Impact of Government Organizational Reform to Scientific Research Legal System and Response Thereto (2) – For Example, The Finnish Innovation Fund (“SITRA”)

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)。

※Impact of Government Organizational Reform to Scientific Research Legal System and Response Thereto (2) – For Example, The Finnish Innovation Fund (“SITRA”),STLI, https://stli.iii.org.tw/en/article-detail.aspx?no=55&tp=2&i=168&d=6981 (Date:2025/12/12)
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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).

Draft of AI Product and System Evaluation Guidelines Released by the Administration for Digital Industries to Enhance AI Governance

Draft of AI Product and System Evaluation Guidelines Released by the Administration for Digital Industries to Enhance AI Governance 2024/08/15 I. AI Taiwan Action Plan 2.0 In 2018, the Executive Yuan launched the “AI Taiwan Action Plan” to ensure that the country keeps pace with AI developments. This strategic initiative focuses on attracting top talent, advancing research and development, and integrating AI into critical sectors such as smart manufacturing and healthcare. The action plan has sparked growing discussion on AI regulation. Through these efforts, Taiwan aims to position itself as a frontrunner in the global smart technology landscape. Later in 2023, the Executive Yuan updated the action plan, releasing “AI Taiwan Action Plan 2.0” to further strengthen AI development. “AI Taiwan Action Plan 2.0” outlines five main pillars: 1. Talent Development: Enhancing the quality and quantity of AI expertise, while improving public AI literacy through targeted education and training initiatives. 2. Technological and Industrial Advancement: Focusing on critical AI technologies and applications to foster industrial growth; and creating the Trustworthy AI Dialogue Engine (TAIDE) that communicates in Traditional Chinese. 3. Enhancing work environments: Establishing robust AI governance infrastructure to facilitate industry and governmental regulation, and to foster compliance with international standards. 4. International Collaboration: Expanding Taiwan's role in international AI forums, such as the Global Partnership on AI, to collaborate on developing trustworthy AI practices. 5. Societal and Humanitarian Engagement: Utilizing AI to tackle pressing societal challenges such as labor shortages, an aging population, and environmental sustainability. II. AI Product and System Evaluation Guidelines: A Risk-based Approach to AI Governance To support infrastructure, in March 2024, the Administration for Digital Industries issued the draft AI Product and System Evaluation Guidelines. The Guidelines are intended to serve as a reference for industry when developing and using AI products and systems, thus laying a crucial foundation for advancing AI-related policies in Taiwan. The Guidelines outline several potential risks associated with AI: 1. Third-Party Software and Hardware: While third-party software, hardware, and datasets can accelerate development, they may also introduce risks into AI products and systems. Therefore, effective risk management policies are crucial. 2. System Transparency: The lack of transparency in AI products and systems makes risk assessment relatively challenging. Inadequate transparency in AI models and datasets also pose risks for development and deployment. 3. Differences in Risk Perception: Developers of AI products and systems may overlook risks specific to different application scenarios. Moreover, risks may gradually emerge as the product or system is used and trained over time. 4. Application Domain Risks: Variations between testing results and actual operational performance can lead to differing risk assessments for evaluated products and systems. 5. Deviation from Human Behavioral Norms: If AI products and systems behave unexpectedly compared to human operations, this can indicate a drift in the product, system, or model, thereby introducing risks. The Guidelines also specify that businesses have to categorize risks when developing or using AI products and systems, and manage them in accordance with these classifications. In alignment with the EU AI Act, risks are classified into four levels: unacceptable, high, limited, and minimal. 1. Unacceptable Risk: If AI systems used by public or private entities provide social scoring of individuals, this could lead to discriminatory outcomes and the exclusion of certain groups. Furthermore, if AI systems are employed to manipulate the cognitive behavior of individuals or vulnerable populations, causing physical or psychological harm, such systems are deemed unacceptable and prohibited. 2. High risk: AI systems are classified as high-risk in several situations. These include applications used in critical infrastructure, such as transportation, where there is potential risk to citizens' safety and health. These situations also encompass AI systems involved in educational or vocational training (such as exam scoring), which can determine access to education or professional paths. AI used as safety-critical product components, such as robot-assisted surgery, also falls into this category. In the employment sector, AI systems used for managing recruitment processes, including CV-sorting software, are considered high-risk. Essential private and public services, such as credit scoring systems that impact loan eligibility, also fall under high-risk. AI used in law enforcement in ways that it may affect fundamental rights, such as evaluating the reliability of evidence, is also included. AI systems involved in migration, asylum, and border control, such as automated visa application examinations, are categorized as high-risk. Finally, AI solutions used in the administration of justice and democratic processes, such as court ruling searches, are also classified as high-risk. If an AI system is classified as high risk, it must be evaluated across ten criteria—Safety, Explainability, Resilience, Fairness, Accuracy, Transparency, Accountability, Reliability, Privacy, and Security—to ensure the AI system’s quality. 3. Limited risk: When an AI product or system is classified as having limited risk, it is up to the enterprise to determine whether an evaluation is required. The Guidelines also introduce specific transparency obligations to ensure that humans are informed when necessary, thus fostering trust. For instance, when using AI systems such as chatbots or systems for generating deepfake content, humans must be made aware that they are interacting with a machine so they can take an informed decision to continue or step back. 4. Minimal or no risk: The Guidelines allow the free use of minimal-risk AI. This includes applications such as AI-enabled video games and spam filters. Ⅲ. Conclusion The AI Product and System Evaluation Guidelines represent a significant step forward in establishing a robust, risk-based framework for AI governance in Taiwan. By aligning with international standards like the EU AI Act, these Guidelines ensure that AI products and systems are rigorously assessed and categorized into four distinct risk levels: unacceptable, high, limited, and minimal. This structured approach allows businesses to manage AI-related risks more effectively, ensuring that systems are safe, transparent, and accountable. The emphasis on evaluating AI systems across ten critical criteria—including safety, explainability, and fairness—reflects a comprehensive strategy to mitigate potential risks. This proactive approach not only safeguards the public but also fosters trust in AI technologies. By setting clear expectations and responsibilities for businesses, the Guidelines promote responsible development and deployment of AI, ultimately contributing to Taiwan's goal of becoming a leader in the global AI landscape.

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