IMPACT OF ARTIFICIAL INTELLIGENCE ON INTELLECTUAL PROPERTY BY: - P. KOUSHIKA
IMPACT OF ARTIFICIAL INTELLIGENCE
ON INTELLECTUAL PROPERTY
AUTHORED BY: - P. KOUSHIKA
B.A., B.L., LLM (Intellectual
Property Law)
ABSTRACT
Artificial intelligence (AI) is
altering the Intellectual Property (IP) landscape, creating both obstacles and
possibilities for organizations and innovators. AI's ability to develop,
manage, and exploit intellectual property raises complicated legal and ethical
concerns around ownership, patentability, copyright infringement and data
protection. One of the most significant legal difficulties offered by
artificial intelligence to intellectual property is the issue of ownership and
authorship of AI-generated works. AI can
be used to generate original work with a high level of originality, but the
question remains: 'Who owns that work?' the person who directs the AI system to
create the work (User) or the AI system's creator or the AI system itself. Some
responses to these issues are based on interpretations of current laws. Legal
proceedings are currently underway to address additional issues. Some legal
scholars argue that current intellectual property laws established for human
creativity are outdated and need to be reformed. According to traditional
intellectual property law, the creator or author of the work is regarded the
only owner of the work, but this is not in the case of AI-generated art. Current
IPR laws offer rights to entities with legal personhood (whether natural or
corporate); as a result, in most jurisdictions, an AI system is currently
barred from receiving such protection. However, because AI technology is still
in its early stages and definitions of AI and "autonomy" is ambiguous,
legislation on this issue appears to be problematic. This complicates
determining the standards connected with IPR regulations, such as the duration
of protection, identifying the beneficiary for licensing remuneration,
distinguishing between human and AI innovations, and so on. While there are
numerous problems, one justification for treating computers as
inventors/authors and providing them with intellectual property protection is
the 'incentive theory'. While this may not be a motivator for computers, it
will continue to encourage humans to develop such technology since they
recognize the benefits of IPR protection. In 2019, the World Intellectual
Property Organization (WIPO) published a study on trends in patent applications
and grants, stating that there has been an increase in AI-related applications
in the domains of telecommunications, transportation, and life and medical
sciences. This paper aims to discuss about the protection of Intellectual
property in this digital era and to bring changes in the law to cope up with
Artificial intelligence.
INTRODUCTION
AI is revolutionizing the creation,
management, and protection of intellectual property. The technology revolution
presents new difficulties and opportunities for innovators, businesses, and
legislators. AI is creating new IP assets, boosting asset management efficiency
and opening up new economic models for exploitation. AI presents complicated
legal and ethical challenges, including ownership, patentability, copyright
infringement and data protection.
This research paper examines AI's
impact on intellectual property rights, including difficulties and prospects.
The study examines the legal and ethical consequences of AI for IP 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.
BACKGROUND ON AI AND IP
Artificial intelligence (AI) is a
vast subject of computer science that involves creating intelligent machines
capable of performing activities that would normally need human intelligence.
AI has the potential to revolutionize various parts of our lives, including the
development, management and exploitation of intellectual property. Intellectual
property includes innovations, literary and artistic works, symbols, names,
images and designs, all of which are legally protected.
AI can create new intellectual
property assets, including innovations, artwork, and music. AI can help manage
intellectual property assets, including searching, analyzing, licensing, and
enforcement. AI has the capacity to produce new types of intellectual property,
including music, art, and inventions produced by machines. AI is also useful
for managing intellectual property assets, helping with licensing, enforcement,
and search and analysis. However, using AI to generate and exploit intellectual
property also brings up a variety of ethical and legal issues, including data
protection, ownership, patentability, and copyright infringement.
The area where AI and IP converge is
quickly developing and needs careful thought and study. The area where AI and
IP converge is quickly developing and needs careful thought and study. The
purpose of this research paper is to give a thorough examination of the
implications of artificial intelligence (AI) on intellectual property rights,
as well as to point out the potential and problems that this new technology
presents. In doing so, the paper will offer insights into the policy and legal
frameworks required to guarantee that intellectual property law adapts to the
demands of the quickly advancing technology landscape.
