The Rising Dragon: How Singapore’s AI Leadership is Leaving the West Behind
The AI Leader You Didn’t See Coming - Understanding Singapore’s Meteoric Rise
Which country do you think leads AI? And does it matter who does?
Many people worldwide believe the United States leads in AI. Others who may do a bit of reading around, might say soon it could be China leading on AI.
If you want to make an AI global leadership joke or be a little cruel, you might say well maybe Europe is a leader in AI? as a few nervous Europeans like to say.
It's a joke because, apart from perhaps 1 exception (Anthropic) Europe has no significant AI industry at all, even though it desperately wants to believe it can be a big player in the global playground at AI, despite European resolve usually being about as firm as an undercooked croissant.
What if I were to say to you Singapore is an AI global leader, doing things very differently from everyone else? What would you say?
Perhaps you might say 'Where's Singapore?' (it is a small city-state in Asia). Or if you read a little, you might say 'I read that Singapore is really good for high-end shopping, is very clean, and they have a nice airline, but that's about all I know'.
Well the thing about living in the West, as my non-Western readers will already know, is that we tend to be a little bit self-obsessed with ourselves. Is that fair comment do you think? We are the biggest fans, of ourselves.
We tend to think we in the West are the best at everything, what we do, our values, and that everything we do is superior to other countries, of course. So why should you care too much about what goes on in other countries, apart from maybe researching some nice sunny holiday destinations?
Despite also living in the West, I have never understood or agreed with that point of view, which I don't think is very smart. Even if we are the best at everything (I don't quite believe that) how would we know if that's true, without taking a bit of interest in finding out what's going on in other countries?
But perhaps you're already sold on that one, or maybe you're not sure yet. But first, we need to understand why which country leads in AI matters.
Why AI Global Leadership Matters
You might think, well does it matter who leads in AI? After all, despite say the United States leading in many tech areas, whichever country in the world you live you can still pretty much use Facebook, or buy an iPhone, so why would it matter who leads in AI if you can get most tech almost anywhere in the world anyway regardless who is the country leading it?
While that's true for now, there are other reasons why you might care which country is leading in AI.
Most articles written about why global AI leadership matters are from a Geo-political point of view. These tend to stress that AI leadership is all about:
Military dominance
Economic development & growth
Governance & Political Function
National and Global Regulation
As an article from Lazard describes:
Leadership in AI — and emerging technologies more generally — has become the frontier of U.S.-China geostrategic competition. AI is critical, not only to the defence of countries (through next-generation autonomous weapons), but also to their political functions, as AI changes how the creation and distribution of information is understood.
A report from Goldman Sachs also takes a similar view that is common to the geopolitical mindset:
The emergence of generative AI marks a transformational moment that will influence the course of markets and alter the balance of power among nations. Increasingly capable machine intelligence will profoundly impact matters of growth, productivity, competition, national defence and human culture. In this swiftly evolving arena, corporate and political leaders alike are seeking to decipher the implications of this abrupt and powerful wave of innovation, exploring new opportunities and navigating new risks.
Something the Goldman Sachs report fleetingly mentions which is almost always ignored and unheard of in most geo-political analyses about AI leadership is the word 'culture', the potential impact of AI leadership from a cultural perspective.
I suggest again this is due to a tendency for Western bias. We in the West don't consider that the AI we have developed is mostly trained on content from our countries, and that content has Western values, social norms etc that are different to the cultures in other regions in the world.
AI is not free from culture or values, AI has cultural and value biases because the data it is trained on, the texts, images etc have cultural norms and values biases in them. There is no culture-neutral or culture-free AI, that my friends, is a fantasy.
How would you feel about using an AI whose values you didn't know and might not share? it would probably engage with you differently. Would you care what culture or values the AI you were using had? I think you might.
Culture & AI isn't only an international issue either. For example the recent debacle & disasters with Google's Gemini AI model that generated images of black nazis or black Vikings after diversity ‘errors’:
This clumsy attempt by Google engineers at trying to 'hard code' and force particular 'diversity' & cultural values into that AI and onto everyone else, of course spectacularly backfired and was a complete disaster.
It also highlights the lack of transparency by most AI companies about the hidden biases & values of their models.
However, the broader point this illustrates is, that the effect of AI leadership on cultural values and the effect of cultural values on the AI leadership, clearly matter to people, even if it's something geopolitical analysts usually ignore.
