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

  1. 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].

  2. 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]:

  1. 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.
  2. 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.
  3. Generation of poems: deep learning trained in the language model with keywords to create poems
  4. 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]:

  1. 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.

  2. 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.

  3. 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]:

  1. Analysis of portraits from training data: A total of 15,000 portraits from the 14th century to the 20th century as the training data
  2. 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:

  1. 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.
  2. 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.
  3. 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:

  1. 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.

  2. 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.

  3. 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.

  1. 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.
  2. 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:

  1. 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.

  2. 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).

Links
※Copyright Ownership for Outputs by Artificial Intelligence,STLI, https://stli.iii.org.tw/en/article-detail.aspx?no=105&tp=2&i=171&d=8194 (Date:2019/12/13)
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Brief Overview of the Recent Progress of the TIPS Project and Important Developments of Taiwan’s IP Protection Environment

Chien-Shan Chiu I. Introduction Taiwan, a country with limited natural resources, has been seen to create rapid economic development for the past few decades. This achievement has been praised as an “economic miracle” and making Taiwan one of Asia’s “Four Tigers1”. The success is a result of the tremendous hard work and efforts exerted by the local people and enterprises and the forward-looking national policies initiated by the government. Recognizing fast technology breakthroughs and globalization trend are going to have major impacts on the traditional ways of managing business and may as a result change the current competitive landscape, the government of Taiwan has promoted vigorously of transforming Taiwan into a “green silicon island” with high value-added production2. The goal is to make Taiwan an innovation headquarters for local enterprises and a regional research and development center for international corporations. It is hoped that eventually, Taiwan will not only be known as a country manufacturing high-quality “ Made in Taiwan” products as it is now, but also an innovative country producing products that are “Designed in Taiwan”. In order to encourage more innovation and to create more high value-added products, several national strategies were initiated by the government. One of the most important policies in today’s knowledge-based economy is certainly to provide a sound and effective intellectual property protection environment so that the results created from human intelligence can be well protected and utilized. This essay provides an overview of the recent progress of the TIPS (stands for Taiwan Intellectual Property System) project, which is currently promoted by the Science and Technology Law Center. The TIPS project is an innovative program solely developed by the Taiwanese scholars in year 2003 and has since achieved quite significant success. The second part of this essay gives a brief introduction of the recent changes made to the intellectual property system in Taiwan. II. Overview of the Recent Progress of the TIPS Project 1. The “Developmental Stage” The TIPS project has been promoted at the initiative of the Intellectual Property Office of the Ministry of Economic Affairs in 2003. The main goal of this project is to develop a set of guidelines for managing intellectual property to be implemented by the Taiwanese enterprises. At “developmental stage”, academic journal articles and relevant legislative requirements were gathered; intellectual property management experts were consulted and companies with good and effective intellectual property management practices were interviewed. All of the information and advises were collected and analyzed and formulated into a set of guidelines which basically covers the whole cycle of intellectual property management right starts from its creation, protection, maintenance and exploitation. The types of intellectual property rights managed include patent, trade mark, copyright and trade secret. A hearing for the draft guidelines was held in 2004. A pilot study was done by selecting eight representative domestic companies in 2005. All the public opinions, comments and advises from the trial companies were collected and used to revise the draft guidelines. The revised guidelines were then formally promulgated on March 23, 2007. The project then entered into a full “promotional stage” where the Science