Introduction

• Author: Cepilovs, Aleksandrs
• Pages: 7-9

AI IN THE OPERATIONAL MANAGEMENT OF LARGE-SCALE IT SYSTEMS  7

1. Introduction

Over the recent decades, digitalisation has had a transformative effect on human existence, and has also been

an important driving force in public sector transformation, enabling the streamlining of public service delivery.

However, digital transformation should not be perceive d as a destination. Instead, it should be viewed as a

process of continuous development, constantly on-boarding new technologies, such as artificial intelligence (AI)

which has become one of the key variables in the equation. Although AI was mostly confined to science fiction,

laboratories and academic discussions just a couple of decades ago, to day we rely on it on a daily basis 

sometimes unknowingly. The exponential growth in big data analytics and artificial intelligence applications has

been fuelled by a combination of two factors, namely the availability of large-scale data sets and the growing

availability of distributed computing power.

When discussing artificial intelligence, it is important to distinguish it from simple automation based on pre-

programmed algorithms, which has existed for a long time. For the purpose of this discussion, we define AI as a

concept that refers to a machine or a computer programme capable of observing its environment, learning and,

based on the knowledge gained, proposing decisions or taking intelligent a ction. AI is more than simple

automation in that it has the ability to function as an autonomous actor capable of engaging in activity that has

not been explicitly pre-programmed.

The growth of computing power and avai lability of data have led to the development of new te chnologies and

approaches in artificial intelligence, which already allow machines to outperform humans in specific tasks.

Although in its current state of development AI is still far from human intelligence, as a general purpose

technology, it has great potential to transform the way organisations conduct their business, and also societies

more generally. In particular, AI offers great promise for the public sector at a time when pu blic sector

organisations are facing growing demands on their services in an increasingly complex environment.

Over the last few years, the debate around AI in the EU has picked up pace for a number of reasons. First, this is

largely due to the realisation that AI has been deployed on a very large scale by s ocial m edia and other

platforms, posing significant risks to democracy and having a significant effect on other aspects of human

existence4. Second, it has been widely recognised that the EU is lagging behind the US and China in terms of

both development and deployment of AI solutions in practice. Although the EU has been one of the leaders in

terms of basic AI research, it has trailed behind the US and China in reaping the benefits from this research 5.

Last is the expected positive economic effects (but also potential economic disruption) that can be caused by

automation using AI.

One of the essential characteristics of AI is that development of these technologies requires massive a mounts

of data. Today it is often private companies operating online platforms that possess data on the necessary scale,

rather than any single state. In this regard European enterprises are lagging behind, especially when it comes

to consumer applications of AI, including online platforms6. However, Europe is leading in terms of digitalisation

of industry (i.e. Industry 4.0) and the development of low-power computing devices, particularly relevant to the

Internet of Things (edge computing) and high-performance computing7. A common European approach to data

use a nd development of AI is thus necessary in order to avoid conflicting national initiatives and attain the

necessary scale.

4 https://www.technologyreview.com/2020/01/08/130983/were-fighting-fake-news -ai-bots-by-using-more-ai-thats-a-mistake/ or Graham et al. (2020) Artificial

intelligence in hiring: Assessing impacts on equality. Institute for the future o f work.

5 Renda A. (2019) Artificial Intelligence. Ethics, governance and policy challenges. Report of the CE PS Task Force. Brussels: Centre for European Policy Studies.

Available online: https://www.ceps.eu/wp-content/uploads/2019/02/AI_TFR.pdf

6 (ibid.)

7 COM(2020) 65 final. White Paper On Artificial Intelligence  A European appro ach to excellence and trust. Available online: https://ec.europa.eu/info/publica

tions/white-paper-artificial-intelligence-european-approach-excellence-and-tru st_en