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The United Nations Educational, Scientific, and Cultural Organization (UNESCO) today unveiled its latest Science Report. The massive undertaking — this year’s report totals 762 pages, compiled by 70 authors from 52 countries over 18 months — is published every five years to examine current trends in science governance. This latest edition includes discussion of the rapid progress toward Industry 4.0 and, for the first time, a deep analysis of AI and robotics research around the globe. Going beyond just the global leaders, it offers an overview of almost two dozen countries and global regions, examining AI research, funding, strategies, and more. Overall, the report determines “it is the field of AI and robotics that dominated scientific output” in recent years.

“We take a look at the broad field of cross-cutting strategic technologies and break it down comprehensively into the 10 subfields. Artificial intelligence and robotics is one of those subfields, and it’s the biggest based on the number of publications,” report team deputy editor Tiffany Straza told VentureBeat. “Globally, there was kind of an easing off of interest around 2015, and then it spiked right back up. To me, it represents that this is a priority topic around the world.”

Indeed, the report, which aggregates data on spending, personnel, scientific publications, and patents, shows AI and robotics dominated scientific output from 2018 to 2019 in countries of all income levels. Almost 150,000 articles were published on these subjects in 2019 alone, a 44% increase from 2015. For comparison, only 18,000 were published on biotechnology in 2019.

The report also shows that the rise in AI publishing by lower-income countries since 2015 has mechanically shrunk the G20’s share of output. Lower middle-income countries overall contributed 25.3% of publications in the field in 2019, compared to only 12.8% in 2015. This clearly demonstrates that interest in AI is global. Across the world, the researchers found that more than 30 countries have adopted specific AI strategies over the past five years, including China, Russia, the United States, India, Mauritius, and Vietnam.


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To learn more, we spoke with Straza about the report and what she learned about AI and robotics while working on it.

This interview has been edited for brevity and clarity.

VentureBeat: Industry 4.0 and the digital transformation of factories with AI and robotics comes up often throughout the report. What’s the state of this currently?

Tiffany Straza: I’m going to talk about India and the U.S. because they have really different approaches to this. In the U.S., there’s this real big concern about manufacturing and “made in the USA” versus made in other countries. And there’s this fear that robotics is going to replace factory workers and take away jobs. By contrast, in India, the car manufacturing sector has the largest representation of robotics, and there’s been a huge uptick in their use. And I think it’s fabulous because they see fewer injuries and factory accidents. Now you can’t just bring in the robots. It has to be accompanied by a transition where you upskill workers. So, again, the robots themselves aren’t the enemy. It’s how we use them and how we as a government make decisions to interact with the technology. What support do we need to make that transition work for everyone? It’s not just spending money on tech; it’s bringing the system together.

VentureBeat: One interesting finding is that international scientific collaboration is up, especially among high-income countries. The report didn’t break this down in terms of specific technologies — do you have a grasp on how much this applies to AI? Considering the competitiveness in the field, it’d be interesting to know.

Straza: I can tell you in general that crosscutting strategic tech has less foreign collaboration than some of the other fields. The most intensely collaborative fields are environmental sciences and geosciences, which makes a bit of sense because they’re relatively neutral. Whereas in crosscutting strategic tech and engineering, I think it’s important to note this includes the subfield of strategic defense and security studies, so military research. So some of that might be because of security and not wanting to share all of our cutting-edge things that could be used for defense. But also something that would be patented and used for economic gain. I think there’s some pressure there to keep these research teams small and local.

VentureBeat: The report goes in-depth on the United States’ dedicated strategies and funding uptick for AI. The U.S. federal government has prioritized strategic initiatives in AI since 2016, and in 2020, the White House’s budget request even included AI as a separate category. This year, the White House proposed an even more significant increase for non-defense AI, including a more than 70% increase over the previous year for the National Science Foundation (NSF). Congress even came together to propose a major bipartisan proposal to bolster U.S. technology leadership in AI, among other digital technologies. You also dive deep into the landscape in China and Russia, which are, of course, considered the other leading countries in the field. What’s similar and what’s different about these countries’ approaches to AI? How would you summarize their efforts? 

