Digital Commons Network^™

Artificial Intelligence (Ai) In Forensic Psychology: An Umbrella Review Of Potentials And Pitfalls, Ysabel Thereze Ang Guevarra, Nur Eva Alisha Binte Mohamed Hisham, Andree Hartanto

Research Collection School of Social Sciences

Artificial intelligence (AI) is becoming increasingly embedded within forensic psychological practice, shaping how criminal risk, legal responsibility and public safety are assessed. AI tools are now used in recidivism prediction, behavioural analysis, deception detection and investigative support, high-stakes domains where errors can have profound consequences. Despite this rapid adoption, the existing literature remains fragmented, with most reviews confined to narrow subdomains and offering limited integrated synthesis of AI′s broader role in forensic psychology. Thus, this umbrella review addresses this gap by synthesising findings from 43 reviews obtained from five major databases, namely EBSCOhost ERIC, EBSCOhost PsycInfo, PubMed, Scopus and Web …

You Can’T Spell Audit Without Ai: The Current Uses Of Artificial Intelligence In Audit, Jena Perkins

Senior Honors Theses

The accounting profession continuously adapts to the innovations provided by the broader context in which it exists. Artificial intelligence (AI) is a forerunner among tools used to enhance and optimize auditing services within the accounting profession. The realm of AI offers advancements to procedures used within an audit to detect misstatements. Based on the proprietary platforms developed by Big 4 accounting firms, AI is a key component in maintaining an advanced approach towards auditing.

Generative Identity Theft: Criminalizing Deepfakes Using The Right Of Publicity, Dustin Marlan

Akron Law Review

No abstract provided.

Application Paths Of Semantic Modeling In Financial Fraud Detection And Risk Identification, Victor P. Gauthier, Daniel S. Wu

Computer Science Faculty Publications

Financial fraud and risk pose significant threats to economic stability and individual well-being. Traditional detection methods often struggle to keep pace with increasingly sophisticated fraudulent schemes. Semantic modeling, which focuses on understanding the meaning and relationships within data, offers a promising avenue for enhancing fraud detection and risk identification. This review paper explores the application paths of semantic modeling in this domain. We begin with a historical overview of fraud detection techniques, highlighting the limitations of traditional approaches. Subsequently, we delve into core themes, including knowledge graph-based fraud detection and semantic rule-based inference for risk assessment. We then compare and …

Stranger Disputes: When Artificial Intelligence Turns Arbitration Upside Down, Imre Stephen Szalai

Pepperdine Dispute Resolution Law Journal

Arbitration agreements are everywhere in the United States. These agreements already block access to courts in a troubling manner, and pursuant to these agreements, parties must resolve their disputes before a private, human arbitrator with broad, virtually unreviewable powers. However, with the growth of AI, companies could easily redraft their contracts to require arbitration before non-human bots or AI arbitrators instead of a human arbitrator. Based on the history, values, policy, and text of the Federal Arbitration Act (FAA), this Article concludes that the FAA would govern and support the use of an AI arbitrator. As a result, a pre-dispute …

Real-Time Fraud Detection Using Big Data, Abdulla Matar Alketbi

Theses

In today’s digital world, fraud detection has become an important part of financial security. This study explores and compares the performance of different machine learning models in identifying fraudulent transactions using the IEEE-CIS Fraud Detection dataset. Techniques such as Random Forest, Gradient Boosting, Deep Neural Networks, and Logistic Regression were evaluated. The dataset was pre-processed using SMOTE to balance the classes and improve model sensitivity to fraud cases. Each performance of the model was assessed using accuracy, precision, recall, and F1-score. The Random Forest model achieved the highest overall performance with an F1-score of 99.23

Ai Governance And Algorithmic Auditing In Financial Institutions: Lessons From Singapore, Nydia Remolina Leon

Research Collection Yong Pung How School Of Law

This paper examines the role of algorithmic auditing as a mechanism for responsible AI development and deployment in the financial sector, with a particular focus on Singapore’s regulatory and institutional initiatives. Against the backdrop of fragmented global artificial intelligence (AI) governance frameworks, the study analyses how Singapore has developed operational tools — such as the Veritas Toolkit, AI Verify, Project Moonshot and Project Mindforge — that go beyond abstract ethical principles to provide measurable, use-case-specific standards for auditing AI systems. These initiatives contribute to standardising audit practices, enhancing transparency and bridging trust gaps between financial institutions, regulators and stakeholders. The …

Gleeson Library Ai Taskforce Final Report, Anders Lyon, Amanda Raver, Kristie Barlas, Shawn P. Calhoun, Annie Pho, Brian Schumacher, Claire Sharifi, Gina Solares

