What is AI Readiness?
AI Readiness is the extent to which any organisation is prepared to take advantage of AI. In 2017, Oxford Insights published the first Government AI Readiness Index to measure whether national governments are well-placed to exploit AI. The latest 2019 Government AI Readiness Index now has 11 metrics (compared to 9 in 2017), scoring 194 countries. Dataset was constructed using four clusters: (i) governance, (ii) infrastructure and data, (iii) skills and education and (iv) government and public services. Based on this data, Singapore ranks first in AI Readiness, with the United Kingdom in second place.
For the researchers and data scientists reading this blog, the methodology used to construct the data might be interesting to delve into. For instance, ‘data protection’ is measured using the presence – or absence – of legislation to protect citizen data (read AIBE Summit’s previous blogs for more information on privacy and regulation). Under the skills and education cluster, the size of national AI sectors is determined by the number of AI startups registered on Crunchbase. Crunchbase describe themselves as “the leading platform for professionals to discover innovative companies” (see their What We Do). Proxies like this demonstrate the novelty of the research topic.
Why does it Matter?
Preparation for AI will be key for countries to get a competitive advantage in AI, according to a report on AI readiness by Deloitte, where it is stated that “many countries believe their future hangs in the balance”. AI investment, strategy and training can make the difference between gaining a large competitive advantage and lagging behind. Out of 1900 organisations surveyed, early adopters believe that AI will be critically important in the next 2 years. Further, the window for gaining a competitive advantage is closing rapidly. Increasingly, this is becoming a national concern for governments. Many countries have published national AI strategies in the last few years (for more detail, see AIBE Summit’s last post on National AI Strategy).
Does AI Readiness have implications for global inequality?
Overall, the Index shows AI is developing unevenly. North American and Western European countries currently occupy the top rankings while African and Asia-Pacific countries have the lowest rankings on average. The trend is clear from the map below (interactive version of map here).
Government Artificial Intelligence Readiness Index 2019
“This is a timely reminder of the ongoing inequality around access to AI”
Rankings in the Index are likely to change drastically in the years to come with new AI policies. For instance, with China’s detailed AI plan, Oxford Insights points out that its’ low position in the rankings(20th) does not reflect the reality. As a result, regional-level analysis will prove important. Here are some observations by regional experts:
- Africa: there is growing interest for AI, and future Indexes may show drastic changes in the near future.
- Asia-Pacific: there is uneven progress, with Singapore and Japan in the top 10 versus North-Korea and Micronesia in the bottom 10 globally.
- Eastern Europe: the top 5 ranked countries for this region are Estonia, Poland, Russia, the Czech Republic, and Latvia. While Eastern Europe ranks higher than global average, there is also uneven progress.
- Latin America: only two countries to date have AI policies (Mexico and Uruguay), however a lack of regulation allows for experimentation without proper guidance.
Overall, it is clear that Australia, New Zealand, Western Europe and North America are above the global average in terms of AI Readiness. Yet, as Deloitte points out, AI “shouldn’t be considered a zero-sum game. All adopters can learn from one another.”
Perhaps developing countries can also find ways to counter inequality. India, for example, has uniquely planned to use AI for economic growth and social inclusion. The idea is to establish itself as an ‘AI Garage’ for effective AI strategies tailored to the developing world. Implications of AI for inequality should be taken into account by AI adopters and leaders.
Written by Tanya Beck