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Osmania University Journal of IPR [OUJIPR]
Vol.1 | Issue 1 July 2023
Impact of Artificial Intelligence on Intellectual Property
Rights: Challenges and Opportunities
Dr. Mohd Akhter Ali & M. Kamraju
Pages: 21 – 50
Recommended Citation
Dr. Mohd Akhter Ali & M. Kamraju, ‘Impact of Artificial Intelligence on
Intellectual Property Rights: Challenges and Opportunities’ (2023) 1(1) OUJIPR,
21 <https://ouipr.in/oujipr/vol1/iss1/2> accessed [date]
Available at: https://ouipr.in/oujipr/vol1/iss1/2
This Article is brought to you for free and open access by DPIIT IPR-Chair, Osmania University.
It is published in the Osmania University Journal of IPR [OUJIPR] and copyright therein remains
jointly with the Contributor and the OUJIPR.
For more information, please contact: editor.oujipr@ouipr.in
21
Impact of Artificial Intelligence on Intellectual Property
Rights: Challenges and Opportunities
- Dr. Mohd Akhter Ali
1
& M. Kamraju
2
Abstract
Artificial Intelligence (AI) is transforming the intellectual property (IP) landscape, presenting
both challenges and opportunities for businesses and inventors. AI can create, manage, and
exploit IP assets, raising complex legal and ethical issues related to ownership, patentability,
copyright infringement, and data protection. On the other hand, AI can also help automate
and streamline the management of IP assets, assist in the search and analysis of existing IP
assets, create new business models, and improve IP enforcement. It is essential for policymakers
and IP professionals to stay abreast of these developments to ensure that IP law evolves to meet
the needs of this rapidly changing technological landscape. This paper discusses the challenges
and opportunities that AI is presenting in the context of intellectual property rights.
Keywords: Artificial Intelligence, Intellectual Property, Ownership
Introduction
Artificial intelligence (AI) has emerged as a powerful tool that is
transforming the way intellectual property (IP) is created, managed, and
exploited. This technological revolution is creating new challenges and
opportunities for inventors, businesses, and policymakers. On the one
hand, AI is enabling the creation of new types of IP assets, improving the
efficiency of IP asset management, and facilitating new business models
for IP exploitation. On the other hand, AI raises complex legal and ethical
issues related to ownership, patentability, copyright infringement, and
data protection.
This research paper aims to explore the challenges and
opportunities presented by AI in the context of intellectual property
rights. The paper analyses the legal and ethical implications of AI for IP
1
Assistant Professor, Department of Geography & Joint Director, Directorate of Admissions,
Osmania University, Hyderabad; email: drmohdakhterali@gmail.com
2
Researcher, Urban and Spatial Studies, Department of Geography, Centre for Economic and
Social Studies, Osmania University, Hyderabad; kamraju65@gmail.com
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 22
ownership, patentability, and copyright infringement. The paper will also
examine how AI can be used to improve the management of IP assets,
search and analysis of existing IP assets, and create new business models
for IP exploitation. Finally, the paper discusses the policy and legal
frameworks that are needed to ensure that IP law evolves to meet the
needs of this rapidly changing technological landscape. The article draws
on existing literature and case studies to provide a comprehensive analysis
of the impact of AI on intellectual property rights. Further,
recommendations are provided for policymakers and IP professionals to
navigate the complex terrain of AI and intellectual property rights.
Purpose and Significance
The purpose of this research paper is to provide a comprehensive
analysis of the impact of artificial intelligence (AI) on intellectual property
rights (IPRs), including the legal and policy frameworks needed to address
the challenges and opportunities presented by this rapidly changing
technological landscape. The paper explores the ways in which AI is
transforming the creation, management, and exploitation of IP assets, and
will identify the legal and ethical issues related to ownership, patentability,
copyright infringement, and data protection. Additionally, the paper
analyzes the ways in which AI can improve the management of IP assets,
search and analysis of existing IP assets, and create new business models
for IP exploitation.
The research paper aims to provide insights into the complex legal
and policy issues that arise from the intersection of AI and IPRs, and to
provide recommendations for policymakers, IP professionals, and legal
scholars. By doing so, the paper seeks to contribute to the ongoing debate
on the impact of AI on the law and society, and to provide guidance on
the best practices and frameworks needed to ensure that the benefits of
AI are realized while minimizing the potential risks and challenges.
23 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
Methodology and Scope
This research paper uses a qualitative methodology, primarily
through a literature review of existing academic research, policy
documents, and legal cases related to the intersection of AI and
intellectual property rights. Additionally, the paper analyzes the current
legal and policy frameworks for IPRs in key jurisdictions, including the
United States, the European Union, and China.
The scope of the paper will focus on the impact of AI on four
main areas of intellectual property rights: patent law, copyright law,
trademark law, and data protection law. The paper will analyze the
challenges and opportunities presented by AI in each of these areas, and
will provide case studies and examples to illustrate the issues at hand.
The paper also examines the use of AI in the management of
intellectual property assets, including the role of AI in IP search and
analysis, licensing, and enforcement. The paper will analyze the ways in
which AI can improve the efficiency and effectiveness of IP management,
while also highlighting the potential ethical and legal concerns that arise
from the use of AI in these contexts.
Finally, the paper explores the legal and policy frameworks that
are needed to address the challenges and opportunities presented by AI
in the context of intellectual property rights. The paper will provide
recommendations for policymakers and legal professionals on how to
adapt current legal frameworks to ensure that they are responsive to the
changing technological landscape, while also protecting the rights of
intellectual property owners and promoting innovation and creativity.
