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Chng Kai Fong, Second Permanent Secretary of the Smart Nation and Digital Government Group (SNDGG) gave the opening address at the STACK-X Data Science Conference in Singapore today (July 7).

The conference is STACK-X Community’s flagship tech and largest government-led conference, with the aim of bringing together like-minded individuals who share a passion for exploring innovative ways of using Tech for Public Good.

STACK-X Community was conceived in 2019 by GovTech, a governmental agency that spearheads Singapore’s digital government transformation, and a key contributor to the Smart Nation vision. 

Chng was joined by other government and industry speakers to share more on the theme of using data science and artificial intelligence (AI).

Specifically, they discussed how the Singapore government is partnering with various industries to democratise the use of data for public good through the use of data infrastructure, engineering capabilities, and more that they have developed in accordance with data governance policies.

Harnessing the power of AI

stack x data science connect govtech
Image Credit: Screenshot by Vulcan Post

During his opening speech, Chng acknowledges that “the power of AI is in its ability to continuously improve with more data exceeding human performance,” citing huge advances in consumer internet and fintech as examples. 

[T]his power will soon expand to more domains. As we capture more data, as more data becomes digitised, AI will know us better than we know ourselves. It’s going to change how we work differently. So in government, we all better get up to speed.

– Chng Kai Fong, Second Permanent Secretary of SNDGG

He adds that data science and AI must be taken advantage of by having them integrated into our work such as changing how policies are made, how operations are done, and how services are delivered.

In fact, some agencies have already started doing so, like how National Environment Agency (NEA) works with GovTech in using AI to identify mosquito species, or how the Ministry of Manpower (MOM) uses AI to improve bomb searches.

He went on to further outline three ways in which this use of data and AI in government can be scaled up: getting the data right, building capability and capacity, and working with people both across and outside of the government. 

1. Getting the data right

To get the data right, Chng shares that it can be done through government data architecture (GTA) since the quality of the data set comes before AI. 

He reminisces about the time in which data was only available months after request, in PDF format. Now with GTA, he highlights that retrieving data only takes seven working days for 99 per cent of data requests within the government.

Furthermore, there are now tools like Vault which enhances the discoverability of data, and analytics.gov to enable public servants to better analyse data. 

“But we still have a long way to go and we can still do better. We should be capturing more data. We should be sharing it more real time. We also have to take into account data security [and] data privacy,” he emphasises.

2. Building capability and capacity

Chng Kai Fong sndgg
Image Credit: Screenshot by Vulcan Post

Taking in consideration today’s context, Chng highlights how there are playbooks and guides to aid in levelling up at a central level, as well as bootcamps and courses to give agencies a boost. 

However, despite embedding data science officers from GovTech in agencies working alongside policymakers, Chng reveals that “not enough of us are using data to make decisions.”

[W]hen I was at EDB (Economic Development Board), we had an extensive data-driven decision making exercise. In fact, we put all data on Tableau — a dashboard — and we try to incorporate it in our decision-making process.

But when I asked the staff for statistics on how often the dashboards are used, the staff sheepishly told me: ‘Oh, only once a year’. So I think we all have a long way to go.

– Chng Kai Fong, Second Permanent Secretary of SNDGG

He stresses that this capability and capacity to fully make use of data frequently has to be an occurrence within the whole organisation, and become a “leadership priority.”

3. Working with people in and out of government

Chng highlights that “the public sector does not have all the answers of expertise”, and that scaling up data science and AI requires working with others.  

He suggests that those in the government sector have to work with others better, not just across government, but also with those outside of the government. 

“[W]e have to build into our system the culture of working together with others outside,” he says. This means building relations with others and being more confident and open and publishing more data. 

I think the right framework is to enable public data to be shared and fused with private datasets, while ensuring that we have security and privacy and actually a proactive approach in working on projects together.

– Chng Kai Fong, Second Permanent Secretary of the Smart Nation and Digital Government Group (SNDGG)

He concludes his opening remarks by linking back to the purpose of the STACK-X conference, which is to facilitate this very behaviour of working together, learning from each others’ expertise, and enabling the exchange between the public and private sector.

“Let us explore possibilities,” he sums up.

Featured Image Credit: Screenshot by Vulcan Post

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