At some point, a collaborative approach to AI problem-solving will become essential.
Artificial intelligence, or AI, is driving massive shifts across the globe, and every day more questions arise. The narrative in the media focuses heavily on an “AI arms race”, with the US and China as the key players. But there is more to the story. The US and China are certainly central figures but they are not the only ones in the race, and the finish line and what characterizes a “winner” is still unclear. There is no doubt, however, that AI will have a generational impact; for example, PwC estimates that AI could increase global GDP by $15.7 trillion by 2030.
Given the sweeping societal considerations and monetary benefits, it is not surprising that governments around the world are taking steps to win in the digital race. Countries as small as Kenya and as large as China have created or are working to create formal national AI frameworks that tackle the important questions AI raises for society, the economy and government.
AI policy is about maximizing benefits while minimizing risks and harms. Questions that government – and in many cases the private sector – are trying to solve include: what impact will AI have on the workforce and how can we prepare for it? How can we encourage economy-boosting and job-creating technologies? How can we ensure that AI will be implemented ethically and with minimal bias? How will society benefit?
Embracing – or refraining from – AI policy
In recent years, Canada, China, Denmark, the European Commission, Finland, France, India, Italy, Japan, Mexico, the Nordic-Baltic region, Singapore, South Korea, Sweden, Taiwan, the UAE and the UK have all released official strategies to promote the use and development of AI and to address these important questions.
But to address their different needs and opportunities, countries are taking vastly different approaches. For example, the European Commission – the European Union’s executive branch – recommended its member states increase their public and private sector investment in AI. It pledged billions in direct research spending. Meanwhile, China laid out its plan for global dominance last year – one that has also been backed up with massive investment. China’s goal is to lead the world in AI technology by 2030. France’s leadership has been clear in its public-private partnership approach. Canada, the first country to release an AI strategy, is primarily research – and talent-driven. The UAE was the first country to create a Ministry of Artificial Intelligence, and its focus is on using AI to enhance government performance.
None of the US, Israel and Russia have a formal national AI policy yet. Private sector companies such as Google, Amazon and Apple and the US department of defence are driving the bulk of AI investment in the United States. Though Israel does not have a specific policy, it is keenly focused on AI and has seen the number of AI start-ups triple since 2014. Russian President Vladimir Putin’s assertion that “whoever becomes the leader in this sphere will become the ruler of the world” was interpreted as a declaration of Russia’s investment in AI, and thus Russia is often viewed as a leader in the field. However, the country’s estimated annual spend is only roughly $12.5 million, and it has no official national strategy.
Learning from one another
Which countries are approaching AI most effectively, and to what degree is there opportunity for greater international collaboration? It may be too early to tell; however, when analyzing the best practices of existing national AI policies, there is much that can be learned. These are the specific areas to consider. Data. From self-driving vehicles to smart cities, data is the driver behind AI. According to a McKinsey Global Institute study, nations that promote open data sources and data sharing are the ones most likely to see AI advances. A Brookings Institute report notes that “in this regard, the United States has an advantage over China. Global ratings on data openness show that US ranks eighth overall in the world, compared to 93rd for China”. But right now, innovation in the United States is limited without a national strategy that answers questions about protocol and ownership. France and Denmark, on the other hand, are opening government data. France is hosting troves of centrally collected public and private data that it plans to make available as part of its strategy. Conversely, by taking a restrictive position on issues of data collection (as indicated by the implementation of General Data Protection Regulation), the EU is putting manufacturers and software designers at a disadvantage while balancing the demand for privacy.
Talent. The demand for AI talent far outweighs the available supply. According to a study by Element AI, there are only 22,000 PhD-educated AI researchers in the world. As a result, almost every nation’s strategy addresses talent development. Canada’s AI strategy is distinct in that it primarily focuses on research and talent strategy. The country boasts AI degree programmes and is building a $127 million research facility in Toronto. Companies like Facebook and my own company, Uptake, are investing in Canada to access this talent pool.
Legal. A whole host of legal questions swirl around AI. Estonia has been a leader in addressing legal questions related to AI: the country is developing a bill for AI liability that will be ready in March 2019. The government hopes the legal framework will attract investors by providing a simple, comprehensive guideline to enable the broad use of AI systems. Issues that arise are being tackled early, giving the country an advantage and serving as a roadmap for others.
Inclusion. One of the great promises of AI is its potential for improving quality of life. But without the right planning and oversight, we risk exacerbating problems of inequality or marginalizing groups of people. As an example, India’s AI strategy is focused on leveraging the technology not only for economic growth, but also for social inclusion. The approach is called #AIforAll and outlines a strategy that aims to empower Indians with the skills to find the quality jobs, invest in research, and scale Indian-made AI solutions to the rest of the developing world. India is not the first country to incorporate AI and inclusion. Canada and France, for example, recently announced a task force to develop an international study group on inclusive and ethical AI.
Which way forward?
I am not naive enough to think that competition won’t drive individual strategies, but I do believe that at some point this will shift to a more collaborative approach. In April, Beijing was the first city to host a major international standards meeting, demonstrating eagerness to set global standards around controversial aspects of AI, such as algorithmic bias and transparency in algorithmic decision-making. In another show of collaboration, the UAE and India signed an agreement in July to spur discussion and explore options for the countries to convene and collaboratively grow their AI economies. The UK and France also entered a partnership intended to seize the economic and social benefits of fast-developing tech such as AI.
We have a unique opportunity at this juncture in history to make decisions that will have worldwide, lasting impacts not only on our national economies but on society as a whole. While each country must consider its specific needs, there is early indication – and early promise – that a global framework may actually create more innovation and allow us to solve more complex and pressing global issues. I am encouraged by the opportunity for collaboration and believe that many of the questions we are grappling with today will be answered if we take the time to learn from one another.
[Source: “Why countries need to work together on AI” published by World Economic Forum]Photo Credits: World Economic Forum
