Struggling with AI transformation
The world is in a mess, and the acceleration of artificial intelligence (AI) usage is disrupting every business and the way we live. We are all struggling to understand what the AI transition means for each of us as consumers, parents, teachers, businesses, or government leaders.
The debate over the pros and cons of AI is raging, especially in its dual military-civilian usage. AI will guide the next drone or missile at you with faster accuracy than ever imagined. It can also develop the next miracle drug to change our health. We simply do not know the outcome, whether AI is ultimately good or bad, only that the bandwidth of risk and opportunity is widening at frightening speed.
We have never seen technology being adopted as AI in daily activities in terms of speed, scale, and scope. The AI revolution has pushed Nvidia and other AI platform stock valuations into the trillion-dollar league. Big powers and big platforms are all investing in AI, trying to figure out how to beat the competitors in achieving scale and domination.
The digital divide means that those ahead in AI will be richer, faster, smarter, and more powerful, whereas those who don’t implement AI tools are marginalized.
Clearly, the rich and advanced economies stand to gain more from AI and technology, whereas emerging and developing market economies are still struggling with how to use AI to help them develop or at the minimum, tackle their myriad problems of people and planetary injustices. The most obvious benefit of AI is that it could improve productivity, which has declined globally across the board for several decades.
McKinsey research suggests human-centric generative AI adoption may well automate up to 30 percent of business activities across occupations by 2030. Analyzing 63 user cases, they estimated that generative AI could add roughly $2.6 trillion to $4.4 trillion annually to the global economy, equivalent to adding 2.5-4.2 percent to current global GDP, which has been forecast by the World Bank to slow down to half the growth before the global crisis in 2008.
The potential for turning around development in multidirections using AI looks huge. How can this be achieved?
AI is essentially a human-invented tool for learning and using for change. Given the right amount of data, it can help make better decisions and eliminate inefficiencies in the system. It can also do bad things at scale. Ethics in the usage of AI is at the heart of the current debate. In the wrong hands, AI is what rockstar historian Yuval Noah Harari calls “data colonization and digital dictatorship.”
Nobel Laureate economist Joseph Stiglitz propounded that the job of governments was to create a learning (knowledge) society since knowledge is a public good. Fellow Nobel Laureate Robert Solow (1924-2023) first quantitatively identified that the most important determinant of economic growth was technological change. Kenneth Arrow (1921-2017) showed that markets by themselves do not yield efficiency in the production and dissemination of knowledge.
More recent case studies on building tech ecosystems showed that learning is really about copying or imitating global knowledge and adapting these to local needs. Korean professors Kim and Lee (2022) showed that Taipei and Shenzhen evolved into tech powerhouses by first importing foreign technology by welcoming multinational companies and then developing local champions that increased research and development, primarily in process engineering, and then moving to original ideas, products, and services that began to rival foreign competitors.
In short, human learning is always about copying others and then personalizing or internalizing such knowledge to create new ideas and actions. This “copy-learn-adapt-innovate-scale” approach is exactly the path that AI usage is following.
When we face something totally new, we have four essential choices. The first is to deny or reject because we fear the unknown. The second for those who are curious is to learn and experiment. The third is to do nothing or simply follow the crowd because that appears to be the safest way out of disruptive change.
The brave and risk-takers are those who decide to leap into the unknown and become innovative or entrepreneurs. These become the change agents. In today’s existential threats of nuclear war, ecological collapse, and technological disruption, doing nothing or business as usual is not an option. You either eat lunch or be the lunch.
In sum, we all need to adopt AI tools to generate the productivity that is needed to achieve more with less. Although change is best tackled bottom-up, it needs leadership, courage, and passion to engineer change. That takes human intelligence, with AI as a tool, but impactful change is never about one individual, but about the whole and all of us. Asia News Network
Andrew Sheng is former chair of the Hong Kong Securities and Futures Commission.
