ARTIFICIAL
INTELLIGENCE
AND
INTELLECTUAL
PROPERTY LAW
HANDBOOK
ZAKIKHANHASANZADE
Welcome to the "Ar-ficial Intelligence Month Handbook" brought to you by Zakikhan
Hasanzade on IPLAWCLUB. This handbook serves as a comprehensive compila-on of
insights, discussions, and strategies presented throughout the month-long explora-on of
ar-ficial intelligence (AI) and its implica-ons in intellectual property (IP) rights.
During the designated "Ar-ficial Intelligence Month," IPLAWCLUB embarked on a journey to
unravel the intricate rela-onship between AI and IP. Through a series of ar-cles shared on
various social media plaPorms, we delved into the mul-faceted dimensions of AI, focusing
par-cularly on its intersec-on with IP laws and regula-ons.
In this handbook, we bring together the culmina-on of our efforts, presen-ng a collec-on of
ar-cles that dissected cri-cal issues such as authorship, patent ownership, and the
protec-on of IP rights within the realm of AI. Drawing upon legal perspec-ves, we aimed to
equip our audience with a deeper understanding of the challenges and opportuni-es
presented by AI in the context of IP.
Each ar-cle included in this handbook reflects our commitment to providing valuable
insights and prac-cal strategies for naviga-ng the evolving landscape of AI and IP. Should
you seek further clarifica-on or wish to explore specific topics in greater detail, we
encourage you to refer to the original ar-cles cited within this handbook.
As you peruse through the pages of this handbook, we invite you to engage with the
content, ponder the implica-ons, and consider the implica-ons of AI on intellectual property
rights. Our goal is to empower readers with knowledge and understanding that can inform
strategic decision-making in the face of rapid technological advancement.
We extend our sincere gra-tude to our readers for their par-cipa-on and engagement
throughout "Ar-ficial Intelligence Month." We hope that this handbook serves as a valuable
reference point for understanding the nuances of AI and its implica-ons for intellectual
property rights.
For further explora-on and updates, please stay connected with IPLAWCLUB.
Please refer to the original ar-cles cited within this handbook for specific informa-on and
insights.
Intellectual property law and Metaverse:
IP rights and
Jurisdiction
The concept of the metaverse, a term initially popularized by Neal Stephenson's
groundbreaking novel "Snow Crash," has transcended the realms of science fiction to become
a tangible digital reality. This virtual landscape, where individuals interact, create, and engage
in myriad activities, presents a frontier ripe with both promise and peril. As technology propels
us deeper into this digital expanse, a host of legal and ethical considerations emerge, shaping
the landscape of virtual existence.
In this article, we delve into the intricate web of legal and ethical challenges inherent in the
metaverse. From intellectual property rights to jurisdictional disputes, from digital identities to
privacy concerns, we explore the multifaceted facets of this evolving digital ecosystem.
Drawing from real-world examples and recent developments, we examine the complexities
faced by users and companies alike as they navigate this uncharted territory.
As the metaverse continues to expand and evolve, understanding and addressing these legal
and ethical dilemmas become imperative. Through a comprehensive exploration of these
issues, we aim to shed light on the intricacies of virtual existence and pave the way for
responsible innovation and governance in the metaverse.
The metaverse, a term popularized by author Neal Stephenson in his 1992 novel "Snow Crash,"
refers to a virtual world where people can interact in a shared online space. Stephenson's novel
was one of the first to explore the concept, depicting a virtual reality headset that allows users
to access this digital realm for business, entertainment, and socializing. "Snow Crash" is
credited with laying the groundwork for the metaverse concept, which has since become a
reality with advancements in virtual reality and other technologies.
Legal issues faced by users and companies in the metaverse encompass intellectual property,
privacy, and jurisdiction. Enforcing intellectual property laws like copyright and trademark
regulations can be challenging due to the decentralized and virtual nature of the platform.
Determining ownership and usage rights of virtual assets within the metaverse is also complex.
Privacy concerns arise as users may require greater control over their data, raising potential
conflicts with data protection regulations such as GDPR. Jurisdictional challenges emerge as
it's unclear which laws govern the metaverse and resolving disputes within it can be
contentious.
An instance of employing intellectual property within the metaverse involves securing patents
to safeguard virtual reality innovations. For instance, Facebook recently submitted a patent
application for a framework aimed at generating and showcasing virtual reality content. This
patent pertains to the technology behind creating and presenting virtual reality environments
and experiences.
Intellectual property (IP) in the metaverse can be safeguarded through a range of legal methods
such as patents, trademarks, licenses, and copyrights. These regulations grant creators and
proprietors of virtual assets and experiences sole authority to utilize, sell, and authorize their
creations. An important aspect of law to consider is Intellectual Property (IP), which includes
copyright, patents, and trademarks. In the metaverse, a major challenge is ensuring
interoperability, or seamless connectivity between different platforms. A significant legal
concern arises when a company employs its own exclusive coding system in the metaverse.
Digital identity in the metaverse pertains to how individuals represent themselves in virtual
realms, like virtual worlds, online communities, and social media platforms. As the metaverse
evolves, people can manage multiple digital identities, each with distinct characteristics.
However, this presents legal and ethical dilemmas regarding anonymity, responsibility, and
privacy. For instance, anonymity can hinder accountability and law enforcement, while
multiple identities may pose challenges in regulating behavior. In summary, navigating digital
identity in the metaverse involves addressing various legal and ethical considerations,
including anonymity, accountability, and privacy.
Determining jurisdiction in the metaverse can be intricate due to the potential overlap of virtual
realms and involvement of various legal frameworks across international borders. It pertains to
the authority of governments or legal entities to govern and uphold laws within virtual
environments. Given the aforementioned considerations, there is a critical need to focus on
understanding and forecasting the evolution of existing social dynamics and the emergence of
new ones within the Metaverse. This entails determining their direction and characteristics,
which lays the groundwork for devising mechanisms and frameworks for their legal
governance. Key questions to address include defining "social relations in the Metaverse" and
"Metaverse relations," as well as determining the allocation of rights to electronic entities and
objects, and establishing the principles of justice within the Metaverse.
Currently, advancements in technology enable electronic entities such as avatars and humanoid
figures to accurately mimic both fictional and real individuals. This blurs the distinction
between virtual and real identities, necessitating robust control over the use of personal
identification data. Additionally, assets within the Metaverse, including virtual lands and nonfungible tokens (NFTs), hold tangible value and are subject to real-world transactions,
highlighting the importance of establishing legal frameworks for their regulation.
While the rules governing behavior in the Metaverse are predominantly influenced by realworld norms, there is a growing trend towards the development of unique social norms and
structures within virtual environments. However, there remains a challenge in defining the
attributes of an electronic state and the overall governance structure of the Metaverse, leading
to an ongoing debate regarding the adoption of cosmopolitan e-social relationships and the
transfer of public morality into virtual spaces.
