ARTIFICIAL INTELLIGENCE AND GROWTH

Abstract
Artificial Intelligence is intelligence of machines, in contrast to the natural intelligence displayed by humans. Technology is a shaping factor in growth of economies; traditional growth theory in economics explained the development basing on the population growth, but human factors and labour skills in globalised economies largely explain the differences in growth rates among countries. The evolution of AI had strong impact on the labour market in the globalised economy; AI crowded out unspecialised workers and low value added firms, by allowing highly technological firms to provide goods and services at a fraction of the price, thanks to automated processes. In  2019 the OECD and G20 countries agreed on AI principles in order to restore confidence, respects human rights and democratic values.


The digital revolution allows Governments to have access to better data; digitalization allows for greater storage and tracking of information through electronic records, linking of data registries between different parts of government, and enhanced capabilities to handle and analyse large data sets (IMF 2017, p.1). Many countries are already finding that it costs less to collect taxes, deliver public services, administer social programs, and manage public finances. For example, the introduction in Italy in 2019 of the electronic bill allowed the Treasury to collect more than € 2billion euro in less than six months.
Artificial Intelligence is intelligence of machines, in contrast to the natural intelligence displayed by humans. Artificial intelligence can be classified into three different types of systems: analytical, human-inspired, and humanized artificial intelligence.
Analytical AI has refers to cognitive intelligence; generating cognitive representation of the world and using learning based on past experience to deliver future decisions. Human-inspired AI refers to cognitive and emotional intelligence; understanding human emotions, in addition to cognitive elements, and considering them in their decision making. Humanized AI has characteristics of all types of competencies (i.e., cognitive, emotional, and social intelligence). Pedro Domingos, professors at the University of Washington, contributed with a book to widespread the basic knowledge and problems in this complex field (The Master Algorithm).
The traditional problems (or goals) of AI research include reasoning, knowledge representation, planning, learning, natural language processing, perception and the ability to move and manipulate objects (Domingos 2015). General intelligence is among the field's long-term goals. Approaches include statistical methods, computational intelligence, and traditional symbolic AI. Many tools are used in AI, including versions of search and mathematical optimization, artificial neural networks, and methods based on statistics, probability and economics. The AI field draws upon computer science, information engineering, mathematics, psychology, linguistics, philosophy, and many other fields.
Artificial intelligence allows for precise identification of individuals and their associated activities, to monitor and record biometric characteristics providing a unique, secure, and less-costly alternative to more traditional paper-based official documentation systems. In many developing countries, this technology has allowed governments and citizens the means to study the interconnections of citizens, raising certain problems with respect to privacy of data (Big Data, privacy & state).
In the private sector, the constant recording of digital information in real time has given rise to a data economy; businesses are already buying and selling these data, and using them in conjunction with artificial intelligence algorithms to better target their advertising efforts and business models (IMF 2017, p. 3).
Technology is a shaping factor in growth of economies; traditional growth theory in economics explained the development basing on the population growth, but human factors and labour skills in globalised economies largely explain the differences in growth rates among countries. In classic economic theory the growth of the economy is given by capital (K), labour (L) and technology (sigma). Capital is fixed in the short term, and labour depends on population; technology evolves in a non linear fashion and strongly contributes to growth.

                                                    Y = f(K, L, sigma)

Economic models do not consider the level of capital/labour, but often rely on variation of labour and capital (i.e., the productivity that is given by the variation of capital/labour with respect to production Y).
The evolution of AI had strong impact on the labour market in the globalised economy; AI crowded out unspecialised workers and low value added firms, by allowing highly technological firms to provide goods and services at a fraction of the price, thanks to automated processes. The Bill & Melinda Gates Foundation (https://www.gatesfoundation.org/) has been among the first to underline the structural risks beyond this evolution, since the AI structurally reduces the demand for labour in Western countries, while tax revenues of States did not compensate the reduced wellbeing and consumption (Digitalisation and Taxation).
The OECD monitors the evolution of innovation and technology and their impact on labour and capital productivity; details data, reports and statistics are available here https://data.oecd.org/innovation-and-technology.htm). The OECD adopted in May 2019 the Principles on Artificial Intelligence (https://www.oecd.org/going-digital/ai/principles/); they promote artificial intelligence (AI) that is innovative and trustworthy and that respects human rights and democratic values. The OECD AI Principles are the first such principles signed up to by governments. Beyond OECD members, other countries including Argentina, Brazil, Colombia, Costa Rica, Peru and Romania have already adhered to the AI Principles, with further adherents welcomed.
In June 2019 G20 countries agreed on guiding principles for using artificial intelligence, which are created based on those adopted last month by the 36-member OECD and an additional six countries. The G20 guidelines call for users and developers of AI to be fair and accountable, with transparent decision-making processes and to respect the rule of law and values including privacy, equality, diversity and internationally recognized labor rights. These principles push governments to ensure a fair transition for workers through training programs and access to new job opportunities. It is important to note that China and Russia are among the G20 participants but did not undersigned the OECD principles. The Japanese presidency of the 2019 G20 underlined the need for the free flow of data across borders based on trust (Data Free Flow with Trust – DFFT).

References
Domingos Pedro (2015) The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, Penguin, New York.
G20 (2019) Ministerial Meeting on Trade and Digital Economy, June 8-9, Japan https://g20.org/en/documents/
International Monetary Fund (IMF) 2017. Digital revolutions in public finance. Edited by Sanjeev Gupta, Washington, DC, ISBN 9781484315224.
OECD (2019) Principles on AI, May 22, Paris. https://www.oecd.org/going-digital/ai/