The use of artificial intelligence (AI) and big data offers untapped opportunities for Thailand. In particular it has enormous potential to contribute to ‘Thailand 4.0’, a new value-based economic model driven by innovation, technology and creativity that is expected to unlock the country from economic challenges resulting from previous economic development models (agriculture – Thailand 1.0, light industry – Thailand 2.0, and heavy industry – Thailand 3.0), the ‘middle income trap’, and the ‘inequality trap’.
A core aspect of ‘Thailand 4.0’ puts emphasis on developing new S-curve industries, which includes investing in digital, robotics, and the regional medical hub.
Today, the digital economy – with extensive use of AI and big data – is growing at a pace that far exceeds the global economy.
In just the last few years we have seen the development of AI systems capable of processing enormous amounts of increasingly complex data at ever increasing speed, with terabytes of data being generated globally every 60 seconds.
At the same time the costs of IT infrastructure has been declining. Thirty years ago, it cost more than $560 to store 1GB of data; now it costs less than $0.01.
Coupled with better analytics capabilities more real-world information is available for policy and decision makers than ever before.
AI and big data Enhancing human development
AI is already being used extensively in the private sector for commercial and profit-making purposes, including forecasting demand, predicting churns, suggesting advertisements on social media platforms, and recommending products to potential buyers.
However, not many people realise that AI and big data can also be used to enhance human development and to address many developmental and social challenges. A few examples of how AI can enhance human development incude:
- Analysing vast quantities of healthcare data, leading to scientific breakthroughs
- Predicting and identifying optimal budget allocation for effective and cost-effective interventions to achieve a government’s goal
- Revolutionise classrooms by providing individual learning pathways and virtual mentors
- Mapping poverty from space, enabling real-time resource allocation
- Predicting and identifying optimal production levels to reduce waste
- Making available ‘Uber-like’ sharing services for tractors and refrigeration, providing poorer farmers with access to the services that they need only at certain times of the year
- Producing models capable of predicting climate-related disasters
- Tracking the movement of fishing boats to combat illegal fishing
- Predicting consumption patterns for efficient and safe water provisions
- Driving more balanced hiring practices and spotlighting gender inequality
While we know that AI and big data can help drive exponential innovation, their use is currently limited. Despite terabytes of data being generated every minute, only 1 per cent of this data is being used or analysed. Public sector use of big data analytics and AI is the lowest.
Shared innovations lighten the load
The World Bank has been supporting the use of AI and big data to achieve its goals of decreasing poverty and increasing shared prosperity.
It recently launched the AI for Development initiative and an Artificial Intelligence Lab, complemented by a skills-building programme in Bangkok focusing on big data, AI, and decision science in health and nutrition.
The five-day event included the participation of World Bank country teams, as well as government and academic partners from Bangladesh, India, Indonesia, Lao PDR, Myanmar, Nepal, Pakistan, Papua New Guinea, Rwanda, Samoa, Tajikistan, Thailand, Uzbekistan, Vietnam, and Zimbabwe.
Similar training was also held in Bucharest, Romania, and Pretoria, South Africa, engaging decision makers in public health from Latin America, Europe, Central Asia, and Africa.
In addition to outlining the utilisation of AI and decision science in health and nutrition, the workshop also focused on building the skills of decision makers by training them on various tools that utilise these technologies and aid in the decision-making processes.
Participants were then able to apply their newly acquired skills to tackle real-world scenarios, many of which were from their own regions or countries. Attendees also learned how to utilise tools such as Optima HIV, a Health Service Prioritisation tool, as well as broader big data techniques in addressing challenges facing public health decision makers today.
The workshop achieved its goal of creating awareness of the need for analytics to improve decision and delivery choices in health and development, and building capacity in the use of analytical optimisation tools that can answer pertinent policy and implementation questions for sectors.
In Thailand government officials and World Bank staff intend to apply their newfound knowledge to improving the efficiency of resource allocations to support the national roadmap of ending the ‘AIDS epidemic’ there as a public health threat by 2030, with a goal of cutting the number of new HIV infections annually from the current 6,500 cases to less than 1,000, AIDS-related deaths from almost 13,000 to under 4,000, and slash HIV-related discrimination in health-care settings by 90 per cent.
Feature photo OpenGov Asia/ ICAPlants
- Google launches Thai AI project to screen for diabetic eye disease (Reuters)
- Is Thailand 4.0 coming to fruition? (The Asean Post)
- Advancing ASEAN’s digital economy (Myanmar Times)
The World Bank Group consists of: The International Bank for Reconstruction and Development, The International Development Association, The International Finance Corporation, The Multilateral Investment Guarantee Agency, and The International Centre for Settlement of Investment Disputes.
By 2030 The World Bank aims to:
1. End extreme poverty by decreasing the percentage of people living on less than $1.25 a day to no more than 3%.
2. Promote shared prosperity by fostering the income growth of the bottom 40% for every country.
It aims to achieve this by providing low-interest loans, zero to low-interest credits, and grants to developing countries.
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