Artificial Intelligence and Trademark Assessment

Artificial intelligence (AI) has an unparalleled potential for facilitating intellectual property (IP) administration processes, in particular in the context of examining trademark applications and assessing prior marks in opposition and infringement proceedings. Several stakeholders have developed AI-based algorithms that are claimed to enhance the productivity of trademark professionals by carrying out, without human input, (parts of) the legal tests required to register a trademark, oppose it, or claim an infringement thereof. The goal of this chapter is to assess the functionality of the AI tools currently used and to highlight the possible limitations of AI tools to carry out autonomously the legal tests enshrined in trademark law. In fact, many of these tests are rather subjective and highly depend on the facts of the case, such as an assessment of the distinctive character of a mark, whether the relevant public is likely to be confused or whether a third party has taken unfair advantage of a mark. The chapter uses doctrinal research methods and interview data with fourteen stakeholders in the field. It finds that AI tools are so far unable to reflect the nuances of the subjective legal tests in trademark law and, it is argued, even in the near future, AI tools are likely to carry out merely parts of the legal tests and present information that a human will have to assess, taking prior doctrine and the circumstances of the case into account.

Computer-generated Works under the CDPA 1988

Copyright protection in some commonwealth jurisdictions extends to computer-generated works. Although many scholars deem the right over computer-generated works to be a neighbouring right, it is still not clear under what circumstances a work is a computer-generated work. With the increasing application of artificial intelligence (AI), the copyright controversies associated with computer-generated works have become even more complicated. This chapter focuses on policy and legal issues surrounding the output of AI and copyright protection of computer-generated work under the Copyright, Designs and Patents Act (CDPA) 1988 in the UK. The CDPA approach to computer-generated work deviates from the mainstream international copyright practices, where human creativity is essential for authorship and copyright protection. From a policy perspective, it is important to explore whether this deviation can be justified. This chapter also investigates authorship issues concerning computer-generated works based on case law and its application, in particular who the person making the necessary arrangements is, and what the necessary arrangements in the AI environment are. Other issues relevant to computer-generated work, such as copyright term and joint authorship will be analysed as well.

The Rise and Application of Artificial Intelligence in Healthcare

The overall purpose of this chapter will be to broadly explore both the existing and possible implementations of artificial intelligence (AI) in healthcare. The scope of this chapter will be explored from the unique perspectives of various stakeholders in the healthcare industry, namely the healthcare providers, patients, pharmaceutical companies, healthcare financial institutions, and policymakers. The chapter will seek to identify the potential benefits and pitfalls that faced by these stakeholders in implementing the use of AI, from the molecular level to a macroeconomics level; as well as seeking to understand the legal, professional, and ethical boundaries of the medical domain that are challenged as AI increasingly becomes irreversibly intertwined with the practice of medicine.

Roadmap to Artificial Intelligence and Intellectual PropertyAn Introduction

This introductory chapter provides an overview of the relationship between artificial intelligence (AI) and intellectual property (IP). While human beings have used various instruments and technologies to create and innovate, they themselves have been the main driving force of creativity and innovation. AI puts that into question, raising numerous challenges to the existing IP regime. Traditionally, the “intellectual” part of “intellectual property” refers to human intellect. However, since machines have become intelligent and are increasingly capable of making creative, innovative choices based on opaque algorithms, the “intellectual” in “intellectual property” turns out to be perplexing. Existing human-centric IP regimes based on promoting incentives and avoiding disincentives may no longer be relevant—or even positively detrimental—if AI comes into play. Moreover, AI has sparked new issues in IP law regarding legal subjects, scope, standards of protection, exceptions, and relationships between actors.

Rethinking Software Protection

The core of artificial intelligence (AI) applications is software of one sort or another. But while available data and computing power are important for the recent quantum leap in AI, there would not be any AI without computer programs or software. Therefore, the rise in importance of AI forces us to take—once again—a closer look at software protection through intellectual property (IP) rights, but it also offers us a chance to rethink this protection, and while perhaps not undoing the mistakes of the past, at least to adapt the protection so as not to increase the dysfunctionality that we have come to see in this area of law in recent decades. To be able to establish the best possible way to protect—or not to protect—the software in AI applications, this chapter starts with a short technical description of what AI is, with readers referred to other chapters in this book for a deeper analysis. It continues by identifying those parts of AI applications that constitute software to which legal software protection regimes may be applicable, before outlining those protection regimes, namely copyright and patents. The core part of the chapter analyses potential issues regarding software protection with respect to AI using specific examples from the fields of evolutionary algorithms and of machine learning. Finally, the chapter draws some conclusions regarding the future development of IP regimes with respect to AI.

