Hard Law or Soft Law? –Global AI Regulation Developments and Regulatory Considerations
Hard Law or Soft Law?
–Global AI Regulation Developments and Regulatory Considerations
2023/08/18
Since the launch of ChatGPT on November 30, 2022, the technology has been disrupting industries, shifting the way things used to work, bringing benefits but also problems. Several law suits were filed by artists, writers and voice actors in the US, claiming that the usage of copyright materials in training generative AI violates their copyright.[1] AI deepfake, hallucination and bias has also become the center of discussion, as the generation of fake news, false information, and biased decisions could deeply affect human rights and the society as a whole.[2]
To retain the benefits of AI without causing damage to the society, regulators around the world have been accelerating their pace in establishing AI regulations. However, with the technology evolving at such speed and uncertainty, there is a lack of consensus on which regulation approach can effectively safeguard human rights while promoting innovation. This article will provide an overview of current AI regulation developments around the world, a preliminary analysis of the pros and cons of different regulation approaches, and point out some other elements that regulators should consider.
I. An overview of the current AI regulation landscape around the world
The EU has its lead in legislation, with its parliament adopting its position on the AI ACT in June 2023, heading into trilogue meetings that aim to reach an agreement by the end of this year.[3] China has also announced its draft National AI ACT, scheduled to enter its National People's Congress before the end of 2023.[4] It already has several administration rules in place, such as the 2021 regulation on recommendation algorithms, the 2022 rules for deep synthesis, and the 2023 draft rules on generative AI.[5]
Some other countries have been taking a softer approach, preferring voluntary guidelines and testing schemes. The UK published its AI regulation plans in March, seeking views on its sectoral guideline-based pro-innovation regulation approach.[6] To minimize uncertainty for companies, it proposed a set of regulatory principles to ensure that government bodies develop guidelines in a consistent manner.[7] The US National Institute of Standards and Technology (NIST) released the AI Risk Management Framework in January[8], with a non-binding Blueprint for an AI Bill of Rights published in October 2022, providing guidance on the design and use of AI with a set of principles.[9] It is important to take note that some States have drafted regulations on specific subjects, such as New York City’s Final Regulations on Use of AI in Hiring and Promotion came into force in July 2023.[10] Singapore launched the world’s first AI testing framework and toolkit international pilot in May 2022, with the assistance of AWS, DBS Bank, Google, Meta, Microsoft, Singapore Airlines, etc. After a year of testing, it open-sourced the software toolkit in July 2023, to better develop the system.[11]
There are also some countries still undecided on their regulation approach. Australia commenced a public consultation on its AI regulatory framework proposal in June[12], seeking views on its draft AI risk management approach.[13] Taiwan’s government announced in July 2023 to propose a draft AI basic law by September 2023, covering topics such as AI-related definition, privacy protections, data governance, risk management, ethical principles, and industrial promotion.[14] However, the plan was recently postponed, indicating a possible shift towards voluntary or mandatory government principles and guidance, before establishing the law.[15]
II. Hard law or soft law? The pros and cons of different regulatory approaches
One of the key advantages of hard law in AI regulation is its ability to provide binding legal obligations and legal enforcement mechanisms that ensure accountability and compliance.[16] Hard law also provides greater legal certainty, transparency and remedies for consumers and companies, which is especially important for smaller companies that do not have as many resources to influence and comply with fast-changing soft law.[17] However, the legislative process can be time-consuming, slower to update, and less agile.[18] This poses the risk of stifling innovation, as hard law inevitably cannot keep pace with the rapidly evolving AI technology.[19]
In contrast, soft law represents a more flexible and adaptive approach to AI regulation. As the potential of AI still remains largely mysterious, government bodies can formulate principles and guidelines tailored to the regulatory needs of different industry sectors.[20] In addition, if there are adequate incentives in place for actors to comply, the cost of enforcement could be much lower than hard laws. Governments can also experiment with several different soft law approaches to test their effectiveness.[21] However, the voluntary nature of soft law and the lack of legal enforcement mechanisms could lead to inconsistent adoption and undermine the effectiveness of these guidelines, potentially leaving critical gaps in addressing AI's risks.[22] Additionally, in cases of AI-related harms, soft law could not offer effective protection on consumer rights and human rights, as there is no clear legal obligation to facilitate accountability and remedies.[23]
Carlos Ignacio Gutierrez and Gary Marchant, faculty members at Arizona State University (ASU), analyzed 634 AI soft law programs against 100 criteria and found that two-thirds of the program lack enforcement mechanisms to deliver its anticipated AI governance goals. He pointed out that credible indirect enforcement mechanisms and a perception of legitimacy are two critical elements that could strengthen soft law’s effectiveness.[24] For example, to publish stem cell research in top academic journals, the author needs to demonstrate that the research complies with related research standards.[25] In addition, companies usually have a greater incentive to comply with private standards to avoid regulatory shifts towards hard laws with higher costs and constraints.[26]
III. Other considerations
Apart from understanding the strengths and limitations of soft law and hard law, it is important for governments to consider each country’s unique differences. For example, Singapore has always focused on voluntary approaches as it acknowledges that being a small country, close cooperation with the industry, research organizations, and other governments to formulate a strong AI governance practice is much more important than rushing into legislation.[27] For them, the flexibility and lower cost of soft regulation provide time to learn from industries to prevent forming rules that aren’t addressing real-world issues.[28] This process allows preparation for better legislation at a later stage.
Japan has also shifted towards a softer approach to minimize legal compliance costs, as it recognizes its slower position in the AI race.[29] For them, the EU AI Act is aiming at regulating Giant Tech companies, rather than promoting innovation.[30] That is why Japan considers that hard law does not suit the industry development stage they’re currently in.[31] Therefore, they seek to address legal issues with current laws and draft relevant guidance.[32]
IV. Conclusion
As the global AI regulatory landscape continues to evolve, it is important for governments to consider the pros and cons of hard law and soft law, and also country-specific conditions in deciding what’s suitable for the country. Additionally, a regular review on the effectiveness and impact of their chosen regulatory approach on AI’s development and the society is recommended.
[1] ChatGPT and Deepfake-Creating Apps: A Running List of Key AI-Lawsuits, TFL, https://www.thefashionlaw.com/from-chatgpt-to-deepfake-creating-apps-a-running-list-of-key-ai-lawsuits/ (last visited Aug 10, 2023); Protection for Voice Actors is Artificial in Today’s Artificial Intelligence World, The National Law Review, https://www.natlawreview.com/article/protection-voice-actors-artificial-today-s-artificial-intelligence-world (last visited Aug 10, 2023).
[2] The politics of AI: ChatGPT and political bias, Brookings, https://www.brookings.edu/articles/the-politics-of-ai-chatgpt-and-political-bias/ (last visited Aug 10, 2023); Prospect of AI Producing News Articles Concerns Digital Experts, VOA, https://www.voanews.com/a/prospect-of-ai-producing-news-articles-concerns-digital-experts-/7202519.html (last visited Aug 10, 2023).
[3] EU AI Act: first regulation on artificial intelligence, European Parliament, https://www.europarl.europa.eu/news/en/headlines/society/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence (last visited Aug 10, 2023).