Background on AI and IP
Artificial intelligence (AI) is a broad field of computer science that
encompasses creation of intelligent machines capable of accomplishing
tasks that typically require human intelligence. AI has the potential to
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 24
revolutionize many aspects of our lives, including the creation,
management, and exploitation of IP. Intellectual property refers to
creations of the mind, such as inventions, literary and artistic works,
symbols, names, images, and designs, which are protected by law.
3
AI has
the ability to generate new forms of IP assets, such as machine-generated
inventions, works of art, and music. AI can also assist in the management
of IP assets, including search and analysis, licensing, and enforcement.
However, employing AI in the generation and exploitation of IP also
raises a number of legal and ethical challenges, such as ownership,
patentability, copyright infringement, and data protection.
The intersection of AI and IP is a rapidly evolving field that
requires careful consideration and analysis. This research paper aims to
provide a comprehensive analysis of the impact of AI on intellectual
property rights, and to identify the challenges and opportunities presented
by this emerging technology. By doing so, the paper will provide insights
into the legal and policy frameworks that are needed to ensure that IP law
evolves to meet the needs of rapidly changing technological landscape.
AI and IP – Ownership Issues
AI is transforming the manner in which IP is created, managed,
and protected. One of the key issues arising from employing AI in the
creation of IP is ownership. In traditional IP regimes, ownership is
typically assigned to human creators or inventors. However, with the
increasing use of AI, the question of ownership becomes more complex.
AI can be used to create inventions that are novel and non-
obvious, but the question of ownership arises when it is unclear who
should be credited as the inventor. The current legal frameworks in most
jurisdictions do not address the issue of AI-generated inventions, leaving
uncertainty as to whether AI should be considered an inventor or whether
3
Girija, Aish, ‘What is AI (Artificial Intelligence)?’ (GeeksforGeeks. 4 March 2023)
<https://www.geeksforgeeks.org/what-is-aiartificial-intelligence/> accessed 4 May 2023.
25 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
ownership should be assigned to the person or organization that owns or
controls the AI system.
The European Patent Office (EPO) has taken the position that an
inventor must be a human being and therefore cannot be an AI system.
In the United States, the United States Patent and Trademark Office
(USPTO) has also stated that an inventor must be a human being, but has
not yet addressed the issue of AI-generated inventions
4
. However, some
legal scholars argue that the current legal frameworks are not equipped to
deal with the complexities of AI-generated inventions and that new legal
frameworks are needed.
Similar issues arise in the context of copyright law. AI can be used
to generate works of authorship, such as paintings, music, and literature.
However, under the copyright law, it is a pre-requisite that a work be
generated by a human author, for it to qualify for copyright protection.
The current legal frameworks do not address the issue of AI-generated
works of authorship, leaving uncertainty as to whether copyright should
be granted to the AI system or to the person or entity that controls or
oversees the system. Some legal scholars argue that the current legal
frameworks are not equipped to deal with the complexities of AI-
generated works of authorship and that new legal frameworks are needed.
The issue of ownership in the context of AI-generated IP is
complex and raises important legal and policy questions. The current legal
frameworks in most jurisdictions are not equipped to deal with the
complexities of AI-generated IP, leaving uncertainty as to who should be
credited as the creator or inventor. New legal frameworks are needed to
address these issues and to ensure that the benefits of AI are realized while
also protecting the rights of IP owners
5
.
4
Frąckiewicz, M, ‘The ethics of ai-generated content: Navigating the world of Deepfakes’ ( TS2
SPACE, 3 April 2023) <https://ts2.space/en/the-ethics-of-ai-generated-content-navigating-the-
world-of-deepfakes/> accessed 4 May 2023.
5
Ray, P. P., ‘ChatGPT: A comprehensive review on background, applications, key challenges, bias,
ethics, limitations and future scope.’ (2023) 3 ITCPS 121.
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 26
Legal and Ethical issues in Ownership of AI-Generated IP
The question of ownership of AI-generated IP raises a number of
legal and ethical issues. From a legal perspective, the lack of clarity in
current legal frameworks creates uncertainty as to who should be credited
as the creator or inventor. This uncertainty can give rise to conflicts and
legal proceedings, which consume time and cause significant expenses.
From an ethical perspective, the issue of ownership raises
questions about the role of AI in society and the extent to which AI
should be considered autonomous. The use of AI in the creation of IP
blurs the line between human and machine creativity, and raises questions
about the value of human creativity and the role of AI in society
6
.
There are also concerns about the impact of AI-generated IP on
innovation and competition. If ownership of AI-generated IP is
concentrated in the hands of a few large organizations, this could have a
chilling effect on innovation and competition, as smaller organizations
may be unable to compete or innovate in the same way. To address these
legal and ethical issues, new legal frameworks and policy solutions are
needed. One possible solution is to establish a new legal category for AI-
generated IP, which would clarify ownership and attribution. Another
possible solution is to require that AI systems be registered as inventors
or creators, which would ensure that ownership is assigned to the
appropriate parties. Another possible solution is to develop ethical
guidelines for the use of AI in the creation of IP, which would promote
transparency and accountability. These guidelines could address issues
such as bias, transparency, and accountability, and could help to ensure
that AI is used in a responsible and ethical manner.
The question of ownership of AI-generated IP is complex and
raises important legal and ethical issues. New legal frameworks and policy
solutions are needed to clarify ownership and attribution, and to ensure
that AI is used in a responsible and ethical manner. By addressing these
6
Ray (n 5).
27 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
issues, we can ensure that the benefits of AI are realized while
simultaneously safeguarding the rights of IP owners and promoting
innovation and creativity.
