The activities of accessing to Taiwan's biological resources can be governed within certain extent described as follows.
Taiwan's existing regulation empowers the government to control the access to biological resources within certain areas or specific species. The National Park Law, the Forestry Act, and the Cultural Heritage Preservation Act indicate that the management authority can control the access of animals and plants inside the National Park, the National Park Control Area, the recreational area, the historical monuments, special scenic area, or ecological protection area; forbid the logging of plants and resources within the necessary control area for logging and preserved forestry, or control the biological resources inside the natural preserved area. In terms of the scope of controlled resources, according to the guidance of the Wildlife Conservation Act and the Cultural Heritage Preservation Act, governmental management authority is entitled to forbid the public to access the general and protected wild animals and the plant and biological resources that are classified as natural monuments.
To analyse the regulation from another viewpoint, any access to resources in areas and of species other than the listed, such as wild plants or microorganism, is not regulated. Therefore, in terms of scope, Taiwan's management of the access to biological resources has not covered the whole scope.
Taiwan's current management of biological resources adopts two kinds of schemes: access permit scheme and entrance permit in specific areas. The permit allows management authority to have the power to grant and reject the collection, hunting, or other activities to access resources by people. This scheme is similar to the international standard.
The current management system for the access to biological resources promoted by many countries and international organizations does not usually cover the guidance of entrance in specific areas. This is resulting from that the scope of the regulation about access applies for the whole nation. However, since Taiwan has not developed regulations specifically for the access of bio-research resources, the import/export regulations in the existing Wildlife Conservation Act, National Park Law, Forestry Act, and Cultural Heritage Preservation Act may provide certain help if these regulations be properly connected with the principle of access and benefit sharing model, so that they will help to urge people to share the research interests.
Comparing to the access for the purpose of business operation, Taiwan's regulations favour the research and development that contains collection and hunting for the purpose of academic researches. The regulation gives permits to the access to biological resources for the activities with nature of academic researches. For instance, the Wildlife Conservation Act, National Park Law, and theCultural Heritage Preservation Act allow the access of regulated biological resources, if the academic research unit obtains the permit, or simply inform the management authority.
In addition, the access by the aborigines is also protected by the Forestry Act, Cultural Heritage Preservation Act, and the Aboriginal Basic Act. The aborigines have the right to freely access to biological resources such as plants, animals and fungi.
In topics of the access to and benefit sharing of biological resources, the PIC between parties of interests has been the focus of international regulation. Similarly, when Taiwan was establishing theAboriginal Basic Act, this regulation was included to protect the aborigines' rights to be consulted, to agree, to participate and to share the interests. This conforms to the objective of access and benefit sharing system.
The existing Wildlife Conservation Act, National Park Law, Forestry Act,Cultural Heritage Preservation Act, Aboriginal Basic Act provide the regulation guidance to the management of the access to biological resources within certain scope. Comparing to the international system of access and benefit sharing, Taiwan's regulation covers only part of the international guidance. For instance, Taiwan has no regulation for the management of wild plants and micro-organism, so there is no regulation to confine the access to wild plants and microorganism. To enlarge the scope of management in terms of the access to Taiwan's biological resources, the government authority has authorize the related scholars to prepare the draft of Genetic Resources Act.
The aim of the Genetic Resources Act is to establish the guidance of the access of genetic resources and the sharing of interests in order to preserve the genetic resources. The draft regulates that the bio-prospecting activity should be classified into business and academic, with the premise of not interfering the traditional usages.
After classification, application of the permit should be conducted via either general or express process. During the permit application, the prospector, the management authority, and the owner of the prospected land should conclude an agreement jointly. In the event that the prospector wishes to apply for intellectual property rights, the prospector should disclose the origin of the genetic resources and provide the legally effective documents of obtaining these resources. In addition, a Biodiversity Fund should be established to manage the profits derived from genetic resources. The import/export of genetic resources should also be regulated. Violators should be fined.
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. [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).
