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The Key Elements for Data Intermediaries to Deliver Their Promise

The Key Elements for Data Intermediaries to Deliver Their Promise

2022/12/13

　　As human history enters the era of data economy, data has become the new oil. It feeds artificial intelligence algorithms that are disrupting how advertising, healthcare, transportation, insurance, and many other industries work. The excitement of having data as a key production input lies in the fact that it is a non-rivalrous good that does not diminish by consumption.[1] However, the fact that people are reluctant in sharing data due to privacy and trade secrets considerations has been preventing countries to realize the full value of data. [2]

　　To release more data, policymakers and researchers have been exploring ways to overcome the trust dilemma. Of all the discussions, data intermediaries have become a major solution that governments are turning to. This article gives an overview of relevant policy developments concerning data intermediaries and a preliminary analysis of the key elements that policymakers should consider for data intermediaries to function well.

I. Policy and Legal developments concerning data intermediaries

　　In order to unlock data’s full value, many countries have started to focus on data intermediaries. For example, in 2021, the UK’s Department for Digital, Culture, Media and Sport (DCMS) commissioned the Centre for Data Ethics and Innovation (CDEI) to publish a report on data intermediaries[3] , in response to the 2020 National Data Strategy.[4] In 2020, the European Commission published its draft Data Governance Act (DGA)[5] , which aims to build up trust in data intermediaries and data altruism organizations, in response to the 2020 European Strategy for Data.[6] The act was adopted and approved in mid-2022 by the Parliament and Council; and will apply from 24 September 2023.[7] The Japanese government has also promoted the establishment of data intermediaries since 2019, publishing guidance to establish regulations on data trust and data banks.[8]

II. Key considerations for designing effective data intermediary policy

1.Evaluate which type of data intermediary works best in the targeted country

　　From CDEI’s report on data intermediaries and the confusion in DGA’s various versions of data intermediary’s definition, one could tell that there are many forms of data intermediaries. In fact, there are at least eight types of data intermediaries, including personal information management systems (PIMS), data custodians, data exchanges, industrial data platforms, data collaboratives, trusted third parties, data cooperatives, and data trusts.[9] Each type of data intermediary was designed to combat data-sharing issues in specific countries, cultures, and scenarios. Hence, policymakers need to evaluate which type of data intermediary is more suitable for their society and market culture, before investing more resources to promote them.

　　For example, data trust came from the concept of trust—a trustee managing a trustor’s property rights on behalf of his interest. This practice emerged in the middle ages in England and has since developed into case law.[10] Thus, the idea of data trust is easily understood and trusted by the British people and companies. As a result, British people are more willing to believe that data trusts will manage their data on their behalf in their best interest and share their valuable data, compared to countries without a strong legal history of trusts. With more people sharing their data, trusts would have more bargaining power to negotiate contract terms that are more beneficial to data subjects than what individual data owners could have achieved. However, this model would not necessarily work for other countries without a strong foundation of trust law.

2.Quality signals required to build trust: A government certificate system can help overcome the lemon market problem

　　The basis of trust in data intermediaries depends largely on whether the service provider is really neutral in its actions and does not reuse or sell off other parties’ data in secret. However, without a suitable way to signal their service quality, the market would end up with less high-quality service, as consumers would be reluctant to pay for higher-priced service that is more secure and trustworthy when they have no means to verify the exact quality.[11] This lemon market problem could only be solved by a certificate system established by actors that consumers trust, which in most cases is the government.

　　The EU government clearly grasped this issue as a major obstacle to the encouragement of trust in data intermediaries and thus tackles it with a government register and verification system. According to the Data Government Act, data intermediation services providers who intend to provide services are required to notify the competent authority with information on their legal status, form, ownership structure, relevant subsidiaries, address, public website, contact details, the type of service they intend to provide, the estimated start date of activities…etc. This information would be provided on a website for consumers to review. In addition, they can request the competent authority to confirm their legal compliance status, which would in turn verify them as reliable entities that can use the ‘data intermediation services provider recognised in the Union’ label.