and Technology Law Centered entrusted by The Industrial Development Bureau of the Ministry of Economic Affairs was responsible for promoting the project. As the fundamental objective of TIPS is to assist companies to establish an effective internal intellectual property management system at relatively low cost, the whole system was developed based upon the ISO 9001:2000 Quality Management Standard. Since the ISO standards are widely recognized and adopted by many Taiwanese enterprises, for an enterprise with ISO system implemented, TIPS can be easily integrated into the existing ISO standards, conflicts between these two systems will be minimized and it will only require minimum organization structural changes and implementation costs. Further, by incorporating the PDCA (Plan-Do-Check-Action) model and “process-oriented approach” of ISO 9001:2000, the IP management processes implemented within an enterprise possess the feature of being able to be continuously improved. 2. The “Promotional Stage” In order to facilitate the promotion and draw more public attention to TIPS, various supplementary measures were introduced: (1) Free on-line self-assessment tool A collection of 50 questions is provided on the TIPS website3. Once a company has registered as a member of TIPS (simply by filling up some details about the company), it can use these questions to self-assess the effectiveness and adequacy of its existing (if any) IP management infrastructure. After the company has completed all the questions, the on-line tool would automatically generate few suggestions relating to the management of intellectual property based on the answers provided by the company. The company can also find out how they stand among all the enterprises which have taken the assessment previously. The on-line self-assessment tool is the initial step for those companies wanting to know more about TIPS. Once they realize that they are far behind the requirements of an effective IP management system, they can then move on to the next stage to implement TIPS. (2) On-Site Diagnostic and Consulting Service Once a company has completed the on-line self-assessment questions, it is then eligible to apply for a more detailed assessment of its internal IP management infrastructure conducted by a qualified IP service consultant. The IP service consultant will interview the managers responsible for managing IP related matters within a company and check relevant internal policies and documents. Concrete advises in relation to the implementation of TIPS will be given based on the inadequacies and problems uncovered during the on-site visit. The cost for the diagnostic and consulting service is fully covered by the government. (3) Model Companies Every year since 2004, some model companies are chosen as “demonstrative” companies for the implementation of TIPS. For instance, a total of 14 enterprises were selected as model companies this year. Among these companies, 3 “clusters of enterprises”, each of which contains 3 companies were chosen. The so-called “cluster of enterprises” is a group of companies that can be constituted by companies providing similar products or services within the same industry, or companies having the relationships as suppliers and consumers or companies within the same corporate structure. The introducing of implementing TIPS through “cluster of enterprises” is a promotion strategy that aims to disseminate the TIPS project more effectively and efficiently. For these selected model companies, certain percentage of the cost for implementing TIPS is subsidized by the government. (4) Certification After an enterprise has fully implemented TIPS, they can then apply for certification. All the prescribed documents must firstly be sent to the TIPS working team which is responsible for all the administrative works of TIPS. After a formality check, 2 or 3 (depending on the size of the enterprise) IP experts will be chosen to conduct an on-site inspection to determine whether the newly implemented IP management system meets the minimum requirements of TIPS. If the experts are satisfied with the inspection result, a certificate for the compliance of TIPS will be issued by the Industrial Development Bureau (IDB) of the Ministry of Economic Affairs. The certificate serves as government’s assurance to the public that the certified enterprise has at least the minimum ability (evaluated in accordance with government’s standard) to manage and protect its intellectual property. (5) IP Management Courses Three types of courses are provided to train IP management personnel. The basic course is an introductory course, which covers the basic principles of TIPS. The intermediate course called The Practical Implementation Course covers more detailed explanations of TIPS and how it can be implemented into the enterprise. Any person who has completed this course and passed the test will receive a certificate. The advance course called Self-Assessment Course teaches students how to evaluate and determine whether their newly developed IP management system conforms to the TIPS requirements. Again, a person who has completed this course and passed the test will receive a certificate. In order for an enterprise to be eligible to apply for a certificate for the compliance of TIPS, the enterprise must firstly furnish a self-assessment report to be completed by a “qualified person”. Such “qualified person” is the person who has successfully obtained the certificate for the completion of Self-Assessment Course. 