AI and IP Ownership – International Perspective
The issue of ownership of AI-generated IP is a complex issue that
requires a comparison of IP laws in place in different countries. While
there are some similarities between IP laws of different countries, there
are also significant differences that can affect the ownership and
attribution of AI-generated IP. For example, in the United States, patent
law requires that the inventor be a natural person. This means that AI
systems cannot be credited as inventors, and ownership of AI-generated
IP would likely fall to the individual or organization that developed the
AI system. In contrast, the European Patent Convention does not require
that the inventor be a natural person, which means that AI systems could
potentially be credited as inventors.
Similarly, copyright law varies significantly between countries, and
can have a significant impact on ownership of AI-generated IP. In the
United States, copyright law grants ownership to the person who creates
the work, which means that ownership of AI-generated works would
likely fall to the individual or organization that developed the AI system.
In contrast, in the European Union, copyright law grants ownership to
the person who creates the work, but also recognizes the concept of “moral
rights”, which gives the creator certain rights over the work, including the
right to be credited as the author.
These differences in international IP laws can have significant
implications for the ownership and attribution of AI-generated IP. As AI
becomes more prevalent in the creation of IP, it will be important to
harmonize IP laws of different countries to ensure that ownership and
attribution are clear and consistent across different countries.
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 28
Case Studies – Ownership Issues
Case studies can provide valuable insights into the legal and ethical
issues surrounding the ownership of AI-generated IP. The following are
some of the recent cases that highlight these issues:
• The DABUS case: In 2018, an AI system called DABUS (Device for
the Autonomous Bootstrapping of Unified Sentience) created two
inventions, a food container and a light beacon, that were submitted
for patent applications in the UK, the US, and Europe. The
applications were rejected on the grounds that an AI system cannot
be considered an inventor under current patent law. The case is
currently being appealed, and could have significant implications for
the ownership and attribution of AI-generated IP.
• The “Edmond de Belamy” artwork: In 2018, a French art collective called
Obvious used an AI system to create a portrait called “Edmond de
Belamy.” The artwork was sold at auction for over $400,000, raising
questions about the ownership and attribution of AI-generated art.
While the collective was credited as the creator, the role of the AI
system in the creation of the artwork is unclear.
• The OpenAI GPT-2 language model: In 2019, OpenAI released a language
model called GPT-2 that was capable of generating realistic text. The
release of the model raised concerns about the ownership and
attribution of the text generated by the AI system. OpenAI ultimately
decided not to publish the complete version of the model, citing issues
pertaining to the possible misuse of the technology.
These case studies highlight legal and ethical issues surrounding
the ownership and attribution of AI-generated IP. As AI becomes more
prevalent in the creation of IP, it will be important to address these issues
to ensure that the benefits of AI are realized while also protecting the
rights of IP owners and promoting innovation and creativity.
29 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
Patentability of AI Inventions
The rapid development and widespread adoption of artificial
intelligence (AI) technology is transforming many industries and creating
new opportunities for innovation. However, the issue of whether AI-
generated inventions can be patented is a complex and evolving area of
intellectual property (IP) law.
On the one hand, patent protection can encourage investment in
AI research and development by providing legal rights to exclude others
from using or commercializing the invention. On the other hand, there
are concerns that allowing AI-generated inventions to be patented could
result in the displacement of human inventors, limit access to important
technologies, and create new forms of inequality.
Legal and Ethical issues in AI-generated Inventions
The increasing use of AI in the development of new inventions
has led to a range of legal and ethical issues related to the ownership and
patentability of AI-generated inventions. In this section, we will examine
some of these issues in more detail.
• Ownership of AI-generated inventions: One of the key issues related to
AI-generated inventions is ownership. In some cases, the creator of
the AI system that generates the invention may argue that they should
own the resulting invention. However, in other cases, it may be argued
that the owner of the data used to train the AI system should own the
invention. This issue is further complicated by the fact that in some
cases, the AI system may generate an invention that is beyond the
capacity of any human to understand or replicate. In such cases, it may
be difficult to determine who should be considered the inventor.
• Patentability of AI-generated inventions: Another issue related to AI-
generated inventions is the question of patentability. Patent laws in
different countries vary in their treatment of AI-generated inventions.
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 30
Some countries, such as the United States, allow for the patenting of
AI-generated inventions as long as they meet the criteria for
patentability, such as being novel and non-obvious. However, in other
countries, such as Australia and New Zealand, the law currently
requires that an invention be the product of human inventiveness in
order to be patentable.
• Ethical considerations: Alongside these legal issues, there are also
a range of ethical considerations related to the ownership and
patentability of AI-generated inventions. One key concern is the
potential impact on employment, as AI-generated inventions may
displace human inventors and lead to a loss of jobs. Additionally, there
are concerns about the impact of AI-generated inventions on society,
such as the potential for bias or the creation of new technologies that
could be used for harmful purposes.
The legal and ethical issues related to AI-generated inventions are
complex and multifaceted. As AI technology continues to advance, it will
be important to develop legal and policy frameworks that can address
these issues in a way that promotes innovation and creativity while also
protecting the rights of inventors and ensuring that the advantages of AI
are distributed fairly across society.
Patenting AI Generated Inventions – International Perspectives
The question of whether AI-generated inventions can be patented
is a complex issue that is influenced by the different legal framework. In
this section, a comparison of patent laws of several countries is made to
explore different approaches to patentability of AI-generated inventions.
• United States: In the United States, the patentability of AI-
generated inventions is determined by the same criteria as any other
invention. According to the US Patent and Trademark Office
(USPTO), a patent may be granted for any new and useful process,
machine, manufacture, or composition of matter, or any new and
31 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
useful improvement thereof, that is non-obvious and adequately
described or enabled in the patent application. This means that AI-
generated inventions are generally considered patentable in the United
States, as long as they meet the criteria for patentability. However,
there are some concerns that allowing AI-generated inventions to be
patented may lead to the displacement of human inventors and create
new forms of inequality.
