Law Commons^™

Regulating Artificial Intelligence In International Investment Law, Mark Mclaughlin

Research Collection Yong Pung How School Of Law

The interaction between artificial intelligence (AI) and international investment treaties is an uncharted territory of international law. Concerns over the national security, safety, and privacy implications of AI are spurring regulators into action around the world. States have imposed restrictions on data transfer, utilised automated decision-making, mandated algorithmic transparency, and limited market access. This article explores the interaction between AI regulation and standards of investment protection. It is argued that the current framework provides an unpredictable legal environment in which to adjudicate the contested norms and ethics of AI. Treaties should be recalibrated to reinforce their anti-protectionist origins, embed human-centric …

Legal Dispositionism And Artificially-Intelligent Attributions, Jerrold Soh

Research Collection Yong Pung How School Of Law

It is conventionally argued that because an artificially-intelligent (AI) system acts autonomously, its makers cannot easily be held liable should the system's actions harm. Since the system cannot be liable on its own account either, existing laws expose victims to accountability gaps and need to be reformed. Recent legal instruments have nonetheless established obligations against AI developers and providers. Drawing on attribution theory, this paper examines how these seemingly opposing positions are shaped by the ways in which AI systems are conceptualised. Specifically, folk dispositionism underpins conventional legal discourse on AI liability, personality, publications, and inventions and leads us towards …

Crossing The Rubicon: Evaluating The Use Of Artificial Intelligence In The Law And Singapore Courts, Ming En Tor

Research Collection Yong Pung How School Of Law

In recent years, Artificial Intelligence (“AI”) has challenged many fundamental assumptions of how organisations and industries should operate. The Courts, traditionally seen as a hallowed ground graced by the best of lawyers, still remains as unchartered territory for AI’s infiltration. Yet, there is growing evidence which suggest AI may soon cross this frontier to replace important court functions.

This paper critically assesses the use of AI in law and the courts. Part II will first examine the arguments for and against the adoption of AI in the legal profession. Thereafter, Part III will critically examine whether AI should …

Towards A Calibrated Trust-Based Approach To The Use Of Facial Recognition Technology, Gary Kok Yew Chan

Research Collection Yong Pung How School Of Law

The use of facial recognition technology has given rise to much debate relating to issues concerning privacy infringements, bias and inaccuracies of data and outputs, possibilities of covert use, the lack of data security and the problem of function creep. Certain states and jurisdictions have called for bans and moratoria on the use of facial recognition technology. This paper argues that a blanket ban on facial recognition technology would be overly precautionary without fully considering the wide range of uses and benefits of the innovation. To promote its acceptance, trust in facial recognition technology should be developed in a calibrated …

Grand-Vision: An Intelligent System For Optimized Deployment Scheduling Of Law Enforcement Agents, Jonathan Chase, Tran Phong, Kang Long, Tony Le, Hoong Chuin Lau

Research Collection School Of Computing and Information Systems

Law enforcement agencies in dense urban environments, faced with a wide range of incidents to handle and limited manpower, are turning to data-driven AI to inform their policing strategy. In this paper we present a patrol scheduling system called GRAND-VISION: Ground Response Allocation and Deployment - Visualization, Simulation, and Optimization. The system employs deep learning to generate incident sets that are used to train a patrol schedule that can accommodate varying manpower, break times, manual pre-allocations, and a variety of spatio-temporal demand features. The complexity of the scenario results in a system with real world applicability, which we demonstrate through …

An Ecosystem Approach To Ethical Ai And Data Use: Experimental Reflections, Mark Findlay, Josephine Seah

Research Collection Yong Pung How School Of Law

While we have witnessed a rapid growth of ethics documents meant to guide artificial intelligence (AI) development, the promotion of AI ethics has nonetheless proceeded with little input from AI practitioners themselves. Given the proliferation of AI for Social Good initiatives, this is an emerging gap that needs to be addressed in order to develop more meaningful ethical approaches to AI use and development. This paper offers a methodology-a 'shared fairness' approach-aimed at identifying AI practitioners' needs when it comes to confronting and resolving ethical challenges and to find a third space where their operational language can be married with …

