Executive Spotlight: Shamlan Siddiqi, CTO of NTT DATA’s Public Sector

Shamlan Siddiqi

Shamlan Siddiqi, chief technology officer of NTT DATA’s public sector division, recently spoke with ExecutiveBiz regarding the impact artificial intelligence is having on the U.S. government, the reason why there’s so much red tape in AI innovation, why attracting talent is such a challenge in today’s climate and how the government can implement emerging technology more effectively.

Looking at data as an asset is absolutely essential.”

ExecutiveBiz: Why is the government struggling to implement AI? Why is there so much red tape?

“The short answer is government, but there are a lot of different reasons. Talent shortage is a big challenge that always comes up. However, a lack of understanding of what AI is and how and when it can and should be applied is the biggest issue.

For those on the ground who are sustaining and maintaining large scale applications, introducing emerging technologies is usually not even on the radar – or at best an afterthought with very little clarity on how to apply it to gain meaningful benefits. In general, many aren’t fully aware or trained on the capabilities of artificial intelligence or the strategies to optimize AI across their IT landscape. For this reason, many don’t see it as an important facet for consideration.

Our government is planning and exploring the technology, but a lot of times they are working with very limited funds. There’s also the dynamic of how services are procured in federal government. On the positive side, we’re still ahead of most nations in regard to innovating and implementing AI.”

ExecutiveBiz: How can the government implement AI more effectively to overcome those obstacles?

“One of the questions we advise our customers on is why they want to implement AI. If they have a direct use case and the proper reasoning behind implementation, we also ask if they are ready for it. Readiness relies on whether they have sufficient data, strong data governance and the outcomes expected from AI.

Looking at data as an asset is absolutely essential. In most ways, it’s a precursor to applying AI properly because AI implementation only makes sense if you have enough data to back up your implementation efforts. It is often effective for governments to consider smaller proof of concepts, such as using chatbots integrated to citizen or employee facing services via portals, virtual cognitive agents for contact centers/service desks, or robotic process automation to streamline and automate key business processes, including reducing case backlog for Justice agencies.

At the end of the day, talent and education are very important as well. It is essential to improve the awareness of the power of AI, including the challenges, myths and realities, in order to have a firm grasp on all aspects of artificial intelligence and how to implement it.  Education has to start earlier with a stronger emphasis in schools, universities and the workplace on STEM education. Robotics competitions are a good start to this.”

ExecutiveBiz: Why has attracting and acquiring talent become such an issue for the government? What are the key barriers keeping some talent from working with the government?

“Personally, I’ve seen this issue evolve over the years from the government not being able to invest in and retain talent to implementing training programs and mentorship, as well as providing interesting and exciting initiatives for talent to work on. The real challenge is still attracting talent. We have seen agencies offer scholarships, pay tuition and essentially guarantee candidates a job as part of a conscious effort to attract talent.

The problem now is an engineer out of a top school would prefer to go to Facebook or Google because of the salaries and benefits. But it’s not just about money, because of the slow adoption of emerging technology within the government in general, it is difficult to hire top talent. Top talent often wants to work on emerging technologies, and those larger tech companies offer those opportunities more immediately.

I have to give credit where it’s due though. I’m seeing a new crop of talent emerging to support government initiatives across agencies, and the government has begun integrating AI based technologies, such as chatbots, RPA, and applied machine learning, into both greenfield development projects, as well as existing operations & maintenance and end-user services type areas. That’s a good start.”

ExecutiveBiz: What are some of the biggest leaps you’ve seen in AI innovation over the past few years?

“AI has made a big difference in healthcare. For instance, it used to take 10 years and hundreds of millions of dollars to discover and create new drugs/medications. Using AI like applied machine learning, we have seen drug discovery happen much more quickly. We’ve seen radical changes in capturing vital sign data and recording patient history, analyzing symptoms and recommending proper treatment, which is eliminating some bigger challenges in healthcare and changing the game altogether.

AI is also radically changing cybersecurity. Large credit card companies and banks are using AI to manage fraud detection. I know a company that’s saved tens of millions of dollars in fraud through the application of neural network technology. The list goes on and on, and AI isn’t showing any signs of slowing down.

Finally, the areas of Public Safety and National Security and Defense are seeing dramatic changes and improvements through the intelligent use of AI based technologies. We are now capable of predicting the possibility and magnitude of a crime in a city, while also reducing the time between incident awareness and emergency response to ensure public safety and “smarter cities.”

We are protecting borders by equipping agents with AI-driven dashboards to identify and capture multiple voices, translate those in real-time and provide predictive threat intelligence based on possible threat sentiments. This allows border agents to make more informed decisions while protecting the borders.

Innovative use cases for AI will continue to progress rapidly in the coming years, and government agencies need to actively explore opportunities to integrate AI to achieve their missions.”

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