A Preliminary Study on The Legal Effect of the Blockchain-Generated Data in Taiwan

A Preliminary Study on The Legal Effect of the Blockchain-Generated Data in Taiwan

I. Preface

  Governments around the world have set various regulations and guidelines to deal with the increasing application of blockchain technology, trying to keep the law up to date with technological development and the latest trends. Among them, the application of blockchain technology to regulations has become a hot topic. Because of its features, such as immutable, easy to verify and transparently disclosed, it can improve the efficiency of law enforcement and reduce cost. Moreover, decentralization and the verification mechanism generated by mathematical computation can avoid the disputes arising from the existing system, in which the mechanism is set up and controlled by independent institutions, and thus the credibility could be universal. The international trend also shows the importance attached to the application of blockchain technology in the legal field. In 2017, the “Legal Services Innovation Index”, a study conducted by the Michigan State University College of Law and Google evaluated the level of innovation of law firms according to the search data on innovation indicators of the world’s major law firms. Blockchain has the highest number of clicks among all indices, and the average number of clicks of blockchain is more than twice that of AI.[1] In addition, there are international cases regarding the connection between the blockchain technology and legal provisions as well as the real cases that used blockchain technology to handle legal matters.[2] An organization, such as the Global Legal Blockchain Consortium (GLBC), work with enterprises, law firms, software development units, and schools to study the standards formulation and application methods of the application of blockchain technology to law-related matters. [3] This article will first discuss the legal enforceability of data generated by the blockchain technology through international cases, then review Taiwan’s current status and the legal enforceability of the data generated by the blockchain technology and to explore possible direction for regulatory adjustment if the government intends to ease the restriction on the application of blockchain in the fields of evidence authentication and deposition.

II. International cases

1. US case: adjust the existing regulations and recognize the enforceability of blockchain technology

  The amendment HB2417[4] to the Arizona Electronic Transactions Act (AETA) signed by Arizona in April 2017 defines the blockchain technology and smart contracts and recognizes their legal effect on signatures, records and smart contracts. HB2417 defines “blockchain technology” as a “distributed, decentralized, shared and replicated ledger, which may be public or private, permissioned or permissionless, or driven by “tokenized crypto economics or tokenless” and provides that the “data on the ledger” is protected with cryptography, is immutable and auditable and provides an uncensored truth.” It’s worth noting that although, by definition, the data is true, it is uncensored truth in nature, which emphasizes the originality of the data. A “smart contract” is an “event driven program, with state, that runs on a distributed, decentralized, shared and replicated ledger that can take custody over and instruct transfer of assets on that ledger.” Under the original AETA regulations, records or signatures in electronic form cannot be deprived of legal validity and enforceability merely because they are in electronic form. To eliminate the legal uncertainty of any blockchain related transactions and smart contracts related to digital assets, HB 2417 states that a signature that is secured through blockchain technology is considered to be in an electronic form and to be an electronic signature, and a record or contract that is secured through blockchain technology is considered to be in an electronic form and to be an electronic record.  The statute also provides that smart contracts may exist in business, and a contract relating to a transaction may not be denied legal effect, validity or enforceability solely because that contract contains a “smart contract term.” This makes the enforceability of electronic signing and electronic transactions made by Arizona’s blockchain technology equivalent to that of the signature and contract made by the traditional written format. In the following year, the Ohio governor signed the amendment SB220[5] to the Uniform Electronic Transactions Act (UETA) in August 2018, which took effect from November. The focus of the amendment is the same as that in Arizona. Although, unlike HB 2417, SB220 does not define blockchain technology, the added content can still guarantee the enforceability of electronic signatures and contracts made by the blockchain technology. The focus of the two amendments in the US is to supplement and revise the laws and regulations made in the past so that they are applicable to the transaction method under blockchain technology and have the same effect as other recognized methods. This reduces the uncertainty related to blockchain technology at the regulatory and commercial application level, and is expected to attract the blockchain related companies, investors and developers.

2. Case of China: The enforceability of blockchain technology in evidence deposition is recognized in line with courts’ new type of judgment.

  In September 2018, the Supreme People's Court implemented “The Provisions on Several Issues Concerning the Trial of Cases by Internet Courts,”[6] in which Paragraph 2 of Article 11 mentions that where the authenticity of the electronic data submitted by a party can be proven through electronic signature, trusted time stamp, hash value check, blockchain or any other evidence collection, fixation or tamper-proofing technological means, or through the certification on an electronic evidence collection and preservation platform, the Internet court shall make a confirmation. It shows that the Internet court can recognize the evidence deposited by blockchain technology, and its enforceability is equivalent to that of other technologies if its authenticity can be proved. Paragraph 1 of the same article also proposes the basis for review and judgment on the relevant standards for the broad definition of electronic evidence recognition. “The authenticity of generation, collection, storage and transmission process of the electronic data shall be examined and judged, and the items to be reviewed include whether the hardware and software environments such as the computer system based on which electronic data is generated, collected, stored and transmitted are safe and reliable; whether electronic data originator and generation time are specified, and whether the contents shown are clear, objective and accurate; whether the storage and safekeeping media of electronic data are definite, and whether the safekeeping methods and means are appropriate; whether electronic data extractor and fixer, and electronic data extraction and fixation tools and methods are reliable, and whether the extraction process can be reproduced; whether the contents of electronic data are added, deleted, modified or incomplete, or fall under any other circumstance; and whether electronic data can be verified in specific methods.” The judgment is based on a clear review. It is a supplement to the notarization process, which was the solo judgment basis for the enforceability of digital evidence. In addition, the rules on proof are clearly set out in Article 9, which covers two situations: online and offline. For offline evidence, the parties can convert it into electronic materials by scanning, re-shooting and duplicating, and then upload it to the litigation platform. For online evidence, it can be divided into two situations. One is the online electronic evidence possessed by the party, which can be imported to the litigation platform by providing links or uploading materials. The other is that the Internet court can obtain the structural information of the relevant cases from the e-commerce platform operators, Internet service providers and electronic data deposition and retrieve platform, and import it to the litigation platform to directly provide the information to both parties so that they can select and prove their claims. In this way, the court can use technical means to complete the migration and visual presentation of information. Before the Supreme People's Court enforced the provisions, the Hangzhou Internet Court of China recognized the enforceability of electronic evidence under the blockchain technology when hearing a copyright dispute in June 2018. The court's judgment pointed out that after reviewing the impartiality, technical level and evidence preservation methods of the blockchain evidence deposit service provider, the enforceability of the evidence is recognized, and thus the case was deemed infringement.[7] Beijing Dongcheng District Court also reviewed the blockchain deposition technology in an infringement of information network communication in September of the same year, including data generation, deposition, preservation, and recognized the enforceability of electronic evidence made by the blockchain technology. The court adopted the electronic evidence[8]. The Beijing Internet Court allows evidence deposition of the litigation files and evidence uploaded to the electronic litigation platform through the Balance Chain of evidence deposition established by the blockchain technology when handling the litigation cases online. This can prevent tampering and ensure the safety of litigation while keeping possible litigation evidence to facilitate verification in the future. While the Balance Chain is going online, the supporting standards, including the Beijing Internet Court Electronic Evidence Platform Access and Management Standards, the Enforcement Rules of the Beijing Internet Court Electronic Evidence Platform Access and Management Standards, the Application Form for Beijing Internet Court Electronic Evidence Deposition Access and the Instruction on the Beijing Internet Court Electronic Evidence Deposition Access Interface, are released simultaneously. These supporting standards prescribe the requirement of receivers, the requirement for the electronic information system of the receiver and the requirement for the juridical application of the evidence platform in details from the practical point of view so that the potential receivers can interconnect in a compliant manner while ensuring the quality of the connected data.

III. Taiwan’s current situation

  In the above cases, the United States amended the laws and regulations related to the electronic transaction by increasing the scope of the terms, such as electronic forms of records, signatures and transactions so that the records, signatures and transactions made by the blockchain technology is as effective as that of other technologies. According to Article 9 of the Taiwanese Electronic Signatures Act, the enforceability of the data generated by blockchain technology shall still be judged case by case in terms of the technology for electronic documents, signature and transaction formation, and its applicability or exclusion shall be determined by laws or administrative agencies. In China, the role of electronic data is discussed in the relevant standards used by the Internet Court to examine the cases. Regarding the definition of electronic materials, electronic records and electronic documents, Paragraph 1 of Article 2 of the Taiwanese Electronic Signatures Act defines electronic document as a record in electronic form, which is made of “any text, sound, picture, image, symbol, or other information generated by electronic or other means not directly recognizable by human perceptions, and which is capable of conveying its intended information.”[9] In addition, Article 4 states “With the consent of the other party, an electronic record can be employed as a declaration of intent. Where a law or regulation requires that information be provided in writing, if the content of the information can be presented in its integrity and remains accessible for subsequent reference, with the consent of the other party, the requirement is satisfied by providing an electronic record. By stipulation of a law or regulation or prescription of a government agencies, the application of the two preceding paragraphs may be exempted, or otherwise require that particular technology or procedure be followed. In the event that particular technology or procedure is required, the stipulation or prescription shall be fair and reasonable, and shall not provide preferential treatment without proper justifications.” [10] The electronic records, regardless of the type of technology, are given the same effect as paper documents with the consent of both parties. In litigation, electronic records, electronic evidence or similar terms are not found in the Criminal Code of the Republic of China, the Civil Code, the Code of Criminal Procedure and the Taiwan Code of Civil Procedure. The adoption of electronic records often refers to Paragraph 2 of Article 220 of the Criminal Code of the Republic of China[11]. An audio recording, a visual recording, or an electromagnetic recording and the voices, images or symbols that are shown through the computer process and are sufficient evidence of intention shall be considered a document. The content that is considered meaningful is that the identity of the person expressing the content is identifiable according to the content and can be used to prove legal relationship or fact in social life. The relevant standards for proof under the electronic evidence follow Article 363 of the Taiwan Code of Civil Procedure[12]. For non-documentary objects which operate as documents, including those are accessible only through technological devices or those that are practically difficult to produce their original version, a writing representing its content along with a proof of the content represented as being true to the original will be acceptable. However, the way of proof or recognition standards are not sufficiently described. Or according to Paragraph 2 of Article 159-4 of the Code of Criminal Procedure, “documents of recording nature, or documents of certifying nature made by a person in the course of performing professional duty or regular day to day business, unless circumstances exist making it obviously unreliable. In addition”, and Paragraph 3 “ Documents made in other reliable circumstances in addition to the special circumstances specified in the preceding two Items.” [13] In fact, the Juridical Yuan started to promote the electronic litigation platform (including online litigation) in 2016, and has launched the online litigation business by gradually opening the application for different types of applicants and litigation.[14] However, there is no description on the technical type and inspection standards of electronic evidence. Moreover, only the litigation evidence is uploaded. There is no evidence deposition before litigation for comparison during litigation.

