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).

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※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:2019/08/18)
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Discussion on the Formation of Taiwan’s Network of Intellectual Property Collaboration System in light of Japan’s Experience

Background Taiwan industries have been facing an increasing pressure from the competitive global market. To assist the Taiwan industries, the Government has approved the “National Intellectual Property Strategy Guideline” (the “Guideline”) on 17 October 2012. The Guideline stipulates six major strategies and twenty-seven relevant enforcement criteria in relation to intellectual property (“IP”). The six major strategies are as follows: (a) creation and utilization of high-value patents; (b) enforcing cultural integrity; (c) creation of high agricultural value; (d) support free flow of IP for academics; (e) support system of IP trade flows and protection; and (f) develop highly qualified personnel in IP. Under the “innovation of high-value patents” strategy, the relevant enforcement criterion, being “establishing academia-industry collaborative system for IP management”, is to support the Taiwan’s current and future technology development program on R&D planning, IP management and technology commercialization. In other words, this enforcement criterion can greatly improve the ambiguity and inadequacy of Taiwan’s research infrastructure which have caused inefficient research operation. Furthermore, this enforcement criterion can also improve network collaboration between organizations on IP management, allowing more efficient process for managing IP and thus achieving the purpose of “creation and utilization of high-value patent”. In light of the above, this article studies Japan’s practice on integrating the IP network resources and improving their IP management under the University Network IP Advisors Program (“IP Advisors Program”). University Network IP Advisors Framework Outline A. Policy background, goals and methodology National Center for Industrial Property Information and Training (“INPIT”) initiated the IP Advisors Program and commissioned Japan Institute for Promoting Invention and Innovation (“JIII”) to implement and carry out the new policy in year 2011. Prior to the implementation of the new policy by JIII, INPIT has assisted with establishing proper IP management systems for more than 60 Japanese universities by dispatching IP experts and advisors (“IP Advisors”) to each of the universities during 2002 to March 2011. After the implementation of the initial policy, review has suggested that by expanding the network collaboration, such as establishing intervarsity IP information sharing system within their university networks, the universities can fully aware of and identify technologies that were created by them and are beneficial to the industrial sector. In addition, expanding the network collaboration can also help the universities to quickly develop mechanisms that will enable them properly protect and utilize their acquired IP rights. Accordingly, after 2011, the initial policy has expanded its scope and became the current IP Advisors Program. Japan is expected to improve its nation’s ability to innovate and create new technologies. To attain this goal, Japan has identified that the basis for industry-academia-government R&D consortiums is through obtaining information on universities’ and other academic organizations’ research technologies and IP so that Japan can appropriately place these universities in the appropriate wide-area network. This will allow the universities within the wide-area network to establish IP management policy to properly protect and utilize their IP rights. The current IP Advisors Program is conducted through application from the universities in established wide-area network to JIII. Upon review of the application, JIII will then dispatch the IP Advisor to the applicant university of that wide-area network. IP Advisors not only can provide solutions to general IP related problems, they can also provide professional advice and service on how to establish and operate IP management system for all the universities within the wide-area network. B. IP advisors’ role In principle, IP Advisors are stationed to the Administrative School or Major Supporting School within the wide-area network. IP Advisors can be dispatched to other member schools (“Member Schools”) or provide telephone inquiry service by answering IP related questions. In other words, IP Advisors are not stationed in any Member Schools to manage their IP management affairs, rather, IP Advisors advise or instruct the IP managers of the Member Schools on how to establish and utilize IP management system based on the Member School’s infrastructure. The contents of IP Advisors roles listed are as follows: (a) Assist with activities within the wide-area network. 1. assist with establishing information sharing system between universities within the wide-area network; 2. assist with solving region-based or technology-based IP problems; 3. provide inquiry service for planning activities within wide-area network; and 4. provide inquiry service on other wide-area networks activities planning. (b) Provide services for Member Schools (Type 1) with undeveloped IP management system. 1. investigate or analyze the available IP management system in the Member Schools; 2. assist with drafting a plan to establish IP management system (through an assisting role) and provide instructions or advices accordingly; 3. direct personnel training (i.e. provide education on invention evaluation, assessment on applying for patent and contracts); 4. advocate different regimes of IP; and 5. collect relevant information on new developing technologies. (c) Provide services for Member Schools (Type 1) with developed IP management system 1. investigate or analyze the available IP management system in the Member Schools; 2. provide advices or instructions on the application of IP management department; 3. provide advices or instructions for solving IP management problems; 4. direct personnel training (i.e. provide education on invention evaluation, assessment on applying for patent and contracts); 5. advocate different regimes of IP; and 6. gather relevant information on new developing technologies. (d) Provide services for Member Schools (Type 2) 1.Share and exchange information through network conference. C. Recruitment process and criteria JIII adopts an open recruitment process without a set number of allocated IP Advisor positions. Working location is based in Member Schools of wide-area network in Japan. In principle, IP Advisors are stationed in Administrative Schools or Major Supporting Schools within the wide-area network and can only provide telephone inquiry service or temporary assignment for assistance to the Member Schools (Type 1). However, it is noted that IP Advisors do not belong to any specific university within the wide-area network, they are employed by JIII under an exclusive contract. Based on 2013 example, IP Advisors’ employment contract started from 1 April 2013 and expires on 31 March 2014. IP Advisors’ salary and travelling expenses are paid by JIII. However, expenses for Members School (Type 1) establishing a working environment and any other disbursements should be paid by the Member School (Type 1). Furthermore, under the implementation of the current policy with respect to IP Advisors who are unable to comply with the new criteria, previous contract is considered as a non-periodical contract for the IP Advisors to continue to station in the university. However, if IP Advisor is stationed in a specific university, it must be limited to a maximum of 3 years. Due to the IP Advisors’ work, they must comply with the privacy law and keep any obtained information confidential. D. IP advisors’ qualification 1. Require a high level of professional knowledge on IP management system IP Advisor candidates must have relevant experience working in the industry with IP management system department, operation planning department, R&D department (collectively refer as “IP Management Related Departments”). 