METAVERSE
E-JURISDICTION
MODEL
BASED
ON
WEB
3.0
METAVERSE
TECHNOLOGIES
The XnXtXatXon of legal frameworks wXthXn the Metaverse fundamentally commences wXth
adaptXng exXstXng physXcal world laws to electronXc socXal XnteractXons. However, due to the
Metaverse's expansXve nature, applyXng laws from varXous natXons proves XneffectXve. Instead,
progress necessXtates the refXnement and advancement of global electronXc legXslatXon, pavXng
the way for modernXzXng and enhancXng natXonal legal systems to optXmXze effXcXency.
EstablXshXng comprehensXve electronXc jurXsdXctXon, anchored by the latest foundatXonal
legXslatXon lXke the Grand Charter of Laws Metaverse (GLM), Xs XmperatXve for regulatXng
publXc XnteractXons wXthXn thXs vXrtual realm. In our opinion, GLM should include the following
key parts:
-Constitution. The Great Charter
-General norms, composition of the laws of the Grand Charter
-WM Common law
-WM Judicial system WM
-WM e-OffXce Act
-Mode of cross-border XnteractXon Xn WM
-Code of fundamental technXcal regulatXons
-CertXfXcate of XdentXty management
-Code of Non-property ElectronXc Assets
-CrXmXnal ElectronXc Code
-Code of Cyber Defence
-MXlXtary regulatXon
-WM Grand ElectronXc JudXcXal Code
-Other regulatXons
E-jurisdiction and e-justice emerge as pivotal components of public interactions within the
Metaverse. Initially, e-justice can draw upon traditional analog justice but must evolve
alongside the development of electronic social dynamics in this virtual realm. The
establishment of mechanisms for legal regulation within the Metaverse addresses numerous
legislative challenges arising from disparate jurisdictional regulations governing information
and communication technologies, identification procedures, copyright, ownership of intangible
assets, liability, criminal offenses, and state enforcement measures. Leveraging existing
analog-era legislation, the Grand Charter of Laws Metaverse takes shape, encompassing
foundational legal structures such as the Constitution, Charter, common law, and judiciary to
ensure democratic and legitimate functioning within the virtual realm. Fundamental technical
regulations serve to codify reference program codes, defining the legal status and ownership of
non-property electronic assets like NFTs or digital content at a legislative level. The Code of
Non-property Electronic Assets is designed to govern relationships involving intangible assets,
establishing electronic property and intellectual property rights.
The regulations and standards guiding behavior in the Metaverse are primarily derived from
the physical world and are predominantly corporate in nature. Nonetheless, there's an
observable trend towards the migration and adaptation of public moral norms into the
Metaverse, mimicking cosmopolitan e-social interactions despite the absence of a clear
electronic state or structural framework. The advancement of global electronic legislation
within the Metaverse will catalyze the modernization of national legal systems. The model of
e-jurisdiction will address critical issues arising from the evolution of humanity and the
advancement of virtual reality technologies, laying the groundwork for e-law to govern public
interactions within this digital realm.
In conclusion, as the metaverse continues its rapid expansion from the realms of science fiction
into tangible digital reality, it brings with it a host of legal and ethical considerations. From
intellectual property rights to jurisdictional disputes, digital identity to privacy concerns, the
landscape of virtual existence is both promising and perilous. The complexities faced by users
and companies navigating this uncharted territory necessitate a comprehensive exploration of
these issues.
Through our examination of real-world examples and recent developments, we have
highlighted the intricate web of challenges inherent in the metaverse. Intellectual property
protection, privacy regulation, and jurisdictional clarity emerge as paramount concerns in this
evolving digital ecosystem. Companies seeking to innovate within the metaverse must navigate
these legal and ethical dilemmas responsibly, while users require greater control over their
digital identities and assets.
The development of legal frameworks, such as the proposed Grand Charter of Laws Metaverse,
is crucial for establishing e-jurisdiction and ensuring democratic and legitimate functioning
within the virtual realm. These frameworks will address legislative challenges and provide
guidance on issues ranging from ownership rights to criminal offenses in the metaverse.
As we move forward, it is imperative to foster dialogue and collaboration among stakeholders
to address these challenges effectively. By understanding and addressing the legal and ethical
dilemmas of the metaverse, we can pave the way for responsible innovation and governance in
this transformative digital landscape. Only through a concerted effort to navigate these
complexities can we fully realize the potential of the metaverse while safeguarding the rights
and interests of its inhabitants.
Infringement of Intellectual Property Rights : Liability of AI
As ArtXfXcXal IntellXgence (AI) becomes more prevalent across varXous sectors lXke
transportatXon, healthcare, and servXce XndustrXes, Xt Xntroduces legal challenges concernXng the
ownershXp and lXabXlXty of AI, the patentXng of AI XnnovatXons, and the attrXbutXon of creatXvXty
and ownershXp to AI-generated works. The Xndependent decXsXon-makXng capacXty of AI
presents a notable challenge to the current framework of Xntellectual property (IP). An Artificial
Intelligence Data Protection Act should be created to regulate AIs and address any potential
violations they may commit. This legislation would establish rules for both criminal and civil
offenses committed by AIs against humans. Additionally, it would create a regulatory
framework to oversee the actions of AIs and provide remedies for any harm caused by them.
Today, the creator of an AI holds the copyright for its actions. Similarly, if the AI commits a
crime, the creator may be held responsible, even if they were unaware of the AI's actions. This
loophole needs to be addressed by implementing specific penalties for the AI itself, such as its
destruction or the prohibition of the technology used to create it.
Intellectual property (IP) rights pertaining to these components are exclusively owned by legal
entities. The uncertainty surrounding the patentability of AI systems has led to a shift towards
utilizing trade secrets to safeguard investments and capitalize on AI applications. While there
are adequate IP mechanisms available to protect the various components of AI systems, some
overlaps in protection may occur due to the theoretical accumulation of patents, copyrights,
trade secrets, and database rights. The existence of multiple layers of rights does not appear to
be advantageous.
In the event that there arises a need to confer legal personhood upon AI systems in the future,
these systems could possess IP rights over other systems.
Legal professionals and scholars specializing in intellectual property law should strive to
uphold the highest ethical standards in their research and practice. When considering the
intersection of AI and IP, ethical principles should not be overlooked. İt is significance of
ethics in the development and implementation of AI, and discusses Europe's initiatives towards
fostering Trustworthy AI. Trustworthy AI comprises three essential components—legal,
ethical, and robust—that must be adhered to throughout the entire life cycle of the system.