  Under Taiwan’s laws and regulations, electronic evidence and its proving method is not significantly different from other types of evidence. The judgment of evidence shall still depend on judges’ recognition on the evidence. Taking the practice of criminal litigation as an example, it can be viewed at three levels[15]: 1. The submission of the evidence. If the evidence is collected illegally, not following a statutory method or is not logically related to the pending matters, it will be excluded. This is the way to determine whether the evidence is eligible to enter the evidence investigation process. 2. In the investigation of evidence, the method of investigation (e.g., whether it is legal), the determination of relevance and the debate on evidence (e.g., to confirm the identity of the person producing the electronic evidence, whether the electronic evidence is identical to the original version without addition, deletion or alteration) are investigated during the investigation procedure. 3. The debate on evidence is to determine the power of the evidence by considering the relationship among the elements that constitute the whole and whether the evidence can prove the connection among all elements.  In addition, whether the electronic evidence is consistent with the original version is often based on Article 80 of the Notary Act, "When making notarial deeds, notaries shall write down the statements listened to, the circumstances witnessed, and other facts they have actually experienced. The means and results of the experience shall also be stated in the notarial deeds.” [16] A notary shall review the electronic evidence and record the inspection process and the inspection results to demonstrate its credibility.

VI. Conclusions and recommendations

  According to the latest 2050 smart government plan[17] announced in the Executive Yuan’s 3632nd meeting held on December 27, 2018, the government is planning to connect the database of each government agency through blockchain technology, and the plan also includes establishment of digital identification. It is foreseeable that there will be more and more electronic materials, documents and records connected by blockchain technology in the future. When it comes to improve management efficiency and reduce the barriers to introduce this technology to various sectors, it is necessary to adjust the related regulations. At present, there are no statutory provisions for the technology that assist the use of the electronic evidence involved in traditional litigation channels or online platforms, including using blockchain for evidence deposition and authentication . This also poses uncertainty to the judges when they make judgments. If we consider the continuous development and breakthrough of technology, which is relatively faster than the legislative process, and the traditional tangible transactions and contracts are still the majority in life, Taiwan has defined electronic materials, electronic records and electronic documents in the Electronic Signatures Act to ensure and strengthen the legal rights and benefits under the adoption of the technology. In addition, the Electronic Signatures Act also reserves the right to determine whether the technology is applicable to the laws and regulations or administrative agencies. In other words, the technology behind electronic materials, records and documents are not specified, and the aforementioned electronic materials have the same effect as the contracts and signature as the traditional written format. However, there are no standards to specify which standards are valid for evidence deposition and authentication for electronic materials on the level of deposition and authentication. In the future, when improving the relevant functions of the online litigation platform, the Juridical Yuan can also consider using technologies, such as blockchain or timestamps to provide evidence deposition service, which is expected to enhance the efficiency of evidence verification for online litigation in the future and prevent wasting review resources on invalid evidence for a better operation mode. This is in line with the government's policy direction. By providing support and demonstration of emerging technologies, not only limited to blockchain, on the legal level, it can reduce the public’s uncertainty and risk on introducing or applying the technology to legal process. This is very helpful in realizing a large scale application of the technology.


[1] Legal Services Innovation Index, Phase 1, Version 1.0, https://www.legaltechinnovation.com/law-firm-index/ (last visited on Jan. 11, 2019).

[2] For example, Arizona's Arizona Electronic Transactions Act (AETA) and Ohio’s Uniform Electronic Transactions Act (UETA) described the electronic signature and the enforceability of contracts under blockchain technology; in China, Beijing Internet Court provides litigation files and litigation evidence deposition service based on blockchain technology for future litigation.

[3] The Global Legal Blockchain Consortium website, https://legalconsortium.org/ (last visited on Jan. 11, 2019).

[4] H.B. 2417, 53th Leg., 1st Regular. (AZ. 2017).

[5] S.B. 220, 132ND General Assembly. (OH. 2017-2018).

[6]“The Provisions on Several Issues Concerning the Trial of Cases by Internet Courts,” the Supreme People's Court of the People’s Republic of China http://www.court.gov.cn/zixun-xiangqing-116981.html
(last visited on Jan. 11, 2019).

[7] Tencent Research Institute, <The era of judicial blockchain has arrived? ——from the two cases of blockchain electronic deposition>, October 23, 2018, https://ek21.com/news/1/132154/ (last visited on Jan. 11, 2019).

[8] Securities Daily, <Beijing Dongcheng District Court confirmed the evidence collection by blockchain for the first time-- application of "blockchain + justice" for new opportunities in history> October 20, 2018, https://www.jinse.com/bitcoin/258170.html (last visited on Jan. 11, 2019).

[9] Paragraph 1 of Article 2 of the Electronic Signatures Act

[10] Article 4 of the Electronic Signatures Act

[11] Paragraph 2 of Article 220, “A writing, symbol, drawing, photograph on a piece of paper or an article which by custom or by special agreement is sufficient evidence of intention therein contained shall be considered a document within the meaning of this Chapter and other chapters. So shall be an audio recording, a visual recording, or an electromagnetic recording and the voices, images or symbols that are shown through computer process and are sufficient evidence of intention.”

[12] Article 363 of the Taiwan Code of Civil Procedure, “The provisions of this Item shall apply mutatis mutandis to non-documentary objects which operate as documents. Where the content of a document or an object provided in the preceding paragraph is accessible only through technological devices or it is practically difficult to produce its original version, a writing representing its content along with a proof of the content represented as being true to the original will be acceptable. The court may, if necessary, order an explanation of the document, object, or writing representing the content thereof provided in the two preceding paragraphs.”

[13] Paragraph 2 of Article 159-4 of the Code of Criminal Procedure

[14] Liberty Times, <The Juridical Yuan is promoting “E-litigation.”  Two new systems are on the road.” August 1, 2018, http://news.ltn.com.tw/news/society/breakingnews/2506118 (last visited on Jan. 11, 2019).

[15] Chih-Lung Chen, “Seminar on the Reform of the Code of Criminal Procedure 3: Revision Direction of Rule of Evidence,” The Taiwan Law Review, Issue 52, Page 71-73 (1999).

[16] Article 80 of the Notary Act.

[17] BlockTempo, <The Executive Yuan Announced the Smart Government New Plan: the Taiwan Government will Use Blockchain Technology to Establish Information Exchange Mechanism of Various Agencies>, January 2, 2019, https://www.blocktempo.Com/taiwan-gv-want-to-use-blockchain-tech-build-data/ (last visited on Jan. 11, 2019).

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※A Preliminary Study on The Legal Effect of the Blockchain-Generated Data in Taiwan,STLI, https://stli.iii.org.tw/en/article-detail.aspx?no=105&tp=2&i=171&d=8253 (Date:2019/12/13)
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A Survey Study on the Intellectual Property Management amongst Taiwanese Companies

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IP management is essential to preserve IP created by companies and the TIPS system would enable companies to foster and strengthen key aspects of IP management such as conduct training in IP issues for employees, evaluate various IPRs required, etc. Some of the complementary measures as such expert consultations and TIPS networks or seminars would also help to alleviate some of the hardships encountered in the process of managing IP. On the other hand, like the “Survey on Business Attitudes to Intellectual Property” being conducted yearly in Hong Kong since year 2004, it is suggested that the present survey research or the alike to be continually carried out to assist promoting IP awareness within Taiwan industry. 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Yearly Update on the Progress of the TIPS Project – summary of a research report on corporate investors’ view on introducing a corporate IP disclosure framework