Straza: The U.S. is focusing on the development of AI for jobs, and for good working conditions for AI professionals to make sure that they’re paid well and stay in the country. Russia is similarly focused on jobs and remuneration, or pay and working conditions for everyone working in the field of AI. This is an important topic for Russia in general because the country’s technical scientist population is aging. Young people have been going to other fields, and there’s also “brain drain,” meaning they’re going elsewhere in Europe or the world. So Russia is making some significant efforts in science overall, and we see that reflected in AI. They’re also looking at educational programs and skills to get more of the public aware and involved in AI.

China is focusing on growing and refining local expertise and innovation in AI, as well as local manufacturing capacity for the technologies. By 2030, the country aims to be “the world’s primary center for innovation in AI,” according to its New Generation Artificial Intelligence Development Plan. China is already the world’s biggest owner of AI patents.

Canada, also a leader, is trying to take this position of AI for the world, and that it’s not just something that’s going to be, you know, used specifically for the military or something where the knowledge is more private. They’re looking at AI and data science for manufacturing and infrastructure sectors, trying to make a link to business. Canada is also trying to keep AI at the forefront of the G7 conversations and the global partnership to look at the responsible development and application of AI.

VentureBeat: Besides these leaders, the report reveals a significant uptick in AI pursuits around the world. For example, it mentions that Cameroon has 28 active tech hubs and had the highest publication density in AI and robotics on the subcontinent in 2019. Also, Ecuador’s output on AI and robotics grew ninefold over the dual periods of 2012 to 2015 and 2016 to 2019, one of the highest rates in the world. What should people know about AI and robotics as a particularly dynamic field of research in lower-middle income countries?

Straza: I think it’s important to note that the countries with the fastest growth aren’t the countries with the highest output. It’s Uzbekistan, Ecuador, Nepal, Ukraine, Indonesia, and some others. And I think we need to see and respect the priority that these topics are receiving around the world. Looking at the global players tells us who’s prioritizing these topics, and it gives us a clue about whose voices are involved in this research. Are there any key gaps? Are these countries or these researchers involved in our conversations and our best practices for collaborative research? What are their priorities for using these technologies? It’s really exciting to see this growth in these countries, and I’d like to make sure that’s sustained. There are a bunch of technologies and potential applications within this field that can be really positive in terms of sustainability research or creating jobs and opportunities for people. It also can include science that could be damaging in some ways. Let’s make sure that we’re also joining that conversation on ethical frameworks and inclusive applications for this research.

VentureBeat: Speaking of inclusion, it’s widely known that women are underrepresented in science, engineering, and technology. And while your report contains some good news (like that parity has almost been achieved in the life sciences), it’s concerning to read that it’s still a long way off in many sectors of growing importance. In AI specifically, women represent only 22% of the workforce. Overall, how does the report underscore the importance of diversity in the field?

Straza: Some of this is really obvious, and some of it is a little bit hard to put numbers to. We do have a growing body of research that says diversity and inclusivity make business sense. We make better decisions and have better relationships with our users when we have this diversity in terms of our decision-making. And we see that there’s action being taken in response to those patterns. For example, the European Union and others say you have to meet gender targets or you’re not eligible for certain types of funding. So we do see this nice shift.

VentureBeat: After your experience working on this report, what aspects of AI do you think need more attention?

Straza: How AI and machine learning is being used, and again, who’s involved in the conversation. Because it relies on big data — data that comes from individuals — I want to talk about access to fair use of data permissions to obtain data and who gets to decide how that’s applied. I think AI can be quite powerful, including to help us address today’s challenges, whether that is our relationship with the planet or with each other. But we need to pay attention to representation within the field, who is conducting the research, who is defining our research priorities. And then in applications, who’s defining our application priorities and who is ensuring we understand the impact of AI today and on future generations.

VentureBeat: Based on your research, do you have any predictions for what’s next for AI?

Straza: In terms of the global policy conversation, I think the use of artificial intelligence in security applications is going to be particularly contentious over the coming years. In terms of business applications, we’ve already seen how this can be tremendously powerful in terms of shaping what people know about and how they connect with the world. It affects how products are marketed to us and so much more. So I’m expecting there to be a continued interest in artificial intelligence and machine learning from the business community. But I would like to see, are we going to align this tool with our commitment to the green transition and to the sustainable development goals?

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