[4] 中國國務院發布立法計畫 年內審議AI法草案，經濟日報(2023/06/09)，https://money.udn.com/money/story/5604/7223533 (last visited Aug 10, 2023).
[5] id
[6] A pro-innovation approach to AI regulation, GOV.UK, https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach/white-paper (last visited Aug 10, 2023).
[7] id
[8] AI RISK MANAGEMENT FRAMEWORK, NIST, https://www.nist.gov/itl/ai-risk-management-framework (last visited Aug 10, 2023).
[9] The White House released an ‘AI Bill of Rights’, CNN, https://edition.cnn.com/2022/10/04/tech/ai-bill-of-rights/index.html (last visited Aug 10, 2023).
[10] New York City Adopts Final Regulations on Use of AI in Hiring and Promotion, Extends Enforcement Date to July 5, 2023, Littler https://www.littler.com/publication-press/publication/new-york-city-adopts-final-regulations-use-ai-hiring-and-promotionv (last visited Aug 10, 2023).
[11] IMDA, Fact sheet - Open-Sourcing of AI Verify and Set Up of AI Verify Foundation (2023), https://www.imda.gov.sg/-/media/imda/files/news-and-events/media-room/media-releases/2023/06/7-jun---ai-annoucements---annex-a.pdf (last visited Aug 10, 2023).
[12] Supporting responsible AI: discussion paper, Australia Government Department of Industry, Science and Resources,https://consult.industry.gov.au/supporting-responsible-ai (last visited Aug 10, 2023).
[13] Australian Government Department of Industry, Science and Resources, Safe and responsible AI in Australia (2023), https://storage.googleapis.com/converlens-au-industry/industry/p/prj2452c8e24d7a400c72429/public_assets/Safe-and-responsible-AI-in-Australia-discussion-paper.pdf (last visited Aug 10, 2023).
[14] 張璦，中央通訊社，AI基本法草案聚焦隱私保護、應用合法性等7面向 擬設打假中心，https://www.cna.com.tw/news/ait/202307040329.aspx (最後瀏覽日：2023/08/10)。
[15] 蘇思云，中央通訊社，2023/08/01，鄭文燦：考量技術發展快應用廣 AI基本法延後提出，https://www.cna.com.tw/news/afe/202308010228.aspx (最後瀏覽日：2023/08/10)。
[16] supra, note 13, at 27.
[17] id.
[18] id., at 28.
[19] Soft law as a complement to AI regulation, Brookings, https://www.brookings.edu/articles/soft-law-as-a-complement-to-ai-regulation/ (last visited Aug 10, 2023).
[20] supra, note 5.
[21] Gary Marchant, “Soft Law” Governance of Artificial Intelligence (2019), https://escholarship.org/uc/item/0jq252ks (last visited Aug 10, 2023).
[22] How soft law is used in AI governance, Brookings,https://www.brookings.edu/articles/how-soft-law-is-used-in-ai-governance/ (last visited Aug 10, 2023).
[23] supra, note 13, at 27.
[24] Why Soft Law is the Best Way to Approach the Pacing Problem in AI, Carnegie Council for Ethics in International Affairs,https://www.carnegiecouncil.org/media/article/why-soft-law-is-the-best-way-to-approach-the-pacing-problem-in-ai (last visited Aug 10, 2023).
[25] id.
[26] id.
[27] Singapore is not looking to regulate A.I. just yet, says the city-state’s authority, CNBC,https://www.cnbc.com/2023/06/19/singapore-is-not-looking-to-regulate-ai-just-yet-says-the-city-state.html#:~:text=Singapore%20is%20not%20rushing%20to,Media%20Development%20Authority%2C%20told%20CNBC (last visited Aug 10, 2023).
[28] id.
[29] Japan leaning toward softer AI rules than EU, official close to deliberations says, Reuters, https://www.reuters.com/technology/japan-leaning-toward-softer-ai-rules-than-eu-source-2023-07-03/ (last visited Aug 10, 2023).
[30] id.
[31] id.
[32] id.
Impact of Government Organizational Reform to Scientific Research Legal System and Response Thereto (2) – For Example, The Finnish Innovation Fund (“SITRA”) III. Comparison of Strength and Weakness of Sitra Projects 1. Sitra Venture Capital Investment Model In order to comprehend how to boost innovation business development to upgrade innovation ability, we analyze and compare the innovation systems applied in Sweden, France and Finland[1] . We analyze and compare the characteristics, strength and weakness of innovation promotion models in terms of funding, networking and professional guidance. Generally, the first difficulty which a start-up needs to deal with when it is founded initially is the funding. Particularly, a technology company usually requires tremendous funding when it is founded initially. Some potentially adequate investors, e.g., venture capitals, seldom invest in small-sized start-up (because such overhead as supervision and management fees will account for a high percentage of the investment due to the small total investment amount). Networking means how a start-up integrates such human resources as the management, investors, technical advisors and IP professionals when it is founded initially. Control over such human resources is critical to a new company’s survival and growth. Professional guidance means how professional knowledge and human resource support the start-up’s operation. In order to make its product required by the market, an enterprise usually needs to integrate special professional knowledge. Notwithstanding, the professional knowledge and talents which are available from an open market theoretically often cannot be accessed, due to market failure[2]. Assuming that Sitra’s funding is prioritized as Pre-seed-Initiation stage, Seed-Development stage and Follow-up – Growth stage, under Finland model, at the Pre-seed-Initiation stage, Sitra will provide the fund amounting to EUR20,000 when Tekes will also provide the equivalent fund, provided that the latter purely provides subsidy, while the fund provided by Sitra means a loan to be repaid (without interest) after some time (usually after commercialization), or a loan convertible to shares. Then, the loan would be replaced by soft or convertible (to shares) investment and the source of funding would turn to be angel investors or local seed capital at the Seed-Development stage. At this stage, the angel investors, local seed capital and Sitra will act as the source of funding jointly in Finland, while Tekes will not be involved at this stage. At the Follow-up-Growth stage, like the Sweden model, Sitra will utilize its own investment fund to help mitigate the gap between local small-sized funding and large-sized international venture capital[3]. How to recruit professional human resources is critical to a start-up’s success. Many enterprises usually lack sufficient professional human resources or some expertise. DIILI service network set up by Sitra is able to provide the relevant solutions. DILLI is a network formed by product managers. Its members actively participate in starts-up and seek innovation. They also participate in investment of starts-up independently sometimes. Therefore, they are different from angel investors, because they devote themselves to the starts-up on a full-time basis[4]. In other words, they manage the starts-up as if the starts-up were their own business. 2. Key to Public Sector’s Success in Boosting Development of Innovation Activity Business In terms of professional guidance, voluntary guidance means the direct supply of such professional resources as financing, human resource and technology to starts-up, while involuntary guidance means the supply of strategic planning in lieu of direct assistance to help the enterprises make routine decisions[5]. The fractured and incomplete professional service attendant market generates low marginal effect. Therefore, it is impossible for the traditional consultation service to mitigate such gap and the investment at the pre-seed initiation stage will be excessive because of the acquisition of the professional services. Meanwhile, professional advisors seldom are involved in consultation services at the pre-seed initiation stage of a start-up because of the low potential added value. Therefore, at such stage, only involuntary professional guidance will be available usually. Under Sitra model, such role is played by an angel investor. Upon analysis and comparison, we propose six suggested policies to boost innovation activities successfully as the reference when observing Sitra operation. First of all, compared with the French model, Finland Sitra and Sweden model set more specific objectives to meet a start-up’s needs (but there is some defect, e.g., Sitra model lacks voluntary professional guidance). Second, structural budget is a key to the successful model. Sitra will receive the funds in the amount of EUR235,000,000 from the Finnish Government, but its operating expenditure is covered by its own operating revenue in whole. Third, it is necessary to provide working fund in installments and provide fund at the pre-seed-initiation stage. Under both of Finland model and Sweden model, funds will be provided at the pre-seed-initiation stage (Tekes is responsible for providing the fund in Finland). Fourth, the difficulty in networking must be solved. In Sitra, the large-sized talent network set up by it will be dedicated to recruiting human resources. Fifth, the voluntary professional guidance is indispensable at the pre-seed-initiation stage, while the same is unavailable at such stage under Sitra model. Instead, the Sweden model is held as the optimal one, as it has a dedicated unit responsible for solving the difficulty to seek profit. Sixth, soft loan[6] will be successfully only when the loan cannot be convertible to shares. At the pre-seed initiation stage or seed-development stage, a start-up is usually funded by traditional loan. Assuming that the start-up is not expected to gain profit, whether the loan may be convertible to shares will also be taken into consideration when the granting of loan is considered (therefore, the fund provider will not be changed to the “capital” provider). Besides, the government authorities mostly lack the relevant experience or knowledge, or are in no position to negotiate with international large-sized venture capital companies. For example, under the French model, the government takes advantage of its power to restrict the venture capital investment and thereby renders adverse impact to starts-up which seek venture capital. Finally, the supply of own fund to meet the enterprises’ needs at seed-development stage and follow-up-growth stage to mitigate the gap with large-sized venture capital[7] is also required by a successful funding model. IV. Conclusion－Deliberation of Finnish Sitra Experience As the leading national industrial innovation ability promoter in Finland, Sitra appears to be very characteristic in its organizational framework or operating mechanism. We hereby conclude six major characteristics of Sitra and propose the potential orientation toward deliberation of Taiwan’s industrial innovation policies and instruments. 