Chien-Shan Chiu Background In the era where inventions drive the economy, the ability to create, capture and protect these inventive ideas has become vital for a corporation to stay competitive and sustain profit growth. Various government policies have been implemented in order to stimulate inventions and to strengthen the ability to protect these inventions through effective use of intellectual property (“IP”) rights. For the past few years, the TIPS (Taiwan Intellectual Property Management System) project has been promoted extensively aiming to increase public awareness towards IP rights and to assist local companies to establish a systematic and comprehensive IP management system. Over the years, the TIPS project has received wide recognition and positive feedbacks, and many TIPS-implemented companies are ready for the next challenges. After an extensive research, the project proposes to follow the international trend of encouraging companies to make better and more disclosure of intangible assets that are not often shown in the traditional financial statements1 . Local companies with effective IP management system and strategy are encouraged to compile an “Intellectual Property Management Report” summarizing its business, R&D and IP management strategies as well as their accumulated IP assets. In order to compile an Intellectual Property Management Report, a company is advised to re-identify its intellectual property, re-think about its strength and weakness in every aspect and where necessary, the company may also need to re-conduct a market, technology trend or competitor’s analysis, through which it is believed that a better and more effective IP strategy will be re-formulated. 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The research report contains the result of a survey conducted between April and June this year (year 2009), consisting questions to uncover local investors’ view and attitudes towards corporate IP, and to identify kinds of IP-related information required when making an investment decision as well as to find out to what extend local investors would support the government’s initiative on promoting a corporate IP disclosure framework. Update on the Yearly Progress of the TIPS Project In order to facilitate the promotion of TIPS, several supplementary services have been introduced (fees and expenses are fully or partially subsidized by the government this year) : (1) Free On-Line Self-Assessment Tool; (2) On-Site Diagnostic and Consulting Service (selected companies were fully subsidized); (3) “Demonstrative” Model Companies (selected companies were partially subsidized); (4) IP Management Courses (partially subsidized); (5) On-Site Auditing (for the Conformance of TIPS requirements) and issuing of the TIPS Compliance Certification (fully subsidized) . To the end of 2009, 401enterprises have completed the on-line self-assessment questions; 93 companies have received on-site diagnostic and consultation services; 847 persons have taken the IP management courses; 64 enterprises have successfully obtained the certificates for the compliance of TIPS and more than 299 enterprises have either completed or in the middle of implementing TIPS. Summary of the Research Report on Corporate Investor s’ View on Introducing a Corporate IP Disclosure Framework Even though it is clear that the idea of encouraging corporations to disclose non-financial information has started few decades ago in Europe and are currently being vigorously promoted by many major countries, we believe that in order to facilitate smooth promotion of the new IP disclosure framework, it is important to find out the local investors’ views and attitudes towards IP and to know how investors see the role of IP can play in a local corporation. Hence a survey was conducted at the initial stage of preparing the new corporate IP disclosure framework in Taiwan. The survey was sent via both mails and emails to 357 corporations, including venture capital firms; trust, investment consulting or management firms; security corporations, financial institutions and banks. More than one set of survey questionnaires could be distributed in one corporation to be filled by investors/analysts that are specialized in investing different industrial sectors. As a result, a total of 495 set of questionnaires were distributed.. Basic Data The survey was conducted between April to June 2009. At the end of June, a total of 150 investors/analysts responded which equals to a 33% response rate. Most of the survey respondents specialized in investing in various industrial sectors which include: semi-conductor; telecommunication; electronic components; 3C products; IT; optical; biotechnology; pharmaceuticals; new energy resources; media; creative and culture and traditional manufacturing industries. Around 50% of the survey respondents have more than 5 years’ experience in investment; among them, 23% of the survey respondents have more than 10 years’ investment experience. Investors recognize the importance of IP A remarkable 94% of the survey respondents recognized that the ability to create, protect, manage and exploit IP has become an essential element for a company to stay competitive and sustain growth in today’s market environment. 88% of the survey respondents believe that companies with more or better IP assets are more likely to generate profits and 91% believe that such companies are more likely to survive in this ever-increasing competitive environment. Yet, 94% of the survey respondents agreed that not only a company should actively create IP assets, but the ability to exploit and thus extract value from the accumulated IP assets is what makes a company stand out among the others. Taking a step further, the survey result reveals that the respondent investors believe a company with effective and well-planned IP strategy is likely to: – Enhance its market competitiveness (84%); – Raise its overall corporate value (71%); – Maintain its market position (55%); – Increase its profitability (32%); – Affect its share price (30%); – Assist investors in evaluating such company’s managerial ability and performance (29%) as well as evaluating its future growth potential (28%). IP-related information influences investors’ investment decisions Given that most investors see the ability to create, manage and exploit IP assets as well as having a well-planned IP strategy are crucial for the survival of a company, 82% of the survey respondents indicate that IP-related information has been considered when making an investment decision. Furthermore, 85% of the survey respondents think that they will place greater emphasis on IP in assessing companies in the future. Indicators that used to assess/evaluate a company Most often used IP-related indicators identified by the survey respondents when making investment decisions are: – Core technology and its market competitiveness (77%) – Research ability (experience and achievement) (73%) – IP protection and management measures (41%) – IP strategy (align with overall corporate strategy and market/technology characteristics) (40%) – Ability to fully utilize self-owned IP assets (38%) – R&D expenditure and investment (35%) – No. of IP assets (35%) – Time taken for competing products to enter into the market (33%) – Cost of maintaining IP assets (19%) Ratio of intangible assets as to the overall corporate value (19%) : 20% of the survey respondents indicated that they have turned down investment in the past for inadequate IP awareness of the target companies. List of local companies with good and effective IP strategy The survey respondents were asked to name local Taiwanese companies which in their mind have most effective and sound IP strategy. Taiwan Semiconductor Manufacturing Company (TSMC), Foxconn, United Microelectrc (UMC), HTC, Acer are the top 5 most named companies given by the survey respondents. Having good quality of patents (such as essential or new technology patents); detailed and complete patent map; sound IP strategy; brand and professional IP/legal department are cited as the reasons that impress these investors. Inadequacy of public available IP-related information While most investors acknowledge the importance of IP and take into account various IP-related indicators when making investment decisions, 76% of the survey respondents expressed that currently, the amount of IP-related information disclosed by companies are not sufficient for them to make an informed investment decision. When a question asking the survey respondents to identify the channels by which they obtained their desired IP-related information, the results were quite spread out. 45% of the survey respondents relied on asking the top managers directly; 43% relied on annual report; media and news (35%); website (34%); industrial journals (25%); competitors (15%) and other private channels (15%). It appears that various sources were used but no particular source provides sufficient information. Indeed, a remarkable 91% of the survey respondents believe that if there are more channels provided for corporations to disclose their internal IP information, more accurate assessment of the corporate value can be made. Support government’s initiative of promoting IP reporting framework Further, 73% of the survey respondents expressed their willingness to support the government’ s initiative of encouraging local companies to disclose their IP-related information. In relation to the initiation and promotion of the corporate IP disclosure framework, 64% of the survey respondents responded that it would be better to adopt a voluntarily disclosure policy and decide whether to switch to mandatory disclosure later; 22% think that only a voluntarily disclosure policy should be adopted followed by 14% of the survey respondents who believe that the government should adopt a mandatory disclosure policy from the start. When the survey respondents were asked to provide suggestions to facilitate the promotion of the corporate IP disclosure framework, the following suggestions were picked by the survey respondents: – Provide valuation tools to assist investors in assessing and analyzing IP related information (40%); – a central platform to collect and display all the complied IP management reports (21%); – lists of compulsory items to be disclosed in the report (21%); and – regulate the frequency of updating the contents of the report (15%). Conclusion Based on the results of the survey, we can conclude that the local investors’ view and attitude towards IP are similar to those in overseas. Majority of the investors (> 90%) see IP as valuable tools that could assist companies to create profits and sustain growth in today’s competitive market. While most of the investors (82%) have taken into account relevant IP information when making investment decisions, 76% of the survey respondents expressed that the amount of corporate IP-related information disclosed by companies are insufficient for them to make informed investment decisions. This is an important message that local companies should pay particular attention. It is hoped that through the introduction of the corporate IP disclosure framework, more adequate corporate IP information will be disclosed to assist investors in making better and accurate investment decisions. Consequently, a company’s true capabilities, managerial efforts and the intangible assets created upon can thus be fully appreciated and reflected on its market value. 1 Various national and institutional initiatives addressing the disclosure of corporate intellectual assets are currently being promoted vigorously at the international level such as Japan’s “IA based Management Report, (METI)”; Denmark’s “Intellectual Capital Statement (MSTI)”; European Union’s “Guidelines on Intangibles, MERITUM project”; U.S.’s “EBR 2.0 (Enhance Business Reporting Consortium)”; and The World Intellectual Capital/Assets Initiative (WICI) is currently working on developing a voluntary global framework for measuring and reporting corporate performance.