3. Achievement The TIPS project has received wide recognition since it first launched in year 2004. To the end of 2008, 297 enterprises have completed the on-line self-assessment questions; 73 companies have received on-site diagnostic and consultation services; 618 persons have taken the IP management courses; 45 enterprises have successfully obtained the certificates for the compliance of TIPS and more than142 enterprises have either completed or in the middle of implementing TIPS. Benefits of implementing TIPS as reported by TIPS implemented enterprises are summarized as follows: (1) Company A: Implementing TIPS provides an assurance that Company A has adequate ability to protect the technology secrecy belongs to its international client. Company A thus obtained a new purchasing order worth more than NT$ 100 million. (2) Company B: TIPS assists in enhancing the level of trust on the company’s ability to protect its international client’s confidential information. A new purchasing order worth NT $ 30 million is placed by such client. (3) Company C: Through systematic IP management and IP inventory audit, Company C starts to formulate a plan for licensing out its non-core IP assets. (4) Company D: The alignment of R&D and business strategies required by TIPS ensures the accuracy of the R&D direction. The systematic way of managing the R&D projects also reduces the R&D phase to 45 days, saving R&D expenditure by 10%. (5) Company E: Implementing TIPS helps Company E to formulate a more clear and definite IP mapping strategy. Company E plans to implement TIPS into its whole corporate group in 2008. (6) Company D: Systematic IP management has reduced the number of litigation allegations. Company D plans to implement TIPS into every business unit within its corporate structure in 2008. 4. Proposed New Features of TIPS In answering to the responses receiving from the TIPS implemented enterprises, two new measures are going to be launched in 2009. First, enterprises with effective IP management system and strategies are encouraged to write up an Intellectual Property Management Report summarizing their business, R&D and IP management strategies as well as their accumulated IP assets. Second, an Experience-Sharing Platform is going to be established where enterprises can freely exchange their experiences of managing IP and how to formulate an effective IP management strategy. III. Recent Development of Taiwan’s IP Protection Environment Year 2008 can be said to be a significant year for the history of IP development in Taiwan where three completely new legislations have taken effect this year. The Intellectual Property Court Organization Act4 and the Intellectual Property Case Adjudication Act5 were both promulgated on March 28 2007 and effective as of July 1 under which a new IP Court was established with new laws to govern the adjudication of IP cases. The Patent Attorney Act which governs the qualification and registration of a new patent attorney profession was promulgate on July 11 2007 and effective as of January 11 2008. It is believed that through the commencement of these three new legislations, the accuracy, consistency as well as efficiency of resolving IP-related disputes in Taiwan are going to be significantly improved. A short introduction for each of the three new legislations is provided below: 1. New IP Court A new IP Court was established pursuant to the Intellectual Property Court Organization Act and began to hear cases on July 1 2008. This Court is given jurisdiction to hear first and second instances of a civil action, first instance of an administrative action and the second instance of a criminal action for matters concerning IP rights. For examples, interests arising under the Patent Act, the Trade Mark Act, the Copyright Act, the Trade Secret Act, the Optical Disk Act, the Species of Plants and Seedling Act, the Fair Trade Act and the Regulation Governing the Protection of Integrated Circuits Configurations. Unlike previously, where the validity issues must be determined by the administrative court, the newly established IP Court can hear and decide the validity of an intellectual property right at issue. This will significantly improve the efficiency of resolving an IP dispute. Eight experienced judges were chosen to sit on the bench of the IP Court. Since most IP related matters involve complex technical issues, nine technical examination officers with various technical backgrounds from the Taiwan Intellectual Property Office were chosen to assist and provide their technical expertise and opinions to the IP Court judges. 