1. Particularity of Organizational Standing In consideration of the particularity of Sitra organizational standing, it has two characteristics observable. First, Sitra is under supervision of the Finnish Parliament directly, not subordinated to the administrative organizational system and, therefore, it possesses such strength as flexibility and compliance with the Parliament’s requirements. Such organization design which acts independently of the administrative system but still aims to implement policies has been derived in various forms in the world, e.g., the agency model[8] in the United Kingdom, or the independent apparatus in the U.S.A. Nevertheless, to act independently of the administrative system, it has to deal with the deliberation of responsible political principles at first, which arouses the difficulty in taking care of flexibility at the same time. In Taiwan, the intermediary organizations include independent agencies and administrative corporations, etc., while the former still involves the participation of the supreme administrative head in the right of personnel administration and is subordinated to the ministries/departments of the Executive Yuan and the latter aims to enforce the public missions in the capacity of “public welfare” organization. Though such design as reporting to the Parliament directly is not against the responsible political principles, how the Parliament owns the authority to supervise is the point (otherwise, theoretically, the administrative authorities are all empowered by the parliament in the country which applies the cabinet system). Additionally, why some special authorities are chosen to report to the parliament directly while other policy subjects are not is also disputable. The existence of Sitra also refers to a circumstantial evidence substantiating that Finland includes the innovation policy as one of the important government policies, and also the objective fact that Finland’s innovation ability heads the first in the world. Second, Sitra is a self-sufficient independent fund, which aims to promote technical R&D and also seeks profit for itself, irrelevant with selection of adequate investment subjects or areas. Instead, for this purpose, the various decisions made by it will deal with the utility and mitigate the gap between R&D and market. Such entity is responsible for public welfare or policy projects and also oriented toward gain from investment to feed the same back to the individuals in the organization. In the administrative system, Sitra is not directed by the administrative system but reports to the Parliament directly. Sitra aims to upgrade the national R&D innovation ability as its long-term goal mission and utilizes the promotion of innovation business and development of venture capital market. The mission makes the profit-orientation compatible with the selection of investment subjects, as an enterprise unlikely to gain profit in the future usually is excluded from the national development view. For example, such industries as green energy, which is not likely to gain profit in a short term, is still worth investing as long as it meets the national development trend and also feasible (in other words, selection of marketable green technology R&D, instead of comparison of the strength and weakness in investment value of green energy and other high-polluted energy). 2. Expressly Distinguished From Missions of Other Ministries/Departments For the time being, Sitra primarily invests in starts-up, including indirect investment and direct investment, because it relies on successful new technology R&D which may contribute to production and marketability. Starts-up have always been one of the best options, as large-sized enterprises are able to do R&D on their own without the outsourcing needs. Further, from the point of view of an inventor, if the new technology is marketable, it will be more favorable to him if he chooses to start business on his own or make investment in the form of partnership, instead of transfer or license of the ownership to large-sized enterprises (as large-sized enterprises are more capable of negotiation). However, note that Sitra aims to boost innovation activities and only targets at start-up business development, instead of boosting and promoting the start-up per se. Under the requirement that Sitra needs to seek profit for itself, only the business with positive development view will be targeted by Sitra. Further, Sitra will not fund any business other than innovation R&D or some specific industries. Apparently, Sitra only focuses on the connection between innovation activities and start-up, but does not act as the competent authority in charge of small-sized and medium-sized enterprises. Meanwhile, Sitra highlights that it will not fund academic research activities and, therefore, appears to be distinguished from the competent authority in charge of national scientific research. Though scientific research and technology innovation business, to some extent, are distinguished from each other in quantity instead of quality, abstract and meaningless research is existent but only far away from the commercialization market. Notwithstanding, a lot of countries tend to distinguish basic scientific research from industrial technology R&D in the administration organization's mission, or it has to be. In term of the way in which Sitra carries out its mission, such distinguishing ability is proven directly. 3. Well-Founded Technology Foresight-Based Investment Business The corporate investments, fund investments and project funding launched by Sitra are all available to the pre-designated subjects only, e.g. ecological sustainable development, energy utilization efficiency, and social structural changes, etc. Such way to promote policies as defining development area as the first priority and then promoting the investment innovation might have some strength and weakness at the same time. First of all, the selection of development areas might meet the higher level national development orientation more therefor, free from objective environmental restrictions, e.g. technical level, leading national technology industries and properties of natural resources. Notwithstanding, an enterprise’s orientation toward innovation R&D might miss the opportunity for other development because of the pre-defined framework. Therefore, such way to promote policies as defining development areas or subjects as the first priority will be inevitably based on well-founded technology foresight-based projects[9], in order to take various subjective and objective conditions into consideration and to forecast the technology development orientation and impact to be faced by the home country’s national and social economies. That is, said strength and weakness will be taken into consideration beforehand for foresight, while following R&D funding will be launched into the technology areas pre-designated after thorough analysis. 4. Self-Interested Investment with the Same High Efficiency as General Enterprises Sitra aims to gain profit generally, and its individual investment model, e.g., DIILI, also permits marketing managers to involve business operation. The profit-sharing model enables Sitra to seek the same high efficiency as the general enterprises when purusing its innovation activity development. The investment launched by Sitra highlights that it is not “funding” (which Tekes is responsible for in Finland) or the investment not requiring return. Therefore, it has the system design to acquire corporate shares. Sitra participates in a start-up by offering its advanced technology, just like a general market investor who will choose the potential investment subject that might benefit him most upon his personal professional evaluation. After all, the ultimate profit will be retained by Sitra (or said DIILI manger, subject to the investment model). Certainly, whether the industry which requires permanent support may benefit under such model still remains questionable. However, except otherwise provided in laws expressly, said special organization standing might be a factor critical to Sitra profit-seeking model. That is, Sitra is not subordinated to the administrative system but is under supervision of the parliament independently, and how its staff deal with the conflict of interest issues in the capacity other than the public sector’s/private sector’s staff is also one of the key factors to success of the system. 