Copyright Ownership for Outputs by Artificial Intelligence

Copyright Ownership for Outputs by Artificial Intelligence One. Introduction I. From Machine Learning to Deep Learning, AI is Thinking   The famous philosopher, mathematician and physicist René Descartes from France in the 17th century said: “Cogito ergo sum”. This is considered a radical skepticism in the context of philosophy. When a philosopher raises the question that how one person can be sure of his/her existence, it is not about the feeling, cognition or experience with the world. Rather, it is about thinking.   Artificial intelligence works like interconnected human neurons, with the logics and algorithms built with codes and processed with high speed. The nutrient it requires is the massive amount of data. In the past, artificial intelligence only works according to the logical setup and instructions from developers. In the era of machine learning today, humans have empowered machines with the capability of processing. This is achieved not by writing comprehensive and exhaustive rules. Rather, it is by making machines able to figure out rules on their own. In other words, all we need to do is to prepare data. Machines can be trained to think and judge. Artificial intelligence will eventually generate its outputs and start to create contents.   Image recognition is a good illustration of how machine learning works, as part of the wider AI. The identification of cats is a classic example. A large number of pictures and photos of cats are provided, with descriptions of features to train machines. The purpose is to train machines into building their own criteria as to what cats are about. According to the Proceedings of the Seventh IEEE International Conference on Computer Vision in 1999, image recognition is processed with the technology similar with neurons for visual recognition by primates[1].   Twenty years on, machine learning (as part of artificial intelligence) has come a long way. The number of neural network models, built on neurons, has grown exponentially[2]. Deep learning has been developed with layers of neurons. There are links only between neighbouring layers to reduce the number of variables and enhance the speed of computing. In the context of machine learning, learning is about the selection of an optimal solution from multiple variables[3]. Big data is fed into the man-made neural networks constructed in the computers so that they are constantly trained and learning. Hung-yi Lee[4], a scholar specialized in artificial intelligence in Taiwan, provides a simple analogy for this technology. Machine learning is like a human brain with one layer of neurons; whilst deep learning works with many neurons and hence can learn on their own, make judgement and establish logics[5]. In other words, artificial intelligence is capable of analysing, identifying and decision-making on its own, and human is becoming less relevant in this process. Artificial intelligence is able to think. This is not only a factual description, but also a trigger to fundamentally change the legal institution of nations. II. Who Owns the Outputs Generated with Thinking?   Over the long run, whether the legal institution and the society are ready to give artificial intelligence “quasi” right of personality is a topic worth exploring. In the immediate term, what normative models should be used to define the ownership of copyrights for the outputs and creations by artificial intelligence?   The decision on copyright ownership has always been a hot topic in the field of intellectual property. The legal system in the U.S. describes the protected entity for copyright as “the fruits of the intellectual labor”. Article 798 of the Civil Code in Taiwan says, “Fruits that fall naturally on an adjacent land are deemed to belong to the owner of such land, except if it is a land for public use”. The fruit, i.e. outputs generated by artificial intelligence, also falls into the society of rules governed by rights and obligations. Of course, it is necessary to first define and regulate the entity that owns the rights. This begs many fundamental questions in the context of copyright laws. Who owns the rights? The developers (perhaps on a pro-rata basis), data owners, or the companies that provide infrastructure to developers? Once the boundary of imagination and reality is pushed further, the ownership of rights is no longer limited to human creators and may be extended to artificial intelligence. Moreover, it is possible for governments to insist that copyrights are only for human creations and the intellectual property created by artificial intelligence may fall into the public domain and hence fall unprotected legally, given the significance of public interest involved.   This paper explores the copyright ownership for the outputs generated by artificial intelligence by systemically observing the real-life cases in the industry. This is followed with an analysis on the perspectives from the European Union, the United Kingdom and the United States. The purpose is to examine the contexts and normative models of artificial intelligence and copyrights and finally develop a preliminary framework for the regulation of artificial intelligence now and the future. Two. Creativity Capability of Artificial Intelligence Is a Reality   With artificial intelligence and Big Data driving the development of industries, the exploration with the construction and normative models of the legal system should start with the reflection of social values, so as to achieve the purpose of social order with laws and regulations.   The construction of the legal system for technology should be anchored on the observation of facts, given the rapid advancement and evolution of emerging technologies. The fact today is that artificial intelligence is being used for art creations such as musical composition, poetry and painting. Developers train artificial intelligence with massive data and enable deep learning to grasp the essence of artworks in order to generate outputs. Whether the ultimate purpose is commercial profitability or not, most of these outputs have reached a certain level of quality. Below is a brief introduction of creative techniques and new business models of artificial intelligence in music composition, poetry writing, painting and news writing. I. Original Music Generated with Deep Learning: Fast and User-friendly   The vibrant development of the Internet has created an online celebrity economy. Youtubers, Internet personalities, cyberstars, Wanghong (or internet fame in Mandarin) produce films or release podcasts to attract the audience for direct/indirect and commercial/non-profit-seeking purposes. The production of such films and live broadcasting, or the creation of original online or PC games creates the demand for background music or sound effects. Ed Newton-Rex, who earned a bachelor of arts degree in music from University of Cambridge, founded JukeDeck[6] after he went to a computer science class in Harvard University. JukeDeck is an online music generator, developed with deep learning(as part of artificial intelligence). This paper believes that JukeDeck meets the industry demand with two offerings[7]: (I) JukeDeck Rapid generation of pleasant and unique music with deep learning The algorithm design by Ed Newton-Rex with artificial intelligence is different from the generation of background music and other music by the websites that use loop audio files. JukeDeck generates music pleasing to the ears with one tone at a time and avoids repetitions by analyzing musical forms, harmonies and tones with deep learning, so that the users in pursuit of originality and unique can acquire the musical materials within approximately 30 seconds, without worrying that they sound similar with others[8]. Greater flexibility in length to create bespoke styles and feelings JukeDeck offers flexibility in the length of music, up to five minutes depending on the preference of users. An extension is possible by mixing up different fragments. It is also possible to define musical styles and formats, e.g. piano, folksongs, electro and ambient music[9], as well as the feelings to be aroused, such as uplifting and melancholic. The music generated by deep learning is different from the free or paid music databases which use the so-called canned music and suffer the problems of mismatches between the film length and music length[10]. (II) Amper Music   Amper Music was founded by the Hollywood songwriter Drew Silverstein (founder/CEO), Sam Estes and Michael Hobe[11] with the ambition to take a step further from music generation by artificial intelligence. In the spring of 2018, the company raised another $4 million for the development of music composition with artificial intelligence, the expansion of international markets and the recruitment of more talents. In the press release, Drew Silverstein said, “Amper’s rapid growth is a testament to how the massive growth of media requires a technological solution for music creation. Amper’s value stems not only from the means to collaborate and create music through AI, but also from its ability to help power media at a global scale.”[12]   Similar with JukeDeck’s appeal to the public, Amper Music’s artificial intelligence allows users with no musical experience to create real-time and order original music[13]. It supports all the media formats. All is required is the choice for rhythms, styles and musical instruments desired[14]. Meanwhile, Amper Music posits that its music is royalty free, and comes with a global, perpetual license when synced to the outputs. In other words, users do not have to worry about legal procedures or financial costs[15]. II. Writing Pens Take Flight: A Challenge to the Fundamental of Literary Creation and Trigger for Labor Transformation   Neuhumanismus (or Neohumanism) is about the achievement of self-mastery and humanity ideals through the study of classics. Compared with humanism, neohumanism places a greater focus on emotional expression and artistic creation. It also emphasizes the importance of language learning to self-realization of individuals.[16] After studying the works of 519 contemporary poets in the Chinese society, artificial intelligence has published modern poetry and made successful inroads to the world of literature traditionally driven by emotions and imaginations. In fact, it has posed a credible challenge to the human-centric humanism where only humans are endowed with the gift of artistic creativity. Artificial intelligence has been nominated for literary awards, evidenced of the quality of outputs generated by deep learning. With the support of massive data and analytics, it is only a matter of time for artificial intelligence to possess the literary creativity comparable to humans.   However, the concern for originality in literature and the issues surrounding plagiarism and copyrights are the key determinants that influence of literary creation by artificial intelligence. This begs the questions about the ethics of literary creation. It is necessary to start with an understanding of how artificial intelligence creates, before the analysis of ethical and regulatory frameworks. (I) Xiaoice’s Collection “Sunshine Misses Windows”   Xiaoice is the chatbot launched by Microsoft’s Software Technology Center Asia (STCA) in China in 2014. In 2017, Xiaoice published her collection of poems “Sunshine Misses Windows”[17], written by looking at pictures. The deep learning algorithms behind were co- developed by Wu Zhao-Zhong and Cheng Wen-Feng, two students in the Graduate Institute of Networking and Multimedia, National Taiwan University.   The artificial intelligence writes poetry with the following methodology[18]: Use of image recognition technology to identify the keywords in the pictures: The adoption of image recognition technology developed by Microsoft’s Software Technology Center Asia (STCA) to identify the nouns in the pictures such as the bridge, skies and trees and the adjectives that express feelings such as beautiful or annoying. Matching of keywords from the training database: The training data for the matching of keywords and poetry database was the works of a total of 519 contemporary poets since the 1920s. The purpose was to fill in the gap between keywords and training data. Generation of poems: deep learning trained in the language model with keywords to create poems Improvement of poems: literary professionals and readers invited to give ratings. Submission of writings as an anonymous author to improve Xiaoice’s capability.   The above is a summary of Xiaoice’s creative journey. Microsoft claims that the collection of poems was 100% written by Xiaoice, and it is the first collection of poems 100% written by artificial intelligence in history. The poems were not edited by humans and wrong characters were maintained as they were. The title “Sunshine Misses Windows” was also named by Xiaoice herself[19]. Despite all these, the originality and even the most fundamental “literality” of these poems are still questioned.   