• European Union: In the European Union, the patentability of AI-
generated inventions is determined by the European Patent
Convention (EPC). Under the EPC, an invention may be patented if
it is new, involves an inventive step, and is capable of industrial
application. Currently, the EPC does not have specific provisions
regarding the patentability of AI-generated inventions. However, the
European Patent Office (EPO) has stated that AI-generated
inventions can be patented if they meet the criteria for patentability,
such as being new and non-obvious.
• Japan: In Japan, the patentability of AI-generated inventions is
determined by the Patent Act. According to the Patent Act, an
invention may be patented if it is new, involves an inventive step, and
is capable of industrial application. There is no specific provision
regarding the patentability of AI-generated inventions. However, the
Japan Patent Office (JPO) has stated that AI-generated inventions can
be patented if they meet the criteria for patentability.
• Australia and New Zealand: In Australia and New Zealand, the
patentability of AI-generated inventions is currently limited by the
requirement that an invention be the product of human inventiveness
in order to be patentable.
This means that AI-generated inventions may not be patentable
in these countries, unless they involve some degree of human
inventiveness. The patentability of AI-generated inventions varies
depending on the legal framework in different countries. While some
countries allow for the patenting of AI-generated inventions as long as
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 32
they meet the criteria for patentability, others require that an invention be
the product of human inventiveness in order to be patentable. As AI
technology continues to develop, it will be important to develop legal
frameworks that can address the patentability of AI-generated inventions
in a way that promotes innovation and creativity while also protecting the
rights of inventors and ensuring that the benefits of AI are distributed
fairly across society.
Case Studies – Patentability of AI Generated Inventions
To better understand the issues surrounding the patentability of
AI-generated inventions, let us examine a few case studies of recent patent
disputes involving AI.
• DABUS (Device for the Autonomous Bootstrapping of Unified Sentience):
DABUS is an AI system created by Dr. Stephen Thaler that is capable
of generating new inventions. In 2019, Dr. Thaler filed patent
applications in the United States, Europe, and other countries for two
inventions created by DABUS: a beverage container and a flashing
light. The patent applications were rejected on the grounds that an AI
system cannot be listed as an inventor on a patent application, as the
inventor must be a human being.
7
Dr. Thaler has challenged this
decision, arguing that DABUS is the true inventor of the inventions
and should be recognized as such. This case highlights the legal and
ethical issues surrounding the ownership of AI-generated inventions,
as well as the question of whether AI systems can be considered
inventors for the purposes of patent law.
• Qualcomm v. Apple
8
: In 2017, Qualcomm filed a lawsuit against Apple,
alleging that Apple had infringed on several of its patents related to
smartphone technology. One of the patents in question was an AI-
based power management system that was designed to improve the
7
In Thaler v. Vidal, No. 2021-2347 (Fed. Cir. 2022), the U.S. Court of Appeals for the Federal
Circuit ruled in a precedential opinion that artificial intelligence (AI) cannot be an inventor on a
U.S. patent.
8
Qualcomm Inc. v. Apple Inc., Case No.: 3:17-cv-2403-CAB-MDD (S.D. Cal. Aug. 29, 2018).
33 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
battery life of smartphones. Apple argued that the patent was invalid
because it was based on an AI-generated algorithm, and therefore did
not involve human inventiveness. However, the court ultimately ruled
in favor of Qualcomm, finding that the patent was valid and had been
infringed by Apple. This case illustrates the challenges of determining
the inventiveness of AI-generated inventions, as well as the potential
implications for patent disputes involving AI technology.
• Image Processing Technologies LLC v. Samsung Electronics Co.
9
: In 2016,
Samsung Electronics Co. was sued by Image Processing Technologies
LLC for infringing on a patent related to image processing technology.
Samsung argued that the patent was invalid because it was based on
an AI-generated algorithm, and therefore did not involve human
inventiveness. The court ultimately ruled in favour of Image
Processing Technologies LLC, finding that the patent was valid and
had been infringed by Samsung. This case highlights the importance
of ensuring that AI-generated inventions are protected by intellectual
property rights, even if they do not involve direct human input.
These case studies demonstrate the complex legal and ethical
issues surrounding the patentability of AI-generated inventions, and the
need for clear legal frameworks that can address these issues in a way that
promotes innovation and protects the rights of inventors.
Copyright Infringement and AI-Generated Content
As artificial intelligence (AI) continues to progress, it is becoming
increasingly capable of generating creative works such as music, literature,
and visual art. However, this development raises important questions
about the ownership and protection of such works under copyright law.
It is imperative to understand the issues surrounding copyright
infringement in relation to AI-generated content; examine the legal and
ethical implications of copyright ownership of AI-generated content,
9
Image Processing Techs. v. Samsung Elecs. Co., CIVIL ACTION NO. 2:20-CV-00050-JRG-RSP (E.D.
Tex. Jun. 18, 2020)
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 34
compare international copyright laws, and analyze relevant case studies to
provide a thorough comprehension of the current state of copyright
infringement in the realm of AI-generated content.
Scope of Copyright Protection
In light of AI-generated content, it is important to analyze the
scope of copyright protection, which determines the extent to which a
creator can claim ownership over their work. Generally, copyright law
protects original works of authorship fixed in a tangible medium of
expression, including literary, artistic, and musical works. However, the
question arises whether works generated by AI can be considered
“original” and eligible for copyright protection. One argument is that AI-
generated content lacks human element of creativity and therefore should
not be eligible for copyright protection. Others argue that creative input
of human programmers and developers in the creation and training of the
AI system should be sufficient to establish authorship and ownership.