2. Have relevant experience in directing trainings in IP Management Related Departments IP Advisor candidates must have the ability to train personnel in IP Management. 3. Can provide IP strategies based on the demands. IP Advisor candidates must have the ability to plan and utilize IP strategies to achieve optimal outcomes in R&D base on the circumstances and needs of different universities. 4. Have referral from the supervisors. IP Advisor candidates who are currently employed must be able to obtain a referral from their current positions’ supervisor, IP manager or personnel from higher up. IP Advisor candidates who are current unemployed must be able to obtain a referral from their previous employment. E. IP advisors’ selection process Based on JIII’s “University Network IP Advisors Adopted Standards” (“Adopted Standards”), IP Advisors are selected first through written application followed by interview. After a comprehensive assessment, all qualified candidates will be compared based on their compatibility of the essential criteria and other non-essential criteria, and finally selecting the most suitable candidate for the wide-area network. F. Application criteria for IP advisors services 1.Common requirements for Member Schools of wide-area network (a) must be an university or educational organization pursuant to the School Education Act (No. 26 of 1947) and must be able to conduct research and have set number of entry students and graduates per year;and (b) university must have developed IP related technology or design. 2. Criteria for wide-area network (a) Must have minimum of 3 and maximum of 8 Member Schools (Type 1) and 10 or less Member Schools (Type 2) combined, and have Member School (Type 1) entering wide-area network; (b) Must clearly state the nature of network as region-based or technology-based; (c) With Administrative School as base, the network must have collaborative system to plan network events; (d) Administrative School must be able to propose and carry out network events which can benefit Member Schools (Type 1) and the society through annual business plan. (e) Must be capable to provide indirect assistance to IP Advisors who are limited by time and region such that there is a proper environment to conduct wide-area network events. 3. Entry requirement for Member Schools (Type 1) (a) Must include in the university’s policy that they will become a Member School (Type 1) in the network and provide assistance to IP Advisors accordingly; (b) IP management and IP utilization system must be clearly implemented; (c) must clearly state the scope of responsibility in relation to the collaboration with the Administration School; (d) Propose and carry out an annual business plan which can improve IP management and utilization system to a certain level on their own; and (e) Has the facility to allow IP Advisors to provide assistance and service. 4. Entry requirement for Member Schools (Type 2) (a) Must include in the university’s policy that they will become a Member School (Type 2); (b) Same as paragraph F(3)(b) in this article; and (c) Same as paragraph F(3)(c) in this article. G. Current status quo The original aim was to establish the initial IP Advisors Program to assist with university’s IP management system by dispatching IP Advisors to 60 and more universities from 2002 to March 2011. The current wide-area university network IP Advisors Program started on April 2011. Since then, JIII has dispatched IP Advisors to 8 wide-area networks. In addition, IP Advisors have also been dispatched to wide-area network with art and design colleges/universities. During year 2011, IP Advisors has achieved and completed several IP management policies as follows: 7 IP policies, 3 academia-industry collaboration policies, 2 conflicting interest policies and 2 collaborative research policies etc. Recommendation This article is based on a legal perspective view point, taking Japan’s IP Advisors Program as a reference to provide the following recommendations on the topic of network for academia-industry collaboration in Taiwan. A. Separate levels of collaboration base on needs Using Japan’s policy as an example, universities within the wide-area network require different content of services tailored to each university individually, and the universities can be categorized into two types of member schools based to the content of services. Accordingly, it is recommended that the Government should consider a similar approach to the Japan’s policy when establishing IP management alliance and forming network of IP management system. For instance, design different levels of content and collaboration, and thus expand collaboration targets to gradually include major legal research institute, technology transfer centre for universities, and IP services in northern, center and southern area of Taiwan. This will allow collaboration of these organizations to coordinate IP programs such as IP northern, application and utilization with ease. B. Emphasis on the idea of establishing and maintaining IP basic facilities Based on Japan’s past experience, it is recommended that before expanding IP Advisors related policy to solve regional IP problems, universities must first be assisted to improve their own IP management system, which has taken Japan almost 10 years to improve their universities’ IP management system. From the current IP management system policy, it can be observed that the establishment of IP management system has a certain relevant importance. Furthermore, there is an emphasis on IP Advisors’ experience in training IP managers. Accordingly, it is recommended that the Government in future planning of network IP collaborate system should set short term and long term goal flexibly, such that the basic IP facilities within the members of the network can develop continuously. For example, short term goal for a legal research institute can be growing to a certain size for it to adjust or implement IP related policies. As for longer term goal, it can be a requirement to set up a unit or department to operate and manage IP. C. Expanding the definition of ‘Networks” Taiwan and Japan are high populated country on an island with limited land. Thus, if Taiwan and Japan insist on maintaining the geographic position for networking concept and adopting such concept on the regional economics for cluster effects, then it is difficult for Taiwan and Japan to compete with American Silicon Valley or other overseas universities. In light of the above, on establishing network of IP collaborative system, the Government should take reference from Japan’s practice in 2012 and combine same industry such as medicine industry or art industry in the definition of network. This will accelerate the integration of IP experience, information, and operation management capability within the network of same industry. Conclusion In conclusion, in order to establish academia-industry IP collaboration system and efficiently improve Taiwan’s IP management system in research organizations, first must focus on various policies tailored for different levels of collaboration so that it can be integrated and expand the integration of IP resources such that there is a good foundation to develop IP basic facilities. Following the establishment of good IP foundation, it can then be further develop to more complex IP programs such as IP landscape, planning and strategizing etc.