At the end of 2018, the Research Institute for Humanities and Social Sciences, Ministry of Science & Technology and National Taiwan University organized the forum “Culture and Technology II: AI’s Literature Dream — Sunshine Misses Windows. Does Humanity Have a Boundary?” The professor in the Department of Chinese Literature, National Taiwan University and the poet Tang Juan discussed Xiaoice’s works[20] and commented as a critic of contemporary poetry. Xiaoice uses extensively the same vocabulary (such as the beach). Unable to use punctures, she can only break sentences and lines. Most importantly, her writings do not reflect our times and real experience. In other words, Xiaoice’s poems do not possess the unique perspective and soul of poets and literary characters. This may be the outcome of her reading of works from 519 poets from the 1920s. As a result, she is not able to connect with our times and real life and finds it difficult to resonate the shared emotions of people today. Tang Juan’s comment is more than just about literature. It is also about the selection and sourcing of training data, a prerequisite for the development of artificial intelligence, as well as the cost and consideration for copyright licensing.   The research and development by corporates in artificial intelligence requires the corresponding and suitable training materials, particularly in the domain of literature. As commented by the poet Tang Juan, it requires extensive sources of contemporary works. It means the increasing difficulty to circumvent the works still protected by copyrights. If this cost consideration remains a hurdle, it is impossible to make improvements in further research. Put differently, the composition of training data is potentially a cost concern for copyright licensing. Before the legal system becomes well-developed and the establishment of consensus on the issues concerning training data, the possible infringement is an absolutely necessary balancing act for any robust developers and companies involved in artificial intelligence. (II) Yuurei Raita’s “The Day A Computer Writes A Novel”   In 2013, Nikkei started to offer the Nikkei Hoshi Shinichi Literary Award to outstanding short Si-Fi novels, as a tribute to the late science fiction writer Hoshi Shinichi[21]. Three years later, Yuurei Raita’s “The Day A Computer Writes A Novel” appeared on Nikkei’s list of acceptance for competition. Miss Yoko is the leading character in this 2000-character short sci-fi novel[22]. Raita-kun is in fact an artificial intelligence team “Wagamama artificial intelligence as a writer” led by Hitoshi Matsubara, President of the Japanese Society of Artificial Intelligence and a professor in Future University[23]. Below is a description of their deep learning techniques[24]: Analysis of writing styles from training data: The team provides training data as the learning basis for artificial intelligence. (For this competition, the data is approximately 1,000 short stories written by Hoshi Shinichi.) The purpose is to analyze the frequently used words, novel structures and characters. Resource integration by the team: The team integrates the analyzed data with online information, storyline programs, human emotions and settings, and decides on characters, contents and plots[25]. Researchers provide three instructions, i.e., when, the weather, doing what so that artificial intelligence automatically generates detailed and tangible contents. Automatic generation of new works: Artificial intelligence refines the details and polishes the texts, to generate the new story by Hoshi Shinichi with fragments such as: “The same temperature and humidity in the room is maintained as usual. Yoko sits idly on the sofa, dishevelled and playing a dull game uninterested.”   The procedures of novel contents generation described above indicate that artificial intelligence still relies on humans for setups and assistance. In contrast with the claim by the Microsoft team that Xiaoice is 100% artificial intelligence, the team in Japan confessed that artificial intelligence writing is still in a nascent stage.   At least in literature types such as novels, artificial intelligence still needs appropriate guidance from humans for necessary writing elements, in order to generate and connect fragments to establish the finalized pieces. In general, artificial intelligence can only be held responsible for 20% of work[26]. However, the development of technology continues at its pace. When it is no longer easy to differentiate a piece of creative writing is by humans or by machines, the limitation of copyright protection to human’s creative works will be an obsolete approach. (III) Tencent: Robot “Dreamwriter”   The above two AI writing teams focus on creative literature. In China, Tencent has developed Dreamwriter to rapidly generate news products. In the 2018 International Media Conference in Singapore[27] hosted by the East West Center, a think tank in the U.S. at the end of June 2018, Tencent demonstrated its translation engine. Speakers spoke in Chinese and the engine did simultaneous translation into English shown on the projector screen[28].   Tencent’s artificial intelligence “Dreamwriter” project started as a push engine for news flashes such as sports events. It later extended into financial and economic data and reporting, a field with extensive data and conducive to AI development and ML acceleration[29]. Dreamwriter only takes half to one second to generate a piece of news. It can generate approximately 5,000 articles per day, equivalent to the output of 208 journalists. This implies a transformation of labor requirements in journalism. Human reporters will be involved in in-depth coverage that requires creativity, industry knowledge and judgement[30], whilst basic and factual reporting will be completed by artificial intelligence. III. Brave New Work for Paintings: Rights Ownership in the Presence of Sophisticated Deep Learning   In the autumn/winter of 2018, the Paris-based AI team Obvious presented “Portrait of Edmond Belamy”[31] in Prints & Multiples auction in New York. This painting was sold for a surprising high price of[32] $432,000 (or over NT$13 million)[33], as the first AI-generated painting being auctioned. The Obvious team focuses on Generative Adversarial Network (GAN)[34], a hot topic for the development of deep learning. (I) Technique to Improve Deep Learning: Generative Adversarial Network (GAN)   The GAN technique was developed by Ian Goodfellow[35] in 2014 to promote and enhance deep learning by massively reducing the amount of training data required and cutting down on human intervention, assistance and involvement[36].   The GAN method can be illustrated in a high level by referring to the classical example of the image recognition for cats previously mentioned. The neural network model (as a deep learning technique) enables artificial intelligence to learn how to identify cats from a massive volume of pictures of cats. However, it is necessary for humans to train the machine by providing signs and feature descriptions for each picture. In contrast, the GAN technique is about the training of two competing networks,[37] i.e., a generative network and a discriminant network[38]. The generative network is responsible for generating the pictures that resemble real cats (i.e. made-believe cats) and the discriminant network reviews and determine whether the pictures are authentic. The two networks enhance capabilities by competing with each other. The idea is to improve the learning and competence of deep learning[39]. (II) Application in the Art of Paintings   The GAN method can be used to generate paintings such as “Portrait of Edmond Belamy”. It can also identify fake paintings. Founder/CEO Jensen Huang of Nvidia, a leading artificial intelligence company, said in a forum that the GAN technique allows one neural network to paint the pictures in the Picasso style and the other network to identify images and paintings with unprecedented discriminant capabilities[40]. The seventh year of the Lumen Prize gave the biggest award to a nude portrait generated with the GAN technique[41]. The GAN applications have been mushrooming – turning a scribble into an art, a low-definition picture into a high-definition one, an aerial graph into a photo[42].   Below is a brief description of the concepts and procedures for the Obvious research team’s completion of “Portrait of Edmond Belamy”[43]: Analysis of portraits from training data: A total of 15,000 portraits from the 14th century to the 20th century as the training data Generative network vs. discriminant network: The generative network generates paintings on the basis of training data. The discriminant network seeks to identity the difference from human-created paintings in order to improve the capability of the generative network. This process continues until the discriminant network is no longer to tell a machine-created painting from a human-created painting. (III) Ownership of Rights to High Economic Value of Artworks   The winning of the Lumen Prize in the UK by the nude portrait generated by artificial intelligence and the surprisingly high auction price paid for Portrait of Edmond Belamy are the testimony of the artificial intelligence’s creative capability. The ownership of the right to the monetary value of these artworks is a topic worthy of exploration.   “The development team ‘Obvious’ for ‘Portrait of Edmond Belamy’ posits that if the author is the person who paints the painting, it is artificial intelligence. If the author is the person who seeks to convey a message, it is us[44]. The human’s role is being undermined as deep learning technology becomes increasingly sophisticated. Going forward, can artificial intelligence become the owner of rights? What should be the regulatory framework for now? At this juncture, this paper conducts an international comparison by examining how different governments consider the emerging legal issues. Three. Copyright Ownership of Works Created by Artificial Intelligence   The explanatory ruling by the Copyright Division, Intellectual Property Office, Ministry of Economic Affairs issued in 2018[45] has expressed the Taiwan government’s stance on the issue of whether the outputs generated by artificial intelligence can enjoy copyrights. Below is the summary: Presumption: Article 10 and Article 33 of the Copyright Law[46] stipulates that only natural persons or legal persons can be the owner of rights and obligations pertaining to creative works and enjoy the protection of copyrights. Positioning and logics: The outputs generated by artificial intelligence are the intellectual results expressed by machines created by humans. Machines are neither natural persons or legal persons and hence do not attract copyrights. Proviso: If the results are created with participation of natural/legal persons and the machines are being operated for analytics, the copyright of the results expressed should belong to the natural/legal persons concerned.   The above explanatory ruling seems to position artificial intelligence completely as a tool. However, the above example suggests an obvious trajectory for the creative journey for deep learning as an artificial intelligence technique. In the current stage and the foreseeable future, the description that robot analytics are straight mechanical operations is completely obsolete given that artificial intelligence is being applied in industry with dramatically reduced (or even completely without) human intervention and participation.   It is a worthwhile exercise to explore the international thinking regarding how the legal framework should address the ownership of rights for outputs generated with deep learning as an artificial intelligence technique and the derived services/products by either opening up new legal structures or simply extending on the existing system. I. European Union (I) European Parliament: Establishment of Electronic Personhood?   The European Parliament's Committee on Legal Affairs (JURI) passed a report on January 12, 2018 to provide suggestions to the Civil Law Rules on Robotics and urge the European Commission to set up laws and regulations governing robots and artificial intelligence by defining electronic personhood, similar with legal personhood for corporates as litigation entities for any issues associated with rights and obligations of artificial intelligence[47]. (II) Court of Justice of the European Union: Only Works Accomplished by Humans Eligible for Protection   The Court of Justice of the European Union’s landmark case Infopaq International A/S v. Danske Dagbaldes Forening[48]suggests that copyrights are only applicable for original works, with originality reflecting the “author’s own intellectual creation.” The general interpretation is that such works should reflect the author’s personality. Hence, only human authors meet this criterion[49]. The third paragraph of Article 1 of the Directive 2009/24/EC also clearly states that only works that are the authors’ own intellectual creation enjoys eligibility for protection[50]. (III) Data Protection: GDPR and Declaration of cooperation on Artificial Intelligence   The General Data Protection Regulation (GDPR) in European Union attracted significant attention among the companies active in the EU market in 2018. In fact, the GDPR provides comprehensive and representative regulations that have direct influence on technological development of artificial intelligence training, as well as legal protection and right construction on data, the crude oil for deep learning.   