In recent years, the rapid advancement of Large Language Models (LLMs) has driven significant progress in Generative Artificial Intelligence (GAI). By emulating human language capabilities, GAI has unlocked a multitude of applications, ranging from chatbots and virtual assistants to translation services and content-generation tools. However, GAI has evolved into a double-edged sword, giving rise to ethical concerns surrounding transparency, privacy protection, misinformation, bias and fairness, job displacement, and environmental impact.
In this project, the team aims to quantify and validate firms' ethical awareness of GAI and employ econometrics models and quasi-experiments to comprehend its determinants and document consequences. Through these efforts, the project makes a distinctive contribution to the promising trajectory of developing responsible and ethical GAI systems in business, ultimately fostering a sustainable society.
The research aims to leverage modern Large Language Models (such as ChatGPT) to augment scientific practices for causal inference. Consumer behavior plays a critical role in shaping the economy, yet it is dynamically evolving and difficult to predict. The project seeks to equip social scientists with cutting-edge AI-based toolkits to enhance the study of consumer behavior in today's rapidly changing marketplaces, thereby improving understanding for researchers, businesses, and policymakers.
This research investigates the role of AI in enhancing human creativity across three stages: idea generation, idea selection, and idea evaluation. It aims to better understand how collaboration between humans and AI can improve creativity by increasing the quantity and diversity of ideas and reducing the time required for creative tasks. The study will also examine if AI offers greater creative advantages to women and individuals in rule-abiding societies who face constraints due to social norms.
Despite the increased importance of environmental issues for firms, environmental compliance costs are high because of an inefficient and ineffective regulatory system, compounded by the reluctance of businesses to act proactively. Although many firms often recognize the costs of environmental issues for external stakeholders, they may overlook the impact of these issues on internal operations. This project investigates how a firm’s environmental performance impacts its approach toward human capital, including information management, employee retention, recruitment, and talent quality. Additionally, it aims to examine the potential negative externalities of corporate environmental incidents on the information environment in labor markets.
High frequency financial data provides useful real time information about the global economy, represented by stocks, bonds, futures, derivatives, exchange rates, and crypto currencies. Such information is important not only for institutional investors and regulators, but also for ordinary citizens who participates in financial markets. This project aims to develop new econometric methods to optimally extract information from high frequency financial data and investigate how to conduct robust statistical inference concerning economic hypotheses.
Climate change is an increasingly urgent and existential crisis that threatens all sectors of society in all countries of Southeast Asia. The Climate Transformation Programme aims to develop, inspire and accelerate knowledge-based solutions and educate future leaders to establish the stable climate and environment necessary for resilient, just, and sustainable Southeast Asian societies. CTP will generate knowledge and innovation across disciplines including climate and Earth science, ecology, materials science, artificial intelligence, humanities, social sciences and the arts, finance, health, and engineering. It will also translate state-of-the-art scientific results into real world solutions for Singapore, and it will transfer these solutions to Southeast Asia and beyond.
CTP will help to better understand exactly how the climate is changing; to identify and develop ways to contribute to global climate change mitigation efforts; to better assess the environmental, social, and economic risks from climate change; and to design effective solutions to control, reduce and adapt to these risks.
To achieve these multiple objectives, CTP will integrate a matrix of six strategic clusters of research and three cross-cutting themes, where Sonny Rosenthal will participate in and contribute to Cross Cutting Theme 1: Sustainable societies.
(Cross Cutting Theme 1: Sustainable societies will leverage climate research in communication, public opinion and psychology, and artistic impressions to shape public attitudes and behaviours.)
The project aims to enhance the understanding of the legal and economic aspects of sustainability-related trade, investment, and financial relations between the Association of Southeast Asian Nations (ASEAN) countries and Taiwan.
Through this project, the team will investigate the relationship between the extent of use of technology by Singapore- and Australia-based accountants and their work productivity. In examining the relationship, the team will focus on two causal mechanisms: (1) technology distracting accountants from their core tasks and (2) the over-dependence on technology by accountants.
This research seeks to investigate cultural factors that shape people’s tendency to engage in zero-sum thinking. Uncovering novel antecedents of zero-sum thinking is not only theoretically important but can also help generate interventions to temporarily lower zero-sum thinking when cooperation is vital.
This research project aims to study the working preferences of older Singaporeans and understand their perceptions towards upskilling, reskilling and the types of employment that may be meaningful for them. The results from this research are expected to shed insights and inform the design of a jobs-skills-learning recommender, the SkillsFuture Career Transition Programme (SCTP) and other services and facilities catered to older adults’ needs.