5. Investment Model to Deal With Policy Instruments of Other Authorities/Agencies Sitra decides to fund a start-up depending on whether it may gain profit as one of its priorities. As aforesaid, we may preliminarily recognize that the same should be consistent with funding to starts-up logically and no “government failure” issue is involved. For example, the funding at the pre-seed-initiation stage needs to tie in with Tekes’ R&D “funding” (and LIKSA service stated herein) and, therefore, may adjust the profit-seeking orientation, thereby causing deviation in promotion of policies. The dispute over fairness of repeated subsidy/funding and rationality of resource allocation under the circumstance must be controlled by a separate evaluation management mechanism inevitably. 6. Affiliation with Enhancement of Regional Innovation Activities Regional policies cannot be separable from innovation policies, especially in a country where human resources and natural resources are not plentiful or even. Therefore, balancing regional development policies and also integrating uneven resource distribution at the same time is indispensable to upgrading of the entire national social economic benefits. The Finnish experience indicated that innovation activities ought to play an important role in the regional development, and in order to integrate enterprises, the parties primarily engaged in innovation activities, with the R&D ability of regional academic research institutions to upgrade the R&D ability effectively, the relevant national policies must be defined for adequately arranging and launching necessary resources. Sitra's approaches to invest in starts-up, release shares after specific period, integrate the regional resources, upgrade the national innovation ability and boost the regional development might serve to be the reference for universities’ centers of innovative incubator or Taiwan’s local academic and scientific sectors[10] to improve their approaches. For the time being, the organization engaged in venture capital investment in the form of fund in Taiwan like Sitra of Finland is National Development Fund, Executive Yuan. However, in terms of organizational framework, Sitra is under supervision of the Parliament directly, while National Development Fund is subordinated to the administrative system of Taiwan. Though Sitra and National Development Fund are both engaged in venture capital investments primarily, Sitra carries out its missions for the purpose of “promoting innovative activities”, while the National Development Fund is committed to achieve such diversified goals as “promoting economic changes and national development[11]” and is required to be adapted to various ministries’/departments’ policies. Despite the difference in the administrative systems of Taiwan and Finland, Sitra system is not necessarily applicable to Taiwan. Notwithstanding, Sitra’s experience in promotion and thought about the system might provide a different direction for Taiwan to think when it is conceiving the means and instruments for industrial innovation promotion policies in the future. [1] Bart Clarysse & Johan Bruneel, Nurturing and Growing Innovation Start-Ups: The Role of Policy As Integrator, R&D MANAGEMENT, 37(2), 139, 144-146 (2007). Clarysse & Bruneel analysis and comparison refers to Sweden Chalmers Innovation model, French Anvar/Banque de Developpement des PMEs model and Finland Sitra PreSeed Service model. [2] id. at 141-143. [3] id. at 141. [4] id. at 145-146. [5] id. at 143. [6] The loan to be repaid is not a concern. For example, the competent authority in Sweden only expects to recover one-fourths of the loan. [7] Clarysse & Bruneel, super note 26, at 147-148. [8] 彭錦鵬，〈英國政署之組織設計與運作成效〉，《歐美研究》，第30卷第3期，頁89-141。 [9] Technology foresight must work with the innovation policy road mapping (IPRM) interactively, and consolidate the forecast and evaluation of technology policy development routes. One study case about IPRM of the environmental sustainable development in the telecommunication industry in Finland, the IPRM may enhance the foresighted system and indicates the potential factors resulting in systematic failure. Please see Toni Ahlqvist, Ville Valovirta & Torsti Loikkanen, Innovation policy road mapping as a systemic instrument for forward-looking policy design, Science and Public Policy 39, 178-190 (2012). [10] 參見李昂杰，〈規範新訊：學界科專辦法及其法制配套之解析〉，《科技法律透析》，第23卷第8期，頁33（2011）。 [11] National Development Fund, Executive Yuan website, http://www.df.gov.tw/(tftgkz45150vye554wi44ret)/page-aa.aspx?Group_ID=1&Item_Title=%E8%A8%AD%E7%AB%8B%E5%AE%97%E6%97%A8#(Last visit on 2013/03/28)
Executive Yuan’s call to action:“Industrial Upgrading and Transformation Action Plan”I.Introduction Having sustained the negative repercussions following the global financial crisis of 2008, Taiwan’s average economic growth rate decreased from 4.4 percent (during 2000-2007 years) to 3 percent (2008-2012). This phenomenon highlighted the intrinsic problems the Taiwanese economic growth paradigm was facing, seen from the perspective of its development momentum and industrial framework: sluggish growth of the manufacturing industries and the weakening productivity of the service sector. Moreover, the bleak investment climate of the post-2008 era discouraged domestic investors injecting capital into the local economy, rendering a prolonged negative investment growth rate. To further exacerbation, the European Debt Crisis of 2011 – 2012 has impacted to such detriment of private investors and enterprises, that confidence and willingness to invest in the private sector were utterly disfavored. It can be observed that as Taiwan’s industrial core strength is largely concentrated within the the manufacturing sector, the service sector, on the other hand, dwindles. Similarly, the country’s manufacturing efforts have been largely centered upon the Information & Communications Technology (ICT) industry, where the norm of production has been the fulfillment of international orders in components manufacturing and Original Equipment Manufacturing (OEM). Additionally, the raising-up of society’s ecological awareness has further halted the development of the upstream petrochemical and metal industry. Consumer goods manufacturing growth impetus too has been stagnated. Against the backdrop of the aforementioned factors at play as well as the competitive pressure exerted on Taiwan by force of the rapid global and regional economic integration developments, plans to upgrade and transform the existing industrial framework, consequently, arises out as an necessary course of action by the state. Accordingly, Taiwan’s Executive Yuan approved and launched the “Industrial Upgrading and Transformation Action Plan”, on the 13th of October 2014, aiming to reform traditional industries, reinforcing core manufacturing capacities and fostering innovative enterprises, through the implementation of four principal strategies: Upgrading of Product Grade and Value, Establishment of Complete Supply Chain, Setting-up of System Integration Solutions Capability, Acceleration of Growth in the Innovative Sector. II.Current challenges confronting Taiwanese industries 1.Effective apportionment of industrial development funds Despite that Research and Development (R&D) funds takes up 3.02% of Taiwan’s national GDP, there has been a decrease of the country’s investment in industrial and technology research. Currently Taiwan’s research efforts have been directed mostly into manufacturing process improvement, as well as into the high-tech sector, however, traditional and service industries on the other hand are lacking in investments. If research funds for the last decade could be more efficiently distributed, enterprises would be equally encouraged to likewise invest in innovation research. However, it should be noted that Taiwan’s Small and Medium Enterprises (SME) based on their traditional developmental models, do not place research as their top priority. Unlike practices in countries such as Germany and Korea, the research fund input by private enterprises into academic and research institutions is still a relatively unfamiliar exercise in Taiwan. With regards to investment focus, the over-concentration in ICTs should be redirected to accommodate growth possibilities for other industries as well. It has been observed that research investments in the pharmaceutical and electric equipment manufacturing sector has increased, yet in order to not fall into the race-to-the-bottom trap for lowest of costs, enterprises should be continually encouraged to develop high-quality and innovative products and services that would stand out. 2.Human talent and labor force issues Taiwan’s labor force, age 15 to 64, will have reached its peak in 2015, after which will slowly decline. It has been estimated that in 2011 the working population would amount to a meager 55.8%. If by mathematical deduction, based on an annual growth rate of 3%, 4% and 5%, in the year 2020 the labor scarcity would increase from 379,000, 580,000 to 780,000 accordingly. Therefore, it is crucial that productivity must increase, otherwise labor shortage of the future will inevitably stagnate economic growth. Notwithstanding that Taiwan’s demographical changes have lead to a decrease in labor force; the unfavorable working conditions so far has induced skilled professionals to seek employment abroad. The aging society along with decrease in birth rates has further exacerbated the existing cul-de-sac in securing a robust workforce. In 1995 the employment rate under the age of 34 was 46.35%, yet in 2010 it dropped to a daunting 37.6%. 