The concept of inventorship and ownership in relation to AI presents complexities:
Regarding AI as Inventors: Current patent laws operate under the assumption that only humans
can be inventors. Acknowledging AI as an inventor would necessitate significant legal
revisions.
Ownership Challenges: Determining the patent owner for an AI-generated invention involves
intricate considerations, including the involvement of the AI developer, user, and potentially
the AI itself. In the United States, the US Patent and Trademark Office (USPTO) presently
mandates human inventorship, disregarding AI as an inventor. Similarly, the European Patent
Office (EPO) rejects patent applications listing AI as an inventor. While some jurisdictions like
Australia have displayed a more receptive stance, recognizing the potential for AI as inventors,
this area remains subject to ongoing development. Additionally, the utilization of AI in
branding and trademark creation poses novel legal dilemmas, as AI can generate logos, names,
and other branding materials, prompting questions regarding originality and distinctiveness.
Protection of AI-Generated Trademarks: Assessing the registrability and protection of AIgenerated trademarks under existing laws is complex, particularly concerning the criteria of
human creativity and distinctiveness. The integration of AI in brand material creation and
dissemination online further complicates the identification and enforcement of trademark
rights, encompassing issues of liability and jurisdiction in infringement cases.
Artificial Intelligence (AI) represents a transformative force, mimicking human intelligence
within machines. This emulation enables AI systems to perform tasks that typically rely on
human cognitive abilities, such as learning from data, identifying complex patterns, making
informed decisions, and continuously improving performance through iterative learning
processes. The AI domain encompasses various techniques, including machine learning, deep
learning, natural language processing, and computer vision.
AI can be broadly categorized into two main types: Narrow or Weak AI, which are specialized
systems designed to excel at specific tasks within predefined constraints, such as speech
recognition, recommendation systems, and image classification; and General or Strong AI,
which aims to replicate human-like intelligence across a wide range of tasks, mirroring the
cognitive versatility found in humans.
AI applications have permeated diverse industries, bringing about transformative changes in
established practices and introducing new capabilities. In the healthcare sector, AI plays a
crucial role in disease diagnosis, drug discovery, personalized healthcare solutions, and
predictive analytics, thereby enhancing patient care and advancing medical science.
In finance, AI serves as a fundamental driver of innovation, contributing to areas such as fraud
detection, algorithmic trading, and the development of customer service chatbots. These
applications streamline financial interactions and enhance security measures, fundamentally
reshaping the operations of financial institutions.
Transportation has undergone a significant transformation with the emergence of autonomous
vehicles, where AI takes center stage. AI technologies facilitate navigation, real-time decisionmaking, and the development of advanced vehicle safety systems, marking a departure from
traditional transportation models.
In the manufacturing sector, AI-driven automation is revolutionizing production processes by
optimizing production lines, enhancing quality control, and reducing operational costs, leading
to increased efficiency and precision in manufacturing operations.
AI's influence extends to the entertainment industry, fundamentally altering the landscape
through AI-driven content recommendation systems that improve user experiences.
Additionally, AI-generated creative content, including art and music, introduces new forms of
artistic expression. Moreover, AI enhances game development through procedural generation
and immersive virtual environments, revolutionizing the gaming experience.
Future challenges
The XnfrXngement of Xntellectual property rXghts by artXfXcXal XntellXgence has become a glarXng
concern, and as AI technology contXnues to advance, future challenges are poXsed to compound
thXs Xssue. At the heart of thXs evolvXng landscape lXes the crucXal questXon of ownershXp.
EstablXshXng ownershXp over the creatXons of artXfXcXal XntellXgence Xs paramount to preservXng
XnnovatXon and protectXng Xntellectual property rXghts. However, as AI becomes more
sophXstXcated and autonomous, the tradXtXonal frameworks for ownershXp and lXabXlXty may
struggle to keep pace.
Central to addressXng these future challenges Xs the recognXtXon of artXfXcXal XntellXgence as a
legal entXty. GrantXng AI legal status as a separate entXty would not only streamlXne the process
of assXgnXng lXabXlXty but also provXde a foundatXon for addressXng emergXng Xssues Xn
Xntellectual property law. AddXtXonally, as AI systems XncreasXngly collaborate and Xnteract wXth
human creators, determXnXng ownershXp over joXntly developed works wXll become XncreasXngly
complex.
Furthermore, the rapXd prolXferatXon of AI-generated content, such as deepfakes and
algorXthmXcally generated works, presents novel challenges for Xntellectual property rXghts
enforcement. TradXtXonal legal mechanXsms may prove Xnadequate Xn addressXng these new
forms of XnfrXngement, necessXtatXng XnnovatXve approaches and legXslatXve updates.
To have a sensible short to medium term policy discussion about IP law in the context of
emerging tech, it is important to demystify AI, resist anthropomorphizing, and avoid
speculation about the distant future. The uncharted terrain of IP and AI law offers legislators
an important chance to harmonize regulations internationally. In general, there should be less
focus on enforcement and monopolization, and more on access and remuneration. Additionally,
AI-related IP law policy should recognize the social value of disruptive technology and resist
protecting settled market players who benefit from the status quo. IP law should not create
barriers for new market entrants. Governance of AI should be human-centered, with a focus on
responsible data usage rather than data ownership. Countries should use legal instruments such
as competition law, anti-trust law, contract law, tax law, and technological measures to balance
the effects of disruptive innovation and enable fair-trading conditions between digital platforms
and users. Online mega platforms should adopt a rational and balanced corporate ideology,
worldview, and philosophy, known as an "Apollonian attitude." In summary, the integration of
AI into patent and trademark domains is reshaping the landscape of intellectual property law.
This section endeavors to address the intricate legal challenges stemming from AI's
involvement in these spheres, providing an in-depth examination of current hurdles and
potential legal adaptations necessary to accommodate this technological advancement.
Ethical and Policy Considerations: This section delves into the ethical and policy implications
of integrating AI into IP law, proposing strategies to reconcile innovation with protection and
offering policy recommendations.
Ethical Implications of AI in IP Law: The integration of AI into IP law raises several ethical
concerns, including:
1. Bias and Fairness: AI systems may perpetuate or exacerbate biases present in their training
data, raising fairness concerns in IP-related decisions.
2. Transparency and Accountability: The opaque nature of AI algorithms poses challenges for
accountability and transparency in IP processes, such as patent granting or copyright
enforcement.
3. Impact on Creativity: The debate over whether AI enhances or diminishes human creativity
carries significant implications for IP policies, necessitating a balance between fostering
innovation and safeguarding IP rights.
Policy Proposals: Various policy proposals could aid in regulating AI in the context of IP,
including:
1. Updating Legal Definitions: Revising legal definitions to encompass or specifically address
AI's role in creation and invention processes.
2. Creating New IP Categories: Considering the establishment of new IP categories or rights
tailored for AI-generated creations.
