Experts weigh in on AI and big data — hype or hope?

TL:DR: Society is generating ever-larger datasets through the use of connected devices. Artificial intelligence (AI) is thus becoming an important analytical tool for organisations to better understand their client base. Operational objectives aside, the societal impact of AI must also be considered, said speakers at the Big Data & AI 2018 conference.

The world is awash with data—some 2.5 quintillion bytes of it, generated every day. Each click, tap and swipe on a smartphone screen generates a data point, and every surveillance camera and sensor adds to an already burgeoning library of digital information. Big data looks set to get even bigger in the years ahead, making the case for artificial intelligence (AI) to take on an even bigger role in industry and society.

At the Big Data & AI Asia 2018 conference, a panel of experts convened to discuss the question, “How will big data and AI shape up in 2019?”. Moderated by Mr Graham Brown, chairman of Asia Tech Podcast, the panel comprised Mr Devadas Krishnadas, CEO, Future-Moves Group; Dr Cao Hong, head of data science, Ernst & Young; Mr Johnson Poh, head of data science, DBS Bank; Mr Sanjay Bakshi, head of digital transformation and ventures, Shell; Mr Victor Tay, managing partner, Stout (Asia) Advisory Limited; and Mr Vivek Kumar, director, National Trades Union Congress, Singapore.

Keeping an eye on the prize

Like the flavours of ice cream, AI solutions come in a variety of forms, and this diversity is likely to increase in the year ahead. However, Mr Tay noted that many AI applications are “solutions looking for problems”, suggesting that their practical use cases have yet to be identified. Despite this, the hype surrounding AI is tremendous. “Between 2014 and 2016 alone, we saw a 400 percent growth in valuation in the [AI and big data] space,” he said.

Agreeing with Mr Tay, Mr Bakshi added that it is easy to become distracted in this time of optimistic innovation. Business leaders must therefore constantly ask themselves: “Just because other companies are doing things in a certain way, does it mean that their approach is relevant to me?” he said.

Given the lack of a one-size-fits-all solution, Dr Cao recommended that business leaders clearly define the tangible outcomes that they want to achieve with AI and big data. This could help them come up with better roadmaps for the adoption of emerging technologies.

Shaping the future of technology

While there is no denying that AI and big data can help governments and businesses derive economic benefits, the impact on the labour market must also be considered. Mr Kumar emphasised that AI, being a tool of the fourth industrial revolution, must be wielded by the “worker 4.0”. This means that upskilling and retraining will be necessary.

The notion of worker empowerment struck a chord with Mr Poh, who proposed an alternative strategy for narrowing the skills gap—make AI analytics tools easy to use. “We [DBS] take a very product-centric view of the entire data and AI process… [We strive to create] products and platforms to empower employees, whether they be data scientists or business analysts, to build and test their own data models.”

Finally, there is a need for regulation to keep pace with innovation. Although this task is often left to the government, Mr Krishnadas called for industry players and citizens to participate in shaping legislation pertaining to AI and big data.

“Your data and behaviour are helping to create the conditions of technology that then become the conditions for humanity. I think its important that we ask ourselves what needs to change on the structural and institutional side to accommodate, in a more responsible and stable way, the changes that technology will bring,” he said.