AI technology

[dropcap size=small]“F[/dropcap]or the first time in the history of humankind, we have machines doing brain, not brawn,” says Drew Perez, managing director of Adatos A.I., a Singapore-based artificial intelligence start-up. From virtual assistants such as Amazon’s Alexa to Netflix – which serves up films a viewer might enjoy based on his/her viewing history – applications of artificial intelligence technologies have become commonplace in our daily lives. And that’s set to grow. Research firm IDC predicts that the Asia-Pacific AI market alone will expand at a compound annual growth rate of 63.9 per cent between 2015 and 2020.

Perez was one of three panellists speaking at the inaugural edition of Great Minds at The Great Room, a talk series jointly presented by The Peak and co-working space The Great Room. The discussion titled “How to be a Futurist: Connecting the Dots of Current Trends” was moderated by Rosalind Tan, director of operations of Adatos A.I. and saw Perez joined by Vinnie Lauria, founding partner of venture capital firm Golden Gate Ventures, and Violet Lim, CEO and co-founder of dating company Viola.AI and Lunch Actually Group.

For Lauria, whose firm focuses on investing in South-east Asian start- ups, his considerations when it comes to backing companies in the AI space include “identifying the scope of the problem, opportunity and scale of the market, and whether the technology behind it is sophisticated enough to solve the problem”.

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These opportunities, it seems, present themselves even in the most unlikely industries. Take Lim’s dating company, which leverages blockchain – a digital ledger in which transactions are recorded – technology to distinguish between authentic and fraudulent dating profiles. In an industry where online love scams amount to billion-dollar businesses, the currency of trust is one that’s not traded loosely. “These scammers steal random photos o the Internet, put them on dating sites or mobile dating apps, and pretend to be that person. Once they gain the trust of a victim, they start asking for money. With blockchain, we are able to create real ID verification. New applicants have to take a real-time video scan of themselves which we use to match with photos he/she is providing us. We will also ask for access to his/her social media accounts to verify his/her identify,” says Lim. This information is hedged onto an individual’s blockchain, which cannot be altered or duplicated.

While AI has the potential to solve problems across diverse industries, the biggest resistance to its commercial adoption is its perceived threat to the labour market, says Perez. “The technology for autonomous vehicles has worked for years. But why isn’t it out there on the roads? Because we have to wait for regulatory bodies to clear it. Why? Because it takes jobs away. We have the same challenge when it comes to medical imaging, where AI capabilities can read six X-rays per second and do so seven times more accurately than a National Institute of Health radiologist.”

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For Perez, the inability of regulatory frameworks to keep pace with innovations in AI has put mankind at the forefront of an ethical dilemma. “I would liken AI to a gun. It is just a machine. How it’s eventually used is up to the human. At this point in time, I’m limited only by my own moral compass as to how I apply AI to business cases.”

“I would liken AI to a gun. It is just a machine. How it’s eventually used is up to the human.”


For the former US intelligence officer, the lack of regulation in industries presents growth opportunities. To this end, his firm has ventured into precision agriculture, which involves the use of AI and machine learning to analyse geospatial images of land to determine potential for yield of various crops.

“Agriculture is one of the most inefficient industries you can imagine. It hasn’t changed for a hundred thousand years. But the gains are huge. It makes banking look like a convenience store. That’s why we navigate there.” While operating in grey areas are a savvy move for those in the know, the ability of companies to hijack technology for questionable means is a growing concern highlighted by Lim. “Like it or not, there’s a lot of data out there and there are people who might use it for intentions that might not be good,” she says, drawing attention to how Facebook’s algorithms affected polling outcomes at the last US election.

“Like it or not, there’s a lot of data out there and there are people who might use it for intentions that might not be good.”


The gravity of the situation is not lost on those operating in the space. At last year’s Beneficial AI conference in Boston, business leaders and technologists, including the likes of the late physicist Stephen Hawking and Tesla’s Elon Musk, drew up 23 guiding principles regarding the development of AI research, urging the creation of “beneficial intelligence” and strict control measures when it comes to self-replicating AI systems.

For Lauria, these discussions are a timely response: “I’m glad that this group of very smart people – who have a consortium of influence across the space – get together once a year to hash out some of these moral dilemmas.”