Below are a few examples: Article 20 on data portability: The data subject has the right to receive his/her personal data from the data controller in a structured, commonly used and machine-readable format. This helps the industry to establish metadata and forms the basis of the database for artificial intelligence training. The consistency of metadata will enhance the training. Article 22 on automated individual decision-making The data subject has the right not to be subject to a decision based solely on automated processing. The data controller must lay down suitable measures to safeguard the data subject’s rights. Article 35 on data protection by design and by default This article provides the legal protection of large-scale and systematic monitoring of public and open areas with artificial intelligence and strikes a balance between the use of personal data and the interest of data subjects.   On top of the GDPR, the 24 member states of the European Union signed the Declaration of Cooperation on Artificial Intelligence in 2018, in order to enhance access to public sector data for the digital single market. II. United Kingdom (I) Copyright Law: Source of Laws for Program Developers to Obtain Copyrights   The copyright laws are stipulated in the Copyright, Designs and Patent Act (CDPA) 9 (3)[51]. It forms the source of the laws that grant copyrights to the developers of computer-generated works. Article 178 of the CDPA defines computer-generated works as the outputs generated by machines without human authors[52].   In contrast with the Court of Justice of the European Union’s decision that only human authors are eligible for copyright protection, the UK government opens up another door by specifying that program designers can obtain copyrights even if creative sparks come from machines[53]. This system is considered the most efficient because it enhances incentives for investments[54]. (II) Public Sector: Open up Government Data   The UK government also opens up its data by posting all the official statistics on the website www.data.gov.uk. The Digital Economy Bill provides the legal framework for government agencies to use each other’s data for the benefit of the public, so as to effectively address the issues surrounding frauds and debts and improve the real-timeliness and accuracy of national statistics.   As part of the Brexit preparation, the UK government has created its own GDPR (2018) to ensure the continued smooth cross-border operations of companies after Brexit. As it offers higher protection of consumers’ data and information, it is worthwhile to refer to the UK GDPR as a template for legal systems and rights frameworks. III. United States (I) U.S. Copyright Office: Only Intellectual Achievements of the Human Mind Eligible for Protection   The case law originated in 1991——Feist Publications v. Rural Telephone Service Company[55]confirms that copyrights protect the creative powers of the mind. In the Naruto v. Slater (2016)[56] case, the court determines that the photos taken by a monkey are not eligible for copyright protection. Article 313.2 of the implementation guidelines of the Copyright Act issued by the U.S. Copyright Office specify that the works created without human authors are not protected by the Copyright Act. The amendment to Article 313.2 in 2017 states clearly that the U.S. Copyright Act only protects the intellectual achievements of the human mind[57]. The U.S. Copyright Act 503.03(a), titled “Works-not originated by a human author” also states that only works created by a human author can register for copyrights[58]. (II) Employment Principle: Enhanced Incentives and Investment Willingness   The above court judgements and the implementation guidelines of the U.S. Copyright Act indicate that the U.S. Copyright Office does not confer non-human copyright[59]. However, the U.S. judicial rulings have allowed “the work made for hire provision” as exception to the creative authors, in order to encourage corporate investments. The 1909 amendment to the U.S. Copyright Act included the hired employees as authors. Unless otherwise agreed, “the author or proprietor of any work made the subject of copyright by this Act, or his executors, administrators, or assigns, shall have copyright for such work under the conditions and for the terms specified in this Act”. A typical example is the news agency’s employment of full-time journalists to produce editorials. The works by employees are a company’s key copyright assets[60]. (III)Employment/Sponsorship Principle if Realized in Taiwan: Companies Investing in Works to Obtain Copyright Protection   Article 11 of the R.O.C. Copyright Act stipulates the ownership of the right to the works of employees on a case-by-case and factual basis. The decision is based on the nature of work, e.g., completion under the employer’s instructions or planning, the use of the employer’s budgets or resources. It is not necessarily related to the work hours or locations. In principle, the employee is the author of the works completed by him/her on the job. However, the employment contract supersedes if it specifies that the employer is the author. On the other hand, if the employee is the author, the intellectual property belongs to the employer. The contract supersedes if it specifies that the employee enjoys the intellectual property. Article 12 is about sponsorship and commissioning. Unless specified by the contract, the sponsored owns the intellectual property of his/her works and the sponsor has the right to use such intellectual property[61]. In sum, the ownership of the right to the outputs generated by artificial intelligence is similar with the employment/sponsorship principle. It is not set in the vacuum of legal contexts.   Therefore, the scholar in Taiwan Lin Li-Chih suggests that the employment principle in the U.S. may be adopted. She posits that when certain conditions are met, artificial intelligence may be treated as the author, so that the outputs generated by artificial intelligence can be protected and the investing research institutes or corporates can own the works[62]. As both legal persons and natural persons can be authors in Taiwan, Lin Li-Chih proposes this approach to resolve disputes given the massive value to be created by artificial intelligence for different applications and the potential lengthy legislative process or laws disconnected from industry expectations. The idea is to avoid the human author requirement from hindering industry investments and innovations for works generated by artificial intelligence[63]. According to the employment/sponsorship principle, deep learning as an artificial intelligence method can be inferred to as the author and then teams and companies that develop the algorithms should own the intellectual property of the works. This will serve as the legal foundation for intellectual property protection. Four. Conclusion: Legal System and Policy Framework for Emerging Technologies I. Construction of Laws and Regulations on a Rolling Basis According to the Reality of Emerging Technologies   Every law has its purpose, and the contents of laws depend on their regulatory objectives. However, such contents should be anchored on facts, in order to align the intended purposes. This is particularly the case for the laws and regulations governing emerging technologies because such laws and regulations should capture the fact of technological developments. The most straightforward and fundamental approach to relax the control of the existing legal mechanism is via communication, coordination and understanding. It can be initiated with more dialogues between the government agency responsible for the construction of the legal environment and the industries and the public as subjects of the laws and regulations.   Regulators may wish to come up with dedicated laws for the comprehensive coverage of emerging technologies given the lack of understanding about the technology and the sweeping effects of the technology. However, not all technologies require special legislations. According to Frank H Easterbrook’s article “Cyberspace and the Law of the Horse” published by the University of Chicago’s legal journal, it is advised to properly categorize and analyze existing laws and regulations and apply the suitable ones to new technologies for issues surrounding intellectual property, contracts and torts, as if from the Law of the Horse to the Law of Cyberspace[64]. Similarly, the ownership of copyrights associated with artificial intelligence and the governance of emerging technologies such as autonomous driving and robots may be dealt in this way.   The above analysis on the legal regimes in the European Union, the United Kingdom and the United States highlights two issues concerning the regulation of artificial intelligence and the development of legal environments. The growing sophistication of deep learning will enhance the capability of artificial intelligence in thinking, analysis and creation, with human intervention expected to be reduced to almost zero. The legal regime governing emerging technologies cannot stand in the way of technological and industry development or incentives for investment, as originally intended by the intellectual property laws. A balancing act is required.   This paper thus suggests two models: Forward-looking approach to label rights ownership with legal articles This is the route taken by the UK government, by directly amending the intellectual property laws to specify that intellectual property of artificial intelligence belongs to program developers. It is the most efficient approach of paving the way for technological development by providing incentives to companies and developers. Adoption of the employment/sponsorship principle in conjunction with safe harbor clauses Another approach is without touching on the sensitive issue of law amendments. Judicial rulings or administrative interpretations by competent authorities are gradually released in the context of existing laws. A temporary solution is introduced with the adoption of the employment/sponsorship principle with corresponding templates and references for contract construction in the industry. This can work in conjunction with safe harbor clauses in the long run, by slowly converging the diversity of opinions and perspectives from corporates, government agencies and academic/research institutions. Adjustments by tightening or loosening on a rolling basis should be made in order to work out the optimal boundary and establish the basis for legislation in the next stage. II. Data as a Prerequisite for Artificial Intelligence Training   In Taiwan where the legal environment is not yet ready or clear, the ownership of intellectual property for outputs generated by artificial intelligence also involves the potential licensing royalties for the sourcing of training data.   It is worth noting that the use of data for artificial intelligence may affect the basic human rights due to discrimination or bias resultant from training data or algorithms. Therefore, it is necessary to enhance transparency and the protection of human rights conferred by the constitution with corresponding legal systems and ethical frameworks such as due process and fairness principle[65]. The other critical issue is the training database required for artificial intelligence applications. The government should provide more open data as a policy to support technology development in the corporate world or at research organizations. It is also necessary to make government information the structured metadata in order to enhance the efficiency and quality of research outputs. This is to facilitate added value by private sectors with data as an infrastructure provided by the government. Put differently, the government opens up structured data to empower the research and development of artificial intelligence; whilst the private sectors offer professional technology and development capabilities.   