Taiwan Recent Regulatory Development- Promoting Biotech and New Pharmaceuticals IndustryOver the past twenty years, the Government has sought to cultivate the biopharmaceutical industry as one of the future major industry in Taiwan. Back in 1982, the Government has begun to regard biotechnology as a key technology in Technology Development Program, demonstrated that biotechnology is a vital technology in pursuit of future economic growth. Subsequently, the Government initiated national programs that incorporated biotechnology as a blueprint for future industrial development. In order to enhance our competitiveness and building an initial framework for the industry, The Executive Yuan has passed the Biotechnology Industry Promotion Plan. As the Government seeks to create future engines of growth by building an environment conducive for enterprise development, the Plan has been amended four times, and implemented measures focused on the following six areas: related law and regulations, R&D and applications, technology transfer and commercialization, personnel training, investment promotion and coordination, marketing information and marketing service. In 2002, the Executive Yuan approved the Challenge 2008, a six-year national development plan, pointing out biotechnology industry as one of the Two Trillion, Twin Stars industries. The Government planned for future economic growth by benefiting through the attributes of the biotechnology: high-tech, high-reward and less pollution. Thus, since 1997 the Strategic Review Board (SRB) under the Executive Yuan Science and Technology Advisory Panel has taken action in coordinating government policies with industry comments to form a sound policy for the biotechnology industry. Additionally, a well-established legal system for sufficient protection of intellectual property rights is the perquisite for building the industry, as the Government recognized the significance through amending and executing related laws and regulations. By stipulating data exclusivity and experimental use exception in the Pharmaceutical Affair Act, tax benefits provided in Statute for Upgrading Industries , Incentives for Production and R&D of Rare Disease Medicine, Incentives for Medical Technology Research and Development, provide funding measures in the Guidance of Reviewing Programs for Promoting Biotechnology Investment. Clearly, the government has great expectation for the industry through establishing a favorable environment by carrying out these policies and revising outdated regulations. Thus, the Legislative Yuan has passed the “Act for The Development of Biotechnology and New Pharmaceuticals Industry” in June, 2007, and immediately took effect in July. The relevant laws and regulations became effective as well, driving the industry in conducting researches on new drugs and manufacturing new products, increasing sales and expanding the industry to meet an international level. For a biopharmaceutical industry that requires long-term investment and costly R&D, incentive measures is vital to the industry’s survival before the product launches the market. Accordingly, this article will be introducing the recent important regulation that supports the biopharmaceutical industry in Taiwan, and analyzing the government’s policies. Biotechnology is increasingly gaining global attention for its potential in building future economic growth and generating significant profits. In an effort to support the biotechnology industry in Taiwan, the Government has made a step forward by enacting the “Act for the Development of Biotech and New Pharmaceutical Industry”. The biopharmaceutical industry is characterized as high-risk and high-reward, strong government support and a well-developed legal system plays a vital role from its establishment throughout the long term development. Therefore, the Act was enacted tailor to the Biotech and New Pharmaceutical Industry, primarily focuses on tax benefits, R&D activities, personnel recruitment and investment funding, in support of start-up companies and attracting a strong flow of funding worldwide. To pave the way for promoting the biopharmaceutical industry and the Biotech and New Pharmaceutical Company, here the article will be introducing the incentive measures provided in the Act, and supporting development of the industry, demonstrating the efforts made by the Government to build a “Bio-tech Island”. Reference “Act for Development of Biotech and New Pharmaceutical Industry”, webpage of Law and Regulations Database of the Republic of China. 4 July, 2007. Ministry of Justice, Taiwan. 5 Nov. 2008 http://law.moj.gov.tw/Eng/Fnews/FnewsContent.asp?msgid=3180&msgType=en&keyword=undefined
