An Analysis of UK digital transformation and artificial intelligence industry promotion policies

2024년 6월

과학기술정보통신부

윤 홍 권

국외훈련개요

1. 훈련국 : 영국

2. 훈련기관명 : 요크대학교 (University of York)

3. 훈련분야 : 한영과학기술연수 (정책학 석사 : Masters in Public Administration with Public Placement)

4. 훈련기간 : 2022.9.12.~2024.7.11.

5. 훈련기관 소개

- 1963년 10월 230여 명의 학생, 6개 학부(정치, 경제, 영어, 교육, 역사, 수학)로 개교한 후 2024년 현재 10개의 대학으로 구성되며 총 20,480명이 재학 중(학부 15,400, 석사 3,735, 박사 1,345)

- 2012년 3월 영국의 연구 중심 대학 협의체이자 옥스퍼드, 캠브리지 대학 등을 포함한 ‘러셀 그룹(Russel Group)’에 추가

- EXEC(Centre for Experimental Economics)로 알려진 실험경제학 연구소 외 면역·감염 연구센터, 암연구소, 복잡계분석센터, 구조생물학 연구센터, 18세기학 연구센터, 국방경제학 연구센터, 중세학 연구센터, 현대학 연구센터, 여성학 연구센터, 요크전자공학센터 등을 운영 중

Table of Contents

1. Introduction

2. Literature Review

3. Policy Framework

4. Case Study

4.1. An analysis of the evolution of the UK's digital transformation and artificial intelligence promotion policy

4.2. The Korean Government’s artificial intelligence Policy Introduction and Development Process

4.3. Limitations of Data Policy Agenda Setting Necessary to Improve Korea's National artificial intelligence Level

5. Conclusion

6. References

1. Introduction

Korea ranked 6th as of 28 June 2023 in the 'Global AI Index,' announced annually by the British media 'Tortoise Media' after evaluating the artificial intelligence (AI) capacity of 62 countries (USA ranked 1st, UK ranked 4th). However, Korea has been slowing down recently, falling to 7th in 2022 after ranking 5th in 2021. Nevertheless, in the 'Government Strategy' category, Korea (6th) was higher than the US (8th) and the UK (10th). Also, it ranked 6th in the ‘2022 Government AI Readiness Index' announced by the consulting firm 'Oxford Insights.'

Therefore, this study will examine how AI has attracted attention and emerged as a policy issue in Korea and why Korea has been unable to enhance its competitiveness further. Each process is analysed using Kingdon's Multiple Streams Framework (MSF). First, we will examine whether there were independent problems, policies, and political streams until AI promotion policies surfaced in Korea and whether they could be coupled. This study assumes that the reason why Korea has not been able to enhance the competitiveness of AI further recently is that policies for 'data' to be used for AI development have not been established, and this will be a 'double structure' that analyses by applying this to MSF once again.

These courses sequentially examine Korea's policy environment and stakeholders' movements from the mid-2010s to the present. To this end, I would like to present the significance of the Information and Communication Technology (ICT) industry in Korea and why AI has emerged as a critical policy keyword. While 'data' is essential in developing AI and improving its performance, we will examine why there are limits to its use and whether there have been no policy efforts to improve it. Finally, the results of this analysis will be used to seek more advanced policy directions.

When Korea was founded in 1948, it had an underdeveloped economy that relied on agriculture, forestry, and fisheries as its primary industry. In particular, the damage from the Korean War in the early 1950s was concentrated in the manufacturing industry, and the share of the manufacturing industry in the total sector was only 13.8% in 1960 (Do-hoon Kim, 2014). The Korean military regime, which began in 1960, exported light industrial products such as textiles and plywood while implementing the 5-year economic development plan and the Export Promotion Act (1963) under development authoritarianism.

Afterwards, Korea recorded an average annual export growth rate of 41% for ten years, moving from an underdeveloped to a developing country. Entering the 1980s and 1990s, while fostering the manufacturing of electronic products such as colour TVs and semiconductors as the country's primary export industry, Korea's first annual export exceeded $100 billion (1995) (Ministry of Public Administration and Security: National Archives, 2009).

In this process, semiconductors, the most advanced electronic components at the time, surpassed 10 billion dollars in exports for the first time as a single item in 1994, ranking first among Korea's export items. Despite the even growth of various industries, such as ships and automobiles, it showed the potential of the ICT sector as a national strategic technology and industry (Jin-geun Park, 2009). In particular, the share of the ICT industry, including semiconductors, mobile phones, and displays, among Korea's total exports exceeded 30% for the first time in 2016 and reached 34% (USD 233.2 billion/USD 683.6 billion) in 2022 (Statistics Korea: ICT export/import trends, 2023).

The Korean government focused on exports and expanding and advancing domestic information and communication networks. In 1988, after finalising the basic plan for the national backbone computing network project, the first Integrated Services Digital Network (ISDN) commercial service was implemented in 1993. The existing Ministry of Post and Telecommunication was reorganised into the Ministry of Information and Communication the following year (Ministry of Science and ICT: History of Information and Communications Network Development, 2021).

Since then, Korea has ranked first in the world in high-speed Internet penetration rate announced by the OECD in 2001, and in 2002, it launched e-Government for the first time. In addition, the Korean government promoted the establishment of a broadband network (BcN) and nationwide commercialisation (2006), the launch of a pilot IPTV project through cooperation between the government and the Korea Broadcasting Commission (2006), and the commercialisation of 4G LTE service and introduction of Giga Internet in 2011.

Politicians also accelerated policy promotion by enacting the Framework Act on Informatization Promotion (1996) and the Framework Act on National Informatization (2009), and the organisation and operation of the Special Committee on Broadcasting and Communications within the National Assembly. Thanks to these efforts, Korea ranked third in ICT exports (USD 71 billion) in the first half 2015. It ranked first for two consecutive years (2015-2016) in the ICT Development Index announced by the International Telecommunication Union (ITU) under the United Nations (Korea Policy Briefing, 2016).

However, in the mid-2010s, Korea faced a so-called 'nut cracker' situation in which it lost its competitiveness as it was caught between Japan, which was experiencing an economic boom due to the low yen at the time and China, which continued to grow rapidly by investing in the ICT industry (Maekyung Economy, 2015).

The Korean government, industry, and political circles concentrated on discovering new future growth engine technologies and industries to overcome this. Meanwhile, in Korea, a confrontation event between AlphaGo, an AI Go program led by Google, and a human Go player became a major issue (9~16 March 2016). The result of this event was called the 'AlphaGo Shock' and drew public attention, and became the starting point for AI to emerge as a policy keyword in Korea.

Since then, the Korean government has focused on policies to support AI promotion and digital transformation for many years, but at the same time, the use of data resources necessary for AI learning conflicted with privacy and copyright issues, causing controversy. This issue has emerged as a new political controversy that Korea needs to address to secure AI competitiveness (Beom-su Kim et al., 2020).

In line with these times, the UK government is also trying to gain an edge in digital competitiveness. In particular, the government's strategies for accelerating digital transformation and promoting artificial intelligence technology and industry were announced one after another. The UK government's significant policies announced at the same time as the Korean government's introduction of AI promotion policies include 'Artificial Intelligence: Opportunities and implications for the future of decision making' (2016), 'UK Digital Strategy' (2017), 'AI Sector' Deal' (2018).

These can be interpreted as the UK government's policy efforts to leap forward as a digital leader. Thanks to these efforts, the digital sector contributed £151 billion to the UK economy in 2019, accounting for 9% of the country's workforce. And the coverage of the high-speed broadband network reached 97% of the UK.

The UK ranked high in all indicators in the 'Digital Society Index' evaluated by consulting firm 'Dentsu' for major countries such as the US, the UK, and Japan 2018. The UK ranked first in the 'equal development' category, including educational conditions and e-government. In addition, it ranked second in the 'dynamics' category, which evaluates the contribution of ICT to the development of the national economy. It also ranked second in the 'reliability' category, which determines whether IT is safe against the security and privacy invasion of members of society. Accordingly, the British government marked the first place in the total index.

Even after that, the UK government is speeding up digital transformation by announcing 'National AI Strategy' (September 2021, updated October 2022) and 'UK Digital Strategy' (October 2022) one after another. In this way, it will be possible to derive policy implications for strengthening Korea's digital capabilities by analysing the current status of significant UK policies in line with the introduction and development of Korea's AI promotion and digital transformation policies. In March 2023, the UK government published an ‘Artificial Intelligence Whitepaper’ to guide citizens in using AI, drive responsible innovation and maintain public trust in this innovative technology.

2. Literature Review

2.1. New Growth Engine Industries

Industry plays a vital role as a growth engine of the global economy, and a solid industrial base is closely related to higher economic growth and technological progress (IW Consult GmbH, 2013). In particular, the OECD argued in its report 'The Sources of Economic Growth' that the development of the ICT industry is an essential factor in a country's economic growth and that the rapid improvement in productivity since the mid-1990s was due to the introduction of ICT equipment in various industries (2022). However, since the 1980s, low growth has become fixed, especially in developed countries, and productivity improvement has become urgent due to demographic changes, including population ageing; growth through innovation has gradually emerged as a hot topic in the global economy (Tae-gyu Lee, 2015).

In this process, a logic was suggested that if entrepreneurs fail to properly carry out so-called 'self-discovery,' which identifies whether a particular business can make a profit, government intervention can solve the problem (Rodrik, 2004; 2008). Rodrik argued that industrial policy is discovering and building cooperation systems between the government and the private sector so companies can smoothly enter and grow in a specific industry (2004; 2008). Aghion, P. claimed that government intervention is necessary to break the 'lock-in' of the economy and that for this to succeed, government support opportunities must be open to all businesses in a specific sector (2011). In conclusion, industrial policies should be designed and promoted to upgrade the overall economy and society through innovation and technological development beyond protecting and growing specific companies and sectors (Tae-gyu Lee, 2015).

Since the 2000s, global competition has intensified as the Chinese government's investment in high-tech industries such as new materials, renewable energy, and advanced medicine has dramatically expanded. In this regard, countries such as the United Kingdom, the United States, Germany, Japan, and China have announced policies to discover new growth engine industries through science and technology innovation and implementation strategies to expand investment in R&D (Ministry of Science and ICT: Science, ICT Policy and Technology Trends, 2019). The Korean government also announced the "Comprehensive Action Plan for Future Growth Engines" in 2015 after going through the "Next Generation Growth Engine Policy" (2004-2008), "New Growth Engine Vision and Development Strategy" (2009) and "Creative Economy Realisation Plan" (2013). After mid-2016, as AI emerged as a critical technology trend, research cases such as 'Artificial Intelligence and Economic Growth (Aghion et al. 2017)', which arithmetically analysed the positive impact of AI on economic growth as a growth engine, appeared.

