SMU’s Centre for AI and Data Governance releases pilot perceptions study on Singapore’s AI innovation and IP law regime

Research project seeks to understand the needs of Singapore’s innovation community; findings will contribute to Singapore’s IP Strategy 2030

Singapore, 4 October 2022 (Tuesday) – The Centre for AI and Data Governance (CAIDG) at Singapore Management University (SMU) Yong Pung How School of Law has released the findings of a first-ever perceptions study on the Artificial Intelligence (AI) innovation and Intellectual Property (IP) law regime in Singapore. Titled ‘Conversations at the IP and AI Interface’, the four-week study was commissioned by the Intellectual Property Office of Singapore (IPOS) and the Info-communications Media Development Authority of Singapore (IMDA) with an aim to understand the perceptions of key stakeholders in Singapore concerning regulatory stimulation at the IP/AI interface.

The National AI Strategy launched in 2019 recognises top-class IP regime as a critical enabler of AI innovation as it allows innovators and creators to protect their competitive advantage, and maximise returns from their investments. It underscores the need to understand the perceptions and regulatory needs of the local innovation community, and consequently the role that regulators may play to support the commercialisation and sustainability of AI innovation.      

Adopting a conversational focus group methodology[1] that promotes a natural, free-flowing dialogue rather than a rigid, formal Q&A exchange between participants, the CAIDG research team organised four focus group discussions with four groups of key stakeholders representative of the AI ecosystem in Singapore, to draw understandings from their complex personal experiences, beliefs, perceptions, and attitudes towards the role of IP and data in incentivising AI research and investment.

A total of 27 participants from 24 organisations representing the following stakeholder groups participated in CAIDG’s focus group sessions held between April and May 2021: 1. AI practitioners; 2. In-house counsel of organisations utilising AI; 3. Legal practitioners from law firms dealing with IP and AI technologies; and 4. Policymakers from ministries, statutory boards and industry associations involved in IP regulations or enforcement.

The key findings of the study are:

1. There are barriers to communicating the potentials of IP protection

The discussions revealed how AI practitioners may be less convinced that patents are helpful, preferring open access to knowledge over knowledge protection. While policymakers believe that IP rights should serve as “rewards” for innovators’ efforts, they are unsure about the degree of protection they should endorse for AI-related patents to be profitable and to also enable innovation, signalling some extent of shared uncertainty between AI experts and policymakers regarding patenting AI.

2. Some misunderstandings between AI practitioners and IP lawyers prevail

Some tensions were apparent between IP lawyers and AI practitioners. IP lawyers seem to perceive that AI practitioners, working across multiple projects at a time, do not have the time and patience to articulate their inventions in the IP filing process. AI practitioners, on the other hand, felt that lawyers may lack the technical foundations and have problems understanding their technology which makes the whole process of filing IP cumbersome for them.

3. Singapore continues to be attractive as an innovation hub

While AI practitioners felt that there is a need for clearer and more consolidated guidance on data availability and data use restrictions to drive AI innovation, there is consensus that as an innovation hub, Singapore has a good ecosystem in place with well-measured policies and attractive incentives and grants.


IPOS recognises the importance of understanding the local AI innovation landscape, and the role that regulators may play to support AI innovation. They affirmed that this study is an important first step in the conversation amongst policymakers, AI practitioners, and other key stakeholders on the balance between protecting innovation outcomes and facilitating open access, so as to support and enable AI innovation.

Professor Mark Findlay, Director of SMU CAIDG, said, “Innovation is something that should be rewarding but it is also something that should rely on access to knowledge and new ideas. Our study highlights the areas in which communication has been challenging, how it can be more effective, and provides some insight into the way forward. We are glad that the findings of our study will contribute towards the Singapore IP Strategy 2030. This ties in with CAIDG’s objectives of conducting research on contemporary challenges in the regulatory governance of AI and big data, and fostering conversations between community, government and industry, to establish Singapore as a global leader for AI and data use.”

The executive summary and full report can be found here.

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[1] This method was adapted from CAIDG’s Ethics Hub workshopping methodology (See: AI Ethics Hub 4 Asia | Centre for AI & Data Governance ( This method is preferred when the research seeks experiential opinions rather than definitive conclusions.