3.Proportional land-use and environmental concerns Taiwan’s Environmental Impact Assessment (EIA) is a time-consuming and often unpredictable process that has substantially deterred investor’s confidence. Additionally, there exists a disproportionate use of land resources in Taiwan, given that demand for its use predominantly stems from the northern and middle region of the country. Should the government choose to balance out the utilization of land resources across Taiwan through labor and tax policies, the situation may be corrected accordingly. III.Industrial Upgrading and Transformation Strategies The current action plan commences its implementation from October 2014 to end of December 2024. The expected industrial development outcomes are as follows: (1) Total output value of the manufacturing sector starting from 2013 at NTD 13.93 trillion is expected to grow in 2020 to NTD 19.46 trillion. (2) Total GDP of the service sector, starting at 3.03 trillion from 2011 is expected to grow in 2020 to 4.75 trillion NTD. 1.Strategy No.1 : Upgrading of product grade and value Given that Taiwan’s manufacturing industry’s rate for added value has been declining year after year, the industry should strive to evolve itself to be more qualitative and value-added oriented, starting from the development of high-end products, including accordingly high-value research efforts in harnessing essential technologies, in the metallic materials, screws and nuts manufacturing sector, aviation, petrochemical, textile and food industries etc. (1) Furtherance of quality research Through the employment of Technology Development Program (TDP) Organizations, Industrial TDP and Academic TDP, theme-based and pro-active Research and Development programs, along with other related secondary assistance measures, the industrial research capability will be expanded. The key is in targeting research in high-end products so that critical technology can be reaped as a result. (2) Facilitating the formation of research alliances with upper-, mid- and downstream enterprises Through the formation of research and development alliances, the localization of material and equipment supply is secured; hence resulting in national autonomy in production capacity. Furthermore, supply chain between industrial component makers and end-product manufacturers are to be conjoined and maintained. National enterprises too are to be pushed forth towards industrial research development, materializing the technical evolution of mid- and downstream industries. (3) Integrative development assistance in Testing and Certification The government will support integrative development in testing and certification, in an effort to boost national competitive advantage thorough benefitting from industrial clusters as well as strengthening value-added logistics services, including collaboration in related value-added services. (4) Establishment of international logistics centre Projection of high-value product and industrial cluster image, through the establishment of an international logistics centre. 2.Strategy No.2 : Establishment of a Complete Supply Chain The establishing a robust and comprehensive supply chain is has at its aim transforming national production capabilities to be sovereign and self-sustaining, without having to resort to intervention of foreign corporations. This is attained through the securing of key materials, components and equipments manufacturing capabilities. This strategy finds its application in the field of machine tool controllers, flat panel display materials, semiconductor devices (3D1C), high-end applications processor AP, solar cell materials, special alloys for the aviation industry, panel equipment, electric vehicle motors, power batteries, bicycle electronic speed controller (ESC), electrical silicon steel, robotics, etc. The main measures listed are as follows: (1) Review of industry gaps After comprehensive review of existing technology gaps depicted by industry, research and academic institutions, government, strategies are to be devised, so that foreign technology can be introduced, such as by way of cooperative ventures, in order to promote domestic autonomous development models. (2) Coordination of Research and Development unions – building-up of autonomous supply chain. Integrating mid- and downstream research and development unions in order to set up a uniform standard in equipment, components and materials in its functional specifications. (3) Application-theme-based research programs Through the release of public notice, industries are invited to submit research proposals focusing on specific areas, so that businesses are aided in developing their own research capabilities in core technologies and products. (4) Promotion of cross-industry cooperation to expand fields of mutual application Continuously expanding field of technical application and facilitating cross-industry cooperation; Taking advantage of international platform to induce cross-border technical collaboration. 3.Strategy No.3 : Setting-up of System Integration Solutions capability Expanding turnkey-factory and turnkey-project system integration capabilities, in order to increase and stimulate export growth; Combination of smart automation systems to strengthen hardware and software integration, hence, boosting system integration solution capacity, allowing stand-alone machinery to evolve into a total solution plant, thus creating additional fields of application and services, effectively expanding the value-chain. These type of transitions are to be seen in the following areas: turnkey-factory and turnkey-project exports, intelligent automated manufacturing, cloud industry, lifestyle (key example: U-Bike in Taipei City) industry, solar factory, wood-working machinery, machine tools, food/paper mills, rubber and plastic machines sector. Specific implementation measure s includes: (1) Listing of national export capability – using domestic market as test bed for future global business opportunities Overall listing of all national system integration capabilities and gaps and further assistance in building domestic “test beds” for system integration projects, so that in the future system-integration solutions can be exported abroad, especially to the emerging economies (including ASEAN, Mainland China) where business opportunities should be fully explored. The current action plan should simultaneously assist these national enterprises in their marketing efforts. (2) Formation of System Integration business alliances and Strengthening of export capability through creation of flagship team Formation of system integration business alliances, through the use of national equipment and technology, with an aim to comply with global market’s needs. Promotion of export of turnkey-factory and turnkey-projects, in order to make an entrance to the global high-value system integration market. Bolstering of international exchanges, allowing European and Asian banking experts assist Taiwanese enterprises in enhancing bids efforts. (3) Establishing of financial assistance schemes to help national enterprises in their overseas bidding efforts Cooperation with financial institutes creating financial support schemes in syndicated loans for overseas bidding, in order to assist national businesses in exporting their turnkey-factories and turnkey-solutions abroad. 