When it comes to artificial intelligence (AI) roadmaps and governance frameworks, ASEAN countries (and ASEAN itself) have adopted globally best-of-breed, forward-leaning approaches to AI.
This is according to Stephen Braim, Vice President of Government and Regulatory Affairs at IBM Asia-Pacific (left in pic), who explained that “ASEAN is going in a different direction that’s much more about promoting AI, promoting innovation and regulating risk – these attributes are set to give the region a competitive advantage.”
This comes as ASEAN governments use AI as the underpinnings for their government digital transformation platforms, Braim added.
“If we look at ASEAN demographically, it’s unique in the world in the sense that you’ve got very young populations; you’ve got an average age of the population somewhere around 24-25 in Thailand, the Philippines, and Indonesia. You’ve also got high IT adoption, so you’ve got a young population that’s very tech-savvy. Some of them are using AI now on their phones. In all of these countries, you’ve got a very strong innovation focus and a very strong local community of IT innovators.”
AI in ASEAN is a huge productivity driver for economic growth, Braim added. “ASEAN is wedged between China and India and Japan; it really does have this economic opportunity and economic competitive priority to keep growing. Proper deployment and support for AI in ASEAN economies is very much a ticket to global economic competitiveness, with the potential to transform service delivery, health, education, government services, tourism, banking, etc.”
He said this during an IBM media roundtable held yesterday entitled “AI Masterclass: Future of Responsible AI & Governance in ASEAN”, where he was both a session speaker and a panel moderator.
Featuring opening remarks from Catherine Lian, General Manager & Technology Leader at IBM ASEAN (centre in pic), the roundtable also hosted speaker Christina Montgomery, Vice President and Chief Privacy & Trust Officer at IBM (right in pic) and Braim.
The panellists were Lee Wan Sie, Director of Development of Data-Driven Tech at Singapore’s Infocomm Media Development Authority; Dedy Permadi, Digital Policy Advisor to Indonesia’s Minister of ICT; and Purushothama Shenoy, Chief Technical Officer and APAC Ecosystem Technical Leader at IBM.
In her opening remarks, Lian shared several salient statistics about the usage of AI, especially generative AI, both globally as well as regionally in ASEAN.
“Gartner has predicted that the market for AI software will reach almost $134 billion by 2025. As one of the most transformative technologies of our time, AI is projected to unlock an outstanding value of 16 trillion by 2030 according to PwC. Additionally, according to IDC surveys, at least a quarter of the G2000 companies are crediting their AI capabilities with the contribution of more than 5% of their earnings, and half of the G2000 firms plan to expand AI spending as a strategic imperative. In recent research by IDC, by 2028, 80% of the CIOs will leverage organisation changes to harness AI, automation, and analytics to drive agile, insight-driven digital businesses.”
Touching on the AI landscape in ASEAN, Lian stated that IBM believes that generative AI market is expected to drive significant growth in ASEAN in the coming years, with a forecasted CAGR of 24.4% from 2023 to 2030.
“According to the Oxford insights, Malaysia, Singapore, Thailand, Indonesia, Vietnam, and the Philippines, which represent the ASEAN-6 countries that IBM is pivoting towards, are above the global average in terms of government AI-readiness. In fact, East Asia has the highest range of scores in government AI readiness in 2023.”
Lian cautioned that without a responsible AI and AI governance framework, companies will not be able to adopt AI at scale.
“According to IDC’s CEO Sentiments Survey, the top 3 concerns among C-suite executives were in digital skills, the lack of line-of-business trust in IT, and the lack of digital business know-how of C-suite executives. Similarly, according to the AI adoption index, data privacy concerns (57%) and trust/transparency concerns (43%) are the biggest inhibitors of generative AI, according to AI professionals at large organisations not exploring or implementing generative AI. Minimising bias (87%), maintaining brand integrity and customer’s trust (85%), and meeting regulatory obligations (81%) are considered the most important aspects of building a trusted AI .”
IBM has been working with both government and business clients on the matter of fostering trust in AI, through policy recommendations and putting together its own AI programmes according to clear ethical guidelines as ‘client zero’, which it then builds into product offerings for its clients.
Montgomery outlined IBM’s three-fold policy approach.
“We have a policy point of view we’ve been articulating for over 4 years now, which is to regulate the risk associated with AI in deployment and in context, not the technology itself; to hold creators and deployers of AI accountable, not immune to liability; and to support an open innovation regime, not a licensing regime. And we believe in this role, governments and businesses both have roles to play. Governments have to reinforce trust through AI regulation that’s risk-based, prioritising liability over licensing, and supporting open innovation, and companies need to adopt responsible AI practices internally.”
IBM’s ethics around AI involves a multidisciplinary multi-dimensional approach built around a set of principles, Montgomery explained.
“The purpose of AI is to augment, not replace human intelligence; the data and their insights belong to our clients. That’s our business model. We don’t train our AI on client data unless the clients are asking us to do that for them. New technology has to be transparent and explainable. And we have these pillars of trust, and these principles and pillars of trust are at work throughout our entire business. We take this and we build organisational governance around these principles in a multi-layered structure, at the centre of which is our AI Ethics Board, which comprises a diverse set of stakeholders from across the company.”
IBM has been focusing – initially, at least – on three high-impact use cases as starting points for generative AI, where it thinks that will bring the most benefits to the company and its business clients.
“These areas are, in talent, so improvements in HR productivity, for example; in customer service, being able to help infuse AI into virtual assistants to make them intelligent chat bots that will help clients provide a superior level of personalised customer service; and application modernisation and that’s essentially generating code and code conversion from one language to another.”