3.Overcoming trust issues with technology that self-enforces privacy: privacy-enhancing technologies (PETs)

　　Even if there are verified data intermediation services available, businesses and consumers might still be reluctant to trust human organizations. A way to boost trust is to adopt technologies that self-enforces privacy. A real-world example is OpenSAFELY, a data intermediary implementing privacy-enhancing technologies (PETs) to provide health data sharing in a secure environment. Through a federated analytics system, researchers are able to conduct research with large volumes of healthcare data, without the ability to observe any data directly. Under such protection, UK NHS is willing to share its data for research purposes. The accuracy and timeliness of such research have provided key insights to inform the UK government in decision-making during the COVID-19 pandemic.

　　With the benefits it can bring, unsurprisingly, PETs-related policies have become quite popular around the globe. In June 2022, Singapore launched its Digital Trust Centre (DTC) for accelerating PETs development and also signed a Memorandum of Understanding with the International Centre of Expertise of Montreal for the Advancement of Artificial Intelligence (CEIMIA) to collaborate on PETs.[12] On September 7th, 2022, the UK Information Commissioners’ Office (ICO) published draft guidance on PETs.[13] Moreover, the U.K. and U.S. governments are collaborating on PETs prize challenges, announcing the first phase winners on November 10th, 2022.[14] We could reasonably predict that more PETs-related policies would emerge in the coming year.

 

Reference:

[1] Yan Carrière-Swallow and Vikram Haksar, The Economics of Data, IMFBlog (Sept. 23, 2019), https://blogs.imf.org/2019/09/23/the-economics-of-data/#:~:text=Data%20has%20become%20a%20key,including%20oil%2C%20in%20important%20ways (last visited July 22, 2022).

[2] Frontier Economics, Increasing access to data across the economy: Report prepared for the Department for Digital, Culture, Media, and Sport (2021), https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/974532/Frontier-access_to_data_report-26-03-2021.pdf (last visited July 22, 2022).

[3] The Centre for Data Ethics and Innovation (CDEI), Unlocking the value of data: Exploring the role of data intermediaries (2021), https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1004925/Data_intermediaries_-_accessible_version.pdf (last visited June 17, 2022).

[4] Please refer to the guidelines for the selection of sponsors of the 2022 Social Innovation Summit: https://www.gov.uk/government/publications/uk-national-data-strategy/national-data-strategy (last visited June 17, 2022).

[5] Regulation of the European Parliament and of the Council on European data governance and amending Regulation (EU) 2018/1724 (Data Governance Act), 2020/0340 (COD) final (May 4, 2022).

[6] Communication from the Commission to the European Parliament, the Council, the European Economic and Social Committee and The Committee of the Regions— A European strategy for data, COM/2020/66 final (Feb 19, 2020).

[7] Proposal for a Regulation on European Data Governance, European Parliament Legislative Train Schedule, https://www.europarl.europa.eu/legislative-train/theme-a-europe-fit-for-the-digital-age/file-data-governance-act(last visited Aug 17, 2022).

[8] 周晨蕙，〈日本資訊信託功能認定指引第二版〉，科技法律研究所，https://stli.iii.org.tw/article-detail.aspx?no=67&tp=5&d=8422（最後瀏覽日期︰2022/05/30）。

[9] CDEI, supra note 3.

[10] Ada Lovelace Institute, Exploring legal mechanisms for data stewardship (2021), 30~31,https://www.adalovelaceinstitute.org/wp-content/uploads/2021/03/Legal-mechanisms-for-data-stewardship_report_Ada_AI-Council-2.pdf (last visited Aug 17, 2022).

[11] George A. Akerlof, The Market for "Lemons": Quality Uncertainty and the Market Mechanism, THE QUARTERLY JOURNAL OF ECONOMICS, 84(3), 488-500 (1970).