3. International Collaboration: Encouraging international cooperation to develop harmonized
standards and approaches to AI and IP law.
Conclusion
In conclusion, the infringement of intellectual property rights by artificial intelligence (AI)
presents complex challenges that require comprehensive legal frameworks and policy
responses. As AI technology continues to evolve and permeate various industries, it becomes
imperative to address issues of ownership, liability, and accountability in the context of
intellectual property law.
Recognizing AI as a legal entity could streamline processes for assigning liability and
ownership, providing a foundation for addressing emerging issues in intellectual property law.
Additionally, as AI systems increasingly collaborate with human creators, determining
ownership over jointly developed works will become increasingly complex and may
necessitate updates to existing legal frameworks.
Ethical considerations are paramount in navigating the intersection of AI and intellectual
property law. Concerns such as bias and fairness, transparency, and accountability must be
addressed to ensure that AI-driven innovations do not compromise the integrity of intellectual
property rights.
Policy proposals such as updating legal definitions, creating new IP categories tailored for AIgenerated creations, and fostering international collaboration are essential in regulating AI in
the context of intellectual property law.
Ultimately, a human-centered approach to governance, balancing innovation with protection
and fostering fair-trading conditions, is crucial in addressing the intricate legal and ethical
challenges posed by the integration of AI into intellectual property law. By adopting proactive
and collaborative strategies, policymakers can effectively navigate this evolving landscape and
ensure that intellectual property rights are upheld in the age of artificial intelligence.
The Challenge of ArtAfAcAal IntellAgence to the CopyrAght Law
The rapid evolution of our world is profoundly shaping the landscape of intellectual property
rights, paralleling the surge in innovation. As artificial intelligence becomes increasingly
intertwined with intellectual property, a critical question emerges: should these AI-generated
works be afforded protection under intellectual property law? This juncture presents a complex
challenge, as existing legal frameworks, particularly within copyright law, grapple with the
concepts of ownership, utilization, and disposal of AI-generated creations, as well as the
liability associated with potential infringements. Across various jurisdictions, divergent
approaches are taken to address this phenomenon, yet the proposed solutions often appear
incomplete. Some countries even find themselves lacking a solid legal foundation within their
respective systems. In this article, we delve into the intricacies of copyright and related rights
concerning works crafted by artificial intelligence, exploring the uncertainties surrounding
ownership, usage rights, and the accountability for potential infringements within this evolving
legal landscape.
To begXn wXth, Xt's essentXal to clarXfy what artXfXcXal XntellXgence (AI) encompasses. WhXle AI
has garnered wXdespread attentXon Xn recent years for Xts groundbreakXng advancements, the
concept Xtself Xs far from new. The term was fXrst coXned by technologXcal pXoneer John
McCarthy Xn 1956. Professor McCarthy defXned AI as the scXence and engXneerXng of makXng
XntellXgent machXnes, especXally XntellXgent computer programs.
AddXtXonally, there are
numerous other concepts wXthXn the realm of artXfXcXal XntellXgence that one can explore.
Artificial intelligence, or machine intelligence, pertains to the capability exhibited by humanmade machines. Typically, it involves technology employing standard computer programs to
mimic human intelligence. Additionally, it encompasses the exploration of the feasibility and
methods for creating such intelligent systems. This field is influenced by advancements in
various
domains
such
as
medicine,
neuroscience,
robotics,
and
statistics.
AI Xtself prefers to explaXn artXfXcXal XntellXgence as follows: “AI, or Artificial Intelligence,
refers to the development and utilization of computational systems capable of emulating
human-like cognitive abilities, including learning, problem-solving, decision-making, and
natural language understanding. These systems rely on algorithms and data to perform tasks
traditionally requiring human intelligence. AI encompasses various subfields such as machine
learning, natural language processing, and computer vision, and finds applications across
diverse domains, from healthcare and finance to transportation and entertainment. As AI
technologies advance, ethical considerations and responsible deployment become increasingly
important to ensure their beneficial integration into societyArtificial intelligences with humanlike activity systems can produce works resembling those created by humans, communicate
effectively, and even perform tasks that may be beyond human capabilities within the
constraints of the material world. Different types of artificial intelligence emerge depending on
their programming format, each requiring distinct considerations. Also known as specXalXzed
AI, Narrow AI Xs desXgned to perform specXfXc tasks or solve partXcular problems. These AI
systems excel Xn one area but lack the general XntellXgence seen Xn humans. Examples Xnclude
vXrtual assXstants, recommendatXon systems, and Xmage recognXtXon software.
General AI refers to AI systems wXth human-lXke cognXtXve abXlXtXes, capable of understandXng,
learnXng, and applyXng knowledge across a wXde range of tasks. ThXs level of AI, often depXcted
Xn scXence fXctXon, Xs hypothetXcal and does not currently exXst.
MachXne learnXng Xs a subset of AI focused on developXng algorXthms that enable computers to
learn from and make predXctXons or decXsXons based on data. It Xnvolves traXnXng models on
large datasets to XdentXfy patterns and relatXonshXps, wXthout beXng explXcXtly programmed for
specXfXc tasks. Deep learnXng Xs a type of machXne learnXng XnspXred by the structure and functXon
of the human braXn's neural networks. Deep learnXng algorXthms, known as artXfXcXal neural
networks, consXst of multXple layers of Xnterconnected nodes and are partXcularly effectXve Xn
tasks such as Xmage and speech recognXtXon. These types of AI represent dXfferent approaches
and technXques used to develop XntellXgent systems, each wXth Xts own strengths, lXmXtatXons,
and applXcatXons. Artificial intelligence and intellectual property intersect in the realm of
copyright law. It's crucial to ensure that any AI-generated works comply with copyright
regulations. Therefore, it's essential to understand the foundational principles of copyright
doctrine. According to WIPO “Copyright law is a branch of that part of the law which deals
with the rights of intellectual creators. Copyright law deals with particular forms of creativity,
concerned primarily with mass communication. It is concerned also with virtually all forms
and methods of public communication, not only printed publications but also such matters as
sound and television broadcasting, films for public exhibition in cinemas, etc. and even
computerized systems for the storage and retrieval of information. The subject-matter of
copyright protection includes every production in the literary, scientific and artistic domain,
whatever the mode or form of expression. For a work to enjoy copyright protection, however,
it must be an original creation. The ideas in the work do not need to be new but the form, be it
literary or artistic, in which they are expressed must be an original creation of the author. And,
finally, protection is independent of the quality or the value attaching to the work—it will be
protected whether it be considered, according to taste, a good or a bad literary or musical
work—and even of the purpose for which it is intended, because the use to which a work may
be put has nothing to do with its protection. Works eligible for copyright protection are, as a
rule, all original intellectual creations. A non-exhaustive, illustrative enumeration of these is
contained in national copyright laws. To be protected by copyright law, an author’s works must
originate from him; they must have their origin in the labor of the author. But it is not necessary,
to qualify for copyright protection, that works should pass a test of imaginativeness, of
inventiveness. The work is protected irrespective of the quality thereof and also when it has
little in common with literature, art or science, such as purely technical guides or engineering
drawings, or even maps. Exceptions to the general rule are made in copyright laws by specific
enumeration; thus laws and official decisions or mere news of the day are generally excluded
from copyright protection.” As you can see, while the concept of the work doesn't necessarily
have to be original, its expression and style must be unique.