Blockchain in Intellectual Property Protection

Background Blockchain is a technology with the ability to decentral and distribute information. It records encrypted information of the user’s behavior. Blockchain has disintermediate, transparency, programmable, autonomous, immutable and anonymous essential features. The first application of blockchain is to develop cryptocurrency and a payment system, Bitcoin, which has overturned traditional concept of the currency model we knew. So far, blockchain has been widely applied in many territories, such as the intellectual property protection system, called the Blockai, which is a website using blockchain to overcome the plight of piracy in the United States. Example The Library of Congress in the United States found that it had been lack of efficiency for the copyright management. Blockai provided a solution for the Library. Authors will benefit from having proof of publication and copyright monitoring by registering with Blockai. The Blockai system securely timestamps copyright claims in the distributed database based on the Bitcoin protocol. For each copyright claim, a proof file is made available through the footer of the certificate and can be verified by authors using this open source proof verification tool, and it is free of charge for everyone. Although the "Proof of Publication" does not constitute admissible evidence in a trial, it is still credible in its technical features. Conclusion In Taiwan, there is still no copyright registering system. Before a copyright infringement suit may be filed in court, the burden of proof is on the copyright owner. For it is difficult for the copyright owner to provide a credible evidence in trial. We may consider using the experiences of other countries for our reference, developing the intellectual property protection system based on blockchain technology in order to help authors preserve their rights, and provide legal services as a legal technology.

Utilizing TIPS 1 to Establish a Comprehensive Intellectual Property Management System

Chen Yi-Chih, Chen Hung-Chih 2 I. Foreword Intellectual Property (IP) Management is a subject of recent focus in Taiwan . More than 1 million patents have been filed in Taiwan and each year, Taiwan dedicates NT $80 3 trillion in research and development. The estimated cost for IP prosecution, maintenance, litigation, conciliation, compensation and authorization amounts to NT $200 trillion (U.S.$6.5 trillion) 4. Even though many enterprises have gradually recognized the importance of intellectual property, the situation has not significantly improved based on the statistics stated above. Observation shows that only few enterprises in Taiwan have taken active steps to manage their IP and it was only after facing infringement lawsuits and tremendous amount of loyalty payments, most companies started to realize the important of IP management. Two main causes are believed to have negative impact on the lacking and ineffectiveness of most Taiwanese enterprises' IP management: Taiwanese enterprises have not taken proactive measures to handle IP management issues and IP management is only viewed as a mechanism to prevent IP infringement. Taiwanese enterprises have not sought ways to proactively and strategically use their intellectual property as a tool to yield profit. Due to limited professional knowledge and resources, Taiwanese enterprises do not know how to manage and exploit IP generated within their companies . Therefore, it is critical to assist these enterprises to develop and implement an effective IP management strategy under which the full potential of their IP can be utilized and the maximum value of the enterprises' IP can be realized. The Intellectual Property Office of the Ministry of Economic Affairs recognized the importance of governmental role to address this issue. Since 2003, it has collaborated with the Institute of Information Industry to work on a project for developing a standardized IP management system. In 2005, the project was handed over to the Industrial Development Bureau which then carried on the development and promotion of the Taiwanese Intellectual Property Management System (TIPS). Taiwanese enterprises 5 are able to use TIPS as a basis to establish their own comprehensive IP management systems. Based on our experiences in promoting TIPS and the feedbacks from those enterprises which have followed the TIPS's guidance to establish their IP management systems, we are pleased to find that TIPS is capable of assisting enterprises to develop a comprehensive IP management system. The system no only meets an enterprise's operational needs but also can be continuously improved owing to its adoption of the PDCA management cycle 6. II. The Introduction of TIPS A. The Origin and Overview of TIPS On December 9, 2004, The Ministry of Economics, in recognition of the needs to assist Taiwanese enterprises to better manage and more fully utilize their intellectual property, organized a “Taiwanese IP Management Standardization and Promotion Summit”. In order to establish a consensus on IP management among Taiwanese enterprises and to encourage the enterprises to implement an internal IP management system, the Taiwanese government positioned TIPS as an industry standard. In 2006, The Industrial Development Bureau (IDB) of the Ministry of Economic Affairs (MEA) established a TIPS promotion program and revised the 2004 draft of the Intellectual Property Management System Standard to become the Taiwan Intellectual Property Management System (TIPS). The industrial experts' opinions and comments were gathered and used to amend the draft, TIPS was then formally announced 7 on March 23, 2007 and consequently promoted. In hopes to protect Taiwanese enterprises and to improve their market competitiveness, IDB initiated extensive promotion program, encouraging Taiwanese enterprises and organizations to establish a convenient, efficient, and low-cost IP management system by following the TIPS's guidance The main characteristic of TIPS is the incorporation of the PDCA (Plan-Do-Check-Action) model from the ISO 9001:2000 Quality Management System. By adopting this model, not only the challenges of IP management can be resolved, but the whole system can also be continuously improved. Since TIPS shares the ISO's characteristics of being credible, comprehensive, and easily adaptable, TIPS and be easily integrated into the ISO standards within an enterprise such that the conflicts between these two systems will be minimized and it will only require minimum organizational structural changes and implementation costs. If an enterprise has already implemented ISO, implementing TIPS becomes more easily and efficient. In addition, TIPS emphasizes the concepts of using “process-oriented approach” and “systematic management” 8. Enterprises can merge their existing infrastructures and TIPS to establish a convenient, effective and efficient IP management system to reduce losses caused by IP infringement. Enterprises may also strengthen their market competitiveness and increase profits through royalty income. TIPS includes nine chapters. The first four chapters cover Summary, which describes the background of TIPS; Scope of Application and Terminologies. Clause 0.3.1 9 of TIPS states that the purpose of TIPS is to promote the utilization of IP management as one of the means to maximize an enterprise's profits. Rather than an individual or a specific department, protecting IP assets is the responsibility of all employees within the enterprises. In addition, the establishment of an IP management system is essential regardless of the scale, product or service provided by an enterprise. Clause 1.2 of TIPS clearly provides that TIPS is applicable to all enterprises, despite their types, scales, products and services provided. Therefore, TIPS is not designed solely for large enterprises. It can be applied to all kinds of organizations which include but not limit to a company, a specific department/division within a company, a laboratory or a project team. B. The Foundation of TIPS Before establishing TIPS, the government recognized that an enormous amount of resources is required to establish an IP management system. Therefore, the ISO9001:2000 quality management framework was adopted and