Even if you're not so bothered about AI global power games or the effect on the economy, the values inside the AI you use, and who are the leading countries that make that AI with their culture & values, that's something I think you might care about.
Who builds and leads AI, matters.
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Singapore's AI Strategy
A recent report by the TBI for global change covered the unique way Singapore is approaching its AI strategy with a 3 point approach.
Building an Asian AI
Modern AI are known as Large Language Models (LLM's) which are trained on billions of texts and images. Most of the AI's we know in the West such as ChatGPT, Llama2 or Claude, are mainly trained in text & images from western culture. This means that these AI's are biased towards western cultural norms and values in everything they say & output, as we mentioned earlier.
These language based & culture specific AI models are the foundations for most AI applications. As the report explains:
Although LLMs can understand and generate language, their ability to generate contextually appropriate responses is dependent on whether they are trained on input data that is from the relevant (i.e. local) contexts. Yet much of the data that existing LLMs such as ChatGPT are trained on are largely from economically developed, Westernised contexts – leading to accusations of cultural biases at best, and the promotion of certain values at worst.
The first part of Singapore's strategy is to develop local AI's that are trained on text and images from local South-East asian contexts which they call SEA-LION:
Alongside the release of NAIS 2.0, AI Singapore – a national programme set up in 2017 to enhance Singapore’s AI capabilities – launched SEA-LION (Southeast Asian Languages in One Network), a family of LLMs that are foundational to all generative-AI development. Trained on data sets in 11 regional languages, SEA-LION’s models will cater better to South-East Asian contexts.
Building AI models customised to local culture, languages and values, should help develop more useful and successful AI applications for use in Asia.
Agile & Pragmatic Regulation
The second strand to Singapore's AI strategy is balanced regulation that is careful to fully support innovation as a priority while flexibly adapting to potential risks.
This contrasts for example with the approach taken by the European Union with their recent AI legislation which is much more restrictive and prioritises rights and protections over supporting innovation.
The EU's approach towards AI regulation seems perfectly designed to ensure Europe continues to fall even further behind in tech & fail to develop any significant AI capability or leadership. I have written more about this in Why Banning AI Is the Worst Thing You Can do for Your Safety.
In stark contrast, Singapore has developed a more agile regulatory framework that keeps in close contact with industry and rapidly adapts as highlighted in the TBI report:
The rapid pace of AI’s development and our evolving understanding of its risks and beneficial use cases have underscored the importance of policymakers striking the right balance between protecting public interests and supporting innovation.
Although largely orchestrated and led by the government, AI development in Singapore is often carried out in tandem with the private sector to gain buy-in and facilitate knowledge sharing, ensuring the country remains at the cutting edge of global AI advancement.
The report highlights the key advantages of this approach:
To account for new knowledge and risks that emerge, these governance frameworks will be regularly reviewed and adjusted. Coupled with their “living” nature, these frameworks allow for a degree of experimentation and exploration – thereby granting the government considerable agility within its regulatory approaches.
Yet as I alluded to before, we cannot escape culture and cultural & value differences, they influence everything, including how you approach AI regulation.
A World Economic Forum report has highlighted the differences between eastern and western ethics towards AI regulation.
In describing the Chinese perspective:
The Chinese guidelines derive from a community-focused and goal-oriented perspective. “A high sense of social responsibility and self-discipline” is expected from individuals to harmoniously partake into a community promoting tolerance, shared responsibilities and open collaboration. This emphasis is clearly informed by the Confucian value of “harmony”, as an ideal balance to be achieved through the control of extreme passions – conflicts should be avoided. Other than a stern admonition against “illegal use of personal data”, there is little room for regulation. Regulation is not the aim of these principles, which are rather conceived to guide AI developers in the “right way” for the collective elevation of society
And in contrast the European perspective:
The European principles, emerging from a more individual-focused and rights-based approach, express a different ambition, rooted in the Enlightenment and coloured by European history. Their primary goal is to protect individuals against well identified harms. Whereas the Chinese principles emphasize the promotion of good practices, the EU focuses on the prevention of malign consequences. The former draws a direction for the development of AI, so that it contributes to the improvement of society, the latter sets the limitations to its uses, so that it does not happen at the expense of certain people.
This difference between western vs eastern ethics and how they manifest in different approaches to regulation & law is something I also covered in How China is Supporting AI & Creative Freedom Better than the West.