2.2. Digital Transformation (DT)

DT refers to processes that induce significant changes in current attributes through the appropriate combination and application of digital technologies to pursue improvement and progress in a specific subject (Vial, 2019). DT in companies is seen as seeking fundamental changes in delivering corporate operations and customer value by applying digital technology to all business areas (King, 2013). In addition, in the government or public sector, digital technology can be seen as a phenomenon that affects various systems, procedures, cultures, organisational structures, and the responsibilities and tasks of public officials (Tangi et al., 2021). Some argue that DT is a powerful alternative to overcome the limitations of the traditional economic growth strategy centred on factor input amid deepening the so-called 'new normal' paradigm represented by low growth and low employment worldwide (Young-Hyeon Jin et al., 2022).

The Korea Institute of Science & Technology Evaluation and Planning (KISTEP), a national research institute in Korea, also analysed the need for policy preparation for innovation in existing industries, such as the smartization of manufacturing and the introduction of autonomous driving, and the creation of new digital convergence services following the development of AI and networks (Young-Hyeon Jin et al., 2022).

Esra Kasapoglu, Director of AI and Data Economy at Innovate UK, The UK's national innovation agency, suggested AI, Internet of Things (IoT), Cloud, Blockchain, and Cybersecurity as technological elements that need improvement in preparation for DT. She argues that AI (especially with intelligent chatbots and deep learning) is transforming business and driving digital transformation (UK Research and Innovation, 2021).

2.2.1. The Fourth Industrial Revolution

It is a term proposed by Klaus Schwab, president of the World Economic Forum (WEF), and was discussed under the theme of 'Mastering the Fourth Industrial Revolution' at the 46th WEF held in Davos, Switzerland, on 20 January 2016. The '4th Industrial Revolution Committee', which was a government agency in Korea, defined the 4th Industrial Revolution as 'an intelligent revolution based on hyper-connectivity triggered by digital technologies such as AI and big data (The 4th Industrial Revolution Committee website: http://webarchives.pa.go.kr/19th/www.4th-ir.go.kr/)'. Klaus Schwab said that the first industrial revolution was characterised by the mechanisation of production by water and steam, the second by mass production by electricity, and the third by automation of production by electronics and information technology.

In addition, as characteristics of the 4th Industrial Revolution, 'convergence of technologies blurring the boundaries between the physical, digital, and biological realms' and 'unparalleled speed and scope of innovation and systemic changes' were cited (weforum.org, 14 January 2016). There is an opinion that AI and robots will replace human labour, and human history and life will move to another dimension. In addition, it is argued that there is sufficient motivation to call the current change the 'fourth industrial revolution' in the sense of evolving into a new paradigm in which the distinction between the natural and virtual worlds disappears (Myung-bae Yeom, 2018).

2.3. Artificial Intelligence (AI) and Data

AI is a set of technologies that mimic human intelligence, enabling computers to perform various advanced functions, including seeing, understanding, and translating speech and language, analysing data, and making recommendations (Google Cloud). In 1950, British mathematician Alan Turing described a method for testing whether a machine could think, the possibility of developing an intelligent device, and machine learning in a paper titled 'Computing Machinery and Intelligence'. The 'Turing Machine', which realised this, directly or indirectly influenced Professor John von Neumann and became the standard of modern computer architecture. It is generally seen as the beginning and dawn of AI history (Min-sik Joo, 2017).

Since then, AI has not been supported by computer performance for a while, and its development has stagnated. However, in the 2010s, as deep learning technology applied with artificial neural networks developed, AI again received experts' attention (Min-sik Joo, 2017). Afterwards, AI continues to evolve and develops into so-called 'generative AI' that can create sentences and images independently. In November 2022, the American AI company 'Open AI' put 'Chat GPT' on the market, which can generate papers, reports, and coding phrases. It is the 3.5 version of a program named GPT (Generative Pretrained Transformer), which has surpassed 100 million MAU (Monthly Active Users) within two months of its launch (Jun-hwa Jung, 2023).

The three elements of AI implementation are large-scale data, algorithms, and high-performance computers that can perform complex calculations (Songjuk Kim, 2021). In particular, more than a certain amount of data is required to train AI. The quality and quantity of this data determine the performance of AI, and data on fields to implement AI are required (Songjuk Kim, 2021).

According to a survey of AI and data companies conducted by the National Information Society Agency (NIA), a public institution in Korea, they answered that 80% of AI development time and 75% of costs are spent on data acquisition. As such, data plays a huge role in AI development (2020). For example, Chat GPT 3.0, announced in 2020, was trained with a dataset containing about 1 trillion words, and it is known that the number of parameters that AI can combine is 175 billion (Sang-heon Lee, 2023).

2.3.1. Machine Learning (ML) and Deep Learning (DL)

ML, one of the methods of implementing AI, is a bottom-up AI that starts with data in the real world, solves specific application problems, and expects to discover knowledge and rules (Byeong-hee Kim et al., 2017). It adopts a method in which the AI model learns how to solve problems using data and algorithms set by the developer (Byeong-hee Kim et al., 2017). DL is a concept included in the category of ML, and the difference is as follows (ZDNet Korea, 2017).

Machine Learning (ML)	A method in which the developer extracts the data for the AI model to learn and processes it so that the computer can recognise it, and then the AI analyses/accumulates/combines this data to derive an answer
Deep Learning (DL)	If primary data is given as it is, the AI algorithm analyses itself using CNN (Convolutional Neural Network), etc., miming the human brain structure, and then answers

Speech recognition is one of the representative AI research fields. Until the end of the 1990s, the recognition error rate for voice standard data called Switchboard provided by the National Institute of Standards and Technology (NIST) in the United States did not fall below 23% (Byeong-hee Kim et al., 2017). However, in the 2010s, Professor Geoffrey Hinton of the University of Toronto in Canada succeeded in lowering the recognition error rate from 15% (2010) → 7% (2011) → 3.5% (2015) by applying deep learning technology. From then on, DL-based AI again became the spotlight among experts (Min-sik Joo, 2017).

< AI’s ‘object in image’, ‘face in video’, and ‘telephone voice’ recognition rates improved according to the development of DL >

* Source: Recent Advances in Recurrent Neural Networks

(H. Choi, 2015)

2.3.2. AlphaGo

After acquiring 'Deepmind', a British AI startup founded by Demis Hassabis in 2014, Google established 'Alphabet' in 2015. Later, as independent corporations were established for each technology field, 'Google Deep Mind' was born. In February 2015, the company unveiled DQN (deep Q-network), an AI that can play 46 games like a human in the classic video game 'Atari 2600'. Later, in October 2015, it introduced 'AlphaGo', an AI Go player that synthesised the holding company's name and 'Go game' (ITDongA, 2016).

AlphaGo is an AI that applies a 'neural network', in which an AI trained with data automatically extracts rules or patterns and constructs a mutual relationship, and 'reinforcement learning', which induces it to discover the most rewards by itself through data learning (Ji Yeon Kim, 2017).

'Go' is a game in which two players alternately place black and white stones at the intersection of the board according to the rules. After that, the number of houses each player forms and the number of stones taken from the opponent are added, and the player with the most points wins (Foundation Korea Go Club: Go Rules). For the four countries of Korea, Japan, China, and Taiwan, 'Go' is a 'culture representing Asia' and 'a common thing' externally, and internally it is likened to a battleground where they compete for superiority to the extent that they operate multiple international competitions (Chihyung Nam, 2014).

In Go, even before the advent of AlphaGo, there was a strong perception that it would be difficult for an AI model to beat a human. The reason is that the number of decision cases in chess, which is the same board game, is 3580, whereas Go has reached 250150 (Ji Yeon Kim, 2017). Therefore, more training data was needed to increase the win rate of AlphaGo based on DL. Before the match between AlphaGo and a human Go player in Korea in March 2016, Korean Go and AI experts who participated in media interviews most predicted a human victory, and Google, the organiser, also analysed the odds as 50:50 (Korea Policy Briefing, 2016; ZDNet Korea, 2016; The Science Times, 2016). However, in 5 matches, AlphaGo won 4 wins and one loss.

2.3.3. Personal Data Protection and Copyright

Profiling and automated decision, in which AI learns a large amount of personal information to evaluate/analyse/predict an individual's interests, behaviour, location, economic situation, health, etc., can generate economic and social benefits (Korea Data Agency: Data Industry Trend Issue Brief, 2022). However, there are concerns about the asymmetry of data and knowledge holdings between developers and consumers and the leakage or identification of personal information, so the government must regulate them (Korea Data Agency: Data Industry Trend Issue Brief, 2022). In this regard, most countries' personal information protection laws, including the EU's regulation 'General Data Protection Regulation (GDPR)', reflect the personal information protection principles presented by the OECD in 1980 for personal information protection.

However, from the point of view of AI developers, it is ideal to collect as much personal information that is easy to identify as possible and use it for as long as possible, but this can cause conflicts with principles for personal information protection (Do-yeop Kim, 2022). These main principles and conflict factors for each item are as follows (Do-yeop Kim, 2022).

Principles	Detail	Conflict factor
Minimal collection	Personal information collectors and users must collect only the minimum amount of information for the purpose of personal information processing	Since the amount of data learning and the performance of AI is proportional, it is advantageous for developers to retain as much personal information as possible
Limitation of purpose	Personal information collectors and users must clarify the purpose of personal information collection and use and legally collect personal information within the scope necessary to achieve the purpose	It is difficult to specify the purpose of AI development in advance when personal information is first collected
Restriction of use	Personal information shall be stored only for the period necessary to achieve the purpose of processing and shall be immediately destroyed when the retention institution has elapsed or the achievement of the purpose has been completed	Developers benefit from the long-term retention of personal information to improve AI services and reduce bias
Transparency	Personal data subjects must be informed of the purpose and method of data processing, and the notice must be clear, concise and easy to understand	Data processing related to AI development is often complicated for the general public to understand, and the results are also difficult to explain properly

In Korea, the Personal Information Protection Act was amended so that personal information can be collected and used after it has gone through so-called “pseudonymisation,” which deletes or replaces part of personal information so that individuals cannot be identified without additional info (5 August 2020). However, controversy continues regarding the interpretation of ‘scientific research’, one of the conditions for using pseudonymised information, or the possibility of re-identification of pseudonymised information (Seung Jae Jeon et al., 2021).