TIPS was developed based upon the ISO's management principles. By incorporating IP managing strategies into an enterprise's operation goals and internal activities, the IP management system is no longer just a risk management system but a system that is closely aligning to the overall operations of an enterprise. Since it was found that many domestic companies implemented ISO9001:2000 Quality Management System solely for compliance purposes, people are skeptical about its effectiveness. In fact, if one understands the rigorous formulation processes behind the quality management system and its principles, one would recognize that an enterprise's IP management system can be significantly improved by adopting the management characteristics of ISO Quality Management System. The main characteristics shared between TIPS and ISO are outlined as follows: The effectiveness of an IP management system can be evaluated through clear policies and goals Chapter 5 of ISO 9001 : 2000 discusses Management's Responsibility. It states that top management should establish an enterprise's mission, vision, policies and goals, otherwise known as Visionary Leadership. An enterprise should consider its stakeholder's needs, understand the gap between its current status and the ideal state when setting its mission, vision, policies and goals. It should also decide its operational goals by considering available resources and the external environment. Traditional way of IP management only focuses on the operational and managerial processes. Strategic issues such as strategic planning and mission/vision planning are often forgotten, which often leads to a disconnection between strategy and actual operations. The concept of setting clear policies and goals used in ISO Quality Management shall be adopted to manage IP. That is to say, clear policies and objectives should be defined by the top management followed by detailed processes and steps required to realize the goals. Clear operational processes and responsibility help to achieve IP management goals ISO9001:2000 states that quality issues are caused by process, not product and process issues are caused by management since processes are carried out by people. Therefore, all personnel who is involved in carrying out the processes (in other word, all the employees within an organization) shall have the responsibility to improve quality. This concept applies to IP management as well. It is an incorrect general belief that IP management is merely for damage control or risk prevention. It is also an incorrect belief that an IP management is the sole responsibility of the legal department that other departments have no roles to play in enhancing the added-value of IP. For enterprises intending to utilize IP to enhance its competitiveness, some suggestions as listed below should be taken into account when planning their IP strategies: Set IP management as one of the company's operational goals. Organize a team to implement the IP strategy and to determine the processes required to achieve the IP goals. Clearly identify roles and responsibilities for personnel involved in all levels of IP management. Identify tasks required to be documented. Ensure the employees understand the linkage between their assigned tasks and the corresponding organizational goals. Through careful considerations of planning the organizational goals, processes and the expected outputs derived thereupon, enterprises can determine whether the processes so planned are necessary, appropriate, and effective . Consequently, minimizing the resources required to be invested into IP management. Monitoring, evaluation, and corrective actions can help to ensure the effectiveness of an organization's IP management processes Clause 8.2.1 of ISO9001:2000, “customer satisfaction”, emphasizes that customers own the right to evaluate. In the case of IP management, customers are basically the enterprise itself, therefore the performance is evaluated based on whether the set organizational goals can be achieved. It has been observed that many companies implemented the ISO Standards purely for the purpose of obtaining ISO's certification and do not consider whether the processes implemented are, in the practical sense, effective or efficient. Under this circumstance, the enterprises would not gain any actual benefits, despite that the requirements of ISO standards are met. The goal of process management is to improve the process efficiency, effectiveness and adaptability. Clause 8.2.3 of the ISO9001:2000 discusses Monitoring and Measurement of Process and Clause 8.2.4 talks about Monitoring and Measurement of Product. They state that an organization should establish a mechanism to monitor, evaluate, and understand the organization's internal and external customers' needs. This mechanism can also help to determine whether the organization can meet or exceed the expectation of its customers (in terms of processes, products, and/or services), which is also a critical element in establishing a systematic IP management system. If the result of evaluation does not meet expectation, there is a problem. In order to prevent the problem from reoccurring, prevention is the best. The concept of prevention is to design measures to avoid the occurrence of hidden problems. Unexpected problems are inevitable to occur even if preventive measures have been taken. We should analyze the impact of the problems occurred and propose counter measures to minimize their impact. The efficiency of IP Management relies on continuous improvement There are always opportunities to improve any process. Clause 8 of the ISO9001:2000 discusses Measurement, Analysis and Improvement which includes continuous improvement processes. Clause 8.2 Monitoring and Measurement, Clause 8.3 Control of Nonconformity, and Clause 8.4 Analysis of Data discuss the issues surrounding monitoring, measurement, analysis and control of nonconformity. Clause 8.5 discusses Improvement, which covers action taken to address the causes of identified issues. There are many issues that may be identified after analysis which cannot be resolved at once. Clause 5.1 of ISO 9001:2000 Management Commitment requests that the top management team be responsible for setting policy and goals, and providing resources needed to achieve the goals. By introducing ISO9001:2000 measurement, analysis, and improvement methodologies into the IP management system, it is believed that enterprises can thus effectively manage their IP and achieve a win-win scenario with their customers. C. The expected benefits of Implementing TIPS Since TIPS shares the above mentioned characteristics of the ISO Quality Management System, it not only can reduce the risks of infringing the IP rights of the others, but also can assist an organization to achieve its operational goals provided that the organization has designed relevant processes pursuant to the requirements of TIPS and has thoroughly implemented the designed processes. Using TIPS's external evaluation mechanism 10, enterprises implementing with TIPS can prove to their customers and external stakeholders that they have the capability to manage and maintain their IP. If an enterprise follows TIPS to establish its IP management system, its expected benefits include the followings: Enhancing market competiveness and increasing the added-value of an organization An IP management system that is designed to meet the specific needs of an organization shall play a significant role in achieving the organization's operational goals. Take a fitness equipment or an automobile parts manufacturer as an example, if the manufacturer owns the IP rights (ex: new design patent or trademark) embodied within the products, it is expected that the manufacturer can profit more than a purely OEM company which does not own its own brand. This is because the IP rights embodied within the products could provide significant added-value beyond what an OEM company can offer. Increasing customer's ordering intent The guidelines of TIPS also serve as the requirements for certification purpose. A government certified IP management system will ease concerns over trade secret protection and thereby promote cooperation and trusting relationships between the suppliers and the buyers and between