4. Strategy No.4 : Acceleration of growth in the innovative sectors Given Taiwan economy’s over-dependence on the growth of the electronics industry, a new mainstream industry replacement should be developed. Moreover, the blur distinction between the manufacturing, service and other industries, presses Taiwan to develop cross-fields of application markets, so that the market opportunities of the future can be fully explored. Examples of these markets include: Smart Campus, Intelligent Transportation System, Smart Health, Smart City, B4G/5G Communications, Strategic Service Industries, Next-Generation Semiconductors, Next-Generation Visual Display, 3D Printing, New Drugs and Medical Instruments, Smart Entertainment, Lifestyle industry (for instance the combination of plan factory and leisure tourism), offshore wind power plant, digital content (including digital learning), deep sea water. Concrete measures include: (1) Promotion of cooperation between enterprises and research institutions to increase efficiency in the functioning of the national innovation process Fostering of Industry-academic cooperation, combining pioneering academic research results with efficient production capability; Cultivation of key technology, accumulation of core intellectual property, strengthening integration of industrial technology and its market application, as well as, establishment of circulation integration platform and operational model for intellectual property. (2) Creating the ideal Ecosystem for innovation industries Strategic planning of demo site, constructing an ideal habitat for the flourishing of innovation industries, as well as the inland solution capability. Promotion of international-level testing environment, helping domestic industries to be integrated with overseas markets and urging the development of new business models through open competition. Encouraging international cooperation efforts, connecting domestic technological innovation capacities with industries abroad. (3) Integration of Cross-Branch Advisory Resources and Deregulation to further support Industrial Development Cross-administrations consultations further deregulation to support an ideal industrial development environment and overcoming traditional cross-branch developmental limitations in an effort to develop innovation industries. IV. Conclusion Taiwan is currently at a pivotal stage in upgrading its industry, the role of the government will be clearly evidenced by its efforts in promoting cross-branch/cross-fields cooperation, establishing a industrial-academic cooperation platform. Simultaneously, the implementation of land, human resources, fiscal, financial and environmental policies will be adopted to further improve the investment ambient, so that Taiwan’s businesses, research institutions and the government could all come together, endeavoring to help Taiwan breakthrough its currently economic impasse through a thorough industrial upgrading. Moreover, it can be argued that the real essence of the present action plan lies in the urge to transform Taiwan’s traditional industries into incubation centers for innovative products and services. With the rapid evolution of ICTs, accelerating development and popular use of Big Data and the Internet of Things, traditional industries can no longer afford to overlook its relation with these technologies and the emerging industries that are backed by them. It is only through the close and intimate interconnection between these two industries that Taiwan’s economy would eventually get the opportunity to discard its outdated growth model based on “quantity” and “cost”. It is believed that the aforementioned interaction is an imperative that would allow Taiwanese industries to redefine its own value amidst fierce global market competition. The principal efforts by the Taiwanese government are in nurturing such a dialogue to occur with the necessary platform, as well as financial and human resources. An illustration of the aforementioned vision can be seen from the “Industrie 4.0” project lead by Germany – the development of intelligent manufacturing, through close government, business and academic cooperation, combining the internet of things development, creating promising business opportunities of the Smart Manufacturing and Services market. This is the direction that Taiwan should be leading itself too. References 1.Executive Yuan, Republic of China http://www.ey.gov.tw/en/（last visited: 2015.02.06） 2.Industrial Development Bureau, Ministry of Economic Affairs http://www.moeaidb.gov.tw/（last visited: 2015.02.06） 3.Industrial Upgrading and Transformation Action Plan http://www.moeaidb.gov.tw/external/ctlr?PRO=filepath.DownloadFile&f=policy&t=f&id=4024（last visited: 2015.02.06）
The opening and sharing of scientific data- The Data Policy of the U.S. National Institutes of HealthThe opening and sharing of scientific data- The Data Policy of the U.S. National Institutes of Health Li-Ting Tsai Scientific research improves the well-being of all mankind, the data sharing on medical and health promote the overall amount of energy in research field. For promoting the access of scientific data and research findings which was supported by the government, the U.S. government affirmed in principle that the development of science was related to the retention and accesses of data. The disclosure of information should comply with legal restrictions, and the limitation by time as well. For government-sponsored research, the data produced was based on the principle of free access, and government policies should also consider the actual situation of international cooperation[1]Furthermore, the access of scientific research data would help to promote scientific development, therefore while formulating a sharing policy, the government should also consider the situation of international cooperation, and discuss the strategy of data disclosure based on the principle of free access. In order to increase the effectiveness of scientific data, the U.S. National Institutes of Health (NIH) set up the Office of Science Policy (OSP) to formulate a policy which included a wide range of issues, such as biosafety (biosecurity), genetic testing, genomic data sharing, human subjects protections, the organization and management of the NIH, and the outputs and value of NIH-funded research. Through extensive analysis and reports, proposed emerging policy recommendations.[2] At the level of scientific data sharing, NIH focused on "genes and health" and "scientific data management". The progress of biomedical research depended on the access of scientific data; sharing scientific data was helpful to verify research results. Researchers integrated data to strengthen analysis, promoted the reuse of difficult-generated data, and accelerated research progress.[3] NIH promoted the use of scientific data through data management to verify and share research results. For assisting data sharing, NIH had issued a data management and sharing policy (DMS Policy), which aimed to promote the sharing of scientific data funded or conducted by NIH.[4] DMS Policy defines “scientific data.” as “The recorded factual material commonly accepted in the scientific community as of sufficient quality to validate and replicate research findings, regardless of whether the data are used to support scholarly publications. Scientific data do not include laboratory notebooks, preliminary analyses, completed case report forms, drafts of scientific papers, plans for future research, peer reviews, communications with colleagues, or physical objects, such as laboratory specimens.”[5] In other words, for determining scientific data, it is not only based on whether the data can support academic publications, but also based on whether the scientific data is a record of facts and whether the research results can be repeatedly verified. In addition, NIH, NIH research institutes, centers, and offices have had expected sharing of data, such as: scientific data sharing, related standards, database selection, time limitation, applicable and presented in the plan; if not applicable, the researcher should propose the data sharing and management methods in the plan. NIH also recommended that the management and sharing of data should implement the FAIR (Findable, Accessible, Interoperable and Reusable) principles. The types of data to be shared should first in general descriptions and estimates, the second was to list meta-data and other documents that would help to explain scientific data. NIH encouraged the sharing of scientific data as soon as possible, no later than the publication or implementation period.[6] It was said that even each research project was not suitable for the existing sharing strategy, when planning a proposal, the research team should still develop a suitable method for sharing and management, and follow the FAIR principles. The scientific research data which was provided by the research team would be stored in a database which was designated by the policy or funder. NIH proposed a list of recommended databases lists[7], and described the characteristics of ideal storage databases as “have unique and persistent identifiers, a long-term and sustainable data management plan, set up metadata, organizing data and quality assurance, free and easy access, broad and measured reuse, clear use guidance, security and integrity, confidentiality, common format, provenance and data retention policy”[8]. That is to say, the design of the database should be easy to search scientific data, and should maintain the security, integrity and confidentiality and so on of the data while accessing them. In the practical application of NIH shared data, in order to share genetic research data, NIH proposed a Genomic Data Sharing (GDS) Policy in 2014, including NIH funding guidelines and contracts; NIH’s GDS policy applied to all NIHs Funded research, the generated large-scale human or non-human genetic data would be used in subsequent research. [9] This can effectively promote genetic research forward. The GDS policy obliged researchers to provide genomic data; researchers who access genomic data should also abide by the terms that they used the Controlled-Access Data for research.