Gleeson Library Initiatives

During the Fall 2025 semester, the Gleeson Library AI Taskforce examined how artificial intelligence is influencing higher education and what those changes mean for library work at USF. By reviewing AI activity across campus, surveying library staff, and analyzing how Jesuit institutions are responding to AI, the Taskforce found a landscape that is evolving quickly but thoughtfully. Across these contexts, interest in AI literacy is growing, experimentation with new tools is expanding, and there is a clear need for library-specific guidance, particularly given that no Association of Jesuit Colleges and Universities (AJCU) libraries have published AI policies or frameworks of …

Bridging The Protection Gap: Innovative Approaches To Shield Older Adults From Ai-Enhanced Scams, Ld Herrera, London Van Sickle, Ashley L. Podhradsky

Research & Publications

Artificial Intelligence (AI) is rapidly gaining popularity as individuals, groups, and organizations discover and apply its expanding capabilities. Generative AI creates or alters various content types including text, image, audio, and video that are realistic and challenging to identify as AI-generated constructs. However, guardrails preventing malicious use of AI are easily bypassed. Numerous indications suggest that scammers are already using AI to enhance already successful scams, improving scam effectiveness, speed and credibility, while reducing detectability of scams that target older adults, who are known to be slow to adopt new technologies. Through hypothetical cases analysis of two leading scams, the …

Revolutionizing Public Safety And Criminal Justice Through Ai, Alan Saquella

Publications

Artificial Intelligence (AI) is rapidly transforming public safety, criminal justice and security by fundamentally changing how crimes are committed, investigated and prevented. As AI tools become increasingly sophisticated, law enforcement and corporate security professionals are utilizing these advancements to enhance their capabilities. However, integrating AI into these sectors also brings significant challenges, including ethical concerns, recruitment difficulties, and the surge in crime rates. This article examines the transformative impact of AI, the ongoing efforts to unify AI applications across public safety and security sectors, and expert advice on overcoming the associated challenges.

Nidus Idearum. Scilogs, Xiv: Superhyperalgebra, Florentin Smarandache

Branch Mathematics and Statistics Faculty and Staff Publications

In this fourteenth book of scilogs – one may find topics on examples where neutrosophics works and others don’t, law of included infinitely-many-middles, decision making in games and real life through neutrosophic lens, sociology by neutrosophic methods, Smarandache multispace, algebraic structures using natural class of intervals, continuous linguistic set, cyclic neutrosophic graph, graph of neutrosophic triplet group , how to convert the crisp data to neutrosophic data, n-refined neutrosophic set ranking, adjoint of a square neutrosophic matrix, neutrosophic optimization, de-neutrosophication, the n-ary soft set relationship, hypersoft set, extending the hypergroupoid to the superhypergroupoid, alternative ranking, Dezert-Smarandache Theory (DSmT), reconciliation between …

Present Case Studies Highlighting Practical Implications Of Architectural Design Choices, Emily Barnes, James Hutson

Faculty Scholarship

The interpretability of deep neural networks (DNNs) has become a crucial focus within artificial intelligence and machine learning, particularly as these models are increasingly used in high-stakes applications such as healthcare, finance, and autonomous driving. This article explores the impact of architectural design choices on the interpretability of DNNs, emphasizing the importance of transparency, trust, and accountability in AI systems. By presenting case studies and experimental results, the article highlights how different architectural elements—such as layer types, network depth, connectivity patterns, and attention mechanisms—affect model interpretability and performance. The discussion is structured into three main sections: real-world applications, architectural trade-offs, …

Democracy, Discourse, And The Artificially Intelligent Corporation, Michael R. Siebecker

Sturm College of Law: Faculty Scholarship

Does the ascendance of the artificially intelligent corporation threaten the integrity and legitimacy of democracy? The question seems particularly important as the 2024 presidential election approaches. Hardly a day passes without a new report regarding the disruptive impact of harnessing artificial intelligence (“AI”) technologies. A cascading cadre of academics, business leaders, and politicians warn that unchecked development and dissemination of AI could irreparably damage vital institutions of civil society. Despite the warnings about existential threats AI poses to human agency and democratic processes, reliance on AI technologies proliferates at break-neck speed.

The concern about AI’s destructive impact gets exacerbated by …

Analytics Without Borders Program Schedule, Bryant University Department Of Information Systems And Analytics

Analytics Without Borders

No abstract provided.

