FDU-SMU Forum on AI, Digital Governance, and Sustainable Societies: What Executives Need to Know
On 29 September in Singapore, Fudan University (FDU) and Singapore Management University (SMU) closed a high-level forum that brought together scholars and industry leaders from China, Singapore, Germany and beyond. The agenda was direct: how to develop, govern, and apply AI responsibly while reinforcing social resilience and long-term value creation.
Participants agreed that AI has moved from a technical topic to a societal force that affects how we live, work, and govern. The call to action was clear-countries and institutions should collaborate to build a trustworthy, cooperative, and mutually beneficial global AI governance system.
Why this matters for executives
- AI governance is now a strategic capability, not a compliance checkbox. Safety, fairness, and transparency need to be designed into products, policies, and metrics.
- Cross-disciplinary methods and data-sharing agreements will separate leaders from laggards. Collaboration beats siloed innovation.
- Legitimacy is a prerequisite for scale. Without public trust and participation, even accurate systems will stall in the market or at the regulator's desk.
- Leadership profiles are changing. Leaders must blend systems thinking with technical fluency and set clear guardrails for ethical growth.
Keynotes: Practical ideas you can apply
Prof FU Xiaoming showed how AI can surface social mobility patterns from vast historical records by combining prosopography and machine learning. Insight: data-driven historical analysis can inform policy design in today's digital society, offering templates for institutional reforms and equity-focused interventions.
Assoc Prof ZHU Feida outlined "collaborative intelligence" and a tokenized economy as tools for sustainable digital ecosystems. He emphasized quantifying data contributions, fair profit-sharing, and energy-efficient decentralized infrastructure-backed by case studies that move firms from isolated pilots to shared growth models.
Assoc Prof Gilad Abiri argued that the central issue is AI legitimacy, not just alignment. Two blockers-black-box decisions and lack of community ownership-can be addressed through legible procedures and participatory design, creating the foundation for international cooperation.
Prof LI Qiang detailed China's response to fast population ageing, highlighting LLM voice assistants, intelligent monitoring, and telemedicine for elderly care. The takeaway: policy support combined with enterprise innovation can scale digital services while narrowing the digital divide.
Panel takeaways for policy and growth
Panel 1: AI × Governance-Co-evolution, tensions, and synergies underscored that technology and rules influence each other. Lessons from internet-era policies like Section 230 show that growth without accountability creates new risks, from disinformation to weak responsibility models.
- Blend law, ethics, and technology; avoid binary "regulate or not" thinking.
- Use technical tools-differential privacy, distributed computing-to align data protection with social value.
- Operationalize "tech for good" through cross-border and cross-discipline programs, not slogans.
Panel 2: AI-ready leadership-business models, talent, and value creation focused on the leader's new job description. AI pushes firms from linear scaling to intelligence-led systems that demand speed, clarity, and measurable outcomes.
- Leaders need both breadth and depth: transfer knowledge across domains while understanding model behavior, data risk, and integration costs.
- Build human-machine collaboration skills and systems thinking into core leadership development.
- Balance innovation with ethics and security across AI, blockchain, and data tooling to protect trust and margins.
Institutional momentum
Fudan University President JIN Li and SMU President Lily KONG signed a Memorandum of Agreement, witnessed by Fudan Vice President CHEN Zhimin. The partnership will advance AI governance, computational social science, urban sustainability, and ageing societies, converting bilateral collaboration into a wider network with real-world application.
Action list for executive teams
- Establish an AI legitimacy plan: make decision processes explainable, publish model governance procedures, and include community or user participation where material.
- Quantify contributions: track data, model, and compute inputs; align incentives for internal teams and external partners with fair value-sharing.
- Adopt privacy-first data architectures: apply differential privacy and federated or distributed approaches where centralization raises risk.
- Build AI-ready leadership: upskill senior managers on systems thinking, prompt literacy, risk controls, and AI product economics.
- Pilot collaborative intelligence: join or form cross-industry consortia to share non-sensitive data, benchmarks, and evaluation methods.
Resources
- OECD AI Principles for a widely recognized policy baseline.
- AI programs by job role to upskill leadership and functional teams.
Looking ahead
The forum adds weight to Asia's contribution to global AI discourse and to practical governance models that deliver safety, inclusion, and long-term impact. Expect deeper cross-sector projects from FDU and SMU that convert research into deployable solutions.
Contact
Singapore Management University (SMU)
sai.yang@jeffery.asia
+86 13810515693
https://www.smu.edu.sg
Source: Newsfile