Detecting and Prosecuting IP Infringement with AICan the AI Genie Repulse the Forty Counterfeit Thieves of Alibaba?

Drawing from available quantitative and qualitative data, this chapter briefly identifies and describes the automated as well as the more sophisticated AI-driven systems deployed to detect and enforce intellectual property rights (IPR) infringement by trademark and copyright holders in the online environment. It studies the legal basis for the use of such automated systems in copyright and trademark laws, and examines how such automated systems have upended, refocused, and altered many of the issues of IPR infringement and their enforcement. This chapter will also look at the problems of non-compliant Digital Millennium Copyright Act takedown notices, opportunistic copyright trolls, and non-interventionist Internet intermediaries, review the relevant judicial and legislative treatments including those in the Directive on Copyright in the Digital Single Market, and propose possible solutions to these problems.

AI as a Legal Person?

Cyclical advancements in artificial intelligence (AI) are usually accompanied by theories advocating the granting of legal personhood to sophisticated, autonomous computers. This chapter criticizes such theories as incorrect—a possible result of legal scholars being seduced by incomprehensible technical terminology, sensationalistic stories in the popular press, and ‘creative’ photo filters that transform our faces into animals. Discussions as to when computers should be recognized as persons are, logically, outside of the scope of intellectual property law. The granting of legal personhood is not premised on the existence of consciousness, intelligence, or creativity. Recognizing an entity as a legal person is a normative choice dictated by commercial expediency, not the result of fulfilling any technical criteria. While it is necessary to acknowledge the blurring of borders between art and (computer) science, as well as the increase in the technological sophistication of the tools used by authors and inventors, it is also necessary to state that even an exponential increase in ‘computer creativity’ will not sever the link between the computer and its user. Before discarding the idea of legal personhood for ‘creative algorithms’ once and for all, the chapter explores the relationships between autonomy and creativity. In particular, it places technical terms such as ‘AI’ and ‘autonomy’ in their original context and criticizes uninformed attempts to imbue them with normative connotations.

Copyright Protection for Software 2.0?

Traditionally, software programmers write a series of hard-coded rules to instruct a machine, step by step. However, with the ubiquity of neural networks, instead of giving specific instructions, programmers can write a skeleton of code to build a neural network structure, and then feed the machine with data sets, in order to have the machine write code by itself. Software containing the code written in this manner changes and evolves over time as new data sets are input and processed. This characteristic distinguishes it markedly from traditional software, and is partly the reason why it is referred to as ‘software 2.0’. Yet the vagueness of the scope of such software might make it ineligible for protection by copyright law. To properly understand and address this issue, this chapter will first review the current scope of computer program protection under copyright laws, and point out the potential inherent issues arising from the application of copyright law to software 2.0. After identifying related copyright law issues, this chapter will then examine the possible justification for protecting computer programs in the context of software 2.0, aiming to explore whether new exclusivity should be granted or not under copyright law, and if not, what alternatives are available to provide protection for the investment in the creation and maintenance of software 2.0.

Technical Elements of Machine Learning for Intellectual Property Law

Recent advances in artificial intelligence (AI) technologies have transformed our lives in profound ways. Indeed, AI has not only enabled machines to see (eg, face recognition), hear (eg, music retrieval), speak (eg, speech synthesis), and read (eg, text processing), but also, so it seems, given machines the ability to think (eg, board game-playing) and create (eg, artwork generation). This chapter introduces the key technical elements of machine learning (ML), which is a rapidly growing sub-field in AI and drives many of the aforementioned applications. The goal is to elucidate the ways human efforts are involved in the development of ML solutions, so as to facilitate legal discussions on intellectual property issues.

Do Androids Dream of Electric Copyright?

The advent of sophisticated artificial neural networks has opened new artistic opportunities, but also a variety of new legal challenges. Computer programs such as Google’s Deep Dream can take an image and process it in manners that resemble biological networks, producing artwork that is both unique and unpredictable. The law is not unfamiliar with the challenges of artificial intelligence (AI), in the past academics and policymakers have had to deal with the legal implications of autonomous agents in contract formation, to name just one area of interest. However, for the most part the implementation of smart systems has been limited in its reach and scope, and in many instances autonomous agents required quite a lot of direction from the programmer, following a very stringent set of rules. This meant that for the most part all rights, responsibilities, and liabilities arising from artificial agents fell squarely on the program creator. Neural networks are different, these systems have the potential to generate works in which human interaction is minimal. Modern copyright law has been drafted to consider originality as an embodiment of the author’s personality, and originality is one of the main requirements for the subsistence of copyright. So, what happens when you remove personality from the equation? Are machine-created works devoid of copyright? Do we need to change copyright law to accommodate autonomous artists? This chapter will explore this and other questions.