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American International Group, Inc. (AIG) has recently been charged with reporting bogus transactions that hid losses and inflated its net worth. The New York State Attorney General Eliot Spitzer alleges that AIG inflated reserves used for paying claims by millions of dollars and that AIG's CEO Maurice Greenberg repeatedly directed AIG traders late in the day to buy AIG shares to prop up its price, among other allegations. We examine the accounting errors for which AIG and Greenberg are being charged and analyze the opportunities missed by the auditors to detect problems, within the framework of corporate governance. That is, we evaluate the corporate environment that supported these lapses and provided an environment conducive to the perpetration and acceptance of fradulent reporting. We discuss how corporate governance not only promotes better financial reporting, but provides a level of scrutiny that encourages more ethical behavior at all levels of the corporate hierarchy, and we discuss the imperative for accounting education.

Following the surge of documents laying out organizations' ethical principles for their use of artificial intelligence (AI), there is a growing demand for translating ethical principles to practice through AI governance (AIG). AIG has emerged as a rapidly growing, yet fragmented, research area. This paper synthesizes the organizational AIG literature by outlining research themes and knowledge gaps as well as putting forward future agendas.

The authors undertake a systematic literature review on AIG, addressing the current state of its conceptualization and suggesting future directions for AIG scholarship and practice. The review protocol was developed following recommended guidelines for systematic reviews and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).

The results of the authors’ review confirmed the assumption that AIG is an emerging research topic with few explicit definitions. Moreover, the authors’ review identified four themes in the AIG literature: technology, stakeholders and context, regulation and processes. The central knowledge gaps revealed were the limited understanding of AIG implementation, lack of attention to the AIG context, uncertain effectiveness of ethical principles and regulation, and insufficient operationalization of AIG processes. To address these gaps, the authors present four future AIG agendas: technical, stakeholder and contextual, regulatory, and process. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.

To address the identified knowledge gaps, the authors present the following working definition of AIG: AI governance is a system of rules, practices and processes employed to ensure an organization's use of AI technologies aligns with its strategies, objectives, and values, complete with legal requirements, ethical principles and the requirements set by stakeholders. Going forward, the authors propose focused empirical research on organizational AIG processes, the establishment of an AI oversight unit and collaborative governance as a research approach.

For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.

For society, the authors review elucidates the multitude of stakeholders involved in AI governance activities and complexities related to balancing the needs of different stakeholders.

By delineating the AIG concept and the associated research themes, knowledge gaps and future agendas, the authors review builds a foundation for organizational AIG research, calling for broad contextual investigations and a deep understanding of AIG mechanisms. For practitioners, the authors highlight training and awareness, stakeholder management and the crucial role of organizational culture, including senior management commitment.

Ammonia injection grid (AIG) is used as an input device for ammonia which reacts with NO_x in the selective catalytic reduction (SCR) reactor. However, non-uniform concentration distribution of ammonia could produce partially poisoning or deposits of the catalyst. In this work, for making ammonia widely distributed throughout the flue gas and fully mixed, an optimization method of AIG is proposed.

Depending on the complexity of fluid flow, the relation between the concentration distributions of ammonia and the geometric parameters of AIG is nonlinear. Based on a certain amount of AIG samples, the computational fluid dynamics (CFD) simulations are applied to propose the agent model which describes the functional relation of the deviation of ammonia concentration and the geometric parameters of AIG. The optimization model of AIG based on the agent model is established. The optimized AIG based on the agent model can be used to produce uniform concentration distributions of ammonia, especially in the case that velocity distribution of flue gas is non-uniform.

For qualitatively confirming this optimization method, the three-dimensional CFD simulation of the optimized AIG is carried out. The results reveal that the diffusion process of ammonia gas is consistent with the development of the local vortices, which have a certain relation with the velocity distribution of the flue gas. The unequal ammonia injection designed by the optimization based on the agent model promotes a better mixing of ammonia and flue gas.

In this work, first, the method for optimizing AIG based on the agent model is proposed. Second, the three-dimensional CFD modeling and simulation of the optimized AIG is carried out, and the mixing effects of ammonia and flue gas are presented.

Risk-based clearing has been proposed by Rausser et al. (2010) for over-the-counter (OTC) derivatives. This paper aims to illustrate the application of risk-based margins to a case study of the mortgage-backed securities derivative portfolio of the American International Group (AIG) during the period 2005-2008. There exists sufficient publicly available information to examine AIG’s derivative portfolio and how that portfolio would depend on conjectural changes in margin requirements imposed on its OTC derivative positions. Generally, such data on OTC derivative portfolio positions are unavailable in the public domain, and thus, the AIG data provide a unique opportunity for an objective evaluation.

This paper uses modern financial methodology to evaluate risk-based margining and collateralization for the major OTC derivative portfolio of the AIG.

This analysis reveals that a risk-based margin procedure would have led to earlier margin calls of greater magnitude initially than the collateral calls actually faced by AIG Financial Products (AIGFP). The total margin ultimately required by the risk-based procedure, however, is similar in magnitude to the collateral calls faced by AIGFP by August 2008. It is likely that a risk-based clearing procedure applied to AIG’s OTC contracts would have led to the AIG undertaking significant hedging and liquidation of their OTC positions well before the losses built up to the point they had, perhaps avoiding the federal government’s orchestrated restructuring that occurred in September 2008.