Experiences about opening data in private sectorExperiences about opening data in private sector Ⅰ. Introduction Open data is the idea that data should be available freely for everyone to use and republish without restrictions from copyright, patents or other mechanisms of control. The concept of open data is not new; but a formalized definition is relatively new, and The Open Definition gives full details on the requirements for open data and content as follows: Availability and access: the data must be available as a whole with no more than a reasonable reproduction cost, preferably by downloading over the internet. The data must also be available in a convenient and modifiable form. Reuse and redistribution: the data must be provided under terms that permit reuse and redistribution including the intermixing with other datasets. The data shall be machine-readable. Universal participation: everyone must be able to use, reuse and redistribute the data— which by means there should be no discrimination against fields of endeavor or against persons or groups. For example, “non-commercial” restrictions that would prevent “commercial” use, or restrictions of use for certain purposes are not allowed. In order to be in tune with international developmental trends, Taiwan passed an executive resolution in favor of promoting Open Government Data in November 2012. Through the release of government data, open data has grown significantly in Taiwan and Taiwan has come out on top among 122 countries and areas in the 2015 and 2016 Global Open Data Index[1]. The result represented a major leap for Taiwan, however, progress is still to be made as most of the data are from the Government, and data from other territories, especially from private sector can rarely be seen. It is a pity that data from private sector has not being properly utilized and true value of such data still need to be revealed. The following research will place emphasis to enhance the value of private data and the strategies of boosting private sector to open their own data. Ⅱ. Why open private data With the trend of Open Government Data recent years, countries are now starting to realize that Open Government Data is improving transparency, creating opportunities for social and commercial innovation, and opening the door to better engagement with citizens. But open data is not limited to Open Government Data. In fact, the private sector not only interacts with government data, but also produces a massive amount of data, much of which in need of utilized. According to the G20 open data policy agenda made in 2014, the potential economic value of open data for Australia is up to AUD 64 billion per annum, and the potential value of open data from private sector is around AUD 34 billion per annum. Figure 1 Value of open data for Australia (AUD billion per annum) Source: McKinsey Global Institute The purpose for opening data held by private entities and corporations is rooted in a broad recognition that private data has the potential to foster much public good. Openness of data for companies can translate into more efficient internal governance frameworks, enhanced feedback from workers and employees, improved traceability of supply chains, accountability to end consumers, and with better service and product delivery. Open Private Data is thus a true win-win for all with benefiting not only the governance but environmental and social gains. At the same time, a variety of constraints, notably privacy and security, but also proprietary interests and data protectionism on the part of some companies—hold back this potential. Ⅲ. The cases of Open Private Data Syngenta AG, a global Swiss agribusiness that produces agrochemicals and seeds, has established a solid foundation for reporting on progress that relies on independent data collection and validation, assurance by 3rd party assurance providers, and endorsement from its implementing partners. Through the website, Syngenta AG has shared their datasets for agricultural with efficiency indicators for 3600 farms for selected agro-ecological zones and market segments in 42 countries in Europe, Africa, Latin America, North America and Asia. Such datasets are precious but Syngenta AG share them for free only with a Non-Commercial license which means users may copy and redistribute the material in any medium or format freely but may not use the material for commercial purposes. Figure 2 Description and License for Open data of Syngenta AG Source: http://www.syngenta.com Tokyo Metro is a rapid transit system in Tokyo, Japan has released information such as train location and delay times for all lines as open data. The company held an Open Data Utilization Competition from 12 September to 17 November, 2014 to promote development of an app using this data and continues to provide the data even after the competition ended. However, many restrictions such as non-commercial use, or app can only be used for Tokyo Metro lines has weakened the efficiency of open data, it is still valued as an initial step of open private data. Figure 3 DM of Tokyo Metro Open data Contest Source: https://developer.tokyometroapp.jp/ Ⅳ. How to enhance Open Private Data Open Private Data is totally different from Open Government Data since “motivation” is vital for private institutions to release their own data. Unlike