In addition, a representative method of collecting data for learning AI is 'Mining', which usually goes through three steps: access to content → extraction or replication → discovery of knowledge (Gyooho Lee, 2020). However, legal restrictions on content copyright, data protection, or related contracts can become a problem, mainly in the content extraction or duplication stage (Gyooho Lee, 2020). The key issues are that the data used in the learning process of the AI model may infringe on the owner's property rights or privacy and that the copyright holder is unclear when the AI model derives similar results to the original author's work (Dae-hee Lee, 2023).

Therefore, it is argued that allowing the use of data accumulated by the Internet or the Internet of Things or legally mining the necessary data from big data for AI development is currently one of the biggest challenges in the AI industry (Sang-Yook Cha, 2021).

3. Policy Framework

3.1. AI Promotion Policies of Major Countries

Governments of each country have also been swiftly responding with policies to promote AI technology and industry. The Canadian government announced the 'Pan-Canadian AI Strategy' in March 2017. Since June 2022, over 700 AI-related initiatives have been created in 60 countries registered in the OECD's AI Policy Observatory. Among them, national-level initiatives amount to 171 (NIA: IT & Future Strategy, 2022).

First, in 2016, Korea announced the 'Mid- to Long-Term Comprehensive Plan for the Intelligent Information Society', which included promoting AI technology as a critical policy direction. This report defines the 'intelligent information society' as "a society in which new values are created and developed by combining 'AI' on data generated, collected, and accumulated through advanced ICT infrastructure and utilised in all fields of economy and society." did. Afterwards, the Ministry of Science and ICT announced the 'AI R&D Strategy', which revealed that it would invest KRW 2.2 trillion in AI R&D for five years (2018-2022) (January 2018).

In December 2019, the 'National Strategy for AI' was announced, which included ‘100 pan-governmental tasks to spread AI throughout the economy and society'. Subsequently, the 'Korea Digital Strategy', a government support measure for structural innovation of the country using digital technology, was announced, and 'to leap forward as one of the world's top 3 AI powerhouses' was presented as one of the main goals (27 September 2022).

The five countries shown below are countries classified by the NIA, a public institution in Korea, as having evenly developed AI in the private and public sectors (NIA: IT & Future Strategy, 2022). The UK announced the ‘UK Digital Strategy 2017’ in 2017, but there was criticism that it failed to present solutions to the tariff burden and talent exodus caused by Brexit (TechCrunch, 2017). However, this strategy foretells that there will be a review of how industry and government can create an environment where the AI industry can continue growing (TechCrunch, 2017).

Afterwards, ‘Growing the AI Industry in the UK’ (October 2017) and ‘AI Sector Deal’ (May 2018) presented 18 policy recommendations in 4 areas (data accessibility, talent supply, AI research, AI utilisation), which became the basis for the UK government’s AI promotion policy. In 2021, the ‘National AI Strategy’ was announced with the main goals of investing in the long-term needs of the AI ecosystem, ensuring AI advantages in all regions and fields, and operating effective AI governance.

In 2016, the U.S. government considered a leader in AI technology, released two reports containing recommendations on future AI policy directions, although not specific AI policy tasks or initiatives. These are 'Preparing for the Future of AI' (National Science and Technology Council (NSTC)) and 'National AI R&D Strategic Plan' (Office of Science and Technology Policy (OSTP)), respectively. These announcements came just five months after NSTC launched its new Machine Learning and AI Subcommittee (MLAI-SC) in May 2016. In February 2019, the Trump administration also announced 'Maintaining American Leadership in AI', an executive order in preparation for AI hegemony competition with China.

Afterwards, the 'Final report' announced by the Biden Administration's 'National Security Commission on AI (NSCAI)' argues that the malicious use of adversaries will be a significant threat in the AI era beyond the technical and industrial analysis of AI (2021).

The German government presented a plan to promote 'Industry 4.0', which is to increase productivity in the manufacturing industry through digital technology, through the 'High-tech Strategy 2020 for Germany' (2012). Then, Germany became the fourth European country to establish a 'National Strategy for AI' (November 2018), following Finland (December 2017), France (March 2018), and Sweden (May 2018). This strategy advocated 'AI Made in Germany' and differentiated it by 'respecting democratic values and social interests that go beyond technological progress' (NIA: IT & Future Strategy, 2022).

In addition, the cabinet of Prime Minister Lee Hsien Loong, who has been in power since 2004 in Singapore, announced the 'Smart Nation Initiative' in 2015 to realise a digital society, economy and government. Four years later, the National AI Strategy defined AI promotion policies as essential to realising initiatives. After announcing the 'Pan-Canadian AI Strategy', a national AI strategy in 2017, Canada has also established and operated three AI-focused technology research institutes, 'amii', 'Mila', and 'VECTOR' based on this.

3.2. Methodology for analyzing the AI promotion policy introduction process

3.2.1. Research Method: Kingdon’s Multiple Streams Framework (MSF)

Cohen and his colleagues proposed the so-called 'Garbage can model', a theory in which independent streams of problem, solution, participants, and choice opportunity coincidentally meet in a chaotic trash can to make decisions (Cohen et al., 1972). Kingdon's multiple stream frame is a theory that applies this Garbage Can Model to the policy agenda-setting process to explain the policy decision process (Ji-Hyun Song et al., 2012; Jeong-min Choi et al., 2013).

Kingdon summarised complex elements into the 'Problem stream', 'Policy stream', and 'Political stream' while maintaining the ambiguity and contingency characteristic of the Garbage Can Model. He argued that a policy window opens when each stream moves independently, and then a specific event occurs or is combined by a 'policy entrepreneur' (Kingdon, 2013).

3.2.2. Problem/Policy/Political Streams and Policy Window

First, the 'Problem stream' means that one of the immediate problems the government needs to solve emerges as an essential problem at some point and captures attention. For example, changes in indicators such as energy prices or GDP growth, issues related to safety aroused by railroad or aeroplane accidents, or policy feedback raise problems to the surface (Kingdon, 2013).

Second, the 'Policy stream' is the process of emerging alternatives to solve policy problems. Kingdon believes that various concepts and options are floating around and being tested by researchers, parliamentary staff, planning and evaluation offices, budget office staff, academics and interest group analysts, among other professional communities. These ideas continually collide, change, and sometimes, are subject to policymakers' choices. Kingdon calls it "The Policy Primeval Soup." Among them, only a few feasible alternatives can survive and be more specific and adopted as policies according to technical feasibility and value acceptability (Kingdon, 2013).

Third, the 'Political stream' is independent of the previous two streams and is influenced by public mood, election results, factions or ideologies. It is done independently of the opinion of the expert community or of raising questions to those inside and outside the government. Besides, it highly depends on the moves of the parliamentary majority or the new administration (Kingdon, 2013). Particularly, when participants in the political area sense that there is some movement, they jump into the agenda to protect their interests. This sometimes sudden entry into an agenda contributes to rapid agenda change, as their participation benefits to some degree and creates a generalised image of the movement (Kingdon, 2013).

Fourth, a 'policy window' opens when the three above streams move independently and combine. Kingdon argues that political events and topics, such as a change of administration or redistribution of seats in Congress, provide opportunities for those who demand more detailed alternatives to put their ideas to the fore. There are also times when a problem becomes urgent and offers an opportunity for proposal advocates to provide a solution (Kingdon, 2013).

In this process, streams are sometimes combined by policy entrepreneurs who define problems, find alternatives, and ask policymakers to adopt an agenda (Kingdon, 2013). Kingdon argues that they can be in and out of government, in elected or appointed positions, in interest groups or research institutions. They are willing to invest resources such as time, energy, reputation, and sometimes money in anticipation of future returns (Kingdon, 2013). This open window can be closed when participants feel that something has been enacted or decided, an action has been taken, or it has failed, or there is a personnel change in a critical stakeholder. The policy window may also close because no alternatives are available (Kingdon, 2013).

3.2.3. Case Study

In 2017, the Korean Association of Local Governments published 『An Analysis of Domestic Research Applying the Multiple Streams Framework』, which analysed 75 studies on Korean policy cases applying MSF between 2000 and 2016 and 100 policy cases mentioned here. Out of 100 policy cases, 84 were related to policy changes in the central government. Therefore, government officials took 23.9%, and the president took first and second place, respectively, with 16.7% of policy entrepreneurs (Hyunjoo Chang, 2017). These data support the argument that the presidential election and the new government's inauguration are representative political streams and events, as Korea has a robust presidential system with a single five-year term (Seokcheon Kwon et al., 2015, pp.335-362).

In addition, among 100 cases, research on science and technology policy (6) was the 5th largest among 18 policy fields, following welfare (22), education (11), government finance (8), and culture (7). Since then, IT research cases have also increased (Hyunjoo Chang, 2017). However, as of the end of August 2023, it is not easy to find previous research results that analysed the process of forming Korea's AI promotion policy according to MSF. However, studies on setting similar new ICTs as policy agendas and research cases that analysed that a specific event served as an opportunity to open a policy window can be found, as will be described in later chapters.

First, 『A Study on the Formation of ‘Big Data Policy’ in Korea Applying Multiple Stream Framework -Focusing on Rehabilitative Policy Entrepreneur- (Chin-Woo Chung, 2021)』 is similar to the ICT promotion policy, which analyses Korea's big data policy formation process by applying MSF. This study argues that Yong-Sik Moon, director of the NIA, a quasi-governmental agency in charge of consulting and executing Korea's informatisation policy, played an essential role as a 'Rehabilitative Policy Entrepreneur'.

The researcher considered those who pursue linear and gradual development while emphasising continuity, instead of radically denying past policies with high insight and expertise, as 'Rehabilitative Policy Entrepreneurs'. Director Yong-Sik Moon took over the previous government's data-oriented policy stance, selected big data as one of the 19 future growth engines, and played an important role in designing the new government's 'data economy' and 'D.N.A. (Data/Network/AI)' brand policy.

Another example is 『Kingdon’s Multiple Streams Framework and Policy Innovation: The Birth of ‘4 Major Social Hazards’ Policy (Kuk Hee Yeo et al., 2014)』, which analysed the formation process of policies to eradicate the 4 Major Social Hazards (sexual violence, domestic violence, school violence, and junk food) promoted during the Park Geun-hye government in Korea in 2013-2014. Unlike the case above, this analyses that the simultaneous occurrence of specific 'events' before the role of policy entrepreneur became a more critical trigger in opening the policy window.