[12] IMDA, MOU Signing Between IMDA and CEIMIA is a Step Forward in Cross-border Collaboration on Privacy Enhancing Technology (PET) (2022),https://www.imda.gov.sg/-/media/Imda/Files/News-and-Events/Media-Room/Media-Releases/2022/06/MOU-bet-IMDA-and-CEIMIA---ATxSG-1-Jun-2022.pdf (last visited Nov. 28, 2022).

[13] ICO publishes guidance on privacy enhancing technologies, ICO, https://ico.org.uk/about-the-ico/media-centre/news-and-blogs/2022/09/ico-publishes-guidance-on-privacy-enhancing-technologies/ (last visited Nov. 27, 2022).

[14] U.K. and U.S. governments collaborate on prize challenges to accelerate development and adoption of privacy-enhancing technologies, GOV.UK, https://www.gov.uk/government/news/uk-and-us-governments-collaborate-on-prize-challenges-to-accelerate-development-and-adoption-of-privacy-enhancing-technologies (last visited Nov. 28, 2022); Winners Announced in First Phase of UK-US Privacy-Enhancing Technologies Prize Challenges, NIST, https://www.nist.gov/news-events/news/2022/11/winners-announced-first-phase-uk-us-privacy-enhancing-technologies-prize (last visited Nov. 28, 2022).

※The Key Elements for Data Intermediaries to Deliver Their Promise,STLI, https://stli.iii.org.tw/en/article-detail.aspx?no=105&tp=2&i=168&d=8923 (Date:2025/11/10)
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Reviews on Taiwan Constitutional Court's Judgment no. 13 of 2022

Reviews 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.

Impact of Government Organizational Reform to Research Legal System and Response Thereto (2) – Observation of the Swiss Research Innovation System