research collaborations which consequently would foster better research results and potentially more purchasing orders. Minimizing resource wasting and actively creating profits Most small and medium enterprises in Taiwan do not have adequate labor and financial resources to develop a comprehensive IP management system. It is the hope of the government that a simple, effective, and low-cost IP management system can be established which tailors to the specific needs of every enterprise by adopting the TIPS framework. Once enterprises are capable of systematically manage their IP, it is expected that the IP generated and their exploitation can really match the enterprises' requirements and expectations, so that no resource is wasted to produce unwantable IP. The enterprises may further increase their profits by licensing or assigning their IP rights. Fostering an organizational culture that values the importance of intellectual property and the ability to continuous improve Establishing IP management policies, coupled with ongoing IP management seminars and education and training programs for new employee would enhance the awareness of the importance of IP management to the organization among the employees. The employees may further change their attitudes from passively complying with the policies to actively participate the system such as paying particular attention to potential IP risks and offer suggestions for process improvement. One company which implemented TIPS commented that the regular and ad hoc audits requirement and the necessity of assigning roles and responsibilities as required by TIPS assist it to identify problems concerning management issues. Corrective and preventive actions can be rapidly taken to address the problems identified, allocate the liabilities and improve the whole system. As a consequence, the IP management system can be effectively carried out to ensure that the planned objectives are met. It was found that most companies do not have internal audit and continual improvement programs to detect the hidden problems concerning management. Enhancing risk management and the capability to respond Currently, the fundamental and most important goal for an enterprise's IP management is to reduce the risks of infringement. Enterprises which have implemented TIPS found that TIPS is capable of enhancing data sharing across the departments which allows the IP department to detect potential risks at the earliest time. Further, the establishment of risk management mechanism and processes in response to infringement allegations as required by TIPS helps to institutionalize an enterprise's management system in handing legal risks. III. A holistic approach to IP management The Taiwanese government hopes that enterprises can systematically manage their IP through the implementation of TIPS. In other words, following TIPS's guidance, the Taiwanese enterprises should establish an IP management system that incorporates the usage of the PDCA management cycle (Plan-Do-Check-Action) and process management approach and such system must be built by taking into account the enterprise's business operation strategies and objectives. Enterprises should have clear processes and related rules for handling all IP related issues. For example, prior to filing a patent application, there should be a plan for the ways to acquire the targeted IP and prior art research shall be conducted. Based on the search results, enterprises can then decide whether they would like to internally develop the targeted IP or to seek licensing opportunities. Effective IP management processes shall be able to answer the following questions: Whether records are stored property? Who should conduct the audit? Whether the current system meets the IP management policy or goals? What are the roles and responsibilities? The following section aims to explain how Taiwanese enterprises can establish or modify their current IP management system to achieve its full potential: A. Roles and Responsibilities for Implementation All employees within an organization shall participate in order to realize the most benefits out of the IP management system. Leadership responsibilities, roles and responsibilities allocation, training and education programs and the subsequent auditing processes on the performance of operation shall be clearly defined and planned. Establishing a successful IP management system shall not be the sole responsibility of the legal department. During the implementation stage, the following personnel should participate and complete the related tasks: Executive management team (Management executives, ex. CEO, President, COO) a. Establish IP management policy and goals; b. Communicate the importance of compliance to the IP management policy; c. Evaluate and review the effectiveness of the IP management system; and d. Ensure the readiness of the resources available for establishing the IP management system. IP Management System Representatives (Managers who have decision-making authority, ex. EVP, VP) a. Ensure that the required processes for the IP management system are established, implemented, and maintained; b. Report to the executive management team on the performance and improvement needs for the existing system; and c. Ensure employees understand the IP management policy and goals. Department Representatives (All department representatives) a. Execute tasks assigned by the IP management system representatives; b. Execute action items reached by the steering committee meetings; c. Ensure the achievement of IP management goals, and d. Responsible for the Maintaining and improving the IP management system. B. Steps of Implementation Plan Establishing a systematic IP management system requires the participation of all employees and it requires reengineering of the existing processes. It is not an easy task to be established and planned solely by the legal department. All other departments within an enterprise shall participate and offer their suggestions. The followings are the recommended stages for implementing an IP management system: Stage Tasks Description Responsibility Remark 1. Preparation 1). Review of current status Understand resources available and the status of operation Data collection; define roles and responsibilities 2). Establish implementation team Identify team members and team leader Confirm organizational structure for implementation 3). Set goals and establish all management programs Evaluate current situation to formulate IP management policy, and define measurable goals. Processes planning shall be made by taking into account the management responsibility, resource management, product development, and performance analysis and improvement. This helps to identify the position of a process within the overall IP management system and its inter-relationships between the processes themselves. Provide evaluation report; organize IP management deployment document Documentation: IP Management Manual à Procedures à Guidelines à Records 2. Training and Education & System Integration 4). Relevant training and education Understand the direction, method, and spirit of standardization. Participated by the implementation team and management representatives. 