Vietnam AI

Vietnam in 2020 overtook Singapore’s GDP and became the third-largest economy in ASEAN. Immediately after the new national ​leadership was elected at the Communist Party of VVietnam’s Congress in January 2021, President Nguyen Xuan Phuc signed a vital document entitled National Strategy on R&D and Application of Artificial Intelligence or the Strategy Document.

The 14-page document outlines plans and initiatives for Vietnam to “promote research, development and application of AI, making it an important technology of Vietnam in the Fourth Industrial Revolution.” Vietnam aims to become “the centre for innovation, development of AI solutions and applications in ASEAN and worldwide” by 2030.

The strategy document provides some directions to where Vietnam should go in the next decade with ambitious goals.

Vietnam follows China’s and other Asian countries’ footsteps in becoming a techno-developmental state which takes advantage of technological changes for economic developments.

It outlines what 16 ministries and the Vietnam Academy of Science and Technology need to do in the next 10 years. But the document does not show how other players such as startup founders, civil society, and the primary beneficiaries of AI –i.e. everyday users in Vietnam’s AI economy– should do.

It also has no mention of the role of AI ethics in this development.

Without any consideration to important ethical issues such as privacy and surveillance, bias and discrimination, and the role of human judgment, AI development in the country might only benefit a small group of people and possibly bring harm to others.

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Funding

AI developments need a large amount of funding from various sources such as international venture capital firms, local venture capitalists, government fundings, or companies’ profits.

Funding of AI development in Vietnam is lagging behind other Southeast Asian countries. In 2019, Vietnam’s AI investment per capita was under US$1, while the Southeast Asian leader Singapore has US$68 worth of AI investment per capita.

VC investment suffered in the first half of 2020 due to COVID-19. However, with the government’s assistance, there has been some sign of improvement regarding fundings shortly.

At the Vietnam Venture Summit 2020, both foreign and domestic investors pledged to invest US$800 million in Vietnam’s startup ecosystem.

According to Crunchbase, currently, there are 155 venture capital investors with investments in the country.  

Tech startups that received the most investments are in e-commerce, fintech and AI. The government also provided state funding at the national and city level to encourage entrepreneurship.

As a result, the startup ecosystem in cities such as Ho Chi Minh City and Hanoi thrived in 2020, before the fourth wave of COVID-19 hit the country in April 2021. 

The strategy document outlines the role of the Ministry of Planning and Investment to “attract venture capital funds to innovative AI startups in Vietnam.” The question remains open as to what the plans to bring international capital for domestic technological development are; which specific areas of AI should be the main areas of investment; how would the money be distributed, and will there be any accountability mechanisms, and who are these accountability entities?

Businesses

The development of AI in Vietnam has been driven primarily by private businesses. The strategy document outlines a push towards digitisation and industry 4.0 to create incentives for companies to become more aware of the potential of data science and AI.

Vietnamese companies are still in the early stage of development.

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Only a few large corporations are prominent in the AI space, notably FPT, Vingroup, and Zalo, who have the resources to invest in AI research, development, and deployment.

From our conversations with professionals in the space, smaller companies run into a critical challenge: product-market fit. To what extent is the Vietnamese public willing to adopt new AI solutions as opposed to existing solutions?

As Nam Nguyen, the CTO of an e-commerce company in Ho Chi Minh City puts it: “fit takes a lot of money to invest in AI, but its economic benefits are not yet significant. Businesses in Vietnam will not jump on this AI bandwagon. Only big companies with extra capital can be in this AI playing field.” This problem is also prevalent in countries where AI is more mature. Many companies in the US, for example, are still struggling to scale AI solutions where AI was developed before finding customers who are willing to adopt it.

Vietnamese companies also have to compete against foreign or imported AI solutions and the lack of venture capital from domestic and foreign funds. Future strategy documents should address these particular issues in detail. 

Talent pool

There is no shortage of technical talent, but AI education is relatively new in Vietnam. Most of the tech workforce is still working in outsourcing.

The talent pool is young and specialised: young because the majority of the talent pool is IT graduates, working data scientists, or software engineers with few years of experience, and specialised because there is a strong affinity to acquire a technical skillset in niche machine-learning areas (e.g. deep learning, GANs, reinforcement learning)— as opposed to a more general product or project management skillset.

Skilled talents often look for professional opportunities abroad, where salaries would be drastically higher.