3.Commission of Technology and Innovation (CTI) 　　The CTI is also an institution dedicated to boosting innovation in Switzerland. Established in 1943, it was known as the Commission for the Promotion of Scientific Research[1]. It was initially established for the purpose of boosting economy and raising the employment rate, and renamed after 1996. The CTI and SNSF are two major entities dedicated to funding scientific research in Switzerland, and the difference between both resides in that the CTI is dedicated to funding R&D of the application technology and industrial technology helpful to Switzerland’s economic development. 　　Upon enforcement of the amended RIPA 2011, the CTI was officially independent from the Federal Office for Professional Education and Technology (OEPT) and became an independent entity entitled to making decisions and subordinated to the Federal Department of Economic Affairs (FDEA) directly[2]. The CTI is subject to the council system, consisting of 65 professional members delegated from industrial, academic and research sectors. The members assume the office as a part time job. CTI members are entitled to making decisions on funding, utilization of resources and granting of CTI Start-up Label independently[3]. 　　The CTI primarily carries out the mission including promotion of R&D of industrial technology, enhancement of the market-orientation innovation process and delivery of R&D energy into the market to boost industrial innovation. For innovation, the CTI's core mission is categorized into[4]: (1)Funding technology R&D activities with market potential 　　The CTI invests considerable funds and resources in boosting the R&D of application technology and industrial technology. The CTI R&D Project is intended to fund private enterprises (particularly small-sized and medium-sized enterprises) to engage in R&D of innovation technology or product. The enterprises may propose their innovative ideas freely, and the CTI will decide whether the funds should be granted after assessing whether the ideas are innovative and potentially marketable[5]. 　　CTI’s funding is conditioned on the industrial and academic cooperation. Therefore, the enterprises must work with at least one research institution (including a university, university of science and technology, or ETH) in the R&D. Considering that small-sized and medium-sized enterprises usually do not own enough working funds, technology and human resources to commercialize creative ideas, the CTI R&D Project is intended to resolve the problem about insufficient R&D energy and funds of small- and medium-sized enterprises by delivering the research institutions’ plentiful research energy and granting the private enterprises which work with research institutions (including university, university of science and technology, or ETH) the fund. Notably, CTI’s funding is applicable to R&D expenses only, e.g., research personnel’s salary and expenditure in equipment & materials, and allocated to the research institutions directly. Meanwhile, in order to enhance private enterprises' launch into R&D projects and make them liable for the R&D success or failure, CTI’s funding will be no more than 50% of the total R&D budget and, therefore, the enterprises are entitled to a high degree of control right in the process of R&D. 　　The industrial types which the CTI R&D Project may apply to are not limited. Any innovative ideas with commercial potential may be proposed. For the time being, the key areas funded by CTI include the life science, engineering science, Nano technology and enabling sciences, etc.[6] It intends to keep Switzerland in the lead in these areas. As of 2011, in order to mitigate the impact of drastic CHF revaluation to the industries, the CTI launched its new R&D project, the CTI Voucher[7]. Given this, the CTI is not only an entity dedicated to funding but also plays an intermediary role in the industrial and academic sectors. Enterprises may submit proposals before finding any academic research institution partner. Upon preliminary examination of the proposals, the CTI will introduce competent academic research institutions to work with the enterprises in R&D, subject to the enterprises' R&D needs. After the cooperative partner is confirmed, CTI will grant the fund amounting to no more than CHF3,500,000 per application[8], provided that the funding shall be no more than 50% of the R&D project expenditure. 　　The CTI R&D Project not only boosts innovation but also raises private enterprises’ willingness to participate in the academic and industrial cooperation, thereby narrowing the gap between the supply & demand of innovation R&D in the industrial and academic sectors. Notably, the Project has achieved remarkable effect in driving private enterprises’ investment in technology R&D. According to statistical data, in 2011, the CTI solicited additional investment of CHF1.3 from a private enterprise by investing each CHF1[9]. This is also one of the important reasons why the Swiss innovation system always acts vigorously. Table 1 　2005-2011 Passing rate of application for R&D funding Year 2011 2010 2009 2008 2007 2006 2005 Quantity of applications 590 780 637 444 493 407 522 Quantity of funded applications 293 343 319 250 277 227 251 Pass rate 56% 44% 50% 56% 56% 56% 48% Data source: Prepared by the Study (2)Guiding high-tech start-up 　　