Role-Reversibility, Ai, And Equitable Justice - Or: Why Mercy Cannot Be Automated, Stephen E. Henderson, Kiel Brennan-Marquez

JCLC Online

A few years ago, we developed the concept of “role-reversibility” in AI governance: the idea that it matters whether a party exercising judgment is reciprocally vulnerable to the effects of judgment. This idea, we argued, supplies a deontic reason to maintain certain spheres of human judgment even if (or when) truly intelligent machines become demonstrably superior in every utilitarian sense. While computer science remains far from that holy grail, generative AI is raging through systems as diverse as healthcare, finance, advertising, law, and academe, making it imperative to further shore up our claim. We do so by situating role-reversibility within …

The Age Of Synthetic Realities: Challenges And Opportunities, João Phillipe Cardenuto, Jing Yang, Rafael Padilha, Renjie Wan, Daniel Moreira, Haoliang Li, Shiqi Wang, Fernanda Andaló, Sébastien Marcel, Anderson Rocha

Computer Science: Faculty Publications and Other Works

Synthetic realities are digital creations or augmentations that are contextually generated through the use of Artificial Intelligence (AI) methods, leveraging extensive amounts of data to construct new narratives or realities, regardless of the intent to deceive. In this paper, we delve into the concept of synthetic realities and their implications for Digital Forensics and society at large within the rapidly advancing field of AI. We highlight the crucial need for the development of forensic techniques capable of identifying harmful synthetic creations and distinguishing them from reality. This is especially important in scenarios involving the creation and dissemination of fake news, …

A Machine Learning Approach To Deepfake Detection, Delaney Conrad

All Undergraduate Theses and Capstone Projects

The ability to manipulate videos has been around for decades but a process that once would take time, money, and professionals, can now be created by anyone due to the rapid advancement of deepfake technology. Deepfakes use deep learning artificial intelligence to make fake digital content, typically in the form of swapping a person’s face in a video or image. This technology could easily threaten and manipulate individuals, corporations, and political organizations, so it is essential to find methods for detecting deepfakes. As the technology for creating deepfakes continues to improve, these manipulated videos are becoming increasingly undetectable. It is …

Role-Reversibility, Ai, And Equitable Justice — Or: Why Mercy Cannot Be Automated, Stephen E. Henderson, Kiel Brennan-Marquez

Faculty Articles

A few years ago, we developed the concept of “role-reversibility” in AI governance: the idea that it matters whether a party exercising judgment is reciprocally vulnerable to the effects of judgment. This idea, we argued, supplies a deontic reason to maintain certain spheres of human judgment even if (or when) truly intelligent machines become demonstrably superior in every utilitarian sense. While computer science remains far from that holy grail, generative AI is raging through systems as diverse as healthcare, finance, advertising, law, and academe, making it imperative to further shore up our claim. We do so by situating role-reversibility within …

Camouflaged Poisoning Attack On Graph Neural Networks, Chao Jiang, Yi He, Richard Chapman, Hongyi Wu

Computer Science Faculty Publications

Graph neural networks (GNNs) have enabled the automation of many web applications that entail node classification on graphs, such as scam detection in social media and event prediction in service networks. Nevertheless, recent studies revealed that the GNNs are vulnerable to adversarial attacks, where feeding GNNs with poisoned data at training time can lead them to yield catastrophically devastative test accuracy. This finding heats up the frontier of attacks and defenses against GNNs. However, the prior studies mainly posit that the adversaries can enjoy free access to manipulate the original graph, while obtaining such access could be too costly in …

The Future Of Work Now: Ai-Driven Transaction Surveillance At Dbs Bank, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon. Steve Miller of Singapore Management University and I co-authored the story.

Making Corporations More Human Through Artificial Intelligence, Michael R. Siebecker

Sturm College of Law: Faculty Scholarship

Can existing corporate fiduciary principles adequately guide officers and directors regarding the proper development and utilization of artificial intelligence ("AI") technologies? What role should AI play in corporate boardrooms? These questions seem especially pressing considering the increasing prevalence of AI throughout a variety of industries in a host of key functions. It should come as little surprise, however, that with the advent of a powerful new technology, important concerns arise regarding the limits on its use and the ends to which it should be directed. Ethicists warn about AI 's lack of moral sensitivity, empathy, and appreciation for human rights. …

Continuous Monitoring Of Enterprise Risks: A Delphi Feasibility Study, Robert Baksa

Dissertations

A constantly evolving regulatory environment, increasing market pressure to improve operations, and rapidly changing business conditions are creating the need for ongoing assurance that organizational risks are continually and adequately mitigated. Enterprises are perpetually exposed to fraud, poor decision making and/or other inefficiencies that can lead to significant financial loss and/or increased levels of operating risk. Increasingly, Information Systems are being harnessed to reinvent the risk management process. One promising technology is Continuous Auditing, which seeks to transform the audit process from periodic reviews of a few transactions to a continuous review of all transactions. However, the highly integrated, rapidly …