the government data can be disclosed and free to use via administrative order or legislation, all of the data controlled by private institutions can only be opened under their own will. The initiative for open data therefore shall focus on how to motivate private sectors releasing their own data-by ensuring profit and minimizing risks. Originally, open data shall be available freely for everyone to use without any restrictions, and data owners may profit indirectly as users utilizing their data creating apps, etc. but not profit from open data itself. The income is unsteady and data owners therefore lose their interest to open data. As a countermeasure, it is suggested to make data chargeable though this may contradict to the definition of open data. When data owners can charge by usage or by time, the motivation of open data would arise when open data is directly profitable. Data owners may also worry about many legal issues when releasing their own data. They may not care about whether profitable or not but afraid of being involved into litigation disputes such as intellectual property infringement, unfair competition, etc. It is very important for data owners to have a well protected authorization agreement when releasing data, but not all of them is able to afford the cost of making agreement for each data sharing. Therefore, a standard sample of contract that can be widely adopted plays a very important role for open private data. A data sharing platform would be a solution to help data owners sharing their own data. It can not only provide a convenient way to collect profit from data sharing but help data owners avoiding legal risks with the platform’s standard agreement. All the data owners have to do is just to transfer their own data to the platform without concern since the platform would handle other affairs. Ⅴ. Conclusion Actively engaging the private sector in the open data value-chain is considered an innovation imperative as it is highly related to the development of information economy. Although many works still need to be done such as identifying mechanisms for catalyzing private sector engagement, these works can be done by organizations such as the World Bank and the Centre for Open Data Enterprise. Private-public collaboration is also important when it comes to strengthening the global data infrastructure, and the benefits of open data are diverse and range from improved efficiency of public administrations to economic growth in the private sector. However, open private data is not the goal but merely a start for open data revolution. It is to add variation for other organizations and individuals to analyze to create innovations while individuals, private sectors, or government will benefit from that innovation and being encouraged to release much more data to strengthen this data circulation. [1] Global Open Data Index, https://index.okfn.org/place/(Last visited: May 15, 2017)
Hard Law or Soft Law? –Global AI Regulation Developments and Regulatory ConsiderationsHard Law or Soft Law? –Global AI Regulation Developments and Regulatory Considerations 2023/08/18 Since the launch of ChatGPT on November 30, 2022, the technology has been disrupting industries, shifting the way things used to work, bringing benefits but also problems. Several law suits were filed by artists, writers and voice actors in the US, claiming that the usage of copyright materials in training generative AI violates their copyright.[1] AI deepfake, hallucination and bias has also become the center of discussion, as the generation of fake news, false information, and biased decisions could deeply affect human rights and the society as a whole.[2] To retain the benefits of AI without causing damage to the society, regulators around the world have been accelerating their pace in establishing AI regulations. However, with the technology evolving at such speed and uncertainty, there is a lack of consensus on which regulation approach can effectively safeguard human rights while promoting innovation. This article will provide an overview of current AI regulation developments around the world, a preliminary analysis of the pros and cons of different regulation approaches, and point out some other elements that regulators should consider. I. An overview of the current AI regulation landscape around the world The EU has its lead in legislation, with its parliament adopting its position on the AI ACT in June 2023, heading into trilogue meetings that aim to reach an agreement by the end of this year.[3] China has also announced its draft National AI ACT, scheduled to enter its National People's Congress before the end of 2023.[4] It already has several administration rules in place, such as the 2021 regulation on recommendation algorithms, the 2022 rules for deep synthesis, and the 2023 draft rules on generative AI.[5] Some other countries have been taking a softer approach, preferring voluntary guidelines and testing schemes. The UK published its AI regulation plans in March, seeking views on its sectoral guideline-based pro-innovation regulation approach.