In the United States, the Copyright Office has issued a statement
asserting that copyright protection extends to AI-generated works, as long
as they meet the requirements for originality and fixation in a tangible
medium. Similarly, the European Union Intellectual Property Office has
also stated that AI-generated works may be protected under copyright
law, provided that they are the result of a creative process. However, the
scope of protection for AI-generated content may differ from that of
traditional human-created works. For example, in the case of a work
created entirely by AI without any human input, the scope of protection
may be limited due to the absence of human creativity.
Furthermore, the ownership and rights to AI-generated works
may be governed by varying regulations depending on the country of
creation and the ownership of the AI system itself. The analysis of the
scope of copyright protection for AI-generated content requires careful
consideration of the balance between preserving creator’s rights and
35 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
maintaining the relevance and efficacy of copyright law in the face of
technological advancements.
Case studies – Copyright in AI Generated Content
There have been several notable cases that have addressed the
issue of copyright infringement in relation to AI-generated content. One
such case is the “Monkey Selfie” case, in which a photographer’s camera
was used by a macaque monkey to take a series of photographs of itself.
The photographer later claimed copyright ownership of the photographs,
but the court ultimately ruled that the photographs were not eligible for
copyright protection since they were not created by a human author.
In another case, a team of researchers in the United States created
a software program that could generate musical compositions. The team
sought to copyright the compositions, but the Copyright Office initially
rejected the application, stating that the works lacked the human element
of creativity. However, after the team provided evidence of their creative
input in the development of the software, the Copyright Office ultimately
granted copyright protection to the musical compositions.
In a more recent case, a group of artists used an AI system to
generate a series of portraits, which were then sold at auction for
significant sums of money. The question arose as to whether the artists or
the AI system could claim copyright ownership. Ultimately, the auction
house retained copyright ownership, as the terms of the sale agreement
stipulated that the artists relinquished their rights to the portraits.
These cases demonstrate the complexity and evolving nature of
copyright law in relation to AI-generated content. As AI technology
continues to advance, it will be important for courts and lawmakers to
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 36
carefully consider the legal and ethical implications of copyright
ownership and protection in this rapidly changing landscape.
10
Data Protection and Privacy in AI-Driven IP Asset Management
As the use of AI becomes increasingly prevalent in IP asset
management, concerns around data protection and privacy have also
grown. The collection, processing, and storage of large amounts of data
are essential to functioning of the AI systems, but this raises issues around
the use of personal and sensitive information. Additionally, the use of AI
in IP asset management could potentially create new types of IP assets
that require different levels of data protection.
Data Protection and Privacy concerns
The use of AI in IP asset management involves the collection,
processing, and storage of large amounts of data, including personal and
sensitive information. This raise concerns around data protection and
privacy, particularly in the context of increasingly stringent privacy laws
and regulations.
11
One of the main challenges in this area is ensuring that personal
and sensitive information is collected and used in a lawful and ethical
manner. AI systems must comply with applicable privacy laws and
regulations, which can be complex and vary from jurisdiction to
jurisdiction. For example, the General Data Protection Regulation
(GDPR) in the European Union imposes strict requirements for data
processing, including obtaining explicit consent from individuals,
providing individuals with the right to access and delete their data, and
implementing appropriate security measures to protect personal data.
10
Moiz Bukhari, S. A., ‘Exploring the world of artificial intelligence’ (Futurism, 1 January 2023)
<https://vocal.media/futurism/exploring-the-world-of-artificial-intelligence> accessed 1 May
2023.
11
Synodinou, T. E., Jougleux, P., Markou, C., & Prastitou-Merdi, T. (Eds.) ‘EU internet law in the
digital single market’ (2021) Springer Nature.
37 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
Another challenge is ensuring that AI systems are transparent and
accountable in their data processing activities. This encompasses
furnishing individuals with comprehensible and clear information
regarding the utilisation of the data and ensuring that the decisions made
by AI systems are explainable and can be audited. The lack of
transparency and accountability in AI systems’ decision-making processes
has been a source of concern in various domains, including finance,
healthcare, and criminal justice.
The use of AI in IP asset management could potentially create
new types of IP assets that require different levels of data protection. For
example, AI-generated works may contain sensitive information, such as
trade secrets or personal data, which may require additional measures to
ensure their protection. It also raises significant data protection and
privacy concerns, particularly in the context of increasingly stringent
privacy laws and regulations. It is essential to address these concerns
proactively to ensure that AI systems are put to use in a lawful and ethical
manner and that individuals’ privacy rights are respected.
Best practices for IP Asset Management using AI
To address the data protection and privacy concerns related to AI-
driven IP asset management, it is essential to adopt best practices that
promote transparency, accountability, and ethical use of data. Some of the
key best practices include:
• Privacy by design: Integrate privacy considerations into the initial stages
of designing and developing of AI systems. This includes minimizing
the collection and use of personal data, implementing data protection
measures, and providing clear and understandable information to
individuals about how their data is being used.
• Ethical guidelines: Develop and adhere to ethical guidelines for the
development and deployment of AI systems. These guidelines should
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 38
address issues such as bias, transparency, and accountability and
should be informed by the values and principles of the organization.
• Data ownership and consent: Clearly define data ownership and obtain
explicit consent from individuals before collecting and using their
data. This involves providing the right to access and erase their date
to the individuals and implementing suitable security measures to
safeguard personal data.
• Auditing and monitoring: Implement measures to audit and monitor AI
systems’ decision-making processes, including providing clear
explanations for decisions and enabling individuals to challenge or
appeal decisions that impact them.
• Training and awareness: Provide training and awareness programs for
employees and stakeholders involved in AI-driven IP asset
management to promote understanding of the legal and ethical issues
related to data protection and privacy.