This study first suggests that candidate Geun-Hye Park, who had made the elimination of social evils her main pledge just before the 18th presidential election in 2012, was elected. Almost at the same time, films dealing with the seriousness of sexual violence, domestic violence, and school violence are released one after another, and cases in which the sale of unhealthy food has been reported to the media are presented. In the end, in 2013, the Presidential Transition Committee created a policy brand called '4 Major Social Hazards Eradication' and announced the 'Comprehensive Plan for National Safety', which contained it (9 May 2013).

In addition, for this study, it was helpful to look at the policy reports announced by the Korean government in chronological order. In particular, the 'Intelligent Information Society Development Strategy (March 2016)', 'Intelligent Information Society Mid- to Long-term Comprehensive Plan (December 2016)', and 'National Strategy for AI' established by the Ministry of Science and ICT in charge of ICT and AI policies (December 2016)' and 'Digital New Deal (July 2020)' helped examine trends and changes in Korea's ICT policies.

The 'Mid-to-Long-term Comprehensive Plan for Intelligent Information Society', which will be presented as a policy outcome, is the first AI-related pan-governmental report in which, in addition to the Ministry of Science and ICT, the Ministry of Economy and Finance, the Ministry of Public Administration and Security, the Ministry of Trade, Industry and Energy, the Ministry of Culture, Sports and Tourism, the Ministry of Legislation, and the Ministry of Education participated. In addition, government reports such as the 'Annual Work Plan' and 'K-ICT Strategy' of Korean economic ministries around 2015, before AI emerged, were also referred to. In addition, the 'Korea Policy Briefing (https://www.korea.kr/main.do)' was used to read the Korean government's policy press releases and related news.

The 'Future Growth Engine Policy Evaluation (National Assembly Budget Office)' and 'The Meaning and Legislative Tasks of the Mid- to Long-term Comprehensive Plan for the Intelligent Information Society (National Assembly Legislative Research Service)' were also suitable reference materials. In particular, as it is an analysis of ICT and digital technology, Science and Technology Policy Institute (STEPI), Institute for Information & Communication Technology Promotion (IITP), National Information Society Agency (NIA), Korea Data Issue briefings and reports published by agencies and others were referred to.

Regarding data utilisation regulatory issues, 'Key Issues and Improvement Direction of Data Legislation for Development of AI Industry', a study by Attorney HwanKyung Ko, who has served as a member of the Korean government's data policy committee, was also helpful. In addition, this study emphasises that the confrontation event between the AI Go player AlphaGo and the human Go player played an important role, so cases such as 'AlphaGo Shock and the Spread of "The Fourth Industrial Revolution" Discourse (Miseon Maeng, 2017)' referenced.

In addition, reports and contributions from major Korean media outlets, including Yonhap News, Korea Economic Daily, and Maeil Business, related to this event were referred to. Research data on the reaction and prospects of the government/politicians on research-related policies and issues, as well as indicators and statistical data announced by the Korean government and public institutions, were also cited.

3.3. Advantages and Limitations of the Approach

The main strength of the MSF is that it explains well which of the many policy issues in the real world are on the agenda and which are not (Chang-young Kim, 2018). Specifically, MSF helps explain policy dynamics and is valuable in envisioning the convergence of multiple social phenomena so that 'an idea whose time has come' becomes policy (Kingdon, 1984). In addition, MSF emphasised the triggering mechanism and the dynamic interaction of various policy participants in the policy-making process.

Therefore, this model has strengths in systematically analysing the complex phenomena of policy decisions and fluctuations over a sequential flow of time (Yeonju Kim, 2018). In particular, MSF believes that the role of individuals who play the role of actors or policy entrepreneurs is essential beyond the analysis that policy processes are predictable and systemic in advance (Dong-Kyu Lee et al., 2015). Therefore, MSF will help illuminate the people and events that played an essential role in opening the policy window in the stream of issues, policies, and politics related to Korea's AI promotion policy that will be covered in this study.

However, MSF is difficult to explain the policy decision process after the policy window is opened, and there are evaluations that it has limitations in analysing the process of conflict between supporters and opponents of the policy (Sunho Yang, 2009). In addition, it has the disadvantage of poor explanatory power for changes in policy formation and implementation processes other than the process of setting new agendas (Hyun-Seok Shin et al., 2013).

MSF helped explain the process of opening the window of AI promotion policy in Korea, which is the goal of this study. However, additional research would be needed to analyse the conflicts between ministries or the coordination process before publishing the resulting policy report. Also, Korea’s AI promotion policy is gradually expanding its boundaries, such as ‘AI R&D (2018) → government-wide plan to apply AI to all industries/society (2019) → national digital strategy (2022)’. However, it is judged that MSF has limitations in comprehensively explaining these processes.

4. Findings

4.1. An analysis of the evolution of the UK's digital transformation and artificial intelligence promotion policy

4.1.1. UK‘s digital transformation policy trends

The British government announced the ‘UK Digital Strategy’ on June 13, 2022. The strategy announcement was hosted by the ‘Department for Digital, Culture, Media & Sport’. This strategy sets out a new vision to ‘leverage digital transformation and build a more inclusive, competitive and innovative digital economy.’

After announcing the initial plan, the British government announced assistive measures that British companies can use to recruit qualified foreign digital talent. As part of this, ‘Visa routes for digital employers’ was added and supplemented (October 4, 2022).

In its digital strategy, the UK evaluates itself as a country with the highest level of digital competitiveness in Europe. They also expressed their will to take this opportunity to leap forward as one of the world's best digital leaders. In fact, the digital sector's contribution to the UK economy in 2019 amounted to £151 billion. Additionally, it accounts for 9% of the country's workforce, and high-speed broadband coverage has improved to 97% of the country.

① Size of the UK’s data economy

Source : UK Digital Strategy (PDF version, 2022.7.13)

· The UK is Europe's largest data market. The data sector is growing twice as fast as other economic sectors, accounting for about 4% of GDP

· In 2021, the size of the data economy reached 125 billion pounds, twice that of France. In addition, ‘National Data Strategy21’ is being promoted as a major data-related policy

② Number of unicorn companies in major European countries

· In 2021, the number of unicorn companies in the UK was greater than the number of companies in France and Germany combined. The total number is 114

· It is analyzed that a new technology business was created every 30 minutes in the UK in 2020 (Tech Nation)

③ Venture investment amount by European country

· Venture capital investment in the UK’s technology sector in 2021 increased 2.3 times from £11.7 billion in 2020. Its size is 27.4 billion pounds.

· Investment in startups in the UK is twice that of Germany (£13.8 billion) and more than three times that of France (£8.7 billion). This accounts for more than a third of the 79.3 billion pounds invested in Europe.

4.1.2. The six axes of the UK digital strategy

The UK Digital Strategy is a government-wide measure to support strengthening digital capabilities across the UK economy and society. It consists of the following six main axes:

① Digital foundations

- This is an update on the digital regulatory plan and supply-side proposals for the digital economy. This axis includes a focus on digital infrastructure, data, regulation and digital markets, and security.

② Ideas and intellectual property

- This field is concerned with supporting the innovation ecosystem, including universities and the private sector. Emphasizes integrating government support policies based on an innovation strategy focused on digital technologies.

③ Digital skills and talent

- This highlights the UK Government's commitment to reform and improve the supply of skills and talent for the digital economy.

- It also suggests the need to strengthen the digital education pipeline and raise awareness of the path to digital jobs. In addition, work on improving digital technology infrastructure and increasing people's access to digital technologies through alternative pathways was mentioned. It further highlights the need to collaborate with the private and third sectors and support UK companies in recruiting the best global talent.

④ Financing digital growth

- Helping the UK remain one of the world's best places to start and run a digital technology business. To this end, it presents the government's will to improve the technological ecosystem.

- This area proposes improving access to finance through the British Business Bank and British Patient Capital. In addition, it emphasizes the need to introduce technological revolution throughout the economy through Fintech. It also sets out the government's support measures to make the UK the best place to list ambitious technology businesses.

⑤ Spreading prosperity and leveling up

- Presents the need to improve productivity and improve public services through technology adoption. It also provides guidance on using digital technologies to support achieving key strategic priorities such as leveling up and net-zero.

⑥ Enhancing the UK’s place in the world

- Sets out ways the UK can influence global decision-making about the evolving digital world. To achieve this, we focus on how to use our strategic advantages in digital and technology.

- Underlines the Government's commitment to maintaining the UK as a science and technology powerhouse. It then sets out how the UK government is contributing to setting global standards for digital products and services.

In particular, the British government is emphasizing the importance of education for nurturing digital talent through this strategy. The UK's Minister of Education also promised support to strengthen capabilities and access to funds for the growth of UK technology companies.

Additionally, this strategy indicates that it plans to provide the digital capabilities that the real economy actually needs. To this end, education providers, including schools and universities, and companies propose ways to cooperate. This emphasizes the importance of practical and technical training throughout one's career.

< Key contents related to education in the ‘UK Digital Strategy’ >

· Ensure that all schools in the UK have the knowledge to teach computers. As a method, we expand three digital-related education paths. Through this, 15,000 new jobs will be created by 2024-5.

· Provide Cyber Explorers program to 30,000 students. It will also create over 2,000 scholarships for AI and data science fields. Additionally, the British government is actively investing in AI doctoral-level training institutions.

· Investing £12 million in CyberFirst for cybersecurity training. Starting in August 2023, free digital competency training will be provided to adults through the digital qualification program.

In this strategy, the British government emphasized the importance of data sharing and the need for a ‘digital twin.’ Especially in 2017, the 'British National Infrastructure Commission' recommended a 'National Digital Twin' to improve the performance, services, and value provided by British infrastructure and provide benefits to society, businesses, the environment, and the economy. Then, in 2018, an organization was launched to build it.

This was carried out by launching the Digital Framework Task Group (DFTG), an organization that ensures the use of data for the public interest, within the Center for Digital Built Britain (CDBB).

Afterwards, the need to develop principles, roadmaps, and standard frameworks to ensure interoperability between digital twins was raised. To this end, the British government formed the DT Hub, an industry-academia-research network. This network is proactively promoting pilot projects based on each region.