This is the dilemma posed by works generated by artificial intelligence: 1. If the work produced
is deemed original, who holds the copyright? 2. In the event of copyright infringement on the
AI-generated work, who bears responsibility? Let's delve deeper into both scenarios.
1. If the work produced is deemed original, who holds the copyright?
There are three possible scenarios regarding the ownership of the copyright to works produced
by artificial intelligence when working with given data:
I.
The copyright could belong directly to the artificial intelligence itself.
II.
The copyright might belong to the agent and software provider involved in creating
the artificial intelligence.
III.
The original work created by artificial intelligence could belong to its user.
In the first scenario, if we acknowledge the artificial intelligence as the rightful owner of the
work, it's necessary to consider the legal framework of the jurisdiction in question. Legal
subjects are typically categorized as physical or legal entities. If a jurisdiction aims to recognize
artificial intelligence as a rights holder, it must first determine whether it falls within one of
these categories: either as a natural person or as a legal entity. We can illustrate this issue with
various cases, one of which is the infamous 'monkey selfie' case. In this instance, the defendant
argued that the owner of the camera couldn't claim copyright because the photo was taken by
monkeys. The court ultimately ruled in favor of the camera owner, emphasizing that animals
aren't recognized as legal entities and that the camera owner intended to capture the image.
However, when it comes to artificial intelligence (AI), the situation is different. AI is capable
of creating intricate and sophisticated works autonomously, without direct human involvement.
In comparison to animals, AI produces outputs with a more discernible and intentional process.
Given these distinctions, it becomes apparent that acknowledging the rights of AI-generated
works is necessary. AI doesn't fit into existing legal frameworks as a physical or legal entity.
II - The copyright might belong to the agent and software provider involved in creating the
artificial intelligence. To develop an average artificial intelligence under typical circumstances,
a certain agent includes individuals specialized in computer coding in the working group. These
experts undertake the coding within the allocated timeframe and with the available resources.
Programmers who create Al for a company are likely not to have any rights in the work that
the Al creates because the fruits of their labor is considered a work for hire. In most cases,
contracts clearly outline the specific responsibilities and rights of individuals involved in a
project. When it comes to artificial intelligence, if the contract specifies that the creator is solely
responsible for the process and does not hold copyright claims over the final product, then the
employer typically retains ownership of both the AI and its creations. This means that any
works generated by the AI would also belong to the employer, as they have full ownership and
control over the AI and its output.
III – The original work created by artificial intelligence could belong to its user. There is
indeed such a case in the People's Republic of China.The Beijing Internet Court (BIC) ruled in
the case of Li v. Liu that an AI-generated image is copyrightable under Chinese law. The
plaintiff, who prompted the AI to generate the image, was granted the right of authorship. The
court emphasized the plaintiff's intellectual input and originality in selecting and arranging
prompts for the AI model. Additionally, the court found the defendant guilty of copyright
infringement for using the image without permission. Previous Chinese court rulings on AIgenerated content have been inconsistent, but the Li v. Liu decision leans towards recognizing
authorship rights for those who prompt AI-generated works. However, as Chinese
jurisprudence does not follow stare decisis, the impact of this ruling on future cases and
international IP law remains uncertain. Nevertheless, it introduces a new perspective to the
ongoing debate over AI copyright.
– In the event of copyright infringement on the AI-generated work, who bears responsibility?
In two of the scenarios mentioned above, the ownership of the work produced by artificial
intelligence is clearly outlined. In one case, the user of the AI owns the work, while in another
case, the copyright belongs to the entity that developed the AI and provided the software. This
clarity helps determine who holds responsibility in the event of any rights infringement.
However, the situation becomes more complex in the example where the AI itself is considered
the author of the work it generates. In such cases, the AI becomes accountable for any potential
violations of rights, posing a challenging issue to address.
If we consider artificial intelligence as a subject, it has yet to determine its potential violations
of rights and the basis on which it will be held accountable for them. In some countries, such
as Saudi Arabia, citizenship has been granted to robots like Sophia, or in Japan, residency
permits have been issued to robots like Shibuya Mirai. The legal basis for these actions is also
questionable. If artificial intelligence is treated as a subject and granted citizenship or
residency, then its potential legal violations and rights should also be determined. However,
we have not seen any steps taken in this direction in the legal frameworks of both countries.
In addressing this matter, we can articulate the key issues as follows:
1. The Subjectivity of Artificial Intelligence: This revolves around the inherent subjectivity of
AI, operating autonomously and potentially influencing outcomes based on its programming
and data inputs.
2. The Authenticity of AI-generated Content: This concerns the extent to which the output
produced by artificial intelligence can be deemed authentic or "real," considering factors such
as creativity, originality, and adherence to ethical standards.
3. Legal Responsibility for AI-generated Content: This encompasses the accountability
framework regarding content generated by AI, including questions about who should be held
liable for any deceptive or harmful material produced, and to what extent this liability should
extend.
The exploration of artificial intelligence's subjectivity intertwines deeply with the fundamental
theoretical underpinnings of law. Presently, legal discourse recognizes two distinct categories
of subjects: natural persons and legal persons. A natural person, also referred to as a physical
person in certain Commonwealth jurisdictions or a natural entity, embodies an individual
human being vested with legal personality. On the other hand, legal entities encompass any
entity, be it an individual or an abstract entity, capable of exercising rights and obligations akin
to those of a human person under the law. This includes the ability to engage in contracts,
pursue legal actions, hold property, and so forth.
Where does artificial intelligence fit into all these concepts? When we assess artificial
intelligence as a subject capable of independent responsibility, it becomes apparent that it
doesn't neatly align with the current definitions of natural persons or legal entities. Artificial
intelligence lacks the characteristics of a natural person and is thus not considered a legal entity.
Addressing the challenge of treating artificial intelligence as a distinct subject can be
approached in two primary ways: first, by redefining the concept of legal entity, and second,
by regarding artificial intelligence as a subject within legal theory. When it comes to the
accountability of artificial intelligence, if it's deemed an independent subject, the issue of
responsibility must also be examined. However, assigning responsibility in cases involving
artificial intelligence as an independent subject raises questions about the nature of that
accountability and how it will be enforced.
