Governments should pay as much attention to AI and data competitiveness as other economic and social progress.
Investment in research and technological literacy is the key to long-term competitiveness.
Today, COVID-19’s global pandemic is causing catastrophic damage to economic performance, cooperation and productivity. With these changes, data and artificial intelligence are expected to change the economy and improve society. In order to take advantage of these positive results, governments must go beyond the scope of current activities and recognize themselves as stewards of AI competitiveness at home and around the world.
Investment and improvement in artificial intelligence need not be an arms race. Artificial intelligence is a general technology with the potential to change all sectors and forms of economic activities. The enhancement of a country’s competitiveness can benefit allies, trading partners and the global order.
Responsible AI can enhance competitiveness while reflecting high-level thinking about economic resilience and population well-being. Still, it’s dangerous to fall behind. Governments should pay as much attention to AI and data competitiveness as other economic and social progress, and adopt a long-term strategic approach.
In order to improve the competitiveness of AI and data, governments should give priority to these seven factors in their integration strategies.
1. Research on priority investment AI
The government should invest in basic research and provide structural support. They should also reallocate existing research funding to emphasize data and AI across multiple domains. Coordinated government research investment can make the basic research and applied research of responsible AI in specific areas more concentrated, while still enabling innovation to flourish.
Government funding should be fertile soil that can open up a thousand flowers, rather than insisting on building a concrete foundation designed by the government. As Li Kaifu, a leading technology expert, points out, “there is a basic AI innovation – deep learning, and others are adjusting in this field.” For example, the U.S. could instruct the heads of the National Institutes of health, Defense Advanced Research Projects Agency, and 42 federally funded research and development centers (ffrdcs) to fund applications in specific areas without specifying what funding should be provided.
2. Improve the AI and data literacy of the whole people
Every G20 and OECD country has some form of stem (Science, technology, engineering and Mathematics) strategy, usually designed to increase the number of highly skilled graduates from its higher education institutions. While these initiatives are important, AI competitive strategies that emphasize broad-based AI and data literacy are equally important for building people who can fully participate in economic opportunities. This ability must be enhanced through a variety of teams, including humanities graduates, to create effective AI. Gartner believes that without such a diverse team, up to 85% of algorithms will produce wrong results by 2022.
3. Leverage the role of government as a buyer, partner, and provider, while opening up government data sets
The government is not only a promoter of AI, but also a major economic participant. It should use all the elements of its power to improve the AI competitiveness of its country. This could include the government as a responsible buyer of AI. For example, protecting a data center often requires the government to buy a lot of space to accelerate its transition to the cloud. When obtaining these contracts, the government should also open space to non-profit and social welfare organizations or micro small and medium enterprises (MSMEs).
The government can also establish public-private partnerships with technology companies to provide services. You can make yourself a platform to provide other people with their datasets. As Tim O’Reilly, an Internet entrepreneur, puts it, the government’s acceptance of open standards and willingness to allow open APIs to be used on its data promote innovation and competition in both the public and private sectors.
4. Support the application of artificial intelligence in as many fields as possible, especially for small and medium-sized enterprises
In order for responsible AI to penetrate deeply into economy and society, it must be accepted by those who have the least ability to use AI (especially small and medium-sized enterprises). Finland is a global leader in this field and has equipped 1% of its population (about 55000 citizens) with the skills to apply AI and data science to improve productivity through its “Ai challenge”. The country has turned its small-scale advantages into advantages, focusing on rapid skill upgrading and immediate application of existing technologies. Like Mika lintil, Finland’s economy minister ä “We’ll never have so much money that we’re going to be leaders in artificial intelligence,” he said. But how do we use it.
5. Practice digital diplomacy by stimulating and rewarding cross-border cooperation with consistent interests
In the war on tiktok and zoom hegemony, it’s easy to conclude that data and AI applications exist in (fire) walled gardens on (border) borders. This is misleading. Just as economic competitiveness emphasizes fair and open competition for goods and services and cooperation in the field of mutual benefit, governments should also pursue digital and data diplomacy. In the Nordic countries, governments are exploring automatic navigation in the Baltic Sea between Finnish or Swedish ports and are formally negotiating to merge digital infrastructure.
Governments should also extend their commitment to multi stakeholder cooperation to this area. This includes actively participating in and shaping local and global debates about technology use, restrictions and ethics.
6. Actively determine and measure the competitiveness of artificial intelligence as one of the elements of national strategy
In order to achieve any of these goals, governments need to have reliable benchmarks for the current state of data and AI under their control, measurable KPIs, and means of communication through integrated strategies. Such a measure can serve as the basis for regional and global indices, like the world economic forum’s global competitiveness index, which measures a range of factors that assess progress and determine productivity.
7. Keep technology impact at the forefront of decision making
Artificial intelligence can benefit economy, environment and human beings. But we’ve also seen how poorly considered or poorly executed AI can exacerbate problems and create new ones. Governments must insist on giving AI responsibility to all their goals. Because of the erosion of the idea that enterprises must keep in mind the best interests of consumers, “techlash” or strong opposition to some of the largest and most powerful technology companies in the world has appeared in many fields.
AI will need to deal with this growing attitude towards technology to rebuild trust with consumers. After all, there can be no real competitiveness without responsible AI. Prominent mistakes may reduce occupancy and acceptance, thereby impeding future innovation.
Governments need to encourage the design, development and use of AI to ensure that their countries remain competitive in the future, or to try to improve the well-being and GDP of their citizens. When purchasing or building AI, these groups should make use of more and more available resources, such as “procurement in a box” of the world economic forum. The widely tested toolkit was developed with the UK government and large multi stakeholder groups. These resources can help the government avoid future problems.
Economic competitiveness lies in helping people live a rich life freely and get the opportunities brought about by the globalized world fairly. The proliferation of data and the responsible use of AI expand these opportunities. Governments must recognize data and responsible artificial intelligence as the foundation of competitiveness and develop comprehensive national strategies for their investment and deployment.
Editor in charge: Tzh