2. New Laws Governing IP Litigation (1) Litigation procedures The Intellectual Property Case Adjudication Act prescribes rules for adjudicating IP-related disputes. The Act recommends to try an IP infringement case through a 3-step processes. First, to determine the validity of an IP right. Second, to determine whether an IP right has been infringed and finally, to calculate the damages. The IP Court may at any state dismiss the case if it finds the IP right at issue is invalid or not infringed. In order to avoid unnecessary efforts spent on determining whether an IP right is infringed if such right is in fact invalid, the Act requires the IP Court to determine whether a right is infringed only after the invalidity defense raised by the defendant is dismissed. (2) Preliminary injunction The Intellectual Property Case Adjudication Act also introduces the criteria used by the US courts to determine whether a preliminary injunction order should be granted. Before the enactment of this new Act, the requirements for granting preliminary injunction in Taiwan were quite loose as the court could grant a preliminary injunction order without firstly reviewing the merit of the case. The new adopted US criteria require the judges to determine the likelihood of success on the merits of the case; whether a substantial threat of irreparable damage or injury would be caused if injunction is not granted; the balance of harms weighs in favor of the party seeking the preliminary injunction and the impact of the decision on public interest. As the criteria become stricter, it is believed that less preliminary injunctions will be granted. A plaintiff seeking a preliminary injunction order in the future shall put in more efforts in preparing evidences and reasons arguing that an injunction maintaining the status quo is necessary. (3) Protective orders (as to confidential information) As most IP litigation cases involve matters concerning confidential information or trade secrets, which are often crucial for the survival of an enterprise, the Intellectual Property Case Adjudication Act introduces a protective order into practice to preserve the confidentiality of specific information given by parties to the suit or a third party. A party to the suit or a third party can apply to the court to issue a protective order restraining the accessibility to the protected confidential information and restraining those who have accessed to the confidential information from disclosing it to others. Any intentional violation of the protective order is subject to a criminal liability. It is expected that by introducing the protective order, confidential information or trade secret holder may become more willing to reveal such information, which may assist improving the accuracy of resolving the disputes between parties. (4) Improved evidence preservation procedure Unlike the US court system, Taiwan, a civil law country, does not have discovery or Markman hearing procedures. Before the enactment of the Intellectual Property Case Adjudication Act, even though a judge can ask the parties to preserve evidences for the use of the trial, the judge is however, given no authority of compulsory execution. A party can refuse to comply with the judge’s request without any legal consequence. The new Act now provides compulsory execution of an evidence preservation order. Parties who are subject to the evidence preservation order are obligated to comply with the order. Furthermore, the judge may also request assistance from technical examiners or police department to provide advises. 3. New Patent Attorney Profession The Patent Attorney Act sets the requirements for becoming a qualified patent attorney in Taiwan. According to the Act, patent attorneys should be specialized in both technology and patent regulations. A candidate must firstly pass the Patent Attorney Eligibility Examination, followed by a period of prevocational training, such candidate is then able to register with the Taiwan Intellectual Property Office and join the Patent Attorneys Association. It is hoped that by introducing the new patent attorney profession, the quality of patent applications will be improved and thus reduce the ever increasing workload of patent examiners. IV. Conclusion The initiative of the TIPS project, the establishment of the IP court and the newly implemented patent attorney system all demonstrate the government’s determination to create a more sound and efficient environment for the protection of intellectual property. The overwhelming success of the TIPS project evidenced by the number of enterprises implementing the system indicates that Taiwanese companies are self-motivated, able to see the importance of intellectual property as their main source of competiveness and are ready and willing to move into the next stage of “innovative” management. It is believed that through the government’s pragmatic and foresight policies coupled with the adventurous and hard work spirits possessed by the local enterprises, Taiwan will eventually reach its goal of becoming a “green silicon island”, creating another “economic miracle”. Along with Singapore, Hong Kong and South Korea. http://www.asianinfo.org/asianinfo/taiwan/pro-economy.htm (last visited: 12/31/2008) TIPS website: http://www.tips.org.tw/ http://www.taie.com.tw/English/970520a.pdf (last visited: 12/3132008) http://www.taie.com.tw/English/970520a.pdf (last visited: 12/3132008)