4.1.3. An analysis of the current status of major policies for promoting artificial intelligence technology and industry in the UK

The British government announced its first ‘National AI Strategy’ on September 21, 2021. The announcement was led by the ‘Department for Digital, Culture, Media & Sport’ within the UK government. This was announced prior to the announcement of the ‘Digital Strategy’. Their main goals were to strengthen the UK's position as a global scientific leader and to enhance its AI technology potential.

This strategy derives and presents a response plan for the British government and the private sector over the next 10 years, based on the following assumptions.

▲Global competition for access to human resources, data, computing, and finance, which are drivers of AI development

▲AI mainstreaming into the economy

▲The need for governance and regulatory systems to meet rapid changes in AI demand

In addition, the following three key points were set. To achieve this, short-term (3 months), mid-term (6-12 months), and long-term (1 year or later) measures were presented.

① Investment in the artificial intelligence ecosystem

The aim is to maintain the UK’s global leadership in science and artificial intelligence technology. To this end, the British government analyzes the long-term needs of the artificial intelligence ecosystem, establishes plans, and makes investments.

· (Short-term) Government role in promoting data availability, proposal of national cyber-physical infrastructure framework, etc.

· (Mid-term) Presentation of research results related to the use of artificial intelligence for workers, support for strengthening accessibility to artificial intelligence in schools and jobs, etc.

· (Long-term) Government data support for artificial intelligence model development, presentation of national AI research innovation program, etc.

② Delivering artificial intelligence benefits to all regions and sectors

Support the UK-wide transition to an AI-based economy and capture the benefits of national innovation. This ensures that the benefits of artificial intelligence are delivered to all regions and sectors.

· (Short-term) Establishment of a draft strategy for health and social sectors through the NHS and announcement of the defense AI strategy by the Ministry of National Defense, etc.

· (Mid-term) Utilization of AI capabilities for innovation such as energy, expansion of support for innovation in developing countries, etc.

· (Long-term) Technology development in the AI field with high potential and low maturity, support for strengthening AI reliability and transparency, etc.

③ Effective artificial intelligence governance

The UK Government seeks to promote innovation and investment and protect public and fundamental values. To this end, they secure domestic and international governance for artificial intelligence technology rights.

· (Short-term) Publication of the Center for Data Ethics and Innovation (CDEI) roadmap, decision on the role of data protection in AI governance, etc.

· (Mid-term) Publication of white papers on AI management and regulation, development of standards between government ministries and pilot operation of standard hub, etc.

· (Long-term) Investment in GPAI (Global Partnership on Artificial Intelligence: Global Advisory Group) to establish and support AI governance, private sector cooperation on AI ethics in the public sector, etc.

4.1.4. An example of implementation of digitalization by sector: Review of introduction of digital pound

The British government declared the pilot introduction of ‘digital pound’ as ‘CBDC: Central Bank Digital Currency’, a digital currency issued by the central bank through the ‘Bank of England’ (February 2023).

At that time, the British Treasury, together with the Bank of England, published a consultation paper and technical paper. Afterwards, they plan to decide whether to introduce a digital pound after 2025 after gathering expert opinions and conducting technical research. Specifically, they announced that they will move into a design phase to explore the technical and policy requirements for a digital pound over the next two to three years, based on consulting documents and technical working papers.

This reflects the current British government’s will to preemptively introduce it. The Digital Pound project is being actively promoted by Prime Minister Rishi Sunak as one of the measures to improve the status of the pound, which is assessed to have weakened its position in Europe after Brexit.

In April 2022, when he was Minister of Finance, he left a social media message saying ‘We’re working to make the UK a global cryptoassets hub’ and is evaluated as being positive about cryptocurrency. In addition, it is known that the EU is also pursuing research to introduce a digital euro.

The digital pound has the same value as the actual pound currency. Additionally, unlike cryptocurrencies issued by the private sector, it is a form of digital asset issued by the Bank of England and supported by the British government. The UK government argues that a digital pound will help increase payment options. In addition, they stated that the digital pound will give consumers more choices through corporate innovation and efficient payments.

The background for reviewing the introduction of Digital Pound is as follows. The proportion of cash use in the UK is decreasing, and some believe that the emergence of new forms of currency, such as individual cryptocurrencies, could undermine financial stability. Therefore, the need for CBDC has gradually emerged in the UK.

* Source: Bank of England - Money: A question of purpose and trust(10 May 2023)

· As of 2021, the proportion of card payments including credit cards, debit cards, and prepaid cards exceeds 58%

· The proportion of cash payments has steadily decreased, falling below 15%, while other payment methods have also continued to increase, exceeding 27%

Until now, the Bank of England has been cautious about introducing CBDC. However, in January 2023, Governor Bailey took a stance in the National Assembly that ‘introduction is possible depending on public demand’ and then took a more active stance by announcing a review report.

The Digital Pound design and introduction promotion system is as follows. First, we would like to look at the main progress related to the introduction of Digital Pound.

ㅇ (March 2020) The Bank of England publishes CBDC discussion materials and begins research on opportunities, challenges and design, etc.

ㅇ (April 2021) The UK Treasury and the Bank of England jointly established the ‘CBDC Task Force’ and formed the ‘CBDC Engagement and Technology Forums’ in which industry and financial institution officials participated

ㅇ (October 2021) ‘Digital Pound Foundation’, a group of technology innovation and regulation experts to support the government’s CBDC implementation, was launched as an independent non-profit organization

ㅇ (March 2022) The Bank of England and the MIT Media Lab's Digital Currency Initiative team begin joint research on technological challenges, conflicting factors, and risks related to CBDC system design

Through this process, the British government presented the digital pound platform model. The Bank of England has unveiled the following platform model that allows various private entities to participate in the digital pound ecosystem as payment interfaces, service providers, etc.

< The Platform Model (Bank of England, 24 August 2023) >

① CBDC Taskforce

- It is jointly organized by the Bank of England and HM Treasury and takes the lead in preparing the review report. In addition, it operates a cooperative system with the Bank for International Settlements and finance ministers and central banks of G7 countries.

② Engagement Forum

- It is composed of officials from financial institutions, merchants, and civic groups. They discuss currency use cases, user requirements, roles of the public and private sectors, financial and digital inclusion, and issues related to data and privacy, rather than technical issues.

③ Technology Forum

- It consists of officials from financial institutions, universities, fintech companies, infrastructure providers and technology companies. Technical challenges in design, implementation, and operation of Digital Found's system architecture and components will be discussed in each group.

<Main discussion points by subgroup within the technology forum>

(1) Designing technical options and alias services to ensure privacy protection in Digital Found

(2) Interaction model between PIPs

(3) Core ledger technology

(4) Requirements to provide a platform for innovation

④ Academic Advisory Group

- Academics and researchers participate to present academic opinions on the introduction of Digital Pound. This is a group intended to promote interdisciplinary discussion of the ideas and related work. Therefore, the government is not obligated to comply with their recommendations.

⑤ Requests for Information

- This is a working group led by the Bank of England and the Treasury that can respond to public information requests regarding ‘offline payments’ and ‘retailer requirements’ during the digital pound design phase. They cover the feasibility of offline payment implementation, risk mitigation measures, offline payment use cases, requirements for using existing POS devices or QR codes, and e-commerce use.

However, the British public's perception of the introduction of digital pounds was found to be generally negative.

① Redfield & Wilton Strategies (consulting firm) survey (24 August 2022)

- As a result of a survey of 2,500 UK adults about the introduction of digital pounds, 30% of respondents said CBDC could be harmful to the UK. Over 24% said this could be beneficial (46% undecided). Survey respondents' specific concerns about the introduction of digital pounds are as follows.

· [73%] Asset loss due to hacking and cyber attacks

· [70%] Concern about personal information leakage

· [62%] Concern that digital assets may be confiscated by the government

· [45%] Environmental impact of digital currency (energy consumption due to mining, etc.)

② Trezor (cryptocurrency company) survey (3 July 2023)

- According to a survey of 1,037 British adults, 75% of respondents expressed concerns about the possibility of the Bank of England introducing a digital pound (CBDC) proposed by the British government. Survey respondents' specific concerns about the introduction of digital pounds are as follows.

· [73%] Control of government access to personal assets

· [67%] Concerns about imposing time conditions on spending

· [62%] Government control over what goods and services can be purchased

· [59%] Blocking certain individuals’ access to the UK financial system

· [51%] Easy tracking of all financial transactions within the UK

The future plan to introduce Digital Pound and the measures taken by the British government and parliament are as follows.

First, according to the review report, the pilot is planned to be conducted after 2025. In this regard, a rough schedule was presented that would allow a decision to be introduced in the late 2020s. In addition, in the early stages of introduction, they prepared for intensive cash withdrawals by households and businesses to hold digital pounds. For this purpose, it was initially mentioned that a holding limit of approximately 10,000 to 20,000 pounds per individual could be set.

Subsequently, on July 4, 2023, UK Finance, in which more than 300 financial institutions in the UK participate, submitted a recommendation to the Bank of England that the digital pound holding limit per person should be limited to 5,000 pounds.

The British government and the Bank of England have expressed plans to continue efforts to improve access to cash for those who may be marginalized due to the digital transformation of finance. The British Parliament is also seeking to revise the ‘Financial Services and Markets Act’ from July 2022. This introduces the concept of ‘DSAs (Digital Settlement Assets)’ and grants regulatory authority to the UK Treasury over DSA-related service providers and payment systems. The UK Treasury plans to regulate the definition and scope of digital payment assets in the future, taking into account the degree of technological development.

Korea is also actively discussing ways to build CBDC infrastructure, centered on the Bank of Korea. Meanwhile, the Bank of Korea is conducting CBDC linkage experiments between financial institutions starting in May 2023.

In the Korean National Assembly, the ‘Virtual Asset User Protection Act’, which mainly includes disclosure of virtual asset transactions and holdings, user protection, and regulation and punishment of unfair transactions, passed the plenary session on June 30, 2023. This bill excludes CBDC from the scope of virtual assets and includes provisions granting the Bank of Korea the right to request data submission from virtual asset business operators.

Likewise, in Korea, practical work is underway to review the introduction of CBDC, centered around the Bank of Korea. However, it is judged that governance structure and public participation have not yet progressed sufficiently as in the UK case.

Therefore, a detailed and systematic review of technological introduction measures must be conducted first. In addition, it is necessary to establish a promotion system for social consensus, financial consumer protection, and discussion of measures to improve laws and systems.

