Covering Disruptive Technology Powering Business in The Digital Age

Written by: Bailey Martin, Tech Journalist, AOPG.

At the SAS Innovate Summit in Singapore, I met with Dr Steve Bennett, Senior Director of the Office of Public Readiness and Corporate Planning & Director of Public Sector and Financial Services Practice at SAS, who shared his expertise on government use of tech and emerging trends. Before making an impact in SAS, Dr Bennett had worked at Homeland Security in the US for nine years, leading divisions in risk analysis/assessment as well as bio-surveillance at the NBIC. He shared with me that he had opted to work in Homeland Security to do his part in protecting and benefitting civilians of the United States.

When joining SAS afterwards, he stated that he joined them for the same reason as he found that SAS aims to achieve the same benefits for people in both the private and public sectors on a global scale. Sharing this personal truth about himself was a nice illuminating moment to reflect on the standard of talented people that SAS attracts and not just focus only on the innovation they provide.

We jumped right into the hot questions soon after, and when asked how governments could foster collaboration between public and private sectors to drive innovation in technology initiatives, he shared:

“One of them is building consortia, creating environments where government and private sector entities can come together to discuss key issues. Initiatives like AI Verify here in Singapore, and many others in which SAS is involved, are important ways for the government and the private sector to collaborate. However, merely convening meetings isn’t sufficient; the actions that need to come from that should focus on data sharing.”

In addition to ‘consortia’ and ‘data sharing’ between governments and private entities being fundamental for governments to drive innovation from Artificial Intelligence (AI) initiatives—a third approach he mentioned was ‘co-development,’ stating:

“One of the interesting things about the private sector and government is they have very different incentives for why they do what they do. If you’re a private company, you have an incentive to innovate quickly, or your competitors will do it and put you out of business.”

Whereas with governments, according to Dr Bennett, “Government has the benefit of being able to take longer-term risks. They will invest in things that may take a long time to materialise.” So here we can see where co-development allows the public and private sectors to fill each other’s gaps. The private entities focus on driving quick breakthroughs while the public sector can afford to play the long game in innovation.

In nations around the globe (countries in ASEAN being no exception), there are concerns not just among private companies but also governmental bodies that look to adopt AI initiatives purely due to hype without proper in-depth understanding. This can lead to waste, bias, and even misuse of data. When tackling these problems, Dr Bennett shared other strategies and methods to avoid similar pitfalls. The mentioned mistake to avoid is to go about using AI purely thinking of the technology/innovation first. Instead, governments and other consumers of AI ought to focus first on the ‘issue’ they need a ‘solution’ for and then assess how to properly implement AI as a tool to address said issues.

The other tactic, or a better word might be ‘reality,’ is that governments need to be completely sure of the cultural acceptance of AI integration, which again comes from trust and transparency. Another key tactic is to ensure that humans are always kept in the loop, especially in decision-making processes.

Dr Bennett stated about the scenario of a public health department using AI, for example:

“You never want to make a decision to deny a claim just because ‘We love our model. We think our model is great,’ but you should always have a human in the loop. It [should be] the analyst at the National Health Authority that makes the decision. So, the system flags a claim, and the analyst looks at it and says, Okay, the system says these are the pieces of evidence that cause it to say this is likely fraudulent.”

So, from this example, we can take away that the idea is not to let AI take over like ‘autopilot’ but instead to be used by humans as an advanced tool to make decisions. This way, the users of AI can have AI analytics and data to learn more quickly and thus reach decision-making outcomes faster and more efficiently.

When it comes to government applications of tech and AI, Dr Bennett showed to be a wealth of insight and as a SAS executive displayed the traits of a passionate team member who strives for the betterment of the responsible usage of innovative technology. With other like-minded people at SAS, it’s no wonder the company is able to offer a wide range of analytics solutions involving AI in frameworks of LLM, Synthetic Data, and Digital Twins, all with considerations for safety and transparency.

(0)(0)