HKUST Business School Magazine

Biz@HKUST Biz@HKUST 24 25 // Cover // Thought Leader An Ethical and Responsible Culture “HKUST postgraduate students have attended workshops virtually with global leaders to develop data governance guidelines,” Tam says. “These efforts are further supplemented by an increased focus on developing an ethical and responsible culture of technology use, and a focus on training for industry professionals, teams and larger organizations.” Tam recounts that when she opened discussions with the team at Stanford University at the beginning of the project, they were keen to have Hong Kong students participate in the joint research. Since then, students from HKUST have been part of an international group working with international banks to identify and discuss possible ethical dilemmas that could arise from the use of technology in the financial sector and other industries. Taking part in this project is important for students as technology is now an integral part of people’s lives. Those in the workplace must have the skills to balance monetizing data to achieve more value-added services with a duty to protect customers’ data. “How can banks ethically monetize customers’ data to provide value-added services while upholding customers’ best interests? That is a dilemma,” she says. The Risks of AI Tam explains in some parts of the world, such as Europe, there are already laws to regulate how banks can share customers’ data while seeking to innovate. “Banks and insurance companies in Hong Kong can develop their strategy freely to cope with this dilemma,” she says. “So far, most Hong Kong regulations are ‘technology-neutral’, which means that the current laws have not addressed risks which are specific to the use of AI.” There may be risks arising from the use of AI. For instance, the use of some algorithms may result in unfair or biased decisions. If AI is used to screen out candidates in an unfair manner, it may be difficult for a person to be held accountable for the discriminatory decision. “Should the programmer, the HR department, or the AI be accountable for that decision?” Tam says. Keeping AI Honest Frankie TAM is an international technology lawyer and is on the advisory board of Stanford University’s Responsible Digital Leadership Project. This project aims to identify global ethical dilemmas related to the use of technology. She serves as a bridge between Stanford and HKUST - the only Hong Kong university that is taking part in the Project - in contributing to this meaningful international study of data ethics. Frankie Tam, an international technology lawyer at Eversheds Sutherland who also teaches regtech and fintech programs for postgraduate degrees, is confident that data is the “new oil”. Data is a valuable asset for any organization, she says, adding that it is important to put best practices in place to guide responsible innovation. Tam has been a staunch advocate for HKUST’s acceptance of an advisory role on the board of the Responsible Digital Leadership Project – a global project launched by Stanford University - that helps to identify ethical dilemmas related to the use of technology and the processing of data in financial organizations. “I am delighted to serve as a bridge between the two universities in organizing the meaningful international study of data ethics in our increasingly digital world,” she says. “I’ve had the opportunity to share my views from a practitioner’s perspective with leading scholars and outstanding students.” The project aims to build a “library” of ethical dilemmas which relate to the use of technology in the financial sector. It is a joint effort conducted by around 70 postgraduate students from more than 26 top universities around the world. HKUST is the only Hong Kong university that is taking part in the project. Student Voices HKUST students share their experiences of participating in the Responsible Digital Leadership Project. CHEN Xin MSc in Business Analytics As soon as I understood what the organizer was trying to achieve through ‘collecting ideas from people from all fields globally’, I felt really connected. This multidisciplinary project was a huge magnet for me when I saw it for the first time. This project stirred my interest in areas such as education, Chinese classics, and even philosophy. It encouraged me to think about why there are issues and dilemmas between financial technology and climate change. I firmly believe that this is now a future development plan. The contradictory positions between eco and econ is another important matter. Now I have a stronger responsibility towards something bigger. I feel that while technological development is crucial and fundamental, if it is guided by good will and fortitude, this seemingly ‘heartless’, data-driven process can lead to harmony and world peace. This experience has helped me understand that my routine daily work can be a building block that leads to world peace in the future. Ezekiel CHIM MBA I believe that we are now at one of the most critical times in our history where we are striving for a better society with technological advancements. Since the latest emerging technologies are so powerful and revolutionary, we must maintain a proper balance between ethics and fairness and the benefits of technology, and make sure we are not leaving any minorities behind. As an industry practitioner, I can’t wait to be part of this vital stage, and to define the framework and approach to identifying and proposing solutions to the ethical dilemmas that arise when using these emerging technologies. One of the biggest challenges that we have observed is the difficulty in justifying why something could be correct. For example, in one of our studies, we saw that geographic data was used to calculate lending risks, but this could be unfair and biased against those who have negative geographic data but good credit history. If historical data shows that people who live in ‘City A’ have a higher chance of defaulting, and banks therefore reduce the lending or impose a higher interest rate, is this an ethical way of classification? What if AI is doing the classification instead of humans? By listening to the views of consumers, industry professionals, financial institutions, regulators, and researchers, we are learning how to define these dilemmas and make proposals.