5).Drafting documentation Decide documentation framework, format, table of contents, numbering principles, and appoint editors and the completion date. Management team assigns tasks 6). Establishing documentation Drafting and revising procedural documentation Internal discussion and review IP management principles (refer to prior text) Define the scope and content of standard format. Appoint editors and the completion date. Establish standard format as an example before documenting Prepared IP management manual to aid employees and customers to understand the organization's IP management system Implementation team and management team 3.Implementation 7). Provide training & education specifically for the internal audit personnel Explain the purpose of auditing and execution details Participated by Internal audit committee Prepare checklist for auditing to be used by auditing personnel 8). Conduct system implementation and internal audits Execute documentation processes for the management system and conduct internal audits and review the performance Implementation, review, correction and prevention. Participated by all employees 9). Conduct overall examination of the intellectual property management system Implement IP management system Participated by all members of the implementation team C. Implementation Chapter five through chapter eight of TIPS define the core of the guidelines which cover the basic requirements of IP management requirements; top management's responsibilities; resource management; the acquisition, protection, maintenance and exploitation of IP, as well as performance evaluation and improvement. To facilitate Taiwanese enterprises' understanding of TIPS and how to use it to establish a comprehensive IP Management system, we provide the following main steps of establishing an IP management system based on the TIPS's requirements: Define the company's IP management goals Enterprises that would like to establish an IP Management system have to understand their unique features and future operation strategies to evaluate the needs for managing their IP. Clauses 4.1, 5.2, and 5.3.1 of TIPS stipulate that the management team has the responsibility to set clear IP management policy and goals. For example, one policy can be to increase R&D efficiency and the goal can be to reduce the product development cycle by 10%. Defining appropriate IP Management policies can help to establish a IP management system that meets an enterprise's practical needs. It can also be used as basic principles for formulating IP strategies and subsequently the implementation processes of IP management system. The management team should utilize intranet or bulletin boards to inform its employees of the organization's IP management policies, goals, and relevant responsibilities assigned to each department. This will help employees to understand their roles and responsibilities and the importance of their participation in achieving the organization's goals. Develop required processes for achieving enterprise's IP management goals The ultimate purpose of establishing an IP management system is to maximize profits and to minimize losses. To ensure successful acquisition of targeted IP, companies should plan and develop processes and operating procedures based on their needs and business development strategies. During this stage, companies should focus on the followings in order to meet TIPS's requirements: Understand statutory and regulatory requirements concerning IP The management target of TIPS is intellectual property, which includes trademark, patent, copyright, trade secrets and etc. Different IP acquisition approaches apply to different IP targets. Complying with Clause 7.1, companies must firstly understand all the statutory and regulatory requirements before a plan is made for the acquisition of targeted IP. For example, according to the relevant legislations in Taiwan, once a work is created, the authors obtain the copyright in the work. However, the right to patent or trademark can only be acquired through registration. Evaluate options for acquiring the targeted IP Enterprises shall evaluate different options (i.e. self-development, purchase or outsourcing) for acquiring their targeted IP by taking into account of their business operation objectives and the characteristics of their products as the methods of acquiring IP will influence the subsequent processes concerning the protection, maintenance and exploitation of the acquired IP. Clause 7.2 of TIPS requires enterprises to implement processes regarding to the evaluation of the options for acquiring the targeted IP. Clause 7.3.5 further requires enterprises to set up an assessment procedure for every IP application and suggests to incorporate an invention incentive program. Define roles and responsibilities After completing the feasibility study concerning various options to acquire the targeted IP, enterprises have to decide whether to establish an IP management specialized department (ex. legal or IP department) and to define clear roles and responsibilities based on the company's scale and resource available. Companies should pay particular attention on preparation work, such as conducting patent or trademark prior art search, to avoid wasting of resources and voided applications. If enterprises outsource IP management related activities to external bodies, Clause 7.4.1 of TIPS requires them to have a clear knowledge of the service quality provided by the outsourcing bodies and to establish a controlling mechanism over the outsourcing activities (ex. evaluation → outsourcing → contract → periodic evaluation…etc.). Special attention has to be paid to the contractual terms concerning obligations and ownership of IP. Determine Resources Required Enterprises that would like to establish an IP management system not only have to ensure that they have enough resources, but also need to ensure that the resources can be utilized in an effective way. The management team, in accordance of the requirements for Clauses 5.4.2 a nd 6.1 of TIPS, should provide resources (including labor and equipment) required for the implementation of the IP management system. Examples include the continual recruitment of manpower and the purchasing of computer software and hardware equipments and etc. As far as labor is concerned, enterprises, in accordance with Clause 6.2.1 , have to ensure that their employees have adequate abilities to assume their responsibility. Clause 6.2.1 states that companies should provide basic IP education and training to equip the employees with necessary knowledge. Pursuant to Clause 6.2.3, enterprises should provide their patent engineers and legal staff with advanced training, such as intellectual property litigation and arbitration, intellectual property licensing and contracts, techniques for patent design around, IP valuation and so on. In summary, enterprises should enhance the employees' (both new and existing employees) awareness of IP, the importance of complying with statutory requirements and the enterprises' internal IP policies and goals through education and training. Establish an IP Management System After determining the resources required, enterprises need to establish a basic system to manage their IP. The system shall include a documentation control system, an audit program, an internal communication channel and so on. We provide a summary explaining the details of each program required to establish a basic IP management system: Basic IP Management System (1) Documentation Control System: Enterprises should establish a systematic documentation control system based on their IP management policies and goals, such as document control procedures, internal audit process and etc. Among those, the most important one is an IP management manual. Clause 4.3 of TIPS requires the enterprises to state all the following items in their IP management manual: IP management policies and goals; roles and responsibilities; processes and procedures; and flow charts or grid charts to explain the interrelationships between the processes and procedures. Further, Clause 4.4 also states that all documents, no matter whether they are internally generated or externally acquired (ex. court notice, invitation to tender, official documents) should be properly managed. The source, level of confidence, method of management should be clearly labeled for future purposes. (2) Audit Program: Clause 5.4.2 states that top management has to be responsible or otherwise shall designate a management representative (the most senior staff that is responsible for intellectual property matters, such as vice president or director of IP management department) to manage a company's IP related issues. The top management team is also in charge of establishing a management review meeting, and setting agenda for each meeting such as discussing or revising the IP management policies and goals. Through management review meeting, pursuant to Clause 5.5, management representative must confirm that the set IP goals are met or if not, whether to revise the original policies or goals. All departments or responsible personnel (ex. legal, IP, general administration, accounting, human resource) shall participate the management review meeting. (3) Confidentiality Control Program: Enterprises in accordance with Clauses 4.4.1 a nd 7.4.4, should