A Survey Study on the Intellectual Property Management amongst Taiwanese Companies

J. Kitty Huang Chien-Shan Chiu Background In order to provide insight into intellectual property (IP) awareness, the status quo as well as potential hardship and demands arise over IP management, STLC was commissioned by IDB (Industrial Development Bureau) to conduct a survey study in June 2010. In this article, we provide briefings on the contents, research methodology and major findings of this study. About the research The survey questionnaire was sent by means of emails or posts to a total of 1000 business establishments randomly generated from the registration data facilitated by the Ministry of Economic Affairs. This was also the first time that such a survey has been envisaged on such a comprehensive scale, covering businesses located around Taiwan with the aim being to produce an in-depth analysis into IP management in various industries including manufacturing, precision machineries, photonics, bio-medicals, info-techs, semiconductors etc. Sixty-five percent of the respondents have less than fifty employees and the overall response rate achieved was 13.1%.1 A continuing need to strengthen IP awareness is required The first section of the questionnaire dealing with IP awareness gauged respondent companies IP knowledge and understanding through a series of questions relating to IP law and practice. When asked whether formal registration was necessary to obtain a range of intellectual property rights (IPRs), over 70% of companies replied with correct answers, namely patents, designs and trademarks. However, through other questions at a more advanced level, the responses revealed a general lack of knowledge in IP law and hence a continuing need to strengthen IP awareness is required. For instance, overall 70% of companies know that obtaining patents will require formal registration, yet surprisingly even of these over 50% incorrectly thought the manners of patent utilization, such as making products, will not result in infringing others IPRs. This result arguably suggests that respondents are in the main unaware that a patent does not give the patent owner the right to exploit the patented invention himself, but rather, he has only the “exclusive right” to stop others from doing so. For another instance, whilst 32% of respondents inaccurately thought that a formal registration is required to obtain copyrights, nonetheless this does not equate to the result being a near 70% of companies have a full and correct knowledge in regard to copyright. When faced with a slightly more obscure question of who would own the copyright in commissioned work (such as website creation) in the absence of a contract, 26% of companies didn’t know and 30% answered incorrectly. On the same token, though only 10% of respondents erroneously believed that trade secrets would require a formal registration, when asked whether the company’s client list may be a trade secret, the number of correct replies (61%) drops sharply when compared to the previous one. Though intended as a question to discriminate at the upper levels of trade secret awareness, the replies are more likely to reflect a lack comprehension of the subject among Taiwanese companies. The important message arise from the overall scales in the first section of the survey is that the need for IP awareness promotion and enhancement amongst companies in Taiwan still exists. Lack of IP expertise is a major barrier In the second section of the questionnaire companies were asked a series of questions which were intended to measure the status quo through the extent of IP management practices. Perhaps one would agree that the issue of perceptions of the importance of IP to a company is greatly linked to how effective it manages them. When asked to indicate reasons as to why IP is important to their business, the replies were rather polarized. The two most popular reasons were “means to differentiate from competitors” (33%) and “to prevent infringement” (30%). The distinction between the two is clearly that the former reason is relatively active and strategic whilst the latter is perceived to be passive and defensive. On the other hand, “to retrieve the cost of R&D” (4%) and “to attract more investors” (5%) are least likely to be seen as the reasons why IP is important to them. The results may suggest that generally speaking, Taiwanese companies tended not to utilize their IP to generate revenues nor correlate them with the business strategies, but rather, see them more of a shield to avoid infringement. Companies were asked what IPRs they own and the most common ones are trademarks (21%) and utility patents (20%), with invention patents (14%) being the third on the rank. In contrast only 2% of respondent companies own copyrights. While such result may be attributed to the overall structure of the industry, it may also link to the observation that most companies not merely lack the comprehension of copyrights but may also not be aware of owning such IPR. Furthermore, it is also surprising to find that 45% of respondents do not own any IPRs. The absence of IPRs within these companies is perhaps a key indication of poor awareness and inactive management of IPRs amongst many Taiwanese companies. To measure the extent of IP management is not easy as the intensity of it differs both by sector and by size. Therefore, the task is achieved through 9 questions designed on the concept of PDCA (plan-do-check-act) process which