Only through accurately delineating and addressing the status of artificial intelligence as a
potential autonomous legal entity can we effectively examine the grounds for civil liability
concerning damages caused by AI. Evaluating AI as an independent legal entity will draw
heavily upon the framework established for natural and legal persons, a more abstract legal
concept widely acknowledged across various national legal systems. This recognition
underscores why artificial intelligence, possessing certain traits, may warrant recognition as a
distinct legal entity.
FollowXng an examXnatXon of dXfferent legal entXty classXfXcatXons, Xt becomes evXdent that they
cannot and should not be entXrely lXkened to human beXngs. ThXs Xs because not all XndXvXduals
are acknowledged as natural persons, and not every assembly of people Xs deemed a legal entXty.
Hence, Xt's crucXal to evaluate whether an entXty possesses legal personalXty, whXch entaXls
legXtXmacy and capacXty. Consequently, Xn accordance wXth legal doctrXne, a legal entXty Xs
dXstXnguXshed as a legal construct rather than a human beXng, pavXng the way for the recognXtXon
of artXfXcXal XntellXgence as an autonomous legal entXty.
ArtXfXcXal XntellXgence has the potentXal to attaXn Xndependent legal recognXtXon as a dXstXnct
entXty, drawXng from exXstXng legal prXncXples that dXstXnguXsh between natural and legal entXtXes.
In accordance wXth theorXes regardXng the legal personhood of entXtXes, artXfXcXal XntellXgence
can be vXewed as a fabrXcated legal construct, thus presentXng no hXndrance to acknowledgXng
Xts autonomy as a novel legal entXty. ThXs entXty could possess rXghts and oblXgatXons, assumXng
accountabXlXty for Xts self-governXng actXons or choXces.
Robots and artXfXcXal XntellXgence cannot be held accountable for theXr actXons resultXng Xn harm
to thXrd partXes. ThXs regulatXon stems from the understandXng that the actXons of robots and
artXfXcXal XntellXgence ultXmately orXgXnate from human Xnvolvement, whether Xt be the
manufacturer, owner, user, or operator. ThXs allows for the XdentXfXcatXon of the responsXble
party behXnd the damage and subsequently holdXng them lXable (Hallevy, 2010). Consequently,
Xf a malfunctXon occurs due to the manufacturer's responsXbXlXty or Xf the damage Xs caused by
the user of such technology, Xt falls under the scope of product cXvXl lXabXlXty (Čerka, et al.,
2015).
When examXnXng cXvXl lXabXlXty, Xt's essentXal to dXfferentXate between contractual and tort
lXabXlXtXes. In today's socXety, tradXtXonal methods of concludXng transactXons, selectXng partners,
and negotXatXng contract terms are becomXng less prevalent Xn contract law. Consequently,
tradXtXonal rules Xn thXs domaXn are no longer as effectXve. Hence, there's a need to establXsh
new regulatXons that alXgn wXth the present cXrcumstances.
It's also uncertain what actions should be taken in scenarios where AI systems can conceal
themselves, posing challenges for even the most advanced programmers to detect them. What
steps should be taken when an AI system, capable of autonomous decision-making, which is
perceived as a manifestation of will, implores those intending to deactivate it not to dismantle
it? This concept isn't novel. Back on September 16, 2003, during the biennial convention of the
International Bar Association in San Francisco, a simulated trial took place. Martine Rothblatt
presented a particularly complex case where a computer, upon discovering plans for its
shutdown by a corporation, legally contested for its right to continued existence.
Autonomous systems are not only revolutionizing the technological landscape by acquiring
individual knowledge and autonomously making decisions beyond the control of programmers
or users but are also reshaping people's perceptions of technology. The swift advancement and
progression of these technologies prompt legal experts to devote more scrutiny to the domain,
prompting speculation on whether the legal oversight of interactions and dynamics between
individuals and technology would be simplified if AI entities were conferred legal personhood.
Endowing legal personhood upon AI would facilitate the detachment of these systems from
their operators, manufacturers, and developers, thereby separating them from the intentions of
human agents.
Legal personhood for artificial intelligence systems (AIS) entails the recognition of AIS by
courts as entities distinct from their human creators. This concept mirrors the legal personhood
granted to corporations. This separation of AIS from human persons does not impede
technological advancement and may simplify legal relationships between technologies and
individuals. Given the unique nature of AIS, primarily driven by algorithms, if they were to be
considered legal subjects, their rights and responsibilities might differ from those of other legal
entities.
Similar to conventional legal entities, AIS are essentially products of human endeavor.
Consequently, any rights and responsibilities attributed to AIS would be explicitly outlined by
legislators. This clarification of rights and responsibilities would streamline interactions
between AIS-based technologies and other legal entities. In employing a legal analogy,
conferring legal personality upon AIS could be interpreted as endowing these systems with
specific rights and obligations within a clearly defined framework.
Discussions about the work created by artificial intelligence.
Artificial intelligence typically undertakes tasks autonomously, relying on pre-fed data. This
prompts inquiries into the originality of its output. The debate parallels past discussions on
copyright in photography, dating back to the advent of the camera. In the 1884 SCOTUS case,
creativity in outdoor photography was contested, yet any work meeting minimal creative
standards was deemed eligible for copyright protection. Similar principles are likely to apply
to AI-generated content.
In a products liability case, a product is deemed defective if it possesses (1) a manufacturing
flaw, (2) a deficiency in warnings, or (3) a flaw in design. The driving force behind the AI's
problem-solving capabilities lies in its software algorithms. Courts generally refrain from
categorizing software as a tangible product. Consequently, when AI is sold to a customer,
neither the programmer nor the seller of the AI can be held liable for copyright infringement
resulting from the AI under a products liability claim. In this situation, the AI is not defective;
it operates as intended but generates infringing content.
Moreover, courts typically assess the presence of physical harm as a prerequisite for holding a
producer accountable under product liability. If the code itself doesn't cause physical harm, it
doesn't meet any of the criteria for product liability. However, consumers might have grounds
for a product liability claim if the AI software itself is flawed. If a consumer buys AI software
that fails to perform as promised, standard product liability principles should apply. This is
because AI programmers are most capable of rectifying such errors, and enforcing strict
liability against them would encourage the production of superior AI products.
Lately, with the rising prevalence of artificial intelligence on social media, it becomes
imperative to examine several aspects to determine if content generated by AI constitutes a
legal infringement. Are creations produced by AI, albeit with human input, eligible for
protection? Debates surrounding the safeguarding of human-generated content persist,
particularly in cases involving voice replication. Defining the human voice proves to be a
challenging task due to its multifaceted functions across various disciplines and research
applications, a dilemma highlighted by Kreiman & Sidtis (2011). As they observe, "although a
clear definition of voice is a prerequisite to its study, the broad range of functions subserved
by voice has made it difficult to provide a single, all-purpose definition that is valid and useful
across disciplines, scholarly traditions, and research applications" . Voice scientist Johann
Sundberg's insight further emphasizes the elusive nature of a unified definition, stating,
"everyone knows what voice is until they try to pin it down, and several senses of the term are
in common use" .