OWNERSHIP CONCERNS WITH AI AND IP
AI is revolutionizing the creation,
management and protection of intellectual property. Ownership is one of the
main problems that come up when AI is used to create intellectual property.
Ownership under conventional intellectual property regimes is usually
attributed to human creators or inventors. But when AI is used more frequently,
the ownership issue gets trickier to answer. Artificial intelligence (AI) has
the potential to produce original, non-obvious inventions, yet ownership
disputes might occur when it's not evident who should receive credit for the
idea. Most jurisdictions' current legal frameworks do not address the issue of
AI-generated inventions, therefore it is unclear whether AI should be regarded
as an inventor or whether ownership should go to the entity that owns or
manages the AI system.
The European Patent Office (EPO) has adopted the stance that an AI system cannot be an
inventor since an inventor must be a human.
The United States Patent and Trademark Office (USPTO) have declared that an inventor must
be a person in the US, but it hasn't yet addressed the problem of inventions
produced by AI4. Nonetheless, some legal experts contend that new legal
frameworks are required since the existing ones are ill-suited to handle the
complexity of inventions produced by artificial intelligence.
Similar problems occur in relation to
copyright legislation. AI has the ability to produce literary, musical and
artistic works of authorship. However, in order for a work to be eligible for
copyright protection under the law, it must be created by a human author. The
question of authorship for AI-generated works remains unresolved in the present
legal frameworks, raising questions about whether copyright should be awarded
to the AI system itself or to the organization or individual in charge of
it. Frameworks are necessary since the
existing ones are ill-suited to handle the complexity of AI-generated works of
authorship.
AI AND IP OWNERSHIP: AN
INTERNATIONAL PERSPECTIVE
The ownership of AI-generated
intellectual property is a difficult subject that necessitates a comparison of
IP rules across countries. Different nations' IP laws share similarities, but
also have substantial variances that impact ownership and attribution of
AI-generated IP. In the US, patent law requires inventors to be natural
persons. AI systems cannot be acknowledged as inventors. Ownership of
AI-generated IP is likely to fall to the man or group that built the system.
The European Patent Convention
considers AI systems are also inventors it does not require the inventors are
only natural persons. Copyright laws vary among countries, affecting ownership
of AI-generated IP. Copyright law in the United States typically provides
rights to the creator of a work. Therefore, ownership of AI-generated works is
likely to be held by the individual or group that built the system. In the European Union, copyright law provides
creators ownership of their work and acknowledges "MORAL RIGHTS" which include the ability 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.
RELEVANT CASE STUDIES:
1. DABUS case:
In 2018, the AI system DABUS
(Device for the Autonomous Bootstrapping of Unified Sentience) developed two
inventions, a food container and a light beacon, which were patented in the UK,
US, and Europe. The applications were rejected because AI systems cannot be
deemed inventors under current patent legislation. The ruling is being appealed
and might impact the ownership and attribution of AI-generated intellectual
property.
2. EDMOND DE BELAMY
In 2018, the French art collective
"Obvious" created a portrait titled "Edmond de Belamy"
using artificial intelligence. The artwork sold at auction for nearly $400,000,
raising concerns regarding ownership and attribution of AI-generated art.
Although the group was recognized as the creator, the involvement of the AI system in creating the artwork remains unclear.
Although the group was recognized as the creator, the involvement of the AI system in creating the artwork remains unclear.
LEGAL ISSUES OF PATENTING AI
GENERATED INVENTIONS
1.
Ownership
Why Proper ownership of AI-generated inventions is crucial?
The designer of an AI system may that
humans cannot understand or imitate, complicating the situation further.
Identifying the inventor can be challenging in such instances.
2.
Patentability
Is it possible to patent AI-generated
inventions?
Patent laws varied among countries
regarding AI-generated inventions. In some Countries, like as the US,
AI-generated ideas can be patented if they meet certain conditions, including
novelty and non-obviousness. In several nations, including Australia and New
Zealand, inventions must be the result of human inventiveness to be patentable.