Switzerland has learnt that high-tech start-ups are critical to the creation of high-quality employment and boosting of economic growth, and start-ups were able to commercialize the R&D results. Therefore, as of 2001, Switzerland successively launched the CTI Entrepreneurship and CTI Startup to promote entrepreneurship and cultivate high-tech start-ups. 1.CTI Entrepreneurship 　　The CTI Entrepreneurship was primarily implemented by the Venture Lab founded by CTI investment. The Venture Lab launched a series of entrepreneurship promotion and training courses, covering day workshops, five-day entrepreneurship intensive courses, and entrepreneurship courses available in universities. Each training course was reviewed by experts, and the experts would provide positive advice to attendants about innovative ideas and business models. Data source: Venture Lab Site Fig. 3 　Venture Lab Startup Program 2.CTI Startup 　　The CTI is dedicated to driving the economy by virtue of innovation as its priority mission. In order to cultivate the domestic start-ups with high growth potential in Switzerland, the CTI Startup project was launched in 1996[10] in order to provide entrepreneurs with the relevant guidance services. The project selected young entrepreneurs who provided innovative ideas, and guided them in the process of business start to work their innovative ideas and incorporate competitive start-ups. 　　In order to enable the funding and resources to be utilized effectively, the CTI Startup project enrolled entrepreneurs under very strict procedure, which may be categorized into four stages[11]: Data source: CTI Startup Site Fig. 4 　Startup Plan Flow Chart 　　In the first stage, the CTI would preliminarily examine whether the applicant’s idea was innovative and whether it was technologically feasible, and help the applicant register with the CTI Startup project. Upon registration, a more concrete professional examination would be conducted at the second stage. The scope of examination included the technology, market, feasibility and management team’s competence. After that, at the stage of professional guidance, each team would be assigned a professional “entrepreneurship mentor”, who would help the team develop further and optimize the enterprise’s strategy, flow and business model in the process of business start, and provide guidance and advice on the concrete business issues encountered by the start-up. The stage of professional guidance was intended to guide start-ups to acquire the CTI Startup Label, as the CTI Startup Label was granted subject to very strict examination procedure. For example, in 2012, the CTI Startup project accepted 78 applications for entrepreneurship guidance, but finally the CTI Startup Label was granted to 27 applications only[12]. Since 1996, a total of 296 start-ups have acquired the CTI Startup Label, and more than 86% thereof are still operating now[13]. Apparently, the CTI Startup Label represents the certification for innovation and on-going development competence; therefore, it is more favored by investors at the stage of fund raising. Table 2 　Execution of start-up plans for the latest three years Quantity of application Quantity of accepted application Quantity of CTI Label granted 2012 177 78 27 2011 160 80 26 2010 141 61 24 Data source: CTI Annual Report, prepared by the Study 　　Meanwhile, the “CTI Invest” platform was established to help start-up raise funds at the very beginning to help commercialize R&D results and cross the valley in the process of R&D innovation. The platform is a private non-business-making organization, a high-tech start-up fund raising platform co-established by CTI and Swiss investors[14]. It is engaged in increasing exposure of the start-ups and contact with investors by organizing activities, in order to help the start-ups acquire investment funds. (3)Facilitating transfer of knowledge and technology between the academic sector and industrial sector 　　KTT Support (Knowledge & Technology Transfer (KTT Support) is identified as another policy instrument dedicated to boosting innovation by the CTI. It is intended to facilitate the exchange of knowledge and technology between academic research institutions and private enterprises, in order to transfer and expand the innovation energy. 　　As of 2013, the CTI has launched a brand new KTT Support project targeting at small-sized and medium-sized enterprises. The new KTT Support project consisted of three factors, including National Thematic Networks (NTNs), Innovation Mentors, and Physical and web-based platforms. Upon the CTI’s strict evaluation and consideration, a total of 8 cooperative innovation subjects were identified in 2012, namely, carbon fiber composite materials, design idea innovation, surface innovation, food study, Swiss biotechnology, wood innovation, photonics and logistics network, etc.