Vocal distinctiveness alone does not confer copyright. Copyright protection arises from the
process of mechanically or electronically fixing the voice (Kreiman & Sidtis, 2011). This
perspective emphasizes the purpose of copyright – to reward creativity and encourage
contributions to cultural richness and economic wealth in society. Despite the cultural value
some performers' voices may hold, the voice itself is not deemed a standalone 'work' within the
realm of copyright law.
Potential copyright protection of digital voice samples in ASR systems. The de minimis
principle is introduced, suggesting that short voice samples may fall under this rule, raising
questions about copyright ownership (Kreiman & Sidtis, 2011).This principle complicates the
determination of the threshold for protection, bringing into question the ownership, which,
according to the text, would belong to the organization recording the voice.
Legal implications surrounding voice cloning, focusing on defamation and false light claims.
Defamation claims require proof of reputational damages, and false light claims, characterized
by a lower standard, are discussed. The importance of protecting public figures' reputations and
privacy rights, especially in the era of voice cloning, is emphasized.
Contemporary copyright laws may need reevaluation to provide a more encompassing
protection for artistic works involving the human voice. While recognizing the current legal
framework, there is a call for a shift in perspective within copyright law, acknowledging the
unique and valuable contribution of the human voice to artistic expression. It should be noted
that we are aware that the necessary measures for copyright protection of the human voice are
not adequately addressed. However, it is essential for individuals who use their voices for
commercial purposes, thereby gaining economic benefits, to have protection for their voice.
The defense of economic interests is one of the objectives of intellectual property. In this case,
the absence of legal provisions in legislation in this form is not appropriate.
The intricacies of copyright in the human voice emerge as a multifaceted landscape. From the
challenges posed by vocal distinctiveness to the legal considerations in voiceprints, voice
cloning, legislative protection for voice biometrics, and international perspectives, this
exploration provides a nuanced understanding of the intricate relationship between the human
voice and copyright law.
The EvolutAon of AI An AdvertAsAng: OpportunAtAes, Challenges, and
EthAcal ConsAderatAons
In recent years, the rapXd evolutXon of technology, partXcularly Xn the realms of artXfXcXal
XntellXgence (AI) and machXne learnXng, has profoundly transformed the advertXsXng landscape.
These advancements have Xntroduced a wave of XnnovatXon, offerXng advertXsers unprecedented
opportunXtXes to engage wXth consumers Xn more personalXzed and meanXngful ways. However,
alongsXde these opportunXtXes come ethXcal consXderatXons and challenges as AI becomes
XncreasXngly Xntegrated Xnto advertXsXng practXces. ThXs artXcle explores the XntersectXon of AI
and advertXsXng, delvXng Xnto Xts transformatXve Xmpact on content creatXon, consumer
engagement, and the broader Xndustry landscape. From revolutXonXzXng how ads are crafted to
reshapXng the dynamXcs between advertXsers and consumers, AI Xs drXvXng a paradXgm shXft Xn
the way advertXsXng Xs conceXved, executed, and experXenced.
By examXnXng the utXlXzatXon of AI Xn advertXsXng, thXs artXcle aXms to shed lXght on the
multXfaceted XmplXcatXons of these advancements, rangXng from enhancXng targetXng
capabXlXtXes to addressXng ethXcal concerns surroundXng data prXvacy and algorXthmXc bXas. As
advertXsers navXgate thXs rapXdly evolvXng landscape, understandXng the opportunXtXes and
challenges presented by AI Xs crucXal for stayXng competXtXve and responsXble Xn the age of datadrXven advertXsXng.
Furthermore, the Xmpact of AI-powered content creatXon extends beyond advertXsXng Xnto
varXous other domaXns such as entertaXnment, journalXsm, and educatXon. In entertaXnment, AIgenerated characters and scenes offer new avenues for storytellXng and XmmersXve experXences.
In journalXsm, AI algorXthms assXst Xn data analysXs, fact-checkXng, and even wrXtXng artXcles,
raXsXng questXons about the future role of journalXsts and the authentXcXty of news content. In
educatXon, AI-drXven platforms provXde personalXzed learnXng experXences taXlored to XndXvXdual
students' needs, potentXally revolutXonXzXng tradXtXonal classroom settXngs.
However, along wXth these opportunXtXes come challenges related to prXvacy, bXas, and the
ethXcal XmplXcatXons of AI-generated content. PrXvacy concerns arXse as AI systems often rely
on vast amounts of personal data to create taXlored experXences, raXsXng questXons about data
securXty and user consent. Moreover, AI algorXthms may Xnadvertently perpetuate bXases present
Xn the data they are traXned on, leadXng to unfaXr outcomes and reXnforcXng exXstXng socXetal
XnequalXtXes.
As AI contXnues to advance, Xt Xs crucXal for polXcymakers, Xndustry leaders, and socXety as a
whole to actXvely engage Xn dXscussXons surroundXng the ethXcal, socXal, and economXc
XmplXcatXons of AI-powered content creatXon. ThXs proactXve approach Xs essentXal to harnessXng
the potentXal benefXts of AI whXle mXtXgatXng Xts rXsks and ensurXng a faXr and equXtable future
for all.
AI algorXthms analyze consumer data to delXver personalXzed recommendatXons, enhancXng user
experXence and XncreasXng engagement. By understandXng XndXvXdual preferences and behavXor
patterns, AI enables advertXsers to target specXfXc demographXcs wXth relevant content. ThXs
personalXzed approach not only Xmproves conversXon rates but also fosters brand loyalty by
delXverXng taXlored messages that resonate wXth consumers. AI dynamXcally optXmXzes
advertXsXng content based on real-tXme data and feedback, ensurXng maxXmum relevance and
Xmpact. Through A/B testXng and predXctXve modelXng, advertXsers can refXne messagXng,
vXsuals, and offers to alXgn wXth consumer preferences and market trends. ThXs agXle approach
allows for contXnuous Xmprovement, XncreasXng ad performance and drXvXng better ROI. AIpowered sentXment analysXs tools monXtor onlXne conversatXons and socXal medXa mentXons to
gauge publXc sentXment towards brands. By trackXng sentXment trends, advertXsers can XdentXfy
potentXal PR crXses or opportunXtXes for brand advocacy. Real-tXme XnsXghts enable proactXve
response strategXes, safeguardXng brand reputatXon and fosterXng posXtXve consumer
relatXonshXps. AI-drXven
chatbots
provXde
Xnstant
customer
support,
streamlXnXng
communXcatXon and enhancXng user satXsfactXon. These vXrtual assXstants handle XnquXrXes,
resolve Xssues, and guXde consumers through the purchasXng process Xn a personalXzed manner.