INTERNATIONAL PERSPECTIVE OF
PATENTING AI
GENERATED INVENTIONS
In the United States, AI-generated inventions are subject to the same patentability standards
as other inventions. The US Patent and Trademark Office (USPTO) grants patents
for non-obvious and adequately described inventions, including processes,
machines, manufactures, and compositions. AI-generated inventions can be
patented in the US if they meet specific criteria. Allowing AI-generated
innovations to be patented raises concerns about displacing human innovators
and creating new forms of inequity.
In the European Union, the European Patent Convention (EPC) governs the patentability of
AI-generated innovations. The EPC allows patents for inventions that are new,
entail an innovative step, and have industrial applications. Currently, the EPC
does not address the patentability of AI-generated inventions. The European
Patent Office (EPO) allows AI-generated innovations to be patented if they meet
patentability standards, including novelty and non-obviousness.
In Japan, the
Patent Act governs the patentability of artificial intelligence-generated
innovations. The Patent Act allows for the patenting of inventions that are
new, entail an innovative step, and have potential for industrial application.
There is no explicit provision for patenting AI-generated inventions. The Japan
Patent Office (JPO) recognizes AI-generated innovations as patentable if they
meet specific criteria.
In Australia and New Zealand, AI-generated ideas are not yet patentable due to the
requirement for human inventiveness.AI-generated ideas may not be patentable in
certain nations without some human involvement. AI-generated inventions may not
be patentable in many countries due to legal differences.
As AI technology advances, it's
crucial to create legal frameworks that promote innovation, protect inventors'
rights, and ensure equitable distribution of benefits across society.
CASE LAWS
1. Image Processing Technologies LLC v. Samsung Electronics Co:
In 2016, Image Processing
Technologies LLC sued Samsung Electronics Co. for infringing on an image
processing patent. Samsung argued that the patent was invalid since it was
based on an AI-generated algorithm and did not require human invention. The
court concluded that Image Processing Technologies LLC's patent was legitimate
and Samsung had violated it. This case emphasizes the need to secure
intellectual property rights for AI-generated inventions, regardless of human
involvement.
2. Qualcomm v Apple8:
In 2017, Qualcomm sued Apple for
allegedly infringing on its patents relating to smart phone technology. One of
the patents under discussion was for an AI-based power management system to
improve smart phone battery life. Apple argued that the patent was invalid
since it was based on an AI system and did not require human ingenuity. The
court ruled that Qualcomm's patent was valid and Apple had infringed it. This
case highlights the problems of establishing the creativity of AI-generated
innovations and the ramifications for patent disputes employing this
technology.
COPYRIGHT INFRINGEMENT AND
AI-GENERATED CONTENT
AI is becoming more capable of
producing creative creations, including music, literature and visual art. This
development raises concerns regarding the ownership and protection of such
works under copyright law, to understand the current state of copyright
infringement in AI-generated content, it's important to examine the legal and
ethical implications, compare international copyright laws and analyze relevant
case studies.
CASE STUDIES
1.
KADREY VS META PLATFORMS
In Nov 2023, in order to dismiss
Kadrey case which is filed in U.S. District Court for Northern
District of California, plaintiffs are informed of the pleading standards that
they must meet when claiming an AI model's outputs infringed on an author's
copyright.
In July 2023, Richard Kadrey, Sarah Silverman and Christopher Golden filed a class action against Meta on behalf of other authors. They claimed that Meta's large language model, LLaMA was trained on a corpus of components that included their copyrighted books. Meta filed a motion to dismiss, claiming that the plaintiffs' claim of infringement is based on the extraction of information from the books during the training process, not that the AI-generated output is substantially similar to their copyrighted books or that portions of the copyrighted passages exist in the LLaMA codebase. Meta maintained that this was inadequate to make a copyright infringement allegation. Meta did not dismiss Kadrey's claim of copyright infringement connected to the inputs, including the use of copyrighted content as training data. The court agreed with Meta. The court dismissed the plaintiffs' copyright infringement claim against LLaMA's outputs, stating that the plaintiffs would need to prove that the outputs were either actual copies of their protected works or substantially similar to the books, making them derivative works. The plaintiffs' claims were dismissed without prejudice after the court concluded that they did not meet the pleading requirements.