Pragmatic AI - Building Infrastructure That Solves Problems
While in the west with AI for policymakers, the public and the media - the focus is often on imagined (dystopian) fears and risks about AI, privacy, copyright infringement, control. This perhaps reflects the more individualistic cultural values we have in the west, as the previous report highlighted.
In contrast, the Singapore/more eastern policy approach is more pragmatic, what works to create value, what doesn’t work - by building AI infrastructure. This perhaps reflects the more pragmatic and less ideological values attitude more common in Asia.
There are three prongs to this AI infrastructure strategy as highlighted by the TBI report.
Infrastructure Partnerships:
By looking to deepen its substantive partnerships with major compute players and engaging with global multi-stakeholder fora, the country seeks to secure local access to compute capacity and to partake in global discussions about AI ethics and governance.
Support Start-ups:
To bolster the growth of the local AI research scene and start-up ecosystem, the government is partnering with Google Cloud to launch the AI Government Cloud Cluster (AGCC). This dedicated cloud-computing environment will provide critical access to an AI technology stack, including pre-trained generative-AI models.
Grow Talent
To build its pipeline of future tech talent, Singapore has announced plans to increase its AI workforce to 15,000 (a three-fold increase from the current pool) and to increase the availability of AI training programmes and resources.
Together, these three pillars of developing localised Asian AI, agile and pragmatic regulation, and a comprehensive AI infrastructure plan, combine to create a thriving AI eco-system.
Why Singapore is Ahead of the West
Countries that have rapidly and widely adopted AI share a common characteristic: a national strategic direction for AI defined by their governments. Approximately 70% of countries with an AI strategy are developed economies, and their priorities tend to include the development of ethical AI frameworks, investment in education and workforce, and global collaborations to maintain their AI leadership.
In contrast, developing economies typically prioritise capacity building, fostering local talent, and seeking international collaborations to bridge the AI technology gap. This suggests a divergence in the approaches taken by developed and developing nations in their pursuit of AI advancement.
Singapore's new AI strategy reflects a combination of these priorities and has led to a thriving AI ecosystem and great advances. This makes it potentially informative for policymaking discussions in other countries.
While the emphasis on localised large language models (LLMs) mirrors a growing international consensus, Singapore has also demonstrated the potential of voluntary guidelines and "living" frameworks as effective pillars of an agile AI governance approach.
The role of the differences between eastern & western cultures and values as mentioned earlier, is likely to be a key reason why Singapore has applied this strategy so uniquely & effectively.
As UN AI Advisor Neil Sahota describes western cultural values:
In Western culture, movies, and books, it's always been human versus machine, right? But there’s something special about us as humans – we always wind up winning. And so we've kind of grown up with the adversarial relationship: we’re trained to look at AI as a threat. And so that kind of skews our perception.
Contrasted with eastern values:
But look at Eastern culture, movies, and books. They’ve always seen AI and robots as helpers and assistants, as a tool to be used to further the benefit of humans, and as a result, they're actually wired to look for opportunities. And that’s why we see that places like Japan, Korea, and China they’re further ahead of us in the use of AI in healthcare and elevating the quality of services because there you have that kind of mindset. The [US sci-fi] movie Crater ironically plays right to that narrative: there’s this war, Western versus Eastern; Western [culture] wants to eradicate, Eastern culture wants to protect and use.
This, coupled with multi-pronged efforts to build a trusted AI ecosystem geared towards generating value, Singapore's latest AI strategy represents a noteworthy example of effective AI governance on the global stage.
Singapore's more AI friendly culture & values, flexible and responsive regulatory framework, along with its key strengths in government policies, research and innovation, skilled workforce, robust data connectivity, and advanced cloud infrastructure collectively support and enable its thriving AI ecosystem.
That’s what makes Singapore a global leader in AI, that you never saw coming.
But what’s your perspective? Do you agree? Or do you have a very different perspective?
I’d love to know what you think whatever that is, let me know in the comments and let’s continue this important discussion about AI and immortality.
I use AI as part of my writing process, as a tool to help improve my own writing and more. Like to learn how to use AI to help your writing & more?
really good article and thought provoking.....one aspect of what AI does that is not apparent most places yet is the value of storytelling vs. programming...and by the creative aspects of some good journalism university depth in the west should team up with Singapore