On the Saturday morning of December 7, AI Singapore joined a few other AI communities across the Pacific Rim to discuss a number of topics within the complex subject of AI ethics with thought leader Andrew Ng. Connected via video conferencing, we got to hear about Andrew’s views directly from him on this increasingly important area within the unfolding narrative of AI’s permeation into our everyday lives.

Organised by deeplearning.ai, the AI teaching project founded by Andrew, communities in Hong Kong, Tokyo, Manila and Singapore discussed within their own locations specific topics relevant to AI ethics before coming together to share their insights. For Singapore, we dived into how we can ensure that the AI systems that we develop promote the well-being of humans.

Since AI Singapore was established 2 years ago, we have grown to an engineering strength of about 70 and have worked on close to 40 projects (known as 100Es) from start-ups to MNCs, both private and public, across various verticals like healthcare, finance, engineering, IT and media. In each and every project we handled, we have always been mindful of not just the business benefits to organisations, but also the wider impact on individuals and society which AI potentially has.

With the experience accumulated from building AI systems across many domains, we have produced an internal document titled “AI Ethics & Governance Protocols”. Among the 12 protocols defined in the document, our AI engineers have chosen the top 3 to share with Andrew and the global community. Read more about them below.

Personal Privacy

Protection of data containing personal attributes is of utmost importance in any project. Many models we create draw upon such data, from models in healthcare to finance. As we work with organisations, we often have to play the role of gatekeepers to ensure that data provided by them is properly anonymised and does not contain personally identifiable information.

Creativity and Intellect

AI systems are built from many simpler parts, very often from open source code. While much attention is focused on the consumers of AI systems, we believe that producers of such systems, directly or indirectly, should not be neglected. It is important to acknowledge their contributions and respect their terms and conditions. This will encourage greater creativity in the AI ecosystem and by extension greater good in what AI can bring.

Data Integrity and Inclusiveness

Training datasets should be sufficient in amount, unbiased, labelled, machine readable and accessible to a reasonable degree. The benefits of AI should also not favour or disadvantage any group of individuals. This is especially so in Singapore where we have a very diverse population. Datasets should be rigorously questioned for representativeness and biases. For example, we have developed wound diagnosis models and being able to classify wounds across different racial types with equal accuracy has always been a target of the highest priority.

AI Singapore is pleased to have been able to do our part to contribute to the ongoing conversation on AI ethics at a global level. A common lament about the event is that it was too short and we had to end the discussions on time. However, hearing from Andrew was an unforgettable experience and we are also gratified to know that other AI communities in the world are very much involved in this subject. This certainly bodes well for our AI-driven future. You can read more about the event on deeplearning.ai’s blog here.