In July 2023, Richard Kadrey, Sarah Silverman and Christopher Golden filed a class action against Meta on behalf of other authors. They claimed that Meta's large language model, LLaMA was trained on a corpus of components that included their copyrighted books. Meta filed a motion to dismiss, claiming that the plaintiffs' claim of infringement is based on the extraction of information from the books during the training process, not that the AI-generated output is substantially similar to their copyrighted books or that portions of the copyrighted passages exist in the LLaMA codebase. Meta maintained that this was inadequate to make a copyright infringement allegation. Meta did not dismiss Kadrey's claim of copyright infringement connected to the inputs, including the use of copyrighted content as training data. The court agreed with Meta. The court dismissed the plaintiffs' copyright infringement claim against LLaMA's outputs, stating that the plaintiffs would need to prove that the outputs were either actual copies of their protected works or substantially similar to the books, making them derivative works. The plaintiffs' claims were dismissed without prejudice after the court concluded that they did not meet the pleading requirements.
2.
PERRY V. SHEIN
AI litigation has made its way into
the fashion business. AI can help companies keep ahead of trends and generate
popular fashions, especially with the rise of TikTok and Instagram influencers
and low-cost dupes. However, firms should be cautious when adding AI into the
design process. This case was filed in July 2023 in the U.S. District Court for
the Central District of California, includes a civil Racketeer Influenced and
Corrupt Organizations Act claim. A group of individuals and small businesses
allege that Shein's network of related entities uses an algorithm to copy
commercially valuable designs. Shein's algorithm allegedly violated the
plaintiffs' intellectual property rights by making identical replicas of their
works. In December 2023, Shein filed a motion to dismiss both the RICO and
copyright infringement accusations. Shein has not moved to dismiss the majority
of the infringement-related claims. The court's handling of infringement
allegations based on algorithms and RICO claims related to suspected organized
infringing conduct is uncertain. This litigation could create a precedent for
what constitutes infringement in AI and who is ultimately liable, making it
vital for fashion companies to monitor.
This case may impact future IP infringement claims and defenses.
Several significant lawsuits have
addressed copyright infringement in AI-generated content. In the "Monkey Selfie" case, a macaque
monkey utilized a photographer's camera to take self-portraits, then the
photographer claimed copyright ownership of the images, but the court determined
that they did not qualify for copyright protection as they were not made by an
author.
A team of researchers in the US
developed software that generates musical compositions. The team applied to
copyright the compositions, but the Copyright Office rejected the application
due to a lack of innovation. The Copyright Office recognized the team's
innovative contribution to software development and granted copyright
protection to the musical work.
These instances show how AI-generated
content affects copyright law, which is always growing. As AI technology
advances, courts and politicians should carefully analyze the legal and ethical
consequences of copyright ownership and protection in a quickly changing
context.
AI AND TRADITIONAL KNOWLEDGE
Traditional knowledge refers to
skills, know-how, or practices that have been learned or followed over time.
Knowledge is passed down from generation to generation within a community14. AI
may impinge on traditional knowledge by abstracting existing information.
Given the aforementioned discussion,
it is possible that Artificial Intelligence machines or programs may encroach
on traditional knowledge, which is a valuable element of many societies'
heritage.
LIABILITY FOR INFRINGEMENT
The issue of who is responsible for
violating Intellectual Property Rights by AI machines is a hotly discussed
topic. Determine Who is responsible? the programmer, the machine or others.
There is some uncertainty about this feature.
If the programmer was aware of the
machine's potential to breach Intellectual Property Rights while building it,
they will be held liable.
If an AI system or software infringes
intellectual property rights without the programmer's knowledge or intention, it
might be difficult to determine who is responsible for the violation.