Furthermore, these opportunities would enable them to actively participate in the research, development, and deployment of state-of-the-art AI technologies in more AI-mature countries.

Given this landscape, there are challenging conditions to retain talents in Vietnam effectively:

  • Salaries have to be competitive, compared to regional (i.e. Southeast Asia) and global markets.
  • There have to be professional development opportunities for talent (e.g. courses, international conferences, etc.) to keep up-to-date with the latest trends and practices in AI development.

As Tuan Anh, a research scientist at VinAI, claims: “We need to attract Vietnamese scientists back to Vietnam. The key issue is still the salary. It’s difficult for a Vietnamese-based company to compete with Google, DeepMind, Microsoft when it comes to salary.” It is worth mentioning that there is also a language barrier to learning AI. As AI education material is predominantly in English, it is crucial to enable young talents with the necessary language learning support and more technical education in AI.

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“Students in special programmes have English curricula. However, it only accepts 50-60 students per year,” says Khoat Than, a professor at Hanoi University of Science & Technology.

Public perception of AI and the missing ethics conversation

In Vietnam, AI is viewed overwhelmingly positively. It is regarded as a catalytic force for economic and technological advancement. In the public mind, the concept of what AI is, how it is used, and who it affects are not as clear.

Due to the push towards digitization and industry 4.0, the Vietnamese may see AI only as a tool reserved for industries. Some implementation of natural language processing and computer vision is used to further business objectives.

However, these cases are only among many AI applications that the public has already been using in their everyday lives. It might not be immediately apparent that the routes that Grab drivers use to navigate the heterogeneous street network in Saigon are selected by an algorithm, or that the discounted products they see as they log onto e-commerce websites such as Shopee or Tiki may be recommended to them by an algorithm.

This acute awareness is essential because it expands the public’s perspective on the role AI plays in benefiting or harming their lives.

Amidst the COVID-19 pandemic, “rice ATMs,” the automatic rice dispensing machines, were invented and deployed in many cities to provide rice both contactless and free-of-charge to low-income communities. What is often left out in the reports of this story is that facial recognition was also used to ensure compliance with the authorities.

This critical emphasis on AI involvement is the first step in shaping the conversation around AI and its impacts in Vietnam as a part of the much larger global discourse.

The public needs to start having the many conversations about AI around privacy, trust, bias, cybersecurity, and ethics, as well as the nuances, risks, and trade-offs of these aspects (e.g. privacy paradox).

AI ethics is an emergent field concerning the moral agency of machines and humans who design, develop, and deploy them. In practice, AI ethics is understood as a set of ethical principles, informs designers and developers about the harms of AI systems.

Specifically, the harms pertain to various areas: bias (e.g. gender bias in computer-aided health diagnosis), transparency, explainability, and sustainability (e.g. carbon emission of training large language models), among many others.

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The responsibilities of creating ethical AI systems and mitigating harms caused by these systems have fallen onto both corporate and societal organisations. Furthermore, ethical issues and impacts of AI are discussed widely among media, the public, policymakers, academia, and industry, thus establishing a dynamic and interdisciplinary environment where AI systems are created and criticised.

In Vietnam, not only is AI ethics absent from media and public policy discussions but it is also missing in engineering education.

Than, a professor at Hanoi University of Science & Technology notes: “I ethics at the college level lacks for engineering students. What students learn at universities are still ethics in computer science.” Colleges and universities should invest in not only learning from the learning and teaching of this curriculum,  adopting terminologies from the global discourse; they should also invest in doing research, particularly social science, that examines societal impacts of technology in Vietnam.”

At the governmental level, Vietnam can look to other Asian countries which have drafted national strategy documents that created a framework to make AI. One example is the Responsible AI for All Strategy Document, recently published by Niti Aayog, a premier think-tank by the Indian government.

It outlines potential ethical issues that AI would create and that many of those issues need new legal frameworks that different governmental bodies need to work together to address. 

Conclusion

Vietnam has entered the early phase of AI development; the strategy document is by no means the last that the government would produce.

We recommend the new leadership consider other aspects of AI development, including ethical considerations, legal frameworks, and creating partnerships with investors, civil society, and common users to create frameworks to address ethical problems native to Vietnamese community.

Vietnam should be conversing with global AI technologists and ethicists as AI development is truly a global phenomenon. 

This article is co-written by Khoa Lam, For Humanity.

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Image credit: quangpraha

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