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Source: Asia Development Bank

Governments and development partners need to take a methodical approach to the adoption of artificial intelligence technologies in collaboration with the private sector.

Technologies including artificial intelligence (AI), big data, cloud technology and Internet of Things, are fundamentally changing the way we work, live, and relate to one another. The shifts and disruptions they are causing are so massive that the stakes for success are as high as the perils.

There are currently about 20 billion devices connected to the internet, and almost half of enterprises globally are adopting cloud technology as an operative norm. By 2022, one in five workers engaged in non-routine tasks will rely on artificial intelligence. AI augmentation will help business enterprises to recover 6.2 billion hours of worker productivity.  

These technologies hold great potential to dramatically boost economic growth, organizational efficiency, and social development, and could help better manage resources in ways that benefit the environment.

But organizations may be unable or unwilling to adapt, while governments may fail to regulate or employ the tools to reap the benefits. Possible reasons could be lack of capacity, access to affordable research and development, a shifting of power in favor of early adapters, creating inequalities, new security issues, and fragmentation in society.

Five issues must be addressed if we are to prevent this and ensure that the digital divide does not widen and that societies can reap the benefits.

First, data, computing infrastructure, algorithms and enabling environment are four key pillars for fostering AI that will promote diversity and economic growth. Governments and international institutions must work closely to identify appropriate use cases and ensure availability of high-quality data with needed security for effective functioning of the AI ecosystem.

Second, upstream and downstream actions must be developed that will facilitate adoption of AI. The upstream function includes infrastructure creation, funding and sustaining initiatives through the effective use of private sector, ventures, and public-private partnerships. The downstream aspect involves identifying proper use cases and applications.

Third, an offsetting mechanism should be developed to deal with instances where AI results in job losses. An approach such as a robot tax and other mechanisms such as universal service obligations practiced in the telecommunication sector should be developed and executed. Simultaneously we may also examine appropriate taxes and the possibility of tapping corporate social responsibility initiatives to help affected people.

Fourth, we need to study the feasibility of setting up an international body to educate, track, monitor, regulate and serve as appellate body to ensure ethical, responsible, and productive use of AI technologies.

Fifth, there needs to be prioritization of sectors that require massive focus. For example, how fast we can accelerate research and development of new materials and drug discoveries that can help protect people from diseases; is it possible to get a consensus on use of outer space and space technologies to monitor weather and climatic conditions to calculate in advance disaster events and taking appropriate decisions?

There are currently about 20 billion devices connected to the internet.

What are the systems that could use AI for countering terrorism, violence against humanity and biodiversity, and fraudulent monetary transactions and corruption? How can technology be used in the health sector to provide affordable access and efficient health services to the poor and vulnerable?

As the application of technology is immense, it is essential to adopt a two-pronged approach—prioritizing funding and dealing with questions on global public goods and ethics dealt with by governments, international institutions and alliances, while responsible sectoral adoption of technology is left to the private sector with guidance and appropriate regulations and tax methods.

The challenges posed by AI technologies are many and must be handled through collaborative actions, such as cross sectoral programs on regional cooperation, re-skilling, and regulations. They will also require development of trust and transparency in information creation, storage, sharing and use between all stakeholders and among nations, international institutions, and alliances.

Issues that need wider examination include human behavior, data governance, legal, ethical, and capacity building requirements. In addition to these, hard infrastructure—broadband connectivity and digital literacy are crucial factors in making digital developments inclusive and sustainable. With advances in technologies such as 5G systems, the task of providing a level playing field between the digitally advantaged and the digitally less advantaged is huge.

Governments must massively invest in skills building and prepare society for an orderly transition. International collaboration between countries, multilateral agencies, and enterprises should create pilot implementations, develop standards, security protocols, regulations, explore business models including public–private partnerships, develop AI technology demonstration platforms, policies, and information sharing for mainstreaming.

In this context, governments and development partners and initiatives such as the Global Partnership on Artificial Intelligence will have to plan methodic adoption of AI technologies in collaboration with the private sector.

MIL OSI Global Banks