[15] One NTN would be established per subject. The CTI would fund these NTNs to support the establishment of liaison channels and cooperative relations between academic research institutions and industries and provide small- and medium-sized enterprises in Switzerland with more rapid and easy channel to access technologies to promote the exchange of knowledge and technology between both parties. Innovation Mentors were professionals retained by the CTI, primarily responsible for evaluating the small-sized and medium-sized enterprises’ need and chance for innovation R&D and helping the enterprises solicit competent academic research partners to engage in the transfer of technology. The third factor of KTT Support, Physical and web-based platforms, is intended to help academic research institutions and private enterprises establish physical liaison channels through organization of activities and installation of network communication platforms, to enable the information about knowledge and technology transfer to be more transparent and communicable widely. 　　In conclusion, the CTI has been dedicated to enhancing the link between scientific research and the industries and urging the industrial sector to involve and boost the R&D projects with market potential. The CTI’s business lines are all equipped with corresponding policy instruments to achieve the industrial-academic cooperation target and mitigate the gap between the industry and academic sectors in the innovation chain. The various CTI policy instruments may be applied in the following manner as identified in the following figure. Data source: CTI Annual Report 2011 Fig. 5 　Application of CTI Policy Instrument to Innovation Chain III. Swiss Technology R&D Budget Management and Allocation 　　The Swiss Federal Government has invested considerable expenditures in technology R&D. According to statistic data provided by Swiss Federal Statistical Office (FSO) and OECD, the Swiss research expenditures accounted for 2.37% of the Federal Government’s total expenditures, following the U.S.A. and South Korea (see Fig. 6). Meanwhile, the research expenditures of the Swiss Government grew from CHF2.777 billion in 2000 to CHF4.639 billion in 2010, an average yearly growth rate of 5.9% (see Fig. 7). It is clear that Switzerland highly values its technology R&D. Data source: FSO and OECD Fig. 6 Percentage of Research Expenditures in Various Country Governments’ Total Expenditures (2008) Data source: FSO and OECD Fig. 7 　Swiss Government Research Expenditures 2000-2010 1.Management of Swiss Technology R&D Budget 　　Swiss research expenditures are primarily allocated to the education, R&D and innovation areas, and play an important role in the Swiss innovation system. Therefore, a large part of the Swiss research expenditures are allocated to institutions of higher education, including ETH, universities, and UASs. The Swiss research expenditures are utilized by three hierarchies[16] (see Fig. 8): Government R&D funding agencies: The Swiss research budget is primarily executed by three agencies, including SERI, Federal Department of Economic Affairs, Education and Research, and Swiss Agency for Development and Cooperation (SDC). Intermediary R&D funding agencies: Including SNSC and CTI. Funding of R&D performing institutions: Including private enterprises, institutions of higher education and private non-profit-making business, et al. 　　Therefore, the Swiss Government research expenditures may be utilized by the Federal Government directly, or assigned to intermediary agencies, which will allocate the same to the R&D performing institutions. SERI will allocate the research expenditures to institutions of higher education and also hand a lot of the expenditures over to SNSF for consolidated funding to the basic science of R&D. Data source: FSO Fig. 8 　Swiss Research Fund Utilization Mechanism ~to be continued~ [1] ORGANIZATION FOR ECONNOMIC CO-OPERATION AND DEVELOPMENT [OECD], OECD Reviews of Innovation Policy: Switzerland 27 (2006). [2] As of January 1, 2013, the Federal Ministry of Economic Affairs was reorganized, and renamed into Federal Department of Economic Affairs, Education and Research (EAER). [3] The Commission for Technology and Innovation CTI, THE COMMISSION FOR TECHOLOGY AND INNOVATION CTI, http://www.kti.admin.ch/org/00079/index.html?lang=en (last visited Jun. 3, 2013). [4] Id. [5] CTI INVEST, Swiss Venture Guide 2012 (2012), at 44, http://www.cti-invest.ch/getattachment/7f901c03-0fe6-43b5-be47-6d05b6b84133/Full-Version.aspx (last visited Jun. 4, 2013). [6] CTI, CTI Activity Report 2012 14 (2013), available at http://www.kti.admin.ch/dokumentation/00077/index.html?lang=en&download=NHzLpZeg7t,lnp6I0NTU042l2Z6ln1ad1IZn4Z2qZpnO2Yuq2Z6gpJCDen16fmym162epYbg2c_JjKbNoKSn6A-- (last visited Jun. 3, 2013). [7] CTI Voucher, THE COMMISSION FOR TECHOLOGY AND INNOVATION CTI, http://www.kti.admin.ch/projektfoerderung/00025/00135/index.html?lang=en (last visited Jun. 3, 2013). [8] Id. [9] CTI, CTI Activity Report 2011 20 (2012), available at http://www.kti.admin.ch/dokumentation/00077/index.html?lang=en&download=NHzLpZeg7t,lnp6I0NTU042l2Z6ln1ad1IZn4Z2qZpnO2Yuq2Z6gpJCDeYR,gWym162epYbg2c_JjKbNoKSn6A--(last visited Jun. 3, 2013). [10] CTI Start-up Brings Science to Market, THE COMMISSION FOR TECHOLOGY AND INNOVATION CTI, http://www.ctistartup.ch/en/about/cti-start-/cti-start-up/ (last visited Jun. 5, 2013). [11] Id. [12] Supra note 8, at 45. [13] Id. [14] CTI Invest, http://www.cti-invest.ch/About/CTI-Invest.aspx (last visited Jun. 5, 2013). [15] KTT Support, CTI, http://www.kti.admin.ch/netzwerke/index.html?lang=en (last visited Jun.5, 2013). [16] Swiss Federal Statistics Office (SFO), Public Funding of Research in Switzerland 2000–2010 (2012), available at http://www.bfs.admin.ch/bfs/portal/en/index/themen/04/22/publ.Document.163273.pdf (last visited Jun. 20, 2013).