enhance feasible safety controls to protect their IP, such as setting document confidential criteria, physical access control, and control over replication of confidential documentation to limit exposure of important data. Supplemental IP Management System In addition to the above mentioned programs, supplemental IP management programs are required to assist in establishing an effective IP management system. They are outlined as follows: (1) Outsourcing Program: Due to cost or resource concerns, enterprises may outsource its R&D or IP prosecution activities to external professional agencies. Clauses 4.1 and 7.4.1 of TIPS require that the contracts entered into must clearly identify the ownership of IP involved and include a term of confidentiality obligation. This is to ensure that the outsourcing activities can be properly monitored and to prevent the leakage of important data. (2) Contract Review and Human Resource Management Programs: In order to prevent and avoid intellectual property infringement, in accordance with Clause 7.4.6 , enterprises should review all contractual terms of their contracts. As far as human resource management is concerned, in accordance with Clause 7.4.3, enterprises shall require new employees to sign an employment contract . Such contract shall include a term of confidentiality obligation and a non-competing clause may be included if necessary. (3) Internal Consulting and Communication Channel: During the period of establishing an IP management system, enterprises in accordance with Clause 5.5.2 must request relevant departments (ex. legal, sales, finance and accounting) to provide useful information concerning IP management. According to Clause 5.4.3, enterprises must establish communication channels (ex. dedicated mailbox, email) which is used to understand the feelings and to know the difficulties faced by the employees as it is inevitable to face challenges when a new system is being implemented, consistent communication and coordination is the only way to overcome these challenges. Ensure that Auditing and Preventive and Corrective Measures have been Taken Pursuant to Clauses 8.1 and 8.2, enterprises with IP management systems need to establish internal audit plans (including audit frequency, time, or method) to ensure that their IP management policies or goals are being met. Enterprises should ensure that their internal auditors are qualified i.e. have obtained the relevant professional certification, before conducting the internal audits. If nonconformities have been found through internal audits, corrective or preventive measures should be taken pursuant to Clauses 8.4.2 a nd 8.4.3. For instance, if the result of internal audit reveals that the R&D staff failed to keep their R&D records in accordance with the set rules and requirements, companies shall find out the causes (i.e. the reasons of the nonconformity) and then take appropriate corrective or preventive measures. An example of corrective measure can be to increase the frequency of checking the relevant records. And an example of preventive measure can be to provide incentive program to encourage the compliance of the relevant rules and regulations. Pursuant to the requirements of Clause 8.3, enterprises should collect and analyze relevant information, such as the internal audit reports, results of the corrective measures taken, and the results of market/competitors analysis. The above information can be used as input information during management review (Clause 5.5.2 ) to decide whether it is required to amend or set new intellectual property management policies and objectives. Through continual auditing and revising, a systematic IP management system can be established. IV Conclusion In the era of knowledge economy, the abilities of most domestic enterprises to manage tangible assets have gradually matured (ex. ERP system). However, the abilities to manage intangible assets which include intellectual property have yet to be developed. Management systems in most domestic enterprises are fragmented. For example, legal departments are only responsible for contract reviewing tasks; R&D staff has limited IP knowledge. The importance of IP is often overlooked and most enterprises do not see that intellectual property management is the responsibility of every employee. As a consequence, the Taiwanese government establishes and promotes TIPS to encourage domestic enterprises to adopt a systemic approach of managing their intellectual property and TIPS is also provided as a tool to assist enterprises to establish a sound intellectual property management system. The purpose of implementing TIPS is not to request enterprises to establish a separate management system. In order to maintain efficiency and competitiveness, an enterprise has to have an integrated management system to support its core operations and also to meet the requirements of different management system standards. Eliminating overlaps of the requirements between different quality management systems is an inevitable trend. TIPS incorporates IP management with the ISO 9000 quality management system, which is capable of simplifying the complicated IP management tasks into an effective and standardized IP management system. TIPS helps an enterprise to establish a systematic process for managing its IP. Through competitive analysis, market trend analysis, and periodic IP management operations review, a company can revise and amend its IP management policies and goals and continually improve its IP management system. For example, sales departments shall collect market trends, competitive information and shall also consciously avoid acquiring materials that may raise infringement concerns. Human resource departments shall focus their efforts in providing IP education and training. Finance departments shall evaluate the costs required for maintaining the existing IP rights and inform the R&D departments to conduct relevant review at the appropriate time. R&D departments shall conduct prior art search before a new research project is commenced. TIPS offers a simple, efficient, and low-cost management system which assists an enterprise to establish an IP management system that aligns to its business goals and operation activities. We hope that by promoting and encouraging domestic enterprises to adopt and implement TIPS, Taiwan can strengthen its international competitiveness and sustain the growth of its economy and the whole society. 1.Taiwan Intellectual Property Management System (TIPS). The Ministry of Economics Affairs combined the IP management principles and the PDCA (Plan-Do-Check-Action) model used in ISO9001:2000 quality management system to create TIPS. The adoption of PDCA model helps organizations to establish a systematic and effective IP management system which can be continuously improved. 2. Chen Yi-Chih is a Section Manager at the Science and Technology Law Center ; Chen Hung-Chih is a legal Researcher at the Science and Technology Law Center . 3. Data Source: http://www.atmt.org.tw/html/modules/news/article.php?storyid=135&PHPSESSID=cab6428078a0435c5af1b2e7bbe2b121 (last visited: 08/11/2007 ) 4. Data Source: http://www.cyberone.com.tw/ItemDetailPage/PDAFormat/PDAFContent.asp?MMContentNoID=36372(last visited: 08/11/2007 ) 5. “Enterprise” as defined in TIPS includes company, corporate, school, research institute, a specific department or a project team is also included. 6. TIPS was developed based on the PDCA (Plan-Do-Check Action) model, a typical ISO management process which requires continuously monitoring, evaluating, analyzing and improving the whole system. 7. The TIPS guidelines can be found at: http://www.tips.org.tw/public/public.asp?selno=236&relno=236 8. Refer to article: New Philosophy of Intellectual Property – Use ISO Quality Management to establish a systematic IP management in Intellectual Property Journal, issue 74, 02/2005. 9. http://www.tips.org.tw/public/public.asp?selno=236&relno=236 (last visited: 08/12/2007 ) 10. The guidelines of TIPS also serve as the requirements for certification purpose. The Industrial Development Bureau of the Ministry of Economic Affairs will issue a certificate to an organization if such organization has implemented an IP management system satisfying the requirements of TIPS.