In terms of promoting data openness and applications, the government assumes greater accountability in the balancing between data use and data protection, the two equally important public interests. As an island of technology, Taiwan should look beyond the horizon of skies and oceans in the era where information and data flows without borders. The Taiwan government should establish the capability in data openness, protection and control by joining international forums. For instance, the government can apply with the APEC to join the Cross-Border Privacy Rules System in order to encourage regional collaborations in data control and construct datasets with the resources of the country. It is important to focus on the process of data collection, processing, analysis and utilization and ensure policies are implemented with the protection of civil and human rights such as the Right to Know, the Right to Withdraw and Citizen Data Empowerment. [1] David G. Lowe, Object Recognition from Local Scale-Invariant Features, Proceedings of the Seventh IEEE International Conference on Computer Vision, https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=790410 (last visited Dec. 27, 2018) excerpt from “These features share similar properties with neurons in inferior temporal cortex that are used for object recognition in primate vision”. [2] AI Lesson 101: Illustration of 27 Neural Network Models, Tech Orange, January 24, 2018, https://buzzorange.com/techorange/2018/01/24/neural-networks-compare/ (last visited on December 27, 2018) [3] Chen Yi-Ting (Bachelor’s Degree from Department of Physics, National Taiwan University, currently a PhD candidate in Department of Applied Physics, University of Stanford), Artificial Intelligence Starts with Neurons, May 3, 2018, https://case.ntu.edu.tw/blog/?p=30715 (last visited on December 27, 2018) [4] Hung-yi Lee’s personal profile at http://speech.ee.ntu.edu.tw/~tlkagk/. Currently teaching in Department of Electric Engineering, National Taiwan University; previously a guest scientist in MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL); specialization in machine learning and deep learning [5] Chen Yan-Cheng, Who Is Likely to Lose Jobs in the Era of Artificial Intelligence? Experts Explains the Professional Skills in Demand for Deep Learning, December 26, 2018. https://www.managertoday.com.tw/articles/view/56859 (last visited on December 27, 2018) [6] Details available on JukeDeck’s official website at https://www.jukedeck.com/(last visited on January 11, 2019) [7] In addition to the leverage of two key features of artificial intelligence, JukeDeck is also very friendly to creative teams in need of musical materials in terms of royalties, fee structures, UI/UX design. The company offers free downloads to non-commercial users. An individual or a small group (of fewer than 10 people) can enjoy five free downloads each month and pay $6.99 per song for the sixth download and above. Large groups (of ten people or more) should pay $21.99 for each download. [8] DIGILOG Authors, “A Nightmare for Musicians? AI Online Music Composer System – JukeDeck, DIGILOG, June 2, 2016, https://digilog.tw/posts/668 (last visited on January 2, 2019) [9] Laird Studio, Let the Online Music Composer Jukedeck Produce Unique Background Music for Your Films or Games! March 8, 2016, https://www.laird.tw/2016/03/jukedeck-jukedeck-bgm.html (last visited on January 10, 2019) [10] As above. [11] Amper Music’s official website at https://www.ampermusic.com/(last visited on January 10, 2019) [12] GlobeNewswire, Amper Music Raises $4M to Fuel Growth of Artificial Intelligence Music Composition Technology, March 22, 2018, https://globenewswire.com/news-release/2018/03/22/1444796/0/zh-hant/Amper-Music%E7%B1%8C%E8%B3%87400%E8%90%AC%E7%BE%8E%E5%85%83%E4%BB%A5%E6%8E%A8%E5%8B%95%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E7%B7%A8%E6%9B%B2%E6%8A%80%E8%A1%93%E7%9A%84%E7%99%BC%E5%B1%95.html (last visited on January 10, 2019). This round was led by Horizons Ventures, with Two Sigma Ventures, Advancit Capital, Foundry Group and Kiwi Venture Partners. This brings the company's total investment to $9 million. [13] GlobeNewswire, same as above [14] Smart Piece of Wood, Free Online Composer Enabled by AI, Amper Music, March 1, 2017, Modern Musician,https://modernmusician.com/forums/index.php?threads/%E5%85%8D%E8%B2%BB%E7%B7%9A%E4%B8%8A%E5%B9%AB%E4%BD%A0%E4%BD%9C-%E7%B7%A8%E6%9B%B2%E7%9A%84%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%EF%BC%9Aamper-music.225650/ (last visited on January 10, 2019) [15] GlobeNewswire, same as Note 12 [16] Fang Yung-Chuan, Neohumanism, National Academy for Educational Research, http://terms.naer.edu.tw/detail/1312151/(last visited on January 10, 2019). Neohumanism emerged in Europe in the 18th and 19th century, against rationalism and utilitarianism advocated by the enlightenment movement. Neohumanism argues that the value of things is not hinged on practicality. Rather, it stems from the things themselves. Humanity is precious not because of rationality, but resultant from emotional satisfaction in life. Cultures are originated by the spontaneous activities of humanity, on the basis of emotions and imaginations. [17] Synopsis by books.com.tw, who sells online Xiaoice’s “Sunshine Misses Windows”, the first collection of poems generated by artificial intelligence in history, August 1, 2017, China Times Publishing Co. https://www.books.com.tw/products/0010759209 (last visited on January 13, 2019) [18] Wong Shu-Ting, AI Talents in Taiwan Find Stage in China: NTU Students Participate in R&D That Empowers Microsoft’s Xiaoice to Write Poetry by Looking at Pictures, BusinessNext, June 6, 2017, https://www.bnext.com.tw/article/44784/ai-xiaoice-microsoft(last visited on January 10, 2019 [19] Synopsis by books.com.tw, same as Note 17 [20] The organizer did not provide handouts from the speakers. The summary was based on the author’s note. [21]Lin Ke-Hung, “More Than Playing Chess. AI Writes Novels Too. AI Novel Passes Preliminary Screening for a Novel Award! Reading at Frontline, https://news.readmoo.com/2016/03/25/ai-fictions/(last visited on January 10, 2019) [22] Ou Tzu-Jin, “2,3,5,7,11..?AI-written Novel in Japan Nominated for a Literary Award, April 7, 2016, The News Lens , https://www.thenewslens.com/article/38783(last visited on January 10, 2019) [23] TechBang, AI Team in Japan Develops Robots That Write Short Stories and Participates in Literary Competitions, TechNews, March 28, 2016, http://technews.tw/2016/03/28/ai-robot-novel-creation/(last visited on January 10, 2019) [24] Ou Tzu-Jin, same as Note 20 [25] TechBang, same as Note 21 [26] Lin Ke-Hung, same as Note 19 [27] The title of the forum was “What is News Now?”. It attracted over 300 journalists and media experts from the U.S. and Asia Pacific to discuss media phenomena today. Detailed agenda available at East West Centre’s official website at https://www.eastwestcenter.org/events/2018-international-media-conference-in-singapore(last visited on January 10, 2019) [28] Jason Liu, “Robot Writer, Transformation of South China Morning Post, State Monitoring, International Media Conference Day 1, China, Medium, June 25, 2018, https://medium.com/@chihhsin.liu/%E5%AF%AB%E7%A8%BF%E6%A9%9F%E5%99%A8%E4%BA%BA-%E5%8D%97%E8%8F%AF%E6%97%A9%E5%A0%B1%E8%BD%89%E5%9E%8B-%E5%9C%8B%E5%AE%B6%E7%9B%A3%E6%8E%A7-%E5%9C%8B%E9%9A%9B%E5%AA%92%E9%AB%94%E6%9C%83%E8%AD%B0day1-%E4%B8%AD%E5%9C%8B-c9c20bd00d75(last visited on January 10, 2019) [29] Jason Liu, same as above [30] Jason Liu, same as above [31] First Time Ever in the World!AI-Created Portrait, Sold at Christie's Auction for NT$13.34 Million, Liberty Times, October 26, 2018, http://news.ltn.com.tw/news/world/breakingnews/2592633(last visited on January 10, 2019) [32] The selling price is 40x higher than the expected price. The buyer’s identity is unknown. Chang Cheng-Yu, “First Time Ever! AI-Created Portrait Auctioned at Christie’s for NT$13.34 Million, October 26, 2018, LimitlessIQ,https://www.limitlessiq.com/news/post/view/id/7241/ (last visited on January 10, 2019) [33] Lin Pei-Yin, Does the NT$10m Worth AI Portrait Have Intellectual Property?” Apple Daily, Real-Time Forum, November 29, 2018, https://tw.appledaily.com/new/realtime/20181129/1475302/(last visited on January 10, 2019) [34] Jamie Beckett, What Are Generative and Discriminant Networks? Hear What Top Researchers Say, Nvidia, May 17, 2017, https://blogs.nvidia.com.tw/2017/05/generative-adversarial-network/(last visited on January 10, 2019) [35] Jamie Beckett, same as above. Ian Goodfellow is currently a Google research scientist. He was a PhD candidate in the Université de Montréal when he came up with the idea of generative adversarial networks (GAN). [36] Jamie Beckett, same as above [37] Jamie Beckett, same as above [38] Chang Cheng-Yu, same as Note 32 [39] Jamie Beckett, same as Note 34 [40] Video for the speech: GTC 2017: Big Bang of Modern AI (NVIDIA keynote part 4), link at https://www.youtube.com/watch?v=xQVWEmCvzoQ (last visited on January 10, 2019) [41] Wu Chia-Zhen, AI-Generated Nude Portrait Beats Real People’s Works by Claiming the UK Art Award and Prize of NT$120,000, LimitlessIQ, October 15, 2018 https://www.limitlessiq.com/news/post/view/id/7070/(last visited on January 10, 2019) [42] Jamie Beckett, same as Note 34 [43] Chang Cheng-Yu, same as Note 32 [44] Chang Cheng-Yu, same as Note 32 [45] The explanatory ruling by the Copyright Division, Intellectual Property Office, Ministry of Economic Affairs, Email 1070420, issued on April 20, 2018, https://www.tipo.gov.tw/ct.asp?ctNode=7448&mp=1&xItem=666643(last visited on January 2, 2019). The discussion was in response to the training outcome of voice recognition patterns based on analytics of the 1999 Citizen Hotline voice data. [46] According to Article 10 of the Copyright Law, authors enjoy copyright at the time of the work completion. Article 33 stipulates that copyright for legal-person authors lasts 50 years after the first publication of the work concerned. [47] Yeh Yun-Ching, Birth of New Type of Legal Right/Liability Entity ─ Possibility of Robots Owning Copyrights According to 2017 Proposal from European Parliament, IP Observer - Patent & Trademark News from NAIP Issue No. 190, July 26, 2017 http://www.naipo.com/Portals/1/web_tw/Knowledge_Center/Laws/IPNC_170726_0201.htm (last visited on January 2, 2019) [48] C-5/08 Infopaq International A/S v. Danske Dagbaldes Forening. [49] Andres Guadamuz, Artificial Intelligence and Copyright, WIPO MAGAZING, October 2017, https://www.wipo.int/wipo_magazine/en/2017/05/article_0003.html (last visited on January 19, 2019). [50] The article indicates that “A work should be protected in “the sense that is the authors’ own intellectual creation. No other criteria shall be applied to determine its eligibility for protection”. [51] Excerpt from the original legal article: in case of a literary, dramatic, musical or artistic work which is computer-generated, the author shall be taken to be the person by whom the arrangements necessary for the creation of the work are undertaken. [52] Excerpt from the original legal article: generated by computer in circumstances such that there is no human author of the work. [53] Andres Guadamuz, supra note 49. [54] Id. [55] Feist Publications v. Rural Telephone Service Company, Inc., 499 U.S. 340 (1991). “the fruits of intellectual labor that are founded in the creative powers of the mind.” [56] Naruto v. Slater, 2016 U.S. Dist. (N.D. Cal. Jan. 28, 2016). [57] The 2014 version of Article 313.2 provides a list of the examples not eligible for the U.S. Copyright Act protection. These include the works generated by the nature, animals or plants and the works purely generated by machines or machinery at random, without any creative inputs or intervention from humans. The examples given are photos taken by a monkey and murals painted by an elephant. The 2014 version establishes that works not created by humans are not eligible for copyright protection. The 2017 version takes a step further with more specific and straightforward wording. [58] Copyright Act 503.03(a): Works-not originated by a human author. In order to be entitled to copyright registration, a work must be the product of human authorship. Works produced by mechanical processes or random selection without any contribution by a human author are not registrable. Thus, a linoleum floor covering featuring a multicolored pebble design which was produced by a mechanical process in unrepeatable, random patterns, is not registrable. Similarly, a work owing its form to the forces of nature and lacking human authorship is not registrable; thus, for example, a piece of driftwood even if polished and mounted is not registrable. [59] Andres Guadamuz, supra note 49. [60] Lin Li-Chih, An Initial Examination of Copyright Disputes Concerning Artificial Intelligence —— Centered on the Author’s Identity, Intellectual Property Rights Journal, Volume 237, September 2019, pages 65-66 [61] The legislative rationale for Article 12 of the R.O.C. Copyright Act: The sponsor and the sponsored are typically in a more equal position for the works completed with sponsorship. It is different from the situation where the works are completed by an employee by using the hardware and software offered by the employer and receiving salaries from the employer. Therefore, the ownership of copyrights depends on the contract between the sponsor and the sponsored regarding the investment and sponsorship purposes. Unless otherwise specified by the contract, the sponsor typically provides funding because of his/her intention to use the works completed by the sponsored. Therefore, the intellectual property should belong to the sponsored. [62] Lin Li-Chih, same as Note 60, pages 75-76. Further reference of the principle used in the U.S. system: Annemarie Bridy (2016), The Evolution of Authorship: Work Made by Code, Columbia Journal of Law, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2836568. Also the same author (2012), Coding Creativity: Copyright and the Artificially Intelligent Author, Stanford Technology Law Review, https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1888622. [63] Lin Li-Chih, same as Note 60, page 76 [64] Frank H Easterbrook, Cyberspace and the Law of the Horse, 1996 U. CHI. LEGAL F. 207. [65] Please refer to State v. Loomis, 317 Wis. 2d 235 (2016).