4.1.5. Comparison of domestic cases and implications

The UK's digital strategy seeks to expand the national digital base and strengthen intellectual property. In addition, the main focus is on the government's role in strengthening the supply of digital technology and talent and raising funds.

The Korean government's “Korea Digital Strategy,” announced on September 28, 2022, focused on preparing for the digital economy in each field and implementing a digital inclusive society and digital platform government. This is a bit of a departure from the UK's strategy.

Therefore, the Korean government also needs to focus more on nurturing human resources to support the realization of digital and AI strategies, as in the case of the UK. In addition, the government's policy capacity for financing digital industry investment and fostering related ecosystems must be strengthened.

However, the UK is pursuing comprehensive regulation, different from the direction of the EU's detailed personal information protection regulation, GDPR (General Data Protection Regulation). Therefore, there are differing opinions as to whether the effectiveness of implementing the “National AI Strategy” can be sufficiently secured.

The Korean government also announced the “National Strategy for Artificial Intelligence” (December 2019), a government-wide strategy to prepare for the spread of artificial intelligence across all sectors of industry and society, ahead of the UK.

Since then, the Korean government has been promoting periodic performance reviews and detailed strategy implementation. In the future, there is a need to further strengthen government-wide governance like in the UK in relation to the establishment of a venture ecosystem, artificial intelligence semiconductors, and expansion by field.

4.1.6. Policy Recommendation

This study focused on how 'AI promotion policy' emerged and developed as an agenda in Korea. In the 'National Strategy for AI (2019)', the Korean government set 'Innovation of AI technology competitiveness' and 'Comprehensive spread of AI use' as the No. 1 and 2 tasks. In the subsequent "Digital New Deal (2020)," "strengthening the data/network/AI ecosystem," "digital transformation of educational infrastructure," "nurturing non-face-to-face industries," and "digitalisation of SOC" were selected as critical tasks.

As such, Korea's AI policy was promoted with an emphasis on technology and industry promotion. Therefore, it seems necessary to continuously supplement policies to prepare for side effects such as malicious use of AI, biased results for gender and race, or hallucination (generating false information).

Above all, it is necessary to prepare countermeasures to reduce AI technology's abuse and side effects. In particular, it has recently been pointed out that 'generative AI' such as ChatGPT can be used maliciously, creating false content, spam messages, or fraudulent text messages (Yonhap News, 2023; Dong-A Ilbo, 2023). Therefore, it is necessary to review the introduction of regulations or surveillance systems that restrict the use of malicious AI from a policy point of view.

In addition, it will be necessary to establish a system that can track and evaluate whether the AI service is operating according to the development purpose and whether damage may occur due to errors the developer did not predict. Establishing and spreading universal and integrated 'AI ethical standards' is also necessary. Korea's Ministry of Science and ICT presented 'AI ethical standards' in 2021.

However, Korea's large corporations such as Naver, Kakao, and LG also announced individual AI ethical standards, pointing out that it is a 'three company three-colour ethical code' (The Electronic Times, 2022). Therefore, a plan to organise and operate a public-private joint AI ethics governance can be reviewed to discuss integrated AI ethics standards.

In addition, this study analyses that regulations on AI learning data that have not yet been clearly established are causing controversy in South Korea and hindering further AI development. Therefore, it seems necessary to suggest a more straightforward and rational direction for improving AI learning data regulation in the government or politics.

In particular, the current Personal Information Protection Act maintains the past regulatory frame that requires formal consent from information subjects when using personal information (HwanKyung Ko et al., 2020). To fundamentally resolve the controversy, it is necessary to revise the Personal Information Protection Act completely.

But this can lead to a waste of time and social dynamics. Therefore, regarding the use and protection of AI data, it is possible to consider enacting a special law that precedes the Personal Information Protection Act to present explicit usage and regulatory directions.

In addition, regarding the copyright of AI data, it is necessary to establish a clear path led by the government and form a consensus with the political world on whether to allow comprehensively like Japan or introduce regulations specifying the copyright of data used like in Europe. Additionally, work to form a social consensus on whether to grant legal personality to AI about recognising the copyright of AI's creations is also required.

In this process, the role of the policy entrepreneur seems to be necessary. As mentioned, Japan amended the Copyright Act in May 2018 to enable the analysis and use of existing works as data for developing ML AI. Shinzo Abe, then Prime Minister, was a policy entrepreneur who led the law revision as the "head of the Intellectual Property Strategy Headquarters" (Kyunghyang Shinmun, 2016).

As Chair of the European Parliament Special Committee on Artificial Intelligence in a Digital Age (AIDA), Romanian Member Dragoș Tudorache, who continued to insist on the need for AI regulation, led the adoption of 'The AI Act' by the European Parliament in June 2023. As such, the emergence of a policy entrepreneur who can lead issues in the setting of Korea's AI data regulation improvement policy could be the trigger. In particular, if these issues are organised and discussed at the National Data Policy Committee presided over by the Prime Minister, launched under the Data Industry Promotion Act in 2022, individual data law issues can be elevated to pan-governmental discussions.

4.2. The South Korean Government’s AI Policy Introduction and Development Process

This chapter proves the hypothesis that before the AI promotion policy emerged in Korea, there were respective streams according to MSF and that the policy window was opened by meeting specific events and actions of people.

4.2.1. Problem Stream

The Ministry of Economy and Finance of Korea diagnosed Korea's economic situation in its '2015 Economic Policy Direction', saying, "If chronic problems such as a decline in growth engines continue, low growth will become fixed. Besides, preventing a decrease in the potential growth rate will be challenging" (22, December 2014). The International Monetary Fund (IMF) also continued to lower Korea's economic growth rate forecast 2015 from 4.0% to 3.7→3.5→3.1% in its World Economic Outlook (IMF, 2015).

At the time, the Korean government described this situation as a "'Nut cracker' caught between China chasing Korea by securing technological prowess and Japan jumping again based on a weak yen" (Ministry of Science and ICT's 2015 work plan). The global market share of the 13 export items (semiconductors, wireless communication devices, home appliances, computers, automobiles, ships, etc.), which accounted for the most significant portion of Korea's exports at the time, fell from 5.7% in 2011 to 5.4% in 2015. On the other hand, the share of Chinese products for the same item rose from 15.2% in 2011 to 18.3% in 2015 (Economy Chosun, 2016).

In addition, as of 2013, it was found that Korea and Japan overlap by about 50% in major export items such as semiconductors, electronic devices, automobiles, and ships (The Hankyoreh, 2014). In this situation, the Japanese government promoted the so-called 'Abenomics', which enhances the export competitiveness of companies by inducing a weak yen through quantitative easing (Sisa Journal, 2019). At that time, the ordinary income of Japanese companies reached an annual record of 60 trillion yen in 2013 → 65 trillion yen in 2014 → 68 trillion yen in 2015 (Yonhap News, 2017).

'Nut cracker' was not a problem only the government was aware of. In November 2015, 'The Federation of Korean Industries (FKI)', one of the largest economic organisations, including most of Korea's major corporations, surveyed the top 600 companies by sales. As a result, about 90% of respondents predicted that the economic growth rate 2016 would fall below 3%, lower than in previous years (3.2% in 2013-2014 consecutive years). In particular, as the first and second most challenging factors for corporate management, they cited "reduction in sales due to sluggish domestic demand and exports" (48.1%) and "intensifying competition with companies in other countries such as China" (21.1%).

Accordingly, Korea's major conglomerates, like 'Widening the technology gap through R&D investment (Samsung Electronics), discovering new growth engines including IT services (SK Group), expanding R&D investment in automotive IT (Hyundai Kia Motors Group)', were preparing strategies for a new take-off through technology development and the discovery of growth engines (Maeil Business News Korea, 2015).

In line with this, as new digital technologies such as big data, cloud, and IoT develop, major countries such as the United States and Germany have emphasised innovation policies and initiatives to promote DT (Hae-young Lee, 2020). Meanwhile, at the 46th WEF held in Davos, Switzerland, in January 2016, the "fourth industrial revolution" was raised as a topic to explain the situation in which the development of digital technology accelerates economic and social innovation. In the Park Geun-Hye administration, the president attended the WEF in 2014, gave a keynote speech, and was so interested in the WEF that she dispatched a presidential envoy in 2016 (Business Post, 2016).

The Institute for Information & Communication Technology Promotion (IITP), a public organisation that plans Korea's ICT R&D policy, also selected 'The Declaration of the 4th Industrial Revolution at the WEF Davos Forum' as the first issue of the Top 10 domestic and foreign ICT issues in 2016. (Global Science and Technology Policy Information Service, 2017). As a result, the full name of the policy report, which is assumed to be the outcome after the policy window is opened in this study, is also the 'mid- to long-term comprehensive plan for the intelligent information society in response to the 4th industrial revolution'. This report defines the key driver of the 4th industrial revolution as 'intelligent information technology with AI at the forefront'.

4.2.2. Policy Stream

In the 2015 joint work plan report, Korea's economic ministries emphasised that they plan to 'strengthen preemptive investment to create new industries and make existing industries smarter by breaking away from the limitations of existing growth strategies' (Korea Policy Briefing, 15 January 2015).

As part of this, they announced they would promote the 'great transformation of the existing ICT industry' by supporting ICT technology innovation, fostering new industries such as the data industry and IoT, and converging existing industries and ICT. Afterwards, the Korean government decided to select '19 future growth engine industries in four significant areas' as new growth engine industries and intensively support them (24 March 2015).

< 19 Future growth engine industries (2015) >

Future new industries	Intelligent robots, wearable smart devices, realistic content, smart bioproduction system, virtual training system
Flagship industries	Smart car, deep-sea offshore plant, 5G mobile communication, vertical take-off and landing unmanned aerial vehicle
Public welfare and energy Industries	Customised wellness care, renewable hybrid, disaster safety system, direct current transmission and distribution system, micro power generation system
Base industries	Convergence material, intelligent semiconductor, IoT, big data, advanced material processing system

* Source: Korea Policy Briefing (24 March 2015)

The day after announcing this plan, the Korean government announced the 'K-ICT Strategy' (Korea Policy Briefing, 2015). This strategy presented the goal of investing 5 trillion won by 2020 to achieve an 8% growth rate in the ICT industry, 240 trillion won in ICT production, and 210 billion dollars in exports by 2020. In addition, it contains tasks such as strengthening support for ICT R&D and start-ups, creating new demand for ICT convergence, and strategically fostering the new SW industry. Regarding this, some media commented, "The 'K-ICT Strategy' announced by the government is a declaration that ICT will once again be promoted as a driving force for national economic growth" (The Electronic Times, 2015).