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. Reference: [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.

New Version of Personal Information Protection Act and Personal Information Protection & Administration System

I.Summary In 1995, the Computer-Processed Personal Data Protection Law was implemented in the Republic of China. With the constant development of information technology and the limitations in the application of the legislation, the design of the original legal system is no longer consistent with practical requirements. Considering the increasing number of incidents of personal data leaks, discussions were carried out over a long period of time and the new version of the Personal Information Protection Act was passed after three readings in April, 2010. The title of the law was changed to Personal Information Protection Act. The new system has been officially implemented since 1 October, 2012. The new Act not only revised the provisions of the law in a comprehensive way, but also significantly increased the obligations and responsibilities of enterprises. In terms of civil liability, the maximum amount of compensation for a single incident is 200 Million NTD. For domestic industries, how to effectively respond to the requirements under the Personal Information Protection Act and adopt proper corresponding measures to lower the risk has become a key task for enterprise operation. II. Main Points 1. Implementation of the Enforcement Rules of the Personal Information Protection Act Personal information protection can be said the most concerned issue in Taiwan recently. As a matter of fact, the Computer-Processed Personal Data Protection Law was established in Taiwan as early as August 1995. After more than 10 years of development, computer and information technology has evolved significantly, and many emerging business models such as E-commerce are extensively collecting personal data. It has become increasingly important to properly protect personal privacy. However, the previous Computer-Processed Personal Data Protection Law was only applicable to certain industries, i.e. the following 8 specific industries: the credit investigation business, hospital, school, telecommunication business, financial business, securities business, insurance business, and mass media. And other business was designated by the Ministry of Justice and the central government authorities in charge of concerned enterprises. In addition, the law only protected personal information that was processed by “computer or automatic equipment”. Personal information that was not computer processed was not included. There were clearly no sufficient regulations for the protection of personal data privacy and interest. There were numerous incidents of personal data leaks. Among the top 10 consumer news issued by the Consumer Protection Committee of the Executive Yuan in 2007, “incidents of personal data leaks through E-commerce and TV shopping” was on the top of the list. This provoked the Ministry of Justice and the Ministry of Economic Affairs to “jointly designate” the retail industry without physical boutique (including 3 transaction models: online shopping, catalogue shopping and TV shopping) to be governed by the Computer-Processed Personal Data Protection Law since 1 July 2010. To allow the provisions of the personal information protection legal system to meet the environment of rapid change, the Executive Yuan proposed a Draft Amendment to the Computer-Processed Personal Data Protection Law very early and changed the title to the Personal Information Protection Act. The draft was discussed many times in the Legislative Yuan. Personal Information Protection Act was finally passed after three readings in April 2010, which was officially published by the Office of the President on 26 May. Although the new law was passed in April 2010, to allow sufficient time for enterprises and the public to understand and comply the new law, the new version of the personal information protection law was not implemented on the date of publication. In accordance with Article 56 of the Act, the date of implementation was to be further established by the Executive Yuan. After discussions over a long period of time, the Executive Yuan decided for the Personal Information Protection Act to be officially implemented on 1 October 2012. However, the implementation of two articles is withheld: Article 6 of the Act about the principal prohibition against the collection, processing and use of special personal information and Article 54 about the obligation to notice the Party within one year for personal information indirectly acquired before the implementation of the new law. In terms of the personal data protection legal system, other than the most important Personal Data Protection Act, the enforcement rules established in accordance with the main law also play a key role. The previous Enforcement Rules of the Computer-Processed Personal Data Protection Law were published and implemented on 1 May, 1996. Considering that the Computer-Processed Personal Data Protection Law was amended in 2010 and that its title has been changed to the Personal Data Protection Act, the Ministry of Justice also followed the amended provisions under the new law and actively studied the Draft Amendment to the Enforcement Rules of the Computer-Processed Personal Data Protection Act. After it was confirmed that the new version of the Personal Data Protection Act would be officially launched on 1 