Towards A Data-Driven Financial System: The Impact Of Covid-19, Nydia Remolina

Centre for AI & Data Governance

The COVID-19 outbreak has a growing impact on the global economy and the financial sector, which plays a critical role in mitigating the unprecedented macroeconomic and financial shock caused by the pandemic. Given the unprecedented nature of the current crisis, financial regulators and supervisors, central banks, along with governments and legislatures face challenges to maintain financial stability, preserve the well-functioning core markets, and ensure the flow of credit to the real economy. Even though the COVID-19 has slowed down our daily lives and stopped the operation of many industries, it did not have the same effect in the data-driven finance …

Busting Myths And Dispelling Doubts About Covid-19, Mark Findlay

Research Collection Yong Pung How School Of Law

The Centre for AI and Data Governance (CAIDG) at Singapore Management University (SMU) has embarked over past months on a programme of research designed to confront concerns about the pandemic and its control. Our interest is primarily directed to the ways in which AI-assisted technologies and mass data sharing have become a feature of pandemic control strategies. We want to know what impact these developments are having on community confidence and health safety. In developing this work, we have come across many myths that need busting.

Ethics, Ai, Mass Data And Pandemic Challenges: Responsible Data Use And Infrastructure Application For Surveillance And Pre-Emptive Tracing Post-Crisis, Mark Findlay, Jia Yuan Loke, Nydia Remolina Leon, Yum Yin, Benjamin (Tan Renyan) Tham

Research Collection Yong Pung How School Of Law

As the COVID-19 health pandemic rages governments and private companies across the globe are utilising AI-assisted surveillance, reporting, mapping and tracing technologies with the intention of slowing the spread of the virus. These technologies have the capacity to amass personal data and share for community control and citizen safety motivations that empower state agencies and inveigle citizen co-operation which could only be imagined outside such times of real and present danger. While not cavilling with the short-term necessity for these technologies and the data they control, process and share in the health regulation mission, this paper argues that this infrastructure …

Global Challenges And Regulatory Strategies To Fintech, Aurelio Gurrea-Martinez, Nydia Remolina

Centre for AI & Data Governance

The rise of new technologies has changed the operation, regulation and supervision of financial markets, bringing new challenges and opportunities for consumers, regulators, and financial institutions. This Article seeks to explore the most common regulatory strategies used by financial regulators around the world to address the challenges associated with the rise of fintech. These strategies include the imposition of bans, regulatory passivity, adoption of new legislation, permission on a case by case basis, and more interactive approaches such as innovation offices, accelerators and sandboxes. This Article argues that the adoption and desirability of each regulatory approach will depend on a …

Rules As Code: Seven Levels Of Digitisation, Meng Weng Wong

Research Collection Yong Pung How School Of Law

A guide intended to accelerate sensemaking in discussions involving Rules as Code. Without a common frame of reference, project stakeholders risk talking at cross purposes. Stakeholders contemplating a “digital transformation” project in the legal domain, such as a “Rules as Code” exercise or a RegTech / SupTech proof-of-concept, may find this document useful to agree on a common vocabulary to facilitate discussion and planning. To that end, this document classifies “digital transformation” of legal rules into a hierarchy of levels which can be included as terms of reference in planning discussions. While this document is informed by academic discourse, it …

Open Banking: Regulatory Challenges For A New Form Of Financial Intermediation In A Data-Driven World, Nydia Remolina

Centre for AI & Data Governance

Data has taken immense importance in the last years. Consider the amount of data that is being collected worldwide every day, industries are reshaping their activities into a data-driven business. The digital transformation of all industries, portent of the fourth industrial revolution, is creating a new kind of economy based on the datafication of almost any aspect of human social, political and economic activity as a result of the information generated by the numerous daily routines of digitally connected individuals and technology. The financial services industry is part of this trend. Embracing the digital revolution and creating the right foundations …

How To Address The Ai Governance Discussion? What Can We Learn From Singapore’S Ai Strategy?, Nydia Remolina Leon, Josephine Seah

Centre for AI & Data Governance

The following research piece explores how Singapore is addressing the AI Governance discussion. First, the document broadly provides some background to the Singapore’s AI strategy; second, it explains exactly what the Model AI Governance Framework is and how Singapore is addressing the AI Governance discussion; third, it compares Singapore’s approach with other jurisdictions’ and how important it is to contribute to the international debate on AI governance; and fourth, the document mentions some challenges ahead and observations on what is missing from current conversations about AI.