By adopting these best practices, organizations can ensure that
their AI-driven IP asset management activities are carried out in a
transparent, accountable, and ethical manner, while also complying with
applicable data protection and privacy laws and regulations.
Case Studies – AI and IP Asset Management
Some case studies that illustrate the importance of data protection
and privacy in AI-driven IP asset management are:
• Facebook/Cambridge Analytica scandal: In 2018, it was revealed that
Cambridge Analytica had acquired and misused the personal
information of millions of Facebook users without obtaining their
consent. This scandal highlighted the need for better data protection
and privacy measures in the use of AI-driven algorithms for targeted
advertising and political campaigning.
39 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
• Google Street View privacy breach: In 2010, it was discovered that Google’s
Street View cars had collected data from unsecured Wi-Fi networks
as they captured images for the mapping service. This incident led to
fines and legal action against Google in several countries, emphasizing
the importance of obtaining explicit consent and implementing
appropriate data protection measures.
• Healthcare data breaches: Healthcare organizations are increasingly using
AI-driven tools to manage and analyze patient data. However, data
breaches in this area can have severe consequences for patient privacy
and data protection. For example, in 2020, a data breach at a US
healthcare provider led to the exposure of sensitive patient
information, including diagnoses and treatments.
These case studies illustrate the importance of implementing
robust data protection and privacy measures in AI-driven IP asset
management. By doing so, organizations can build trust with customers,
avoid legal and financial penalties, and ensure the ethical use of data.
AI-Assisted IP Asset Search and Analysis
AI-assisted IP asset search and analysis is a rapidly evolving field
that leverages the power of artificial intelligence to help organizations
manage and protect their intellectual property (IP) assets. The use of AI
in IP asset search and analysis can help organizations to identify potential
infringement, monitor competitors, and make informed decisions about
their IP strategy. AI can also help to streamline the IP search and analysis
process, reducing costs and improving efficiency.
Tools and Techniques
There are several tools and techniques that organizations can use
to conduct IP asset search and analysis using AI. These include:
• Natural Language Processing (NLP): NLP is a branch of AI that centres
on the interplay between computers and human language. It can be
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 40
used to analyze large volumes of text-based data, such as patent
documents, to identify key concepts and trends.
• Machine Learning (ML): ML is a type of AI that allows computers to
learn from data without being explicitly programmed. It can be used
to train algorithms to recognize patterns in IP data, such as trademark
applications or patent filings.
• Image Recognition: Image recognition is a type of AI that allows
computers to analyze and classify visual data, such as product designs
or logos. It can be used to identify potential infringement of
trademarks or design patents.
• Network Analysis: Network analysis uses AI algorithms to analyze the
relationships between different IP assets, such as patents, trademarks,
and copyrights. It can be used to identify patterns and trends in IP
portfolios, as well as potential infringement or licensing opportunities.
By using these tools and techniques, organizations can gain
valuable insights into their IP portfolios and make informed decisions
about their IP strategy. However, it is important to note that these tools
and techniques are not fool proof, and human oversight is still necessary
to ensure the accuracy and reliability of the results.
Case Studies – AI-Assisted IP Asset Search and Analysis
• IBM Watson for Patent Search: IBM Watson is an AI platform that
provides natural language processing and machine learning
capabilities. In 2016, the USPTO partnered with IBM to use Watson
for patent search and analysis. By using Watson, the USPTO was able
to reduce the time and cost required to search and analyze patent
applications, while also improving the accuracy of the search results.
• Trademark Now: Trademark Now is a trademark search and analysis
platform that uses AI to analyze trademark applications and identify
potential conflicts. By using machine learning algorithms to analyze
41 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
trademark data, Trademark Now is able to provide faster and more
accurate trademark search results than traditional search methods.
• Alibaba’s Patent Translation System: Alibaba, the Chinese e-commerce
giant, developed an AI-based patent translation system that is able to
translate patents from Chinese to English with a high degree of
accuracy. This system has enabled Alibaba to better understand the
patent landscape in foreign markets and make informed decisions
about its IP strategy.
• IPwe: IPwe is an AI-driven platform for IP asset management
that uses machine learning to analyze patent data and identify
potential licensing opportunities. By using IPwe, companies can gain
insights into the value of their patent portfolios and identify potential
licensing partners.
These case studies illustrate the diverse range of applications for
AI in IP asset search and analysis. By leveraging the power of AI,
organizations can gain valuable insights into their IP portfolios and make
more informed decisions about their IP strategy. However, it is important
to recognize that AI is not a silver bullet, and human expertise and
oversight are still essential to ensure accuracy and reliability of the results.
Monetizing IP Assets through AI-Based Systems
The monetization of IP assets is a critical component of the
revenue streams of many businesses. However, traditional models for
monetizing IP assets, such as licensing and litigation, are often time-
consuming and expensive. In recent years, advances in AI have created
new opportunities for businesses to effectively monetize their IP assets
through AI-based systems.
AI based Business Models for IP exploitation
AI is enabling new business models for monetizing IP assets that
were previously unattainable. One such model involves the use of AI-
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 42
based systems to identify potential licensees and negotiate licensing
agreements. This approach allows businesses to maximize the value of
their IP assets by quickly identifying potential licensees and negotiating
favourable licensing terms. Another emerging model is the use of AI-
based systems to identify infringement of IP assets and initiate litigation
or settlement negotiations.
Furthermore, AI is enabling the creation of new revenue streams
from IP assets through the development of new products and services.
For example, businesses can use AI-based systems to analyze market
trends and identify unmet consumer needs. This information can then be
utilised to create new products and services that capitalize on the market
demand, creating new sources of revenue for the business.