[6] To minimize uncertainty for companies, it proposed a set of regulatory principles to ensure that government bodies develop guidelines in a consistent manner.[7] The US National Institute of Standards and Technology (NIST) released the AI Risk Management Framework in January[8], with a non-binding Blueprint for an AI Bill of Rights published in October 2022, providing guidance on the design and use of AI with a set of principles.[9] It is important to take note that some States have drafted regulations on specific subjects, such as New York City’s Final Regulations on Use of AI in Hiring and Promotion came into force in July 2023.[10] Singapore launched the world’s first AI testing framework and toolkit international pilot in May 2022, with the assistance of AWS, DBS Bank, Google, Meta, Microsoft, Singapore Airlines, etc. After a year of testing, it open-sourced the software toolkit in July 2023, to better develop the system.[11] There are also some countries still undecided on their regulation approach. Australia commenced a public consultation on its AI regulatory framework proposal in June[12], seeking views on its draft AI risk management approach.[13] Taiwan’s government announced in July 2023 to propose a draft AI basic law by September 2023, covering topics such as AI-related definition, privacy protections, data governance, risk management, ethical principles, and industrial promotion.[14] However, the plan was recently postponed, indicating a possible shift towards voluntary or mandatory government principles and guidance, before establishing the law.[15] II. Hard law or soft law? The pros and cons of different regulatory approaches One of the key advantages of hard law in AI regulation is its ability to provide binding legal obligations and legal enforcement mechanisms that ensure accountability and compliance.[16] Hard law also provides greater legal certainty, transparency and remedies for consumers and companies, which is especially important for smaller companies that do not have as many resources to influence and comply with fast-changing soft law.[17] However, the legislative process can be time-consuming, slower to update, and less agile.[18] This poses the risk of stifling innovation, as hard law inevitably cannot keep pace with the rapidly evolving AI technology.[19] In contrast, soft law represents a more flexible and adaptive approach to AI regulation. As the potential of AI still remains largely mysterious, government bodies can formulate principles and guidelines tailored to the regulatory needs of different industry sectors.[20] In addition, if there are adequate incentives in place for actors to comply, the cost of enforcement could be much lower than hard laws. Governments can also experiment with several different soft law approaches to test their effectiveness.[21] However, the voluntary nature of soft law and the lack of legal enforcement mechanisms could lead to inconsistent adoption and undermine the effectiveness of these guidelines, potentially leaving critical gaps in addressing AI's risks.[22] Additionally, in cases of AI-related harms, soft law could not offer effective protection on consumer rights and human rights, as there is no clear legal obligation to facilitate accountability and remedies.[23] Carlos Ignacio Gutierrez and Gary Marchant, faculty members at Arizona State University (ASU), analyzed 634 AI soft law programs against 100 criteria and found that two-thirds of the program lack enforcement mechanisms to deliver its anticipated AI governance goals. He pointed out that credible indirect enforcement mechanisms and a perception of legitimacy are two critical elements that could strengthen soft law’s effectiveness.[24] For example, to publish stem cell research in top academic journals, the author needs to demonstrate that the research complies with related research standards.[25] In addition, companies usually have a greater incentive to comply with private standards to avoid regulatory shifts towards hard laws with higher costs and constraints.[26] III. Other considerations Apart from understanding the strengths and limitations of soft law and hard law, it is important for governments to consider each country’s unique differences. For example, Singapore has always focused on voluntary approaches as it acknowledges that being a small country, close cooperation with the industry, research organizations, and other governments to formulate a strong AI governance practice is much more important than rushing into legislation.[27] For them, the flexibility and lower cost of soft regulation provide time to learn from industries to prevent forming rules that aren’t addressing real-world issues.[28] This process allows preparation for better legislation at a later stage. Japan has also shifted towards a softer approach to minimize legal compliance costs, as it recognizes its slower position in the AI race.