would allow the respondents to review and find out any inadequacy in their IP management as they proceed. One would expect that those companies with effective IP management would take care to evaluate the various IPRs required at different time intervals. Whilst all of the answer choices are considered to be “important timings”, for example “when planning for new skills/products/business” and “when further investment in IP would enhance defense (such as infringement prevention); yet the results revealed that over 60% of the companies did not perform such evaluation at whatever timing. This may suggest that in general, companies in Taiwan are inadequately concerned with the evaluation process within their management of IP. Such a result may consequently make them ignoring means to prevent infringement (such as checking competitors’ IPRs and prior-art search) or pay attention to regulation updates. Effective IP management indisputably requires certain monetary inputs. Companies were asked whether they have regularly spent on obtaining and maintaining IPRs the firm owns, and remarkably only about 36% of respondents answered this question. In addition the companies were asked about how much they spent on “application fees”2,“incentives offered to inventors”, “spending on HR” and “other expense”. Only a paltry 6% of all respondent companies spent on all the abovementioned categories and mostly up to the amount of NT$100,000 (roughly USD$3300) per each. Linked with the spending on IPRs is perhaps whether companies have designated staff responsible for managing IPRs or have a separate IP department. Again, 70% of respondents replied negatively to this question and only 10% of some larger companies (with over 200 employees) have specific personnel or department designated to assume this responsibility. The results may indicate a general lack of expertise in managing IPRs as a barrier to leveraging full value of them as well as making proper legal decision in the event of IP related disputes Companies were asked how to protect their IPRs through a variety of methods of protection though the majority (over 72%) didn’t implement any of them. The most highly identified method being “protect core skills by patents”, however, only 35% of companies adopted such protection. Furthermore, roughly 76% of the companies did not conduct training in IP issues for employees, and over 75% did not attempt to assess the efficiency of their management of IP. The explanation to the above is conceivably a general lack of IP expertise due to inadequate monetary inputs as well as perceived high costs for IP specialists within the company. The results ultimately reflect an inefficient execution of IP management in the massive Taiwanese companies. Most companies have only limited resources The final aspect of IP management that has been surveyed is the hardships occurred and accordingly the resources sought to solve them. When asked what are the major difficulties in the process of managing IP, the most common answers were “high expenditure on filing and maintenance” (18%), “lack of professional advice” (15%) and “regulatory complexity” (15%). These results are arguably all related to the facts already discussed in the afore-mentioned paragraphs. In general, the survey revealed that most companies have only limited resources and therefore highly demand external aids such as government funding or projects to help soften the hardships and improve their management skills. Accordingly, “unifying resources for enhancing IP management through a mutual platform” (22%) and “facilitate industry peer networks” (21%) being the most popular resources sought. Furthermore, 14% of the respondents indicated their urge to receive “on-site expert assistance”, and a remarkable 90% of the respondents have never been aware of the TIPS (Taiwan Intellectual Property Management System) project, which is one initiated by the government to help companies set up a systematic IP management system. As a result, efforts to promote the TIPS project should be further devoted as the initial step to assist companies strengthen their IP awareness and management skills. Conclusion The results of the survey present the status quo of IP management amongst the companies in Taiwan which is proportionally consistent with their IP awareness as well as hardships and resources sought. The present study shows what one might expect, that is larger companies tend to be more IP aware and have greater resources to manage their IPRs, whilst the rest of others (especially SMEs) are in the main inadequately aware of IP, which is crucial to enhance active IP management within and throughout their firms. While various resources are highly demanded, perhaps the government should firstly take steps to promote that awareness within and throughout their organizations. Linked with this is the second important point which is that further promotion of the TIPS project should be aimed at not only enhancing IP awareness but also assisting companies to better manage their IPRs. 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. Finally, we would like to thank everyone who contributed to this survey research and hope that it provides valuable insight into the goals originally proposed. 1.The survey resulted in 157 replies from which 26 of them were nullified by false or incomplete answers. 2.Application fees” include fees occurred from exploring inventions up to application and maintenance, which also include attorney fees.