There has been no published risk-based evaluations of a major OTC portfolio of derivatives for any company, let alone the AIG.

The purpose of this paper is to demonstrate a particular shift in the language used in economic policy debates since the late 1970s. We call this phenomenon the “financialization of public discourse”, which refers to the use of particular metaphors and linguistic styles that are friendly to the economic interest of the financial industry.

We used a rhetorical analysis to discover and analyze the specific cases which exemplify what we call the financialization of public discourse. A case study, the USA Treasury’s justification for its AIG policy, is used to strengthen the thesis of the paper.

As the AIG case helps demonstrate, the language of finance limits the policy conversation and disguises the fact that the government’s role in this case is not different than its overall collective risk management function.

We assume that framing of economic events helps shape public perceptions of the desirability of various policies. This prediction, although reasonable, should be supported with more direct evidence.

This paper intends to articulate a vital risk management role that the government plays in the economy. Specifically, the government is strongly suited to spreading the consequences of aggregate risk over time and thereby insulating the individuals from drastic fluctuations in their welfare. Our approach could potentially inform an array of public policies.

The rhetorical strategies that policy makers use to justify their policy positions and their consequences have been certainly under-researched, particularly in economics. This paper intends to fill this gap in the literature.

Studies of Depression-era financial remediation have generally focused on federal deposit insurance and the provision of equity to banks by the Reconstruction Finance Corporation (RFC). This paper broadens the concept of financial remediation to include other programs – RFC lending, federal guarantees of farm and home mortgages, and the elimination of interest on demand deposits – and other intermediaries – savings and loans, mutual savings banks, and life insurance companies. The benefits of remediation or the amounts potentially at risk to the government in these programs are calculated annually and allocated to the various intermediaries. The slow remediation of real estate loans (two-thirds of these intermediaries' loans) needs further study with respect to the slow economic recovery. The paper compares Depression-era remediation with efforts during the 2008–2009 crisis. Today's remediation contrasts with the 1930s in its speed, magnitude relative to GDP or private sector nonfinancial debt, the share of remediation going to nonbanks, and emphasis on securities markets.

The purpose of this paper is to develop a new guidance scheme for aerial vehicles based on artificial intelligence. The new guidance scheme must be able to intercept maneuvering targets with higher probability and precision compared to existing algorithms.

A simulation setup of the aerial vehicle guidance problem is developed. A model-based machine learning technique known as Q-learning is used to develop a new guidance scheme. Several simulation experiments are conducted to train the new guidance scheme. Orthogonal arrays are used to define the training experiments to achieve faster convergence. A well-known guidance scheme known as proportional navigation guidance (PNG) is used as a base model for training. The new guidance scheme is compared for performance against standard guidance schemes like PNG and augmented proportional navigation guidance schemes in presence of sensor noise and computational delays.

A new guidance scheme for aerial vehicles is developed using Q-learning technique. This new guidance scheme has better miss distances and probability of intercept compared to standard guidance schemes.

The research uses simulation models to develop the new guidance scheme. The new guidance scheme is also evaluated in the simulation environment. The new guidance scheme performs better than standard existing guidance schemes.

The new guidance scheme can be used in various aerial guidance applications to reach a dynamically moving target in three-dimensional space.

The research paper proposes a completely new guidance scheme based on Q-learning whose performance is better than standard guidance schemes.

Describes a Soviet approach to organizational change utilizing a game devised especially for one organization which poses organizational problems to managers and workers. By means of performance of a carefully crafted script, participants in the game devise solutions to the problems which are generally acceptable to all participants.

Henri Fayol is undoubtedly best known in the English‐speaking world for his book Administration Industrielle et Générale. His subsequent activities in promoting the development of management studies and education as a a means of improving both industry and public service performance are less well known. One of his more significant initiatives in this area was to establish the Centre for Administrative Studies (CAS) in 1917. Relates the founding of the CAS to Fayol′s activities at the time, identifies its goals and activities, summarizes some of his contributions to the development of what ultimately became the formalization of management studies in both Europe and North America and notes the Centre′s demise almost concurrently with Fayol′s death. Reveals Fayol′s own reasons for delaying the publication of parts 3 and 4 of Administration Industrielle et Générale.

Traditionally, individual states have shared responsibility for regulating the US insurance industry. The Dodd–Frank Act changes this by tasking the Federal Reserve with regulating the systemic risks that particularly large insurance organizations might pose and assigning the regulation of swap-based substitutes for insurance and reinsurance products to the SEC and CFTC. This paper argues that prudential regulation of large insurance firms and weaknesses in federal swaps regulation could reduce the effectiveness of state-based systems in protecting policyholders and taxpayers from nonperformance in the insurance industry. Swap-based substitutes for traditional insurance and reinsurance contracts offer protection sellers a way to transfer responsibility for guarding against nonperformance into potentially less-effective hands. The CFTC and SEC lack the focus, expertise, experience, and resources to adequately manage the ways that swap transactions can affect US taxpayers’ equity position in global safety nets, while regulators at the Fed refuse to recognize that conscientiously monitoring accounting capital at financial holding companies will not adequately protect taxpayers and policyholders until and unless it is accompanied by severe penalties for managers that willfully hide their firm’s exposure to destructive tail risks.