AI is also facilitating the creation of new business models for IP
monetization through the development of platforms that enable
businesses to license their IP assets directly to consumers. These
platforms use AI to match consumers with relevant IP assets and provide
licensing terms that are customized to their specific needs.
While these new business models present exciting opportunities
for businesses to monetize their IP assets, they also raise important legal
and ethical questions. For example, who owns the IP rights to AI-
generated works, and how can they be licensed? What are the privacy
implications of using AI to analyze consumer data for IP asset
monetization? These are complex issues that require careful consideration
to ensure that AI-based systems are being used ethically and in compliance
with relevant laws and regulations.
Case Studies – AI and IP Exploitation
• IBM Watson and IP Monetization: IBM Watson, the AI-based system
developed by IBM, has been used to identify potential licensees for a
variety of IP assets, including patents, trademarks, and copyrights. By
using Watson to analyze data on potential licensees, IBM has been
43 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
able to identify new revenue streams for its IP assets and negotiate
favourable licensing terms.
• Tencent and IP Asset Management: Tencent, the Chinese tech giant, has
developed an AI-based system for managing its extensive IP portfolio.
It uses machine learning algorithms to identify potential infringers of
Tencent’s IP assets and initiate legal action against them. It also uses
natural language processing techniques to analyze user-generated
content for potential IP violations, such as copyright infringement.
• Alibaba’s IP Platform: Alibaba, the Chinese e-commerce giant, has
developed an IP platform that uses AI to match businesses with
relevant IP assets for licensing. The platform uses machine learning
algorithms to analyze user data and identify potential licensees, as well
as to suggest licensing terms that are customized to specific needs.
• Artificial Intelligence and Copyright Ownership: The use of AI in generating
creative works, such as music or artwork, raises questions about
copyright ownership. In the case of a painting created by an AI
system, for example, who owns the copyright? This issue was explored
in a legal case in France in 2019, where a group of artists sued the
auction house Christie’s over the sale of an AI-generated artwork. The
case highlighted the need for clear legal frameworks for AI-generated
works and their ownership.
Improved IP Enforcement through AI
As the world becomes increasingly digitized, intellectual property
(IP) theft has become a major challenge for businesses across all
industries. The rise of artificial intelligence (AI) offers new opportunities
for businesses to detect and prevent IP theft, as well as to enforce their
IP rights more effectively.
This section of the research paper will explore the ways in which
AI can be used to improve IP enforcement. It will examine the use of AI
in detecting and preventing IP theft, as well as in monitoring and
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 44
enforcing IP rights. Additionally, it will highlight the legal and ethical
issues that arise from the use of AI in IP enforcement, including concerns
about privacy and data protection. Finally, it will examine case studies that
demonstrate the successful use of AI in IP enforcement, as well as the
challenges that businesses have faced in implementing these technologies.
AI for IP Enforcement – Opportunities and Challenges
The use of AI in IP enforcement offers several opportunities and
challenges for businesses. One of the main advantages of AI is its ability
to analyze large amounts of data quickly and accurately, which can help
businesses identify potential infringements of their IP rights more
efficiently. AI can also help businesses monitor the use of their IP assets
more effectively, making it easier to detect and prevent IP theft.
However, the use of AI in IP enforcement also poses several
challenges. One of the main concerns is privacy and data protection. In
order to use AI effectively for IP enforcement, businesses must collect
and analyze large amounts of data, which can include sensitive
information about individuals and companies. This raises concerns about
the collection, storage, and use of this data, as well as the potential for
data breaches and cyberattacks. Another challenge is the legal and ethical
implications of using AI for IP enforcement. Businesses must ensure that
their use of AI adheres to relevant laws and regulations, including data
protection laws and laws governing IP rights. They must also consider the
potential ethical implications of using AI to enforce IP rights, particularly
in cases where the use of AI may result in the infringement of individual
rights and freedoms.
The use of AI in IP enforcement offers both opportunities and
challenges for businesses. To use these technologies effectively,
businesses must carefully consider the legal and ethical implications of
their use and take steps to address any potential risks and challenges.
45 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
Case Studies – AI and IP Enforcement
• Alibaba’s IP protection system: In 2018, Alibaba, the Chinese e-commerce
giant, launched its AI-powered IP protection system called “Alibaba
Intellectual Property Protection Platform.” The system uses machine
learning algorithms to analyze large volumes of data to identify and
remove counterfeit goods from its platforms. The system has
reportedly helped Alibaba to reduce the number of fake products on
its platform by 30% and has increased the speed of IP protection
requests by 50%.
• IBM’s patent analysis tool: IBM has developed an AI-powered patent
analysis tool called “Watson for IP” that helps businesses analyze
patent data and identify potential IP infringements. The tool uses
natural language processing and machine learning algorithms to
analyze patent documents, scientific papers, and other sources of
information to identify potential infringements of IP rights.
• Qualcomm’s patent infringement detection system: Qualcomm, a leading
technology company, has developed an AI-powered patent
infringement detection system that can analyze large amounts of data
to identify potential infringements of its patents. The system uses
machine learning algorithms to analyze patent documents, legal
filings, and other sources of information to identify potential
infringement cases. The system has reportedly helped Qualcomm to
improve the speed and accuracy of its IP enforcement efforts.
These case studies demonstrate the potential benefits of using AI
in IP enforcement, including improved efficiency, accuracy, and speed in
identifying and preventing IP infringements. However, they also highlight
the need for careful consideration of the legal and ethical implications of
using AI in this context.
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 46
Impact of AI on Traditional IP Practices and Jurisprudence
The emergence of AI has significantly impacted various fields,
including IP. AI has revolutionized the way IP assets are created,
managed, and enforced, leading to new opportunities and challenges. This
section of the research paper aims to examine the impact of AI on
traditional IP practices and jurisprudence.