Afterwards, the Ministry of Science, ICT and Future Planning announced its annual work plan on 27 January 2016. Until now, AI had rarely appeared in policy reports in Korea, but in this plan, ‘responding to the information revolution with intelligent information technology’ was presented as one of the 16 tasks (Korea Policy Briefing, 2016).

In the press release, the Korean government defined “intelligent information technology” as “a technology in which software or machines analyse data and learn on their own,” which is very similar to the dictionary definition of ML.

Representative policies include an investment of 30 billion won in intelligent software development, establishing an “Intelligence information technology Institute” centred on universities, research institutes and companies, attracting foreign scholars, and building and opening valuable data. Of course, the word AI was not even mentioned in this report. However, from 2015 to early 2016, the Korean government strengthened support for discovering growth engines and innovation in the ICT industry.

4.2.3. Political Stream

The market-friendly Park Geun-Hye government, which took office in March 2013, presented the 'creative economy' as a paradigm for growth, with 'creativity as a core value and creating added value and jobs through the convergence of ICT, industry and culture' (Hyung Baek Lim, 2015, pp.15-44). After taking office, President Park established the Ministry of Science, ICT and Future Planning, the predecessor of the current Ministry of Science and ICT, to oversee the creative economy's design and implementation.

At the time, the agreement on revising the Government Organization Act between the ruling and opposition parties also included the content that the Ministry of Science, ICT and Future Planning would enact a special law to oversee ICT industry promotion policies. The agreement also included the content that the Ministry of Science, ICT and Future Planning would enact a special law to oversee ICT industry promotion policies (Newspim, 2013).

Therefore, the 『Special Act on the Promotion of Information and Communications and Convergence, etc.』, newly proposed on 5 June 2013, passed the plenary session of the National Assembly in 28 days. The enactment of this law is significant in that it highlighted the policy goals of the new government for the promotion and vitalisation of ICT convergence and established the importance and status of the ICT industry in the creative economy paradigm (Changgeun Hwang, 2014, pp.465- 485).

Even after that, the ruling and opposition parties continued discussions to discover future growth engines for Korea. On 10 April 2014, Gun-Hyun Lee of the ruling party and Sang-Min Lee of the opposition party co-hosted a debate titled "Future Growth Engine Science and Technology Policy Proposal". The event was attended by around 150 people, including representatives of the ruling party, government officials, science and technology and ICT academia, research, and industry (Good Day News, 2014).

Jang Seok-in, a senior research fellow at the Korea Institute for Industrial Economics and Trade (KIET), who was in charge of the presentation at the time, proposed ‘Fostering new industries including big data and cloud’ and ‘fostering high value-added content industries based on ICT’ as policy tasks that require achievement within three years (National Assembly Electronic Library, 2014).

Entering 2015, the National Assembly was also seeking legislative measures to boost economic vitality by promoting the introduction of new technologies and industries. At the time, the ruling party announced the enactment of the ‘Special Act on Corporate Vitality Enhancement’ (aka ‘One-Shot Act’), which facilitated business restructuring and entry into new industries by providing tax benefits and easing requirements for mergers and acquisitions.

Article 2 (2) of this Act limited ‘business reorganisation’ to ‘promoting business innovation, such as entering a new business or introducing new technology.’ Finally, the bill passed the plenary session of the National Assembly on 4 February 2016, 210 days after it was proposed (The Korea Herald, 2016). This legislation is evaluated as a measure to help companies voluntarily overcome oversupply and foster new industries at a time when industries such as semiconductors and automobiles have passed their peak and are entering a recession phase (Chang Sop Shin et al., 2017, pp. 145-198).

4.2.4. Policy Window and the Event

Google DeepMind announced to the media that AlphaGo, an AI Go player, would play against Lee Se-dol, a Korean player with 21 years of professional experience and the previous world No.1 (28 January 2016). Many members of the National Assembly, including the ruling party's floor leader and the head of the opposition party's Emergency Response Committee, and government figures such as the Minister of Science, ICT and Future Planning, and the mayor of Seoul watched the game in real-time. As mentioned earlier, contrary to the expectations of many Go and AI experts in Korea, AlphaGo won 4-1.

Regarding this result, the majority of Korean media as well as the president, expressed it as an "AlphaGo shock" at an official meeting. A study titled 'AlphaGo Shock and the Spread of "The Fourth Industrial Revolution" Discourse' asserted that "the dystopian imagination that AI could outperform and dominate humans rapidly emerged in Korean society at the time" (Miseon Maeng, 2017). The National Assembly's Legislative Research Office also analysed, "It can be said that interest in national policies targeting 'AI' and 'intelligent information society' more clearly amplified after the Go match between Lee Se-dol and AlphaGo in early 2016" (Woo-min Sim, 2017).

Two days after the contest ended, a policy entrepreneur appeared who played an important role in opening the window for AI promotion policies. On 17 March 2016, President Geun-Hye Park invited 20 AI and software experts to the Blue House (the Korean presidential residence) and held an “Intelligence Information Society Experts Meeting” (Korea Policy Briefing, 2016).

President Park said, “It was paradoxically fortunate for us that we were greatly alerted and stimulated by the importance of AI development before it was too late with the AlphaGo shock” (Korea Economic Daily, 2016). In addition, she asked the government to analyse the ‘mid- to long-term impact’ of the progress of the intelligent information society and prepare thoroughly (Korea Economic Daily, 2016).

At the Cabinet meeting on 17 April 2016, it was announced that the Ministry of Science, ICT and Future Planning would lead in establishing a 'mid- to long-term comprehensive plan' for an intelligent information society within 2016 (Korea Policy Briefing, 2016). Policy opinions were gathered the following month through a meeting with about 30 people, including officials from each ministry and private experts, and six public seminars. In September 2016, the 'Intelligent Information Society Promotion Team' was launched, which consisted of 29 personal experts and officials from six ministries to supervise the establishment of the policy.

Finally, on 27 December 2016, the 'Information and Communications Strategy Committee', the Prime Minister's final deliberation body for ICT policies, decided on the 'mid- to long-term comprehensive plan for the intelligent information society' (Korea Policy Briefing, 2016).

AI-related forums were also established one after another in the National Assembly. On 8 June 2016, 33 ruling party members jointly launched the 'National Assembly Future Strategy Forum (aka 'Alpha Forum')' to discuss legislative measures related to AI, robots and IoT (Sisa Journal-e, 2016). On 28 June 2016, three lawmakers from the 1st to 3rd parties, who were experts in science and ICT, co-founded the ‘4th Industrial Revolution Forum of the National Assembly’ with about 30 members participating (YTN Science, 2016).

Since then, the National Assembly has successfully proposed basic laws such as ‘Basic Act for Intelligent Information Society’ (February 2017), ‘Basic Act for Promotion of the 4th Industrial Revolution’ for the establishment of the ‘4th Industrial Revolution Strategy Committee presided over by the Prime Minister (March 2017) to promote AI's safe and effective use.

4.3. Limitations of Data Policy Agenda Setting Necessary to Improve Korea's National AI Level

In Korea, discussions on data policy, the most crucial resource in the development and advancement of AI, were also continuing. However, the policy window for freely utilising data for AI learning or creating a framework for utilisation is not clearly open. In particular, various other interests in personal information and copyright can inhibit each stream's coupling.

4.3.1. Problem Stream

According to the 'ICT Technology Level Survey Report' released annually by IITP, a public institution in Korea, the technology gap between the US and Korea, the leading countries in AI technology, is on the decline, from 2.2 years in 2016 to 1.3 years in 2021 (IITP, 2023). However, after rapidly narrowing the gap from 2.2 years in 2016, when the AI promotion policy began in Korea, to 1.5 years in 2019, the pace of the chase slowed to 1.4 years in 2020 and 1.3 years in 2021 (IITP, 2023).

The level of data utilisation in Korea announced in 2018 by the International Institute for Management Development (IMD) in Switzerland ranked 31st out of 63 countries, and the size of the data-related market was also investigated at 1/400 of the US. It was suggested that the reason is that it is difficult for companies to use data for industrial purposes because Korea's personal information protection regulations are intense and criminal punishment is oriented (HwanKyung Ko et al., 2020).

A representative example is the case of personal information leakage of 'Iruda', an interactive AI service launched by AI startup 'Scatter Lab' in December 2020. To develop an AI chatbot set for women in their 20s, this company collected 100 million messenger conversation records from women in that age group and used them for AI learning without consent. Some of the personal information contained herein was exposed in the generated conversation (Seung Jae Jeon et al., 2021, pp.103-133).

Eventually, the service was temporarily suspended on 11 January 2021, about three weeks after its launch (relaunched on 27 October 2022). Korea's Personal Information Protection Act stipulates' restrictions on the use and provision of personal information for other purposes (Article 18)' following the 'Principle of Personal Information Protection' presented in Chapter 2.3.3 of this study. In this regard, the Personal Information Protection Commission judged that Scatter Lab did not accurately notify the purpose of collecting personal information and imposed a total fine of about KRW 100 million (Seung Jae Jeon et al., 2021, pp.103-133).

Dae-Seop Song, director of policy research at Naver, claimed, “Although this case is a matter of individual startups, the actual impact on the overall AI industry is huge, and AI development attempts may be discouraged.” at a webinar hosted by the Seoul National University AI Policy Initiative (The Electronic Times, 2021).

In addition, with the spread of 'generative AI' such as chat GPT, there is a conflicting position on the copyright of the data used by AI for learning. Article 35-5 of the Copyright Act of Korea stipulates that "a copyrighted work may be used if it does not conflict with the general use of the copyrighted work and does not unreasonably harm the author's interests".

However, it is pointed out as a cause of conflict that there is no provision stipulating whether AI learning falls under this case (Yong-woo Shin, 2023). Along with this, the issue of whether AI creations can be recognised as copyrighted works under the Copyright Act and, if admitted, whether copyright belongs to them has yet to be resolved (Sang-Yook Cha, 2020, pp.5-69).

4.3.2. Policy Stream

The Korean government mainly promoted expanding data supply and presenting guidelines as a data policy for AI learning. For example, the Korean government, which started building 'AI learning data' that any Korean or company can use without legal problems in 2017, released a total of 21 types (33.5 million cases) of data to ‘AI Hub’ (www.aihub.or.kr) as of the end of 2019 (Korea Policy Briefing, 2019). In particular, the Moon Jae-in administration (2018-2022) announced the 'Digital New Deal' on 15 July July 2020, to invest 44.8 trillion won in government funds by 2025 to respond to the spread of non-face-to-face due to Corona 19 and promote DT (Ministry of Science and ICT Press Release, 2020).