South Korea’s Strategy for Reinforcing Protection of Corporate Trade Secrets-Trade Secret Protection Center

Preface In order to increase the strength of addressing issues on the infringement of intellectual property for small and medium enterprises, Korean government launched Consultative Committee for Intellectual Property Policies, leading by Presidential Council on Intellectual property and conducting with Ministry of Culture, Sports and Tourism, Korean Intellectual Property Office and Ministry of Justice, to discuss how to reinforce efficiency on handling infringement of intellecual property and work on policy for intellectual property protection. Korean government has considered trade secret as the core of corporations; however, corporations think little of it. For this reason, Korea Institute of Patent Information’s Trade Secret Protection Section, in charge of the Trade Secret Protection Center, works to avoid the outflow of business skills and trade secrets, to improve trade secret protection system, to raise awareness of trade secret protection and develops South Korea as an intellectual property power. This article aims to briefly introduce the standard management system, the diagnosis of corporate trade secret and the Trade Secret Certification Service which are schemed out by the Trade Secret Protection Center. Explanation on Major Strategies Trade Secret Diagnosis & Standard Management System In an attempt to offer a diagnosis of current problems about trade secret management in corporations for drawing up suggestions for improvements, the Trade Secret Protection Center sets up a series of questions based on the five categories: organization policy management, document access management, staff management, physical management and information technology management. There are in total 32 questions with detailed sub-questions for knowing if corporations have set up regulations and if the regulations are followed; if the regulations are not followed, if they have strategy to tackle with violation. For example, the question for internet management is to examine on how corporation manages intranet and extranet. Some possible policies are to make them separated, to do authority control or to do nothing. Here is the procedure for diagnosis: 1.Preparation Employees are asked to gather information regarding trade secret management and improvement opinions by a questionnaire. 2.Diagnosis Get the result of how well corporation has done for trade secret management by analyzing the questionnaires. 3.Plan Come up with solutions according to diagnosis. 4.Action Provide suggestions with different levels of work. Level Description A (above 81 point, Excellent) Well-formed trade secret management and great operation B (71-80 point, Good) Limited strategy with law protection for trade secret outflow C (61-70 point, Average) Weak strategy with a lack of law protection for trade secret outflow, management needed D (41-60 point, Fair ) Poor law protection for trade secret outflow, management needed badly F (below 40 point, Poor) High Risk of trade secret outflow The Trade Secret Protection Center will examine and offer staff training periodically in an effort to improve following aspects: 1.Corporation Management (1)Avoid crucial information outflow (2)Systemize issue handling and information authentication process 2.Organization Culture (1)Convey the importance of information protection (2)Decrease the incoordination among departments due to protecting key information (3)Build trade secret protection culture 3.Staff (1)Provide long-term training for trade secret protection (2)Build up ability of trade secret protection The trade secret diagnosis is considered as a way to make trade secret the key intangible asset in corporations and even to increase the competitiveness and to create profits. In addition to the trade secret diagnosis, the Trade Secret Protection Center further provides immature business with the standard management system which contains services with trade secret registration, level distinguishments, authority control, staff management, contract management and certification service. The primary goal of the standard management system is to help with production and maintenance of trade secret certification before issue occurs. When issue happens, the system is right here to submit certification of trade secret and guarantee to the court that nobody can access trade secrets except the possessor of the trade secret and the institution. In other words, the system is intended for following goals: 1.Efficientize Trade Secret Management Save time, money and manpower. Manage trade secret and related information efficiently. 2.Raise Awareness of Trade Secret Protection Among Employees Strengthen awareness and application of trade secret protection by using this system as daily work process 3.Link to the Trade Secret Certification Service Prove the original document of trade secret with the time stamp of ownership for judicial evidences. 4.Link to Information Security Solution Cooperate with various information security solutions, such as trade secret control and outflow block. Trade Secret Certification Service The Trade Secret Certification Service which is built to link to standard management system is put into practice in 2010 by Korean Intellectual Property Office. This service operates by taking the hash values from trade secret e-documents and combining them with authorized time values from trusted third-parties, thereby creating time stamps. Time stamps are then registered with the Korea Institute of Patent Information to prove the existence of original document of trade secrets, as well as and their initial dates of possession. A legal basis is built for the Trade Secret Certification Service in 2014. Amendments of Unfair Competition Prevention and Trade Secret Protection Act indicate registration and proof of the Trade Secret Certification Service and explain that an institution with more than 3 qualified staff and required facilities is eligible to be a Trade Secret Certification Service institution. The Trade Secret Certification Service is characterized by the following properties: 1.Block Trade Secret Outflow Radically Instead of the trade secret itself, this service only asks for hash value of e-records and the authorized time of ownership which make it more secure for corporations to manage trade secrets rather than maintaining under a third-party. 2.Various Electronic Records Available Various types of electronic records are available in this service, such as documents, pictures and video files which could contain production process, laboratory notebook, blueprint, marketing records, financial records, selling information and customer information and contracts. 3.Institution with Credibility It is inevitable that any piece of information could be leaked out; hence trade secret management should be executed by credible institution. For example, corporation can ask the Trade Secret Certification Service Institution to register an original document for a blueprint and get a certification. Then, the corporation can ask for new registration for modified blueprint as well. When issue occurs, the certification would be the proof of original document and time of ownership. As the Trade Secret Certification Service Institution gets legalized, the evidence of original document of trade secrets and initial dates of possession would get more convincible in court. Conclusion The trade secret diagnosis plays an essential role in understanding the level of trade secret management in corporations. The standard management system further provides with improvement and solution for trade secret protection based on diagnosis. In addition, legalized Trade Secret Certification Service also levitates the burden of proof on corporation. South Korea’s experience in trade secret management could be a good example for Taiwan to follow.

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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