[10] After NIH approved, researchers could use the NIH Controlled-Access Data for secondary research.[11] Reviewed by NIH Data Access Committee, while researchers accessed data must follow the terms which was using Controlled-Access Data for research reason.[12] The Genomic Summary Results (GSR) was belong to NIH policy,[13] and according to the purpose of GDS policy, GSR was defined as summary statistics which was provided by researchers, and non-sensitive data was included to the database that was designated by NIH.[14] Namely. NIH used the application and approval of control access data to strike a balance between the data of limitation access and scientific development. For responding the COVID-19 and accelerating the development of treatments and vaccines, NIH's data sharing and management policy alleviated the global scientific community’s need for opening and sharing scientific data. This policy established data sharing as a basic component in the research process.[15] In conclusion, internalizing data sharing in the research process will help to update the research process globally and face the scientific challenges of all mankind together. [1]NATIONAL SCIENCE AND TECHNOLOGY COUNCIL, COMMITTEE ON SCIENCE, SUBCOMMITEE ON INTERNATIONAL ISSUES, INTERAGENCY WORKING GROUP ON OPEN DATA SHARING POLICY, Principles For Promoting Access To Federal Government-Supported Scientific Data And Research Findings Through International Scientific Cooperation (2016), 1, organized from Principles, at 5-8, https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/NSTC/iwgodsp_principles_0.pdf (last visited December 14, 2020). [2]About Us, Welcome to NIH Office of Science Policy, NIH National Institutes of Health Office of Science Policy, https://osp.od.nih.gov/about-us/ (last visited December 7, 2020). [3]NIH Data Management and Sharing Activities Related to Public Access and Open Science, NIH National Institutes of Health Office of Science Policy, https://osp.od.nih.gov/scientific-sharing/nih-data-management-and-sharing-activities-related-to-public-access-and-open-science/ (last visited December 10, 2020). [4]Final NIH Policy for Data Management and Sharing, NIH National Institutes of Health Office of Extramural Research, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html (last visited December 11, 2020). [5]Final NIH Policy for Data Management and Sharing, NIH National Institutes of Health Office of Extramural Research, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-013.html (last visited December 12, 2020). [6]Supplemental Information to the NIH Policy for Data Management and Sharing: Elements of an NIH Data Management and Sharing Plan, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-014.html (last visited December 13, 2020). [7]The list of databases in details please see：Open Domain-Specific Data Sharing Repositories, NIH National Library of Medicine, https://www.nlm.nih.gov/NIHbmic/domain_specific_repositories.html (last visited December 24, 2020). [8]Supplemental Information to the NIH Policy for Data Management and Sharing: Selecting a Repository for Data Resulting from NIH-Supported Research, Office of The Director, National Institutes of Health (OD), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-21-016.html (last visited December 13, 2020). [9]NIH Genomic Data Sharing, National Institutes of Health Office of Science Policy, https://osp.od.nih.gov/scientific-sharing/genomic-data-sharing/ (last visited December 15, 2020). [10]NIH Genomic Data Sharing Policy, National Institutes of Health (NIH), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html (last visited December 17, 2020). [11]NIH Genomic Data Sharing Policy, National Institutes of Health (NIH), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-14-124.html (last visited December 17, 2020). [12]id. [13]NIH National Institutes of Health Turning Discovery into Health, Responsible Use of Human Genomic Data An Informational Resource, 1, at 6, https://osp.od.nih.gov/wp-content/uploads/Responsible_Use_of_Human_Genomic_Data_Informational_Resource.pdf (last visited December 17, 2020). [14]Update to NIH Management of Genomic Summary Results Access, National Institutes of Health (NIH), https://grants.nih.gov/grants/guide/notice-files/NOT-OD-19-023.html (last visited December 17, 2020). [15]Francis S. Collins, Statement on Final NIH Policy for Data Management and Sharing, National Institutes of Health Turning Discovery Into Health, https://www.nih.gov/about-nih/who-we-are/nih-director/statements/statement-final-nih-policy-data-management-sharing (last visited December 14, 2020).
Reviews on Taiwan Constitutional Court's Judgment no. 13 of 2022Reviews on Taiwan Constitutional Court's Judgment no. 13 of 2022 2022/11/24 I.Introduction In 2012, the Taiwan Human Rights Promotion Association and other civil groups believe that the National Health Insurance Administration released the national health insurance database and other health insurance data for scholars to do research without consent, which may be unconstitutional and petitioned for constitutional interpretation. Taiwan Human Rights Promotion Association believes that the state collects, processes, and utilizes personal data on a large scale with the "Personal Data Protection Law", but does not set up another law of conduct to control the exercise of state power, which has violated the principle of legal retention; the data is provided to third-party academic research for use, and the parties involved later Excessive restrictions on the right to withdraw go against the principle of proportionality. The claimant criticized that depriving citizens of their prior consent and post-control rights to medical data is like forcing all citizens to unconditionally contribute data for use outside the purpose before they can use health insurance. The personal data law was originally established to "avoid the infringement of personality rights and promote the rational use of data", but in the insufficient and outdated design of the regulations, it cannot protect the privacy of citizens' information from infringement, and it is easy to open the door to the use of data for other purposes. In addition, even if the health insurance data is de-identified, it is still "individual data" that can distinguish individuals, not "overall data." Health insurance data can be connected with other data of the Ministry of Health and Welfare, such as: physical and mental disability files, sexual assault notification files, etc., and you can also apply for bringing in external data or connecting with other agency data. Although Taiwan prohibits the export of original data, the risk of re-identification may also increase as the number of sources and types of data concatenated increases, as well as unspecified research purposes. The constitutional court of Taiwan has made its judgment on the constitutionality of the personal data usage of National Health Insurance research database. The judgment, released on August 12, 2022, states that Article 6 of Personal Data Protection Act(PDPA), which asks“data pertaining to a natural person's medical records, healthcare, genetics, sex life, physical examination and criminal records shall not be collected, processed or used unless where it is necessary for statistics gathering or academic research by a government agency or an academic institution for the purpose of healthcare, public health, or crime prevention, provided that such data, as processed by the data provider or as disclosed by the data collector, may not lead to the identification of a specific data subject”does not violate Intelligible principle and Principle of proportionality. Therefore, PDPA does not invade people’s right to privacy and remains constitutional. However, the judgment finds the absence of independent supervisory authority responsible for ensuring Taiwan institutions and bodies comply with data protection law, can be unconstitutional, putting personal data protection system on the borderline to failure. Accordingly, laws and regulations must be amended to protect people’s information privacy guaranteed by Article 22 of Constitution of the Republic of China (Taiwan). In addition, the judgment also states it is unconstitutional that Articles 79 and 80 of National Health Insurance Law and other relevant laws lack clear provisions in terms of store, process, external transmission of Personal health insurance data held by Central Health Insurance Administration of the Ministry of Health and Welfare. Finally, the Central Health Insurance Administration of the Ministry of Health and Welfare provides public agencies or academic research institutions with personal health insurance data for use outside the original purpose of collection. According to the overall observation of the relevant regulations, there is no relevant provision that the parties can request to “opt-out”; within this scope, it violates the intention of Article 22 of the Constitution to protect people's right to information privacy. II.Independent supervisory authority According to Article 3 of Central Regulations and Standards Act, government agencies can be divided into independent agencies that can independently exercise their powers and operate autonomously, and