The Taiwan Intellectual Property Awareness and Management Survey

The “National Intellectual Property Strategy Program” was announced by the Taiwan government in November 2011 in an effort to promote and raise the intellectual property capability of Taiwanese firms. As policy adviser to the Ministry of Economic Affairs in drafting the “National Intellectual Property Strategy Program,” the Science and Technology Institute under the Institute for Information Industry (STLI) conducted a survey in 2012 in order to gain a broad overview of the level of IP awareness and IP management and use among Taiwanese firms. The survey was distributed to 1,384 firms that are listed either on the Taiwan Stock Exchange or the Gre Tai Securities Markets. 281 companies responded to the survey, achieving a survey response rate of almost 20%. The content of the survey was divided into three parts: IP knowledge and understanding, current IP management within the companies and IP issues that companies face. The Importance of IP to Businesses Intellectual property has become a commonplace asset owned by firms. The growing significance of intellectual property to companies in general is undeniable, and firms are recognizing this as well. An overwhelming 93% of the respondents claim to own some form of intellectual property. The most common type of intellectual property owned by companies is trademarks, followed by patents and trade secret. Many companies are also actively seeking to obtain more intellectual property. Over 68% of the respondents indicated that they have submitted applications for formal intellectual property rights in the past two years. 84% of the respondents agreed with the statement that they believe intellectual property can bring added value for the firm. In addition, over 78% of the respondents also believe that intellectual property helps enhancing the company’s market position. It is clear that the majority of Taiwan firms already consider intellectual property to be a vital asset for their business and that building up and expanding their IP portfolio has become a top priority. This is also reflected in the annual spending that firms allocate for intellectual property. The survey respondents were asked whether a specific budget is allocated toward spending related to intellectual property every year, and the majority of the respondents, almost 70%, responded in the positive. Particularly, the respondents pointed out that they commit the most resources to obtaining and maintaining intellectual property rights every year. 10% of the respondents even indicated that they spent over NT$5 million annually on obtaining and maintaining intellectual property rights. The respondents were also asked about spending on inventor incentive, IP personnel, IP disputes and litigations and staff IP training. The results showed that companies commit the least spending on providing IP training for staff, with more than half of the respondents noting that they spend less than NT$500,000 on IP training each year and only 14% of the respondents noted that they will increase spending on IP training the following year. Weakness in Generating Value from IP As noted above, Taiwan firms are actively seeking to obtain more intellectual property and building up their IP assets. With almost 70% of the respondents noting that they have applied for intellectual property rights in the last two years shows that companies are generating quite a lot intellectual property, but whether all the intellectual property generated is being exploited and creating commercial and economic benefits remains doubtful. Most of the firms, almost 86% of the respondents, acquired their intellectual property through their own research and development (R&D). In contrast, the proportion of firms using other means of acquiring intellectual property is quite low, with only 17% of the respondents acquiring intellectual property through acquisition and 28% through licensing, while 41% percent of the respondents acquired their intellectual property by joint research or contracted research with others. With R&D being the major source of intellectual property for firms, firms are clearly putting in a lot of investment into acquiring intellectual property. However, the returns on these investments may not be proportionate. When asked whether the firm license out their intellectual property, only 13.5% of the respondents claimed to be doing so. This suggests that most Taiwanese firms are not using their intellectual property to generate revenue and commercial value. Instead, intellectual property is still mostly regarded and used as merely a defensive tool against infringement. Companies in Taiwan are also facing increasing risks of being involved in IP-related disputes and litigations. More than 30% of the respondents have already been involved in some kind of IP-related disputes and litigations in the past. The most common type of litigations faced by Taiwanese companies are patent infringement, followed by trademarks infringement, piracy and counterfeit, and disputes with (former) employees. Furthermore, more than 50% of the firms that have been involved in IP litigations noted that patent infringement and trademarks infringement pose the most detriment to the company’s business operations in general. It is evident that intellectual property has become a competitive weapon in businesses, and IP disputes and litigations are inevitable threats that most firms must face in today’s business world. Hence, it is essential for firms to have the necessary strategies and protection in place in order to minimize the risks created by potential legal disputes. With this in mind, it is worrisome to observe that most firms have not incorporated intellectual property into the company risk management program. Nearly 86.1% of the respondents claim to have some kind of risk management program in place within the company, but when asked what is included in the risk management program. Only 40.7% of the firms with risk management programs said that intellectual property is included, which is considerably lower than other types of risks generally seen in risk management programs. With IP disputes and litigations becoming an increasing threat that may bring negative impact for businesses, Taiwanese firms need to incorporate and strengthen IP risk management within the company. IP still not widely considered as business strategy With intellectual property being an important asset, firms should also have the necessary infrastructure and resources to manage IP accordingly and integrate IP into the company’s overall business operations. However, more than 50% of the respondents do not have designated personnel or department that is specifically responsible for managing the company’s intellectual property. Nearly 33% of the respondents indicated that the responsibility for managing IP is shared by other departments within the firm. When further asked about the tasks of the designated personnel or department that is responsible for IP, it is observed that the designated personnel/department mostly undertake routine tasks such as filing for patent applications and trademark registrations and maintaining relevant databases. Tasks such as patent mapping and competitive landscape analysis are the least performed tasks. The proportion of designated personnel/department for IP that are involved in the company’s business and research strategic decision making process is also quite low. This suggests that despite the importance of IP to firms, many Taiwanese firms still have not integrated IP into their overall research and business strategies and utilize their intellectual property as a strategic tool in their business operations. Low Levels of IP Awareness and Training within Firms In order to gauge the level of IP knowledge and understanding in Taiwanese firms, the survey also contained 10 very basic questions on intellectual property. Surprisingly, the respondents that answered all the questions correctly were less than 4%. The proportion of respondents that correctly answered 5 or less questions did not even reach 50%. This means that Taiwanese firms still lack fundamental IP knowledge and understanding in general. This is also reflected in the response to the question whether the company has an overall IP policy in place, which also serves as an indication of the level awareness and concern with intellectual property within the firm. An IP policy that is distributed to company staff means that IP awareness is promoted within the company. However, almost 40% of the respondents claimed that there is no overall IP policy within the company, and nearly 30% of the respondents noted that even if there is an IP policy, it is not made widely known to company staff. This reveals that many Taiwanese companies still need to undertake more IP awareness promotion within the firm. More IP awareness promotion is also justified by the results to the question as to whether the company provides IP training for company staff. The results showed that almost 44% of the respondents do not provide any form of training in IP to company staff at all. This also corresponds to the result noted earlier that most respondents commit the least funding to providing IP training each year. Providing regular IP training to staff is certainly still not the norm for most Taiwanese firms. Issues facing businesses and their policy needs Taiwanese firms still faces many difficulties and challenges in their intellectual property management and hope that the government could provide them with the assistance and resources needed to help them enhance their intellectual property capacity and capability. Some of the major difficulties that the respondents pointed out in the survey include the lack of IP experts and professionals. It is difficult for firms to find and hire people with adequate professional IP skills, as the education and training currently provided by universities and professional schools do not seem to meet the actual IP needs of companies. Another major difficulty faced by Taiwanese firms is the lack of information and knowledge regarding international technical standards and standard setting organizations. A significant portion of the respondents expressed the wish for the government to help them gain entry and participation in international standard setting organizations. Among the other difficulties, the regulatory complexity and lack of clarity with the ownership of intellectual property arising from government-contracted research, which poses as barrier for firms in obtaining licenses for use and exploitation, is also an issue that the majority of the respondents hope the government could improve. In addition to the difficulties mentioned above that Taiwanese firms hope the government would help them encounter, the respondents were also asked specifically what other resources and assistance they would like to seek from the government. 69.4% of the respondents hope that the government could provide more training courses and seminars on IP. Many respondents are also seeking a common platform that can unify all resources that could help enhance IP management. Expert assistance and consultation on obtaining intellectual property rights and providing information on international IP protection and litigation are also resources that Taiwanese firms desire. More than 50% of the respondents also indicated that they would like to receive assistance in establishing IP management system within their firms. Conclusion The results of the survey provided insight into the level of IP management among companies in Taiwan. Although the importance of intellectual property for businesses is undeniable and widely recognized by firms, the results of the survey revealed that there is still much room for improvement and for Taiwanese firms to put in more efforts into strengthening and enhancing their IP capabilities. In general, Taiwanese firms have not incorporated their intellectual property into their management strategies and derived adequate value. Intellectual property remains mostly a defensive tool against infringement. Furthermore, there is still need for greater promotion of IP awareness among firms and within firms. With these IP management difficulties and deficiencies in mind, it should be noted that the respondents of this survey are all listed companies that are already of a certain size and scale and should have greater resources in their disposal to commit to their IP management. It would be reasonable to assume that small and medium firms, with significantly less resources, would face even more difficulties and challenges. Using this survey results as reference, the “National Intellectual Property Strategy Survey” would seek to help Taiwanese companies address these IP issues and provide adequate assistance and resources in overcoming the challenges Taiwanese companies face with their IP management. It is also hoped that this survey would be carried out regularly in the future, and that the survey results from 2012 would serve as a baseline for future surveys that will assist in observing the progress Taiwanese businesses are making in IP management and provide a whole picture of the level of IP awareness and management within Taiwanese firms.

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