October 2012, the Ministry of Justice announced officially the amended enforcement rules on 26 September, 2012. The title of the enforcement rules was also amended to the Enforcement Rules of the Personal Data Protection Act. The new version of personal data protection law and enforcement rules was thus officially launched, creating a brand new era for the promotion of personal data protection in Taiwan. II. Personal Data Administration System and Information Privacy Protection Charter Before the amendment to the Personal Data Protection Act was passed, the Legislative Yuan made a proposal to the government in June 2008 to promote a privacy administration and protection certification system in Taiwan, in reference to foreign practices. In August of the following year, the Strategic Review Board of the Executive Yuan passed a resolution to promote the E-Commerce Personal Data Administration and Information Security Action Plan. In December of the same year, approval was granted for the plan to be included in the key government promotion plans from 2010 to 2013. Based on this action plan, since October 2010, the Ministry of Economic Affairs has asked the Institution for Information Industry to execute an E-Commerce Personal Data Administration System Setup Plan. Since 2012, the E-Commerce Personal Data Administration System Promotion Plan and the Taiwan Personal Information Protection and Administration System (TPIPAS) have been established and promoted, with the objective of procuring enterprises to, while complying with the personal data protection legal system, properly protect consumers’ personal information through the establishment of an internal administration mechanism and ensuring that the introducing enterprises meet the requirements of the system. The issuance of the Data Privacy Protection Mark (dp.mark) was also used as an objective benchmark for consumers to judge the enterprise’s ability to maintain privacy. Regarding the introduction of the personal data administration system, enterprises should establish a content administration mechanism step by step in accordance with the Regulations for Taiwan Personal Information Protection and Administration System. Such system also serves as the review benchmark to decide whether domestic enterprises can acquire the Data Privacy Protection Mark (dp.mark). Since domestic enterprises did not have experience in establishing internal personal data administration system in the past, starting 2011, under the Taiwan Personal Information Protection and Administration System, enterprises received assistance in the training of system professionals such as Personal Data Administrators and Personal Data Internal Appraisers. Quality personal data administrators can help enterprises establish complete internal systems. Internal appraisers play the role of confirming whether the systems established by the enterprises are consistent with the system requirements. As of 2012, there are almost 100 enterprises in Taiwan that participate in the training of system staff and a total of 426 administrators and 131 internal appraisers. In terms of the introduction of TPIPAS, in additional to the establishment and introduction of administration systems by qualified administrators, enterprises can also seek assistance from external professional consulting institutions. Under the Taiwan Personal Information Protection and Administration System, applications for registration of consulting institutions became available in 2012. Qualified system consulting institutions are published on the system website. Today 9 qualified consulting institutions have completed their registrations, providing enterprises with personal data consulting services. After an enterprise completes the establishment of its internal administration system, it may file an application for certification under the Taiwan Personal Information Protection and Administration System. The certification process includes two steps: “written review” and “site review”. After the enterprise passing certification, it is qualified to use the Data Privacy Protection Mark (dp.mark). Today 7 domestic companies have passed TPIPAS certification and acquired the dp.mark: 7net, FamiPort, books.com.tw, LOTTE, GOHAPPY, PAYEASY and Sinya Digital, reinforcing the maintenance of consumer privacy information through the introduction of personal data administration system. III. Event Analysis The Taiwan Personal Information Protection and Administration System (TPIPAS) is a professional personal data administration system established based on the provisions of the latest version of the domestic Personal Data Protection Act, in reference to the latest requirements of personal data protection by international organizations and the experience of main countries in promoting personal data administration system. In accordance with the practical requirements to protect personal data by industries, TPIPAS converted professional legal conditions into an internal personal data administration procedure to effectively assist industries to establish a complete and proper personal data administration system and to comply with the requirements of personal data legislations. With the launch of the new version of the Personal Data Protection Act, introducing TPIPAS and acquiring dp.mark are the best strategies for enterprises to lower the risk from the personal data protection law and to upgrade internal personal data administration capability.

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