Review of Singapore IP Dispute Resolution Development

Review of Singapore IP Dispute Resolution Development Preface   In recent years, advantage of capital and productivity are not enough for company to stand out from the business battle. Innovation and creation become the driver of business growth. Intellectual Property (“IP”) Right turns out to be the power to boost international competitiveness.   In March 2013, Singapore submitted 10-year IP Hub Master Plan to guide Singapore’s development as a Global IP Hub in Asia. Six Strategies are identified from IP Hub Master Plan. This article focuses on strategy 4, developing Singapore as a choice venue for IP dispute resolution through a strong IP Court and deep IP alternative dispute resolution capabilities, to understand how Singapore attracts various stakeholders and hence create a hive of IP activities by adopting tailored processes to facilitate the resolution of IP cases and promoting alternative dispute resolution. Key Points of IP Dispute Resolution   When it comes to IP issue, oblige will take either marketplace or area of IP application into account for choosing jurisdiction of dispute resolution. The major IP war occurs in America and China. Although Singapore deals with less IP case, the government considers itself as a transparent, efficient and neutral justice system, coupling with lots of transnational divisions in Singapore, which creates an opportunity to develop IP dispute resolution.   To achieve the goal, Singapore puts its hand to enhance capabilities of IP Court and IP alternative dispute resolution for bringing more IP litigations and IP alternative dispute resolution to Singapore. 1. Enhance Capabilities of IP Court (1) Efficiencize Processes   In September 2013, the Registrar of the Supreme Court released Circular 2 of 2013 on the issuance of the IP Court Guide, which will apply to all cases under the IP docket of the Supreme Court with immediate effect. An IP Judge will be assigned to hear all interlocutory appeals, milestone pre-trial conferences (“PTCs”) and the trial on liability.   The IP Court Guide provides for two milestone PTCs before set down for trial whereby the lead counsel must personally attend to address the IP Judge on certain specified issues. All other PTCs will be heard by the senior assistant registrar managing the IP docket. Subject to certain exceptions, an assistant registrar will hear all interlocutory applications arising in each IP case.   In addition, to support the IP Court’s adjudication functions, the IP Court Guide provides for the appointment of assessors (for technical expertise) and amicus curiae (for legal expertise) for IP cases. Parties are encouraged to propose a single candidate by agreement. Otherwise, parties should agree on and propose a shortlist of candidates.   Due to improvement, it is more convenient for parties to track trail status. For IP Judges, they can get familiar with cases and related evidence through PCTs before entering trail process. On the whole, this change increases trail efficiency and quality. (2) Set Up Singapore International Commercial Court   The Ministry of Law proposed amendments to the Constitution of the Republic of Singapore and the Supreme Court Judicature Act in October 2014. The new legislation and regulations laid the foundation of Singapore International Commercial Court (“SICC”), which was set up in January 2015.   The SICC, the only one International Commercial Court in Asia, is a division of the Singapore High Court and part of the Supreme Court of Singapore designed to deal with transnational commercial disputes including business issues and patent suits. Key Features of the SICC: A. SICC matters will be heard by a Panel comprising High Court Judges, associate Judges and foreign associate Judges with extensive experience and highly regarded reputation. B. A party may be represented by a registered foreign counsel without any involvement of local Singapore counsel if the matter in question is considered to be an “offshore case”. An “offshore case” is defined in the amended Rules of Court as a case which has no substantial connection to Singapore either because (i) Singapore law is not the law applicable to the dispute and the subject matter of the dispute is not regulated by or otherwise subject to Singapore law, or (ii) The only connection between the dispute and Singapore are the parties’ choice of Singapore as the law applicable to the dispute and the parties’ submission to the SICC’s jurisdiction (“Singapore Law-only Connection”). C. The SICC will hear cases governed by Singapore law and by foreign law, with the Court taking judicial notice of the foreign law. In addition, the SICC is not bound by the domestic rules of evidence at all and may apply other rules of evidence whether they are found in a foreign law or otherwise, if the parties make an application for it. 2.Strengthen Capabilities of IP Alternative Dispute Resolution   Singapore International Arbitration Center (“SIAC”) and the WIPO Arbitration and Mediation Center Singapore Office were set up respectively in 1991 and 2001 to strengthen capabilities of IP arbitration. On the basis of these two centers, in order to enrich alternative dispute resolution, Singapore also established Singapore International Mediation Center (“SIMC”) and launched the service of arbitration-mediation-arbitration (“Arb-Med-Arb”) in November 2014.   Arb-Med-Arb is a process where a dispute is referred to arbitration before mediation is attempted. If the parties are able to settle their dispute through mediation, their mediated settlement may be recorded as a consent award. If the parties are unable to settle their dispute through mediation, they may continue with the arbitration proceedings. Arb-Med-Arb is definitely a better way for parties to reach a consensus on a dispute since arbitration is more costly and mediation is less powerful. Conclusion   The SIMC and the SIAC are now collectively working on mediation, Arb-Med-Arb and arbitration and providing various IP alternative dispute resolutions. Moreover, the SICC and IP Court are charged with IP litigation. These make Singapore a comprehensive IP dispute resolution system.   In the process of revolution, Singapore puts itself up to breakthrough as to amendments and the Supreme Court Judicature Act, which establish legitimacy of SICC. The government also defines IP dispute resolution services, such as SIMC’s mediation, Arb-Med-Arb, arbitration as well as SICC features. Nevertheless, other than SIAC, SICC decision may be difficult to enforce transnationally due to lack of legislation.   To sum up, Singapore earns recognition for aggressively proposing amendments and assigning responsibilities after setting IP target and evaluating obstacles; however, it is better to pay special attention to that if the market can keep up with administrative efficiency or if the IP strategy could accord with the demands of the market.

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