last 30 years. There are three main sections, devoted to monographs, edited collections of papers, and articles. The first two of these sections are each divided into three subsections containing books in each of the main areas of research. The third section is divided into 12 subsections, with 10 subject headings for philosophical articles along with two additional subsections for articles in cognitive science and neuroscience. Of course the division is somewhat arbitrary, but I hope that it makes the bibliography easier to use. This bibliography has first been compiled by Thomas Metzinger and David Chalmers to appear in print in two philosophical anthologies on conscious experience (Metzinger 1995a, b). From 1995 onwards it has been continuously updated by Thomas Metzinger, and now is freely available as a PDF-, RTF-, or HTML-file. This bibliography mainly attempts to cover the Anglo-Saxon and German debates, in a non-annotated, fully formatted way that makes it easy to "cut and paste" from the original file. To a certain degree this bibliography also contains items in other languages than English and German - all submissions in other languages are welcome. Last update of current version: July 13th, 2001

Game Theory Meets Network Security: A Tutorial at ACM CCS

The increasingly pervasive connectivity of today's information systems brings up new challenges to security. Traditional security has accomplished a long way toward protecting well-defined goals such as confidentiality, integrity, availability, and authenticity. However, with the growing sophistication of the attacks and the complexity of the system, the protection using traditional methods could be cost-prohibitive. A new perspective and a new theoretical foundation are needed to understand security from a strategic and decision-making perspective. Game theory provides a natural framework to capture the adversarial and defensive interactions between an attacker and a defender. It provides a quantitative assessment of security, prediction of security outcomes, and a mechanism design tool that can enable security-by-design and reverse the attacker's advantage. This tutorial provides an overview of diverse methodologies from game theory that includes games of incomplete information, dynamic games, mechanism design theory to offer a modern theoretic underpinning of a science of cybersecurity. The tutorial will also discuss open problems and research challenges that the CCS community can address and contribute with an objective to build a multidisciplinary bridge between cybersecurity, economics, game and decision theory

Unpacking capabilities underlying design (thinking) process

Engineering graduates must know how to frame and solve non-routine problems. While design classes explicitly teach problem framing and solving, it is lacking throughout much of the rest of the engineering curriculum and is often relegated to capstone classes at the end of the students’ educational experience. This paper explores problem framing and solving through the lens of experiential learning theory. It captures core problem framing and solving approaches from critical, design and systems thinking and concludes with a table of learning outcomes that might be drawn upon in designing an engineering curriculum that more fully develops the problem framing and solving capabilities of its students

Agent-based Social Psychology: from Neurocognitive Processes to Social Data

Moral Foundation Theory states that groups of different observers may rely on partially dissimilar sets of moral foundations, thereby reaching different moral valuations. The use of functional imaging techniques has revealed a spectrum of cognitive styles with respect to the differential handling of novel or corroborating information that is correlated to political affiliation. Here we characterize the collective behavior of an agent-based model whose inter individual interactions due to information exchange in the form of opinions are in qualitative agreement with experimental neuroscience data. The main conclusion derived connects the existence of diversity in the cognitive strategies and statistics of the sets of moral foundations and suggests that this connection arises from interactions between agents. Thus a simple interacting agent model, whose interactions are in accord with empirical data on conformity and learning processes, presents statistical signatures consistent with moral judgment patterns of conservatives and liberals as obtained by survey studies of social psychology.Comment: 11 pages, 4 figures, 2 C codes, to appear in Advances in Complex System

Cultivating Talent through a Principal Pipeline

This report, the second in a series, describes early results of Wallace's Principal Pipeline Initiative, a multi-year effort to improve school leadership in six urban school districts. The report describes changes in the six districts' practices to recruit, train and support new principals. It also offers early lessons for other districts considering changes to their own principal pipelines