It is widely believed that business is the only most effective source of real innovations and the added value. However, states are gradually becoming strong supporters of innovation, and state-funded innovation programs are making a significant impact on the evolution of mature tech such as artificial intelligence (AI).
Achieving a successful digital transformation by leveraging AI technologies can yield $1.2 trillion in added value until 2021 globally, according to the AI Conference Kyiv 2018. Modern-day cases of AI implementation prove businesses are able to boost their overall productivity by at least 20%. However, one of the most burning questions today is whether AI mass adoption will create havoc and bring about dramatic unemployment to most of the industries, or whether these fears are far-fetched and the positive effects of using AI will outweigh the negative expectations.
No doubt, AI is increasingly affecting our lives and day-to-day routine:
- AI-based decision-making systems are used extensively in FinTech to detect and prevent fraud;
- We rely on high-tech AI-based medical tools to detect rare diagnoses;
- AI-based algorithms analyze search queries to formulate comprehensive recommendations, etc., etc.
On the one hand, the AI industry is facing tremendous challenges and impediments, including:
- The lack of quality data and computational powers;
- Big data safety;
- Human capital: a strong demand for HR reskilling and upskilling, as well as strategies to address future unemployment as a result of robotics and AI evolution;
- Intellectual property: new realms and perspectives as well as new types of AI copyright infringements.
On the other hand, we see a growing competition for the global dominance of Artificial Intelligence; this competition is becoming more and more fierce, as more countries enter the arena.
Over the past 2 years, many South American, European and Asian countries have announced their AI strategies for the months to come. Governments all over the world view AI adoption at the state level as a #1 priority as far as innovation is concerned, and they tend to collaborate with the local and international businesses to fund the creation of AI R&D centers, special new curricula to help retrain people as well as create new policies and build a legal framework for the new AI-driven epoch.
According to Olga Samoylova, PM for Innovations Development at Ukraine’s Reforms Delivery Office, today’s Top 3 AI geographies are:
- USA (accounts for 66% of all global investments in AI developments);
- China (accounts for 17% of all AI investments globally);
- EU (has invested EUR 1.5 billion in AI R&D through their Horizon 2020 project).
To give you some real-world examples of the size of investments, China has one of the most comprehensive national AI development plans and is investing at least $7 billion on a year-on-year basis through 2030, including $2 billion for the construction of a research park in Beijing.
Although the US has no central AI policy, some individual projects are funded by paramilitary and military units like IARPA and DARPA. The country is yet far behind the governmental support of its AI strategy, and most of AI research is funded by academia and private companies.
The UK government is contributing $30 million to build AI tech incubators all over the country, while some VC firms such as Global Britainand Chrysalixare pledging over $150 million funds to encourage more AI developments in the country.
Being one of the first countries in the world to have recognized the value of AI, Canada has made a $125 million commitment to AI research back in 2017. Now Canada is one of the most active recruiters of AI talent in an attempt to “play off the nationalist rhetoric coming out of the White House” after Donald Trump’s election as the US President.
All countries can be divided into 3 separate clusters in terms of their strategic approaches to AI implementations:
- Countries that foster and promote AI adoption by setting up completely new institutions to create national AI policies, legal frameworks and collaboration between stakeholders (e.g., EU).
- Countries that foster AI innovation through existing ministries and departments (e.g., Ukraine, USA)
- Countries that use a hybrid model to foster continuous win-win collaboration between the public and private sectors (e.g., Japan, China).
Furthermore, all countries are different by their key objectives of streamlining AI adoption. For instance, Finland is looking to become a regional leader for AI implementations rather than developments. The country deliberately tends to transform into an AI hub to be able to attract the best tech talents, generate additional revenues, and increase the wellbeing of its population by automating most of the workflows.
As mentioned above, intellectual property protection comes to the forefront when it comes to AI strategy developments. For example, many countries’ existing patent/licensing legislations still refer to “an inventor” as “a human being”. This will no longer be relevant in the near future when some new inventions are created by machines (thanks to deep learning, NLP and other AI technologies), not humans.
Or how will discrimination be perceived and treated when robots become part of our daily life (like smartphones today)?
AI ethic policies have yet to be put in place to ensure transparency and traceability of data processing, data privacy, protection of basic rights, and freedom from any form of discrimination.