Artificial Intelligence and the Digital Divide: From an Innovation Perspective

Abstract

Increasing digitalization has created the concept of the digital divide—concerns about how no or inadequate internet access and use of related information could exacerbate existing socioeconomic gaps between industrialized and developing countries, metropolitan and rural areas, and more and less privileged individuals and groups. The revolution and disruption that artificial intelligence (AI) is expected to bring across all industries and fields of life are currently shifting these discussions toward access to and leveraging of AI, often referred to as the “AI divide,” involving competitive advantage, skillsets, development level and economic growth gap between countries, companies, universities, and individuals (There are discussions about more than one “AI divides”–see for example the three AI divides described in this WEF article referring to companies, skills and countries: https://www.weforum.org/agenda/2018/09/the-promise-and-pitfalls-of-ai).

Related concerns about the current situation or the future are difficult to substantiate. Similarly, the known principle of data science “correlation does not mean causation” applies to this multifactorial issue. This chapter assesses the current AI divide based on scientific and patent publications related to AI as indicators of research and innovation output in the field. By considering the profile of the innovators and researchers, their affiliation, and geographies, it explores how different profiles and geographies already have access to necessary resources, showcase skills in the field of AI, and can or could deploy related applications. This chapter further explores existing policies and initiatives for building AI talent, strengthening AI-relevant skillsets and competencies, funding and strengthening AI research, offering incentives for establishing or attracting AI companies or further policies and measures to create an enabling environment, and leveraging the AI potential.

Patenting activity shows that AI-related research and innovation is rather concentrated both in terms of geographies as well as innovators. The United States and China are leaders in the AI innovation run—as origins of innovation and as locations of patent protection, and therefore as existing or potential markets. Background research related to policies in these jurisdictions and consultation with AI subject matter experts showed that this is largely due to the strength of their policy, education funding, and business ecosystem. Europe is ranked third, with the rest of Asia, Latin America, and Africa lagging behind. The scientific literature shows nevertheless that some research has been carried out in all these regions, but this may not be reflected—or at least not to its full extent—in related patenting activity, which tends to be more of an indicator of commercialization potential and related investment and industrial application. For this reason, it is important to look at patent and scientific literature data side by side before drawing any conclusions, as some countries’ strength in AI research is only or mainly reflected in the volume of scientific publications.

Looking at innovator profiles, there is a small number of ICT companies—mainly from the USA, China, Japan and the Republic of Korea, which lead patenting activity across all possible application fields. The area of transportation is an exception, with automotive industry representatives leading related activity. Moreover, these bigger AI players focus their patent filing strategy on a limited number of patent jurisdictions, indicating that the existing or potential AI markets for bigger AI players is from a commercial perspective and understanding limited to a rather small number of countries. Smaller entities tend to have very small patent profiles and be focused on their local markets.

The findings of the patent and scientific publications research show that a certain AI divide does exist if we consider it from an access and use perspective, looking at both geographies and profiles of AI researchers and innovators. Nevertheless, as AI is an emerging trend that several players are now joining, even the smaller activity across different countries and from different players indicates the potential which seems to already be there, and which can be enhanced and contribute to economic growth and development for all. Moreover, as AI is often based on open-source software and tools, access seems to be more democratized than other digital assets and tools, a factor that can even contribute to lessening the digital divide. A less obvious point for accessing and leveraging AI is the access to and ownership of training data which can facilitate or impede the development and applications of AI, making related policies important for how the future will look like for increasing or decreasing the digital divide.

The question for the future relates to the priorities of individual countries and regions do they envision themselves as competitors to the USA and China or do they prefer to identify their competitive advantage and focus on their own needs and strengths (See related considerations of Andrew Ng in Landing AI, AI Transformation Playbook (2018), available at https://landing.ai/wp-content/uploads/2020/05/LandingAI_Transformation_Playbook_11-19.pdf; and in the WIPO Magazine interview (June 2019 issue) available at www.wipo.int/wipo_magazine/en/2019/03/article_0001.html); and what are other principles that need to be taken into consideration to ensure equitable AI? Different initiatives may enable AI talent building related skills, leveraging the AI potential with applications in industries of interest for the economies in question, in niche areas and adapted to local conditions. To fully realize the AI potential in terms of deployment, scaling-up, and applications, there is a need for sufficient AI which must be aware of the possibilities and limitations of AI and be led by evidence and real needs rather than hype. It is important to create the right conditions so that—similar to the aims of the UN Sustainable Development Goals—“no one is left behind” (Excerpt from Committee for Development Policy, See Official Records of the Economic and Social Council, 2018, SupplementNo.13(E/2018/33); https://sustainabledevelopment.un.org/content/documents/2754713_July_PM_2._Leaving_no_one_behind_Summary_from_UN_Committee_for_Development_Policy.pdf) in the AI revolution.

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Irene Kitsara is IP Information Officer at the World Intellectual Property Organization (WIPO) in Geneva, Switzerland. This chapter is based on the findings of WIPO’s Technology Trends 2019 report on Artificial Intelligence. The views expressed are the author’s own and do not necessarily reflect the views of WIPO.