The responsibility of Artificial
Intelligence machines or programs remains vague and requires more
clarification. If the infringement results in criminal accountability, how will
the AI bear individual responsibility? As we have seen above, the question of
liability is a critical matter and must be addressed otherwise; it would result
in numerous arguments and confusions.
MONETIZING IP ASSETS USING AI-BASED
SYSTEMS
Monetizing intellectual property
assets is crucial to many businesses' revenue streams. Traditional IP
monetization methods, such licensing and litigation, can be time-consuming and
costly. AI-based technologies provide firms new ways to monetise their
intellectual property.
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 favorable 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 utilized 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.
New business models offer opportunity
for organizations to monetize their IP assets, but also bring legal and ethical
concerns. For instance, who owns the intellectual property rights to
AI-generated works and how are they licensed? What are the privacy consequences
of analyzing consumer data with AI for monetizing intellectual property assets?
To ensure ethical and legal usage of AI-based systems, complex concerns must be
carefully considered.
CASE STUDIES
1.
Tencent, the
Chinese digital behemoth, has built an AI-based system to manage its vast IP
portfolio. Tencent employs machine learning algorithms to detect and take legal
action against possible infringers of its intellectual property. Natural
language processing is used to assess user-generated content for suspected
intellectual property infractions, including copyright infringement.
3.
Alibaba's IP
Platform: The Chinese e-commerce giant's AI-powered platform connects
businesses with suitable IP assets for licensing. The platform use machine
learning algorithms to evaluate user data, identify possible licensees, and
provide tailored licensing terms.
WORLD INTELLECTUAL PROPERTY
ORGANIZATION (WIPO)
In September 2019, WIPO hosted a
conference to address the influence of AI on various nations' IP policies, as
well as the pertinent questions, in order to lay the groundwork for member
states to make better informed policy decisions. Following the conference, WIPO
issued a Draft Discussion Paper on IP and AI in December 2019 (WIPO Discussion
Paper), requesting member states and other interested parties to submit
feedback and proposals. The WIPO Discussion Paper highlights thirteen concerns
concerning AI and intellectual property policy:
Issue 1
concerns ownership and inventorship. It addresses questions such as whether the
law should allow or mandate that the AI program be named as the inventor, or
whether this must be a person. Furthermore, it considers the practical
challenges of whether there should be any indicators of which human ownership
or authorship should be attributed to, if AI systems cannot be given ownership,
that is, whether this decision should be left to private arrangements, such as
corporate policy, with the possibility of judicial review by appeal in
accordance with existing laws concerning disputes over inventorship. Finally,
under problem 1, the WIPO Discussion Paper solicits input from member states on
the subject, "Should the law exclude from the availability of patent
protection any invention generated autonomously by an AI application?"
Issue 2 of the
WIPO Discussion Paper addresses patentable subject matter and patentability
principles. It discusses whether inventions generated autonomously by an AI
application should be excluded from IPR laws, whether specific provisions
should be introduced for inventions assisted by AI (or if they should be
treated in the same way as other computer-assisted inventions), whether patent
examination guidelines should be amended for AI assisted inventions, and so on.
Issue 3 of the
WIPO Discussion Paper delves into the concept of the inventive step test that
must be met for an invention to be granted a patent in the context of
artificial intelligence inventions.
Issue 4
addresses technology disclosure and whether AI-assisted or AI-generated
inventions pose any challenges to the disclosure requirement. It also considers
whether the initial disclosure requirement would be sufficient where the
algorithm continuously changes over time through machine learning; how to treat
data used to train an algorithm; and whether human expertise used to select
data and train the algorithm should be disclosed.
Issue 5
addresses general policy considerations such as whether a sui generis IPR
system should be explored for AI-generated inventions, and whether the
interface between AI and IPRs should be considered later, once AI technology
has matured or is better understood.
Issue 6
relates to copyright and discusses authorship and ownership issues, such as
whether copyright be attributed to original literary and artistic works that are
autonomously generated by AI; in whom should copyright in an AI-generated work
vest; whether the issue of granting legal personality to an AI application,
where it creates original works autonomously; and whether a separate sui
generis system of protection ought to be envisaged for original literary and
artistic work autonomously generated by AI.