non- independent agencies that must obey orders from their superiors. In Taiwan, the so-called "dedicated agency"(專責機關) does not fall into any type of agency defined by the Central Regulations and Standards Act. Dedicated agency should be interpreted as an agency that is responsible for a specific business and here is no other agency to share the business. The European Union requires member states to set up independent regulatory agencies (refer to Articles 51 and 52 of General Data Protection Regulation (GDPR)). In General Data Protection Regulation and the adequacy reference guidelines, the specific requirements for personal data supervisory agencies are as follows: the country concerned should have one or more independent supervisory agencies; they should perform their duties completely independently and cannot seek or accept instructions; the supervisory agencies should have necessary and practicable powers, including the power of investigation; it should be considered whether its staff and budget can effectively assist its implementation. Therefore, in order to pass the EU's adequacy certification and implement the protection of people's privacy and information autonomy, major countries have set up independent supervisory agencies for personal data protection based on the GDPR standards. According to this research, most countries have 5 to 10 commissioners that independently exercise their powers to supervise data exchange and personal data protection. In order to implement the powers and avoid unnecessary conflicts of interests among personnel, most of the commissioners are full-time professionals. Article 3 of Basic Code Governing Central Administrative Agencies Organizations defines independent agency as "A commission-type collegial organization that exercises its powers and functions independently without the supervision of other agencies, and operates autonomously unless otherwise stipulated." It is similar to Japan, South Korea, and the United States. III.Right to Opt-out The judgment pointed out that the parties still have the right to control afterwards the personal information that is allowed to be collected, processed and used without the consent of the parties or that meets certain requirements. Although Article 11 of PDPA provides for certain parties to exercise the right to control afterwards, it does not cover all situations in which personal data is used, such as: legally collecting, processing or using correct personal data, and its specific purpose has not disappeared, In the event that the time limit has not yet expired, so the information autonomy of the party cannot be fully protected, the subject, cause, procedure, effect, etc. of the request for suspension of use should be clearly stipulated in the revised law, and exceptions are not allowed. The United Kingdom is of great reference. In 2017, after the British Information Commissioner's Office (ICO) determined that the data sharing agreement between Google's artificial intelligence DeepMind and the British National Health Service (NHS) violated the British data protection law, the British Department of Health and Social Care proposed National data opt-out Directive in May, 2018. British health and social care-related institutions may refer to the National Data Opt-out Operational Policy Guidance Document published by the National Health Service in October to plan the mechanism for exercising patient's opt-out right. The guidance document mainly explains the overall policy on the exercise of the right to opt-out, as well as the specific implementation of suggested practices, such as opt-out response measures, methods of exercising the opt-out right, etc. National Data Opt-out Operational Policy Guidance Document also includes exceptions and restrictions on the right to opt-out. The Document stipulates that exceptions may limit the right to Opt-out, including: the sharing of patient data, if it is based on the consent of the parties (consent), the prevention and control of infectious diseases (communicable disease and risks to public health), major public interests (overriding) Public interest), statutory obligations, or cooperation with judicial investigations (information required by law or court order), health and social care-related institutions may exceptionally restrict the exercise of the patient's right to withdraw. What needs to be distinguished from the situation in Taiwan is that when the UK first collected public information and entered it into the NHS database, there was already a law authorizing the NHS to search and use personal information of the public. The right to choose to enter or not for the first time; and after their personal data has entered the NHS database, the law gives the public the right to opt-out. Therefore, the UK has given the public two opportunities to choose through the enactment of special laws to protect public's right to information autonomy. At present, the secondary use of data in the health insurance database does not have a complete legal basis in Taiwan. At the beginning, the data was automatically sent in without asking for everyone’s consent, and there was no way to withdraw when it was used for other purposes, therefore it was s unconstitutional. Hence, in addition to thinking about what kind of provisions to add to the PDPA as a condition for "exception and non-request for cessation of use", whether to formulate a special law on secondary use is also worthy of consideration by the Taiwan government. IV.De-identification According to the relevant regulations of PDPA, there is no definition of "de-identification", resulting in a conceptual gap in the connotation. In other words, what angle or standard should be used to judge that the processed data has reached the point where it is impossible to identify a specific person. In judicial practice, it has been pointed out that for "data recipients", if the data has been de-identified, the data will no longer be regulated by PDPA due to the loss of personal attributes, and it is even further believed that de-identification is not necessary. However, the Judgment No. 13 of Constitutional Court, pointed out that through de-identification measures, ordinary people cannot identify a specific party without using additional information, which can be regarded as personal data of de-identification data. Therefore, the judge did not give an objective standard for de-identification, but believed that the purpose of data utilization and the risk of re-identification should be measured on a case-by-case basis, and a strict review of the constitutional principle of proportionality should be carried out. So far, it should be considered that the interpretation of the de-identification standard has been roughly finalized. V.Conclusions The judge first explained that if personal information is processed, the type and nature of the data can still be objectively restored to indirectly identify the parties, no matter how simple or difficult the restoration process is, if the data is restored in a specific way, the parties can still be identified. personal information. Therefore, the independent control rights of the parties to such data are still protected by Article 22 of the Constitution. Conversely, when the processed data objectively has no possibility to restore the identification of individuals, it loses the essence of personal data, and the parties concerned are no longer protected by Article 22 of the Constitution. Based on this, the judge declared that according to Article 6, Item 1, Proviso, Clause 4 of the PDPA, the health insurance database has been processed so that the specific party cannot be identified, and it is used by public agencies or academic research institutions for medical and health purposes. Doing necessary statistical or academic research complies with the principles of legal clarity and proportionality, and does not violate the Constitution. However, the judge believes that the current personal data law or other relevant regulations still lack an independent supervision mechanism for personal data protection, and the protection of personal information privacy is insufficient. In addition, important matters such as personal health insurance data can be stored, processed, and transmitted externally by the National Health Insurance Administration in a database; the subject, purpose, requirements, scope, and method of providing external use; and organizational and procedural supervision and protection mechanisms, etc. Articles 79 and 80 of the Health Insurance Law and other relevant laws lack clear provisions, so they are determined to be unconstitutional. In the end, the judge found that the relevant laws and regulations lacked the provisions that the parties can request to stop using the data, whether it is the right of the parties to request to stop, or the procedures to be followed to stop the use, there is no relevant clear text, obviously the protection of information privacy is insufficient. Therefore, regarding unconstitutional issues, the Constitutional Court ordered the relevant agencies to amend the Health Insurance Law and related laws within 3 years, or formulate specific laws.
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