Among them, the representative policy was to drastically increase data from 21 to 1,300 types by investing 2.5 trillion won by 2025. After amending the Personal Information Protection Act (8 August 2020) so that personal information can be pseudonymised and used, 'Pseudonymized Information Handling Guidelines' (24 September 2020) and official commentary (2 December 2020) were announced to reduce confusion. In addition, 'Guidelines for Data Utilization and Processing in the Health Care and Education Field' (30 December 2020) and 'AI Developer's Self-Checklist for Violation of the Personal Information Protection Act' (20 July 2021) were also presented.

However, this approach also had limitations. After the change of government in 2022, the budget for building data for AI learning decreased by 51.6% from 579.7 billion won (fiscal year 2022) to 280.5 billion won (fiscal year 2023). Regarding this, some media outlets reported that "a controversy called 'erasing the former government project controversy' may arise" (Digital Daily, 2022). In addition, the 'Coalition for Economic Justice', one of Korea's most influential civic groups in the economy, said, "Personal information is at risk due to the government's congested data use policy." They pointed out that government policies are focusing on industry promotion rather than citizens' right to personal information self-determination (Daily Pharm, 2019).

In addition, on 24 February 2023, the Korean government launched the 'AI-Copyright Law System Improvement Working Group' with the Ministry of Culture, Sports and Tourism at the centre (Korea Policy Briefing, 2023). The working group, which included figures from academia, law, and industry, announced that it would discuss 'Measures for smooth use of works used for AI learning data', 'Issues of the legal status of AI outputs and whether they are recognised in the copyright system', 'Copyright infringements that occur when using AI technology and measures to regulate liability for them' and more. However, the consultative body supervised by the Ministry of Culture, Sports and Tourism, which operated from July to October 2021 to discuss similar topics, ended without producing government policy or legislation.

4.3.3. Political Stream

Politicians were also contemplating legislation to balance data use and personal information protection. In November 2018, the ruling party proposed an amendment to the 'Three Data Acts' (Personal Information Protection Act, Credit Information Act, and Information and Communications Network Act). The purpose of the law revision was to reorganise the regulations dispersed by each ministry, focusing on the Personal Information Protection Act and expanding the scope of personal information utilisation by individuals and companies (Jaecheon Park, 2020).

This amendment eventually passed the plenary session of the National Assembly in January 2020 and was implemented in August of the same year. However, concerns were also raised about the effectiveness of the revised law. The revised law introduces the concept of 'pseudonymised information', which is processed so that a specific individual cannot be identified without additional information, and stipulates that it can be used (Korea Policy Briefing, 2020). Nevertheless, it takes enormous cost and time to pseudonymise large-scale digital data to a level where individuals cannot be identified.

Therefore, it is believed that it will be difficult to sufficiently secure data essential for vitalising the AI industry (HwanKyung Ko et al., 2020). In addition, Professor Seong-Yeop Lee of the Korea Data Law Policy Society at Korea University argued that "When additional personal information is used, it is stipulated that it must be significantly related to the original purpose of collection, which may limit the use and development potential of AI" (TECH M, 2020).

Under these circumstances, the National Assembly pushed for legislation to promote data utilisation. On 28 September 2021, the 'Basic Act on the Promotion and Use of Data Industry' passed the plenary session of the Korean National Assembly. Some argue that this law can neutralise the protection of personal information because it is designed to view data as 'economic goods' from an industrial point of view, provide grounds to support the production, transaction, and utilisation of data, and minimise regulations (Jungnyum Lee, 2022, pp.265-296).

In addition, on 15 January 2021, Jong-Hwan Do, a member of the National Assembly who served as the first Minister of Culture, Sports and Tourism of the ruling party at the time of the ruling party, proposed an amendment to the Copyright Act to allow data mining for AI learning. This amendment stipulates that 'in the case of analysing a large amount of information, including multiple works, through automated analysis technology using a computer, the copyrighted work may be copied and transmitted' (Sang-Yook Cha, 2021, pp.1-55). In addition, on 31 October 2022, Yong-Ho Lee, a ruling party member, proposed an amendment to the Copyright Act to allow 'crawling', which automatically collects and stores data from Internet websites for ML.

On 30 June 2023, Dong-Hyuk Jang, a ruling party member, co-hosted a seminar, 'Activation of the AI Industry and Harmony of the Copyright System', with the Korea Copyright Law Association. Participants discussed the disclaimer for TDM (Text & Data Mining) for AI learning proposed by Jong-Hwan Do. Organizer Dong-Hyuk Jang said before the seminar, "I look forward to discussing a realistic copyright law revision bill that takes into account the interests of right holders and at the same time does not hinder the vitalisation of the AI industry" (The Electronic Times, 2023).

The National Assembly Research Service in Korea also claimed, "In order to harmonise the development of the AI industry and the protection of creators' rights, it is necessary to activate legislative and policy discussions on the status and rights protection of digital content creators" through a report titled 'Main Issues Related to Copyright of AI Creations' (Jimin Kim, 2022).

4.3.4. Policy Window and the Policy Entrepreneur

After the revision of the 'Three Data Acts', there is a conflict between the claim that additional personal information deregulation is necessary for AI development and the need to strengthen personal information protection. On 30 March 2023, Attorney Koo Tae-eon, who participated as a panellist in the discussion on 'Startup, Utilization and Protection of Personal Information' hosted by Member of the National Assembly Byung-won Kang, made the following remarks. "Current privacy laws are heavily regulated, reducing data availability and hindering AI development. Even Naver, the largest company in Korea, has no choice but to use Chinese data.“

And he pointed out that the current system that regards and regulates even simple information processing as personal information should be improved (Seoul Economic Daily, 2023). On the other hand, on 15 July 2023, a media company published a feature article titled 'Two Faces of Artificial Intelligence: Regulations on 'ChatGPT', a black hole of sensitive information?' (Media Today, 2023). The article pointed out, "Korean IT companies are urging the relaxation of related regulations, saying that personal information-related regulations can become an obstacle in competing with overseas operators such as Google and OpenAI.

On the other hand, unlike the global trend of discussing strengthening regulations, civil society is concerned that this discussion is being pushed to a lower priority". The European Parliament adopted 'The AI Act' on 14 June 2023, which regulates AI services by classifying them into four categories: 'unacceptable risk, high risk, limited risk, and minimal or no risk'. This bill, which banned facial recognition AI in public places, is evaluated as a regulation emphasising data sovereignty, personal information, privacy protection, and security (Law Times, 2023). On the other hand, in Korea, the AI Basic Act, which aims to foster the AI industry, was proposed in 2021 and is still pending in the National Assembly as of the end of August 2023.

On 22 March 2023, five civic groups, including the People's Solidarity for Participatory Democracy, held a joint press briefing and pointed out, "Far from preparing a legal system to protect the safety and human rights of the people, there is a high possibility that it will hinder the introduction of legitimate regulations by introducing the principle of 'priority permitting, post-regulation’ only for industry development." to this bill (People's Solidarity for Participatory Democracy, 2023).

In addition, on 21 July 2023, the Korean government announced the ‘Strategy for Digitalization of the Service Industry’ (Korea Policy Briefing, 2023). This strategy included ‘revising the copyright law to establish requirements and grounds for immunity from copyright infringement in the case of using data for AI learning’. However, a counterargument was immediately raised against this, saying that “a comprehensive exemption clause could discourage the content industry from investing and incite disputes” (Munhwa Ilbo, 2023).

In addition, it was argued that the amendments pursued by the government do not have specific exemption criteria and that there are no apparent restrictions on the commercial use of data by AI developers (Dong-A Ilbo, 2023). On 29 March 2023, the Korea Music Copyright Association announced a statement of opposition to the revision of the Copyright Act, which allows AI to use existing works as learning data without restrictions, infringing on the rights and interests of copyright holders, and launched a response TF (Yonhap News, 2023).

In fact, as of the end of August 2023, all of the amendments to the Copyright Act proposed by Jong-Hwan Do and Yong-Ho Lee mentioned above are still pending in the relevant standing committee.

Unlike the AI promotion policy, in which the president acted as a policy entrepreneur following the "AlphaGo shock" in 2016, no policy entrepreneur has emerged to lead the 'data utilisation' regulation improvement policy issue. Regarding this situation, a media claimed, "Politicians, conscious of elections, were hesitant to reform in the eyes of vested interests, such as existing operators and interest groups, creating an environment in which the engine for future growth was forced to turn off" through the column published on 21 June 2023 (Yonhap News, 2023).

5. Conclusion

Since the 1990s, Korea has fostered ICT as a critical growth engine to achieve economic growth and become recognised as a powerhouse in ICT technology and industry. However, in the mid-2010s, the ICT industry was losing its competitiveness little by little, and all Korean businesses, governments, and politicians focused on discovering new growth engine technologies and industries amidst the global digital transformation. Meanwhile, in early 2016, the so-called 'AlphaGo Shock', in which an AI Go player won over a human, served as an opportunity to emerge AI as a keyword in the government and politics. Right after the event, President Geun-Hye Park ordered the preparation of mid- to long-term comprehensive measures to prepare for the spread of AI, and the AI promotion policy in Korea began in earnest. In other words, the topical event mediated by AI and the president's reaction as a policy entrepreneur played an essential role in coupling each stream.

However, as regulations on the use of 'data', an essential resource for AI development and performance improvement, were not clearly established, Korea was having difficulty improving AI competitiveness. In particular, as ML and DL emerged as crucial AI technologies, securing large amounts of data for AI learning has become an important task. However, there was a conflict between the opinion that the collection and use of data should be comprehensively allowed for AI development and the view that the use of data should be regulated to protect personal information and copyright. The government and political circles have proposed various measures and legislative proposals to solve this problem, but no clear standards or legislation have been established. In this regard, one of the causes is the absence of a policy entrepreneur who can lead the policy agenda-setting in the face of opposition controversy.

Lastly, to further enhance Korea's AI competitiveness, it is necessary to consider alternatives that can overcome and supplement the side effects of AI utilisation along with the promotion of technology and industry. Besides, regarding the regulation of AI data, the government and politicians propose a way to provide a more precise direction together.

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