Issue 7
pertains to IPR infringements and seeks to understand whether the use of data
existing in copyright works without authorization for machine learning would
constitute an infringement of copyright and what impact that would have on the
development of AI and on the free flow of data to improve innovation in AI;
whether an exception should be made for limited types of use of such data in
machine learning, such as the use in non-commercial user-generated works.
Issue 8
examines the issue of 'deep fakes' or 'the generation of simulated likenesses
of persons and their attributes, such as voice and appearance', and whether
copyright can exist in deep fakes themselves; whether there should be a system
of equitable remuneration for persons whose likenesses and
"performances" are used in a deep fake.
Issue 9 refers
to whether there are seen or unforeseen repercussions of copyright on prejudice
in AI applications; whether the dignity of human invention should be valued as
a right above and beyond innovation in AI;
Issue 10
examines whether a new set of IPRs in data should be created or if the existing
regime of IPR laws is sufficient; what types of data would be protected under
such new rights, if created; whether certain qualities in the data, such as
commercial value or protection against certain types of activities, should be
the defining characteristic for these new rights; how such rights would
interact with existing rights and how they would be enforced.
Issue 11
examines industrial designs and discusses topics such as whether design
protection should be provided to an original design produced autonomously by an
AI program, or whether a human designer is required.
Issue 12
discusses capacity building, namely the containment or reduction of the
technology gap in AI capacity, and whether any policy measures are required in
this area.
Issue 13 of
the WIPO Discussion Paper addresses accountability for decisions in
intellectual property administration.
In light of the above,
the current chapter maps IPR policy vis-à-vis AI of various countries, and
their views on these issues in their respective jurisdictions. In most cases,
the legislative framework treats AI systems as equivalent to software, and
therefore offers limited protection; further, in most jurisdictions, the issue
of granting AI itself authorship status is a novel one and is not something
that is accounted for in the existing IPR system.
COMPARATIVE ANALYSIS
Understanding the policy and legal
frameworks for AI and IP requires comparing diverse method jurisdictions. A
comparative analysis can offer insights about the strengths and disadvantages
of various approaches and assist identify areas. There is room for improvement.
For example, the European Union has adopted a proactive approach to regulating
AI and IP with the European Commission published a White Paper on AI in 2020.
The newspaper establishes a framework for creating an ecosystem of confidence
in AI offers a suggestion for a regulatory structure that governs the
Artificial intelligence development and application.
The US has maintained a hands-off
approach to AI, emphasizing innovation and lowering barriers to its usage. The
US Patent and Trademark Office (USPTO) offers guidelines for reviewing
AI-related patent applications, but there are no formal regulations restricting
its usage in intellectual property. Other jurisdictions have adopted differing
tactics. China has announced AI development guidelines that include IP
protection, while Japan has formed a task force to address legal and regulatory
concerns about AI and IP.
Comparing policy and legal frameworks
can reveal best practices and areas for development when tackling AI and IP
challenges and opportunities.
“To address the impact of AI on
intellectual property, politicians and professionals must work together to
develop a suitable legal framework.”
CONCLUSION
Artificial intelligence is
transforming the creation, management, and enforcement of intellectual property
assets. However, it poses several legal and ethical concerns around ownership,
patentability, copyright infringement, data protection, and privacy. The case
studies highlight the practical ramifications of legal and ethical concerns.
Policymakers and intellectual property specialists must create comprehensive
legal frameworks to ensure responsible and ethical usage of AI technologies.
AI has the ability to change the IP
landscape, creating possibilities for both owners and users, but also posing
substantial concerns. Using AI-based technologies to manage intellectual
property assets can provide a competitive edge for owners. More research is
needed on the ethical and legal implications of owning AI-generated
intellectual property, including international IP legislation and case studies.
As AI advances and transforms the IP landscape, continued research is vital to
keep IP rules and practices up to date and meet the problems and opportunities
posed by this developing technology.
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