The traditional IP practices and jurisprudence have been shaped
by human interpretation and application of laws and regulations.
However, with the increasing use of AI in IP, there is a need to re-evaluate
these traditional practices and jurisprudence to ensure that they remain
relevant and effective. This section will discuss the impact of AI on
various aspects of IP, including patent, copyright, and trademark law, and
how it has influenced the interpretation and application of these laws.
AI has transformed traditional IP practices in several ways. For
instance, AI-powered tools and software have made it easier to create and
manage IP assets, including patents, trademarks, and copyrights. These
tools can perform tasks such as prior art searches, patent drafting, and
trademark monitoring more efficiently and accurately than humans. As a
result, the time and cost involved in creating and managing IP assets have
reduced significantly.
Moreover, AI has also impacted the interpretation and application
of IP laws. With the increasing use of AI in creating and managing IP
assets, there is a need to re-evaluate how IP laws are interpreted and
applied. For instance, the issue of patentability of AI-generated inventions
has raised several legal and ethical questions that traditional IP laws may
not address adequately. Similarly, the use of AI-generated content has
challenged the scope of copyright protection and the rights of creators
and users of such content.
The impact of AI on traditional IP practices is profound and far-
reaching. As AI continues to advance, it is likely to transform the way IP
47 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
assets are created, managed, and enforced, requiring a re-evaluation of
traditional IP practices and jurisprudence.
Case Studies – AI and Impact on IP
• Use of AI in patent drafting and prosecution: The law firm, BakerHostetler,
implemented an AI-powered tool called ROSS Intelligence to assist
lawyers in patent drafting and prosecution. The tool uses natural
language processing to analyze patent applications, provide insights,
and suggest possible amendments. The tool helped the firm to reduce
the time and cost involved in patent drafting and prosecution, while
also improving the quality of the patents.
• Impact of AI on copyright law: The use of AI in creating and generating
content has challenged the scope of copyright protection and the
rights of creators and users of such content. For instance, in the case
of Naruto v. Slater, an animal rights group sued a photographer over
a selfie taken by a monkey using the photographer’s camera. The
group argued that the monkey owned the copyright in the photo,
while the photographer argued that he owned the copyright since he
owned the camera. The case highlighted the need to re-evaluate how
copyright laws apply to AI-generated content.
• Role of AI in IP asset management: The IP management company, CPA
Global, implemented an AI-based system called Innography to help
clients manage their IP portfolios. The system uses AI to perform
tasks such as prior art searches, patent landscape analysis, and
competitive intelligence. The system helped clients to reduce the time
and cost involved in IP asset management while also improving the
accuracy and efficiency of the process.
Policy and Legal Frameworks for AI and IP
The increasing use of AI in IP presents new challenges for
policymakers and legal practitioners. As AI technology continues to
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 48
evolve and impact IP rights, it is necessary to ensure that the legal and
policy frameworks are adapted to accommodate these changes. This
section explores the key policy and legal issues related to AI and IP,
including the need for updated laws and regulations, ethical
considerations, and the role of international organizations in shaping the
future of AI and IP. It also examines some case studies of policy and legal
frameworks that have been implemented in different jurisdictions to
address the challenges posed by AI and IP.
Comparative Analysis
One important aspect of understanding the policy and legal
frameworks for AI and IP is to compare the approaches taken by different
jurisdictions. A comparative analysis can provide insights into the
strengths and weaknesses of different approaches, and help identify areas
where improvements can be made. For example, the European Union
(EU) has taken a proactive approach to regulating AI and IP, with the
European Commission releasing a White Paper on AI in 2020. The paper
sets out a framework for developing an ecosystem of trust in AI, which
includes a proposal for a regulatory framework to govern the
development and use of AI.
In contrast, the United States has taken a more hands-off
approach, with the focus on encouraging innovation and reducing barriers
to the development and use of AI. The U.S. Patent and Trademark Office
(USPTO) has issued guidelines for examining AI-related patent
applications, but there are no specific regulations governing the use of AI
in IP. Other jurisdictions have also taken different approaches. For
example, China has released guidelines on the development of AI, which
includes provisions on IP protection, while Japan has established a task
force to examine the legal and policy issues related to AI and IP.
A comparative analysis of policy and legal frameworks can help
identify best practices and areas for improvement in addressing the
challenges and opportunities presented by AI and IP.
49 Osmania University Journal of IPR [OUJIPR] Vol.1 | Issue 1
In light of the rapid advancements in AI and its impact on the IP
landscape, policymakers and IP professionals need to collaborate to
establish an appropriate legal and policy framework.
Conclusion
The development of AI technologies is revolutionizing the way IP
assets are created, managed, and enforced. However, it also raises
numerous legal and ethical issues related to ownership, patentability,
copyright infringement, data protection, and privacy. The case studies
have provided insight into the practical implications of the legal and
ethical issues. Additionally, there is an imminent need for policymakers
and IP professionals to develop comprehensive policy and legal
frameworks to ensure that AI technologies are used in a responsible and
ethical manner.
AI has the potential to transform the IP landscape in various ways,
providing new opportunities for IP owners and users, while also
presenting significant challenges. The best practices and innovative
approaches to managing IP assets using AI-based systems, could help IP
owners gain a competitive advantage in the marketplace. Further
exploration of the ethical and legal issues related to ownership of AI-
generated IP, particularly in the context of international IP laws and case
studies is required. As AI continues to advance and transform the IP
landscape, ongoing research will be crucial in ensuring that IP laws and
practices are up to date and able to effectively address the challenges and
opportunities presented by this emerging technology.
July-2023 Impact of Artificial Intelligence on Intellectual Property Rights: Challenges and Opportunities 50
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