[29] For them, the EU AI Act is aiming at regulating Giant Tech companies, rather than promoting innovation.[30] That is why Japan considers that hard law does not suit the industry development stage they’re currently in.[31] Therefore, they seek to address legal issues with current laws and draft relevant guidance.[32] IV. Conclusion As the global AI regulatory landscape continues to evolve, it is important for governments to consider the pros and cons of hard law and soft law, and also country-specific conditions in deciding what’s suitable for the country. Additionally, a regular review on the effectiveness and impact of their chosen regulatory approach on AI’s development and the society is recommended. [1] ChatGPT and Deepfake-Creating Apps: A Running List of Key AI-Lawsuits, TFL, https://www.thefashionlaw.com/from-chatgpt-to-deepfake-creating-apps-a-running-list-of-key-ai-lawsuits/ (last visited Aug 10, 2023); Protection for Voice Actors is Artificial in Today’s Artificial Intelligence World, The National Law Review, https://www.natlawreview.com/article/protection-voice-actors-artificial-today-s-artificial-intelligence-world (last visited Aug 10, 2023). [2] The politics of AI: ChatGPT and political bias, Brookings, https://www.brookings.edu/articles/the-politics-of-ai-chatgpt-and-political-bias/ (last visited Aug 10, 2023); Prospect of AI Producing News Articles Concerns Digital Experts, VOA, https://www.voanews.com/a/prospect-of-ai-producing-news-articles-concerns-digital-experts-/7202519.html (last visited Aug 10, 2023). [3] EU AI Act: first regulation on artificial intelligence, European Parliament, https://www.europarl.europa.eu/news/en/headlines/society/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence (last visited Aug 10, 2023). [4] 中國國務院發布立法計畫 年內審議AI法草案,經濟日報(2023/06/09),https://money.udn.com/money/story/5604/7223533 (last visited Aug 10, 2023). [5] id [6] A pro-innovation approach to AI regulation, GOV.UK, https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach/white-paper (last visited Aug 10, 2023). [7] id [8] AI RISK MANAGEMENT FRAMEWORK, NIST, https://www.nist.gov/itl/ai-risk-management-framework (last visited Aug 10, 2023). [9] The White House released an ‘AI Bill of Rights’, CNN, https://edition.cnn.com/2022/10/04/tech/ai-bill-of-rights/index.html (last visited Aug 10, 2023). [10] New York City Adopts Final Regulations on Use of AI in Hiring and Promotion, Extends Enforcement Date to July 5, 2023, Littler https://www.littler.com/publication-press/publication/new-york-city-adopts-final-regulations-use-ai-hiring-and-promotionv (last visited Aug 10, 2023). [11] IMDA, Fact sheet - Open-Sourcing of AI Verify and Set Up of AI Verify Foundation (2023), https://www.imda.gov.sg/-/media/imda/files/news-and-events/media-room/media-releases/2023/06/7-jun---ai-annoucements---annex-a.pdf (last visited Aug 10, 2023). [12] Supporting responsible AI: discussion paper, Australia Government Department of Industry, Science and Resources,https://consult.industry.gov.au/supporting-responsible-ai (last visited Aug 10, 2023). [13] Australian Government Department of Industry, Science and Resources, Safe and responsible AI in Australia (2023), https://storage.googleapis.com/converlens-au-industry/industry/p/prj2452c8e24d7a400c72429/public_assets/Safe-and-responsible-AI-in-Australia-discussion-paper.pdf (last visited Aug 10, 2023). [14] 張璦,中央通訊社,AI基本法草案聚焦隱私保護、應用合法性等7面向 擬設打假中心,https://www.cna.com.tw/news/ait/202307040329.aspx (最後瀏覽日:2023/08/10)。 [15] 蘇思云,中央通訊社,2023/08/01,鄭文燦:考量技術發展快應用廣 AI基本法延後提出,https://www.cna.com.tw/news/afe/202308010228.aspx (最後瀏覽日:2023/08/10)。 [16] supra, note 13, at 27. [17] id. [18] id., at 28. [19] Soft law as a complement to AI regulation, Brookings, https://www.brookings.edu/articles/soft-law-as-a-complement-to-ai-regulation/ (last visited Aug 10, 2023). [20] supra, note 5. [21] Gary Marchant, “Soft Law” Governance of Artificial Intelligence (2019), https://escholarship.org/uc/item/0jq252ks (last visited Aug 10, 2023). [22] How soft law is used in AI governance, Brookings,https://www.brookings.edu/articles/how-soft-law-is-used-in-ai-governance/ (last visited Aug 10, 2023). [23] supra, note 13, at 27. [24] Why Soft Law is the Best Way to Approach the Pacing Problem in AI, Carnegie Council for Ethics in International Affairs,https://www.carnegiecouncil.org/media/article/why-soft-law-is-the-best-way-to-approach-the-pacing-problem-in-ai (last visited Aug 10, 2023). [25] id. [26] id. [27] Singapore is not looking to regulate A.I. just yet, says the city-state’s authority, CNBC,https://www.cnbc.com/2023/06/19/singapore-is-not-looking-to-regulate-ai-just-yet-says-the-city-state.html#:~:text=Singapore%20is%20not%20rushing%20to,Media%20Development%20Authority%2C%20told%20CNBC (last visited Aug 10, 2023). [28] id. [29] Japan leaning toward softer AI rules than EU, official close to deliberations says, Reuters, https://www.reuters.com/technology/japan-leaning-toward-softer-ai-rules-than-eu-source-2023-07-03/ (last visited Aug 10, 2023). [30] id. [31] id. [32] id.