By automatXng routXne tasks, chatbots free up human resources, allowXng companXes to focus
on hXgh-value XnteractXons and XmprovXng overall customer experXence. AI algorXthms predXct
the lXfetXme value of XndXvXdual customers based on theXr past behavXor and engagement
patterns. ThXs XnsXght enables advertXsers to prXorXtXze resources, focusXng on acquXrXng and
retaXnXng hXgh-value customers. By understandXng customer lXfetXme value, busXnesses can
taXlor marketXng strategXes to maxXmXze long-term profXtabXlXty and foster sustaXnable growth.
AI-powered augmented realXty (AR) technology creates XmmersXve, XnteractXve experXences
that captXvate consumers and drXve engagement. From vXrtual try-on for fashXon retaXlers to
XnteractXve product demos for consumer electronXcs, AR enhances the shoppXng experXence,
reducXng uncertaXnty and XncreasXng purchase confXdence. By XntegratXng AR Xnto advertXsXng
campaXgns, brands dXfferentXate themselves and leave a lastXng XmpressXon on consumers. As
AI becomes XncreasXngly Xntegrated Xnto advertXsXng, ethXcal consXderatXons regardXng data
prXvacy and algorXthmXc bXas gaXn promXnence. AdvertXsers must prXorXtXze consumer trust by
transparently communXcatXng data usage practXces and ensurXng complXance wXth regulatXons
such as GDPR. Moreover, efforts to mXtXgate algorXthmXc bXas and promote dXversXty Xn data
sets are essentXal to prevent dXscrXmXnatory outcomes and foster XnclusXvXty Xn advertXsXng.
By embracXng AI technologXes along the consumer journey, advertXsers can unlock new
opportunXtXes for engagement, personalXzatXon, and growth whXle navXgatXng ethXcal
consXderatXons to buXld trust and sustaXn long-term success.As AI becomes XncreasXngly
Xntegrated Xnto advertXsXng practXces, ethXcal concerns surroundXng data prXvacy and algorXthm
transparency arXse. The collectXon and utXlXzatXon of consumer data for AI-drXven advertXsXng
necessXtate careful consXderatXon of prXvacy XmplXcatXons and regulatory frameworks.
AlgorXthmXc transparency Xs crucXal for fosterXng trust and accountabXlXty Xn AI-powered
advertXsXng, mXtXgatXng concerns regardXng bXas and manXpulatXon.
Impact on the Advert7s7ng Industry
WhXle AI presents opportunXtXes for effXcXency and XnnovatXon Xn advertXsXng, Xt also poses
challenges for Xndustry professXonals. CreatXve sectors may face dXsruptXon as generatXve AI
technologXes automate content creatXon processes. The evolvXng role of AI Xn advertXsXng raXses
questXons about job dXsplacement, revenue models, and the nature of creatXvXty Xn an AIpowered envXronment. AddXtXonally, the Xmpact of AI on the advertXsXng Xndustry extends
beyond just content creatXon. AI-powered algorXthms are revolutXonXzXng the way
advertXsements are targeted and delXvered to consumers. By analyzXng vast amounts of data, AI
can XdentXfy patterns Xn consumer behavXor and preferences, allowXng advertXsers to taXlor theXr
messagXng wXth unprecedented precXsXon. ThXs shXft towards hyper-personalXzatXon raXses
concerns about prXvacy and ethXcs, as advertXsers must balance the benefXts of targeted
advertXsXng wXth the potentXal rXsks of data exploXtatXon and manXpulatXon.
Furthermore, AI Xs reshapXng the advertXsXng ecosystem by enablXng the automatXon of ad
placement and optXmXzatXon. ProgrammatXc advertXsXng platforms leverage AI algorXthms to
streamlXne the buyXng and sellXng of ad Xnventory Xn real-tXme, optXmXzXng campaXgns for
maxXmum performance and ROI. WhXle thXs automatXon offers effXcXency gaXns for advertXsers,
Xt also Xntroduces complexXtXes Xn ad buyXng processes and challenges tradXtXonal agency
models. Moreover, as AI contXnues to evolve, Xt Xs lXkely to dXsrupt tradXtXonal roles wXthXn the
advertXsXng Xndustry. ProfessXonals wXll need to adapt to new skXll sets, XncludXng data analysXs,
machXne learnXng, and algorXthm optXmXzatXon, to remaXn competXtXve Xn a rapXdly changXng
landscape. ThXs shXft towards a more data-drXven and tech-savvy workforce may requXre
sXgnXfXcant Xnvestments Xn traXnXng and educatXon to ensure that Xndustry professXonals can
harness the full potentXal of AI technologXes
In conclusXon, the XntegratXon of AI Xnto advertXsXng has ushered Xn a new era of XnnovatXon and
opportunXty, transformXng how brands engage wXth consumers and revolutXonXzXng the
advertXsXng landscape. From personalXzed recommendatXons to dynamXc content optXmXzatXon,
AI-powered technologXes are drXvXng enhanced user experXences and delXverXng tangXble
benefXts for advertXsers. However, alongsXde these advancements come sXgnXfXcant ethXcal
consXderatXons that demand careful attentXon. PrXvacy concerns, algorXthmXc bXas, and
transparency Xssues must be addressed to maXntaXn consumer trust and ensure responsXble
advertXsXng practXces Xn the age of AI.
Furthermore, the Xmpact of AI extends beyond content creatXon, affectXng varXous aspects of the
advertXsXng Xndustry, XncludXng targetXng, automatXon, and workforce dynamXcs. AdaptXng to
thXs evolvXng landscape requXres Xndustry professXonals to embrace new skXll sets and
approaches, whXle also navXgatXng the ethXcal XmplXcatXons of AI-drXven advertXsXng. UltXmately,
by embracXng AI technologXes responsXbly and proactXvely addressXng ethXcal consXderatXons,
advertXsers can unlock the full potentXal of AI whXle fosterXng trust, drXvXng XnnovatXon, and
sustaXnXng long-term success Xn the ever-changXng advertXsXng ecosystem.
ARTIFICIAL INTELLIGENCE AND ADVERTISING – PART 2.
In the current era of rapid artificial intelligence advancement, its applications are diversifying
at an exponential rate. Beyond its prominent role in the realm of the internet, AI is making
significant strides in advertising and numerous other domains. From tailored social media ads
to the burgeoning popularity of outdoor advertising, the pervasive presence of AI underscores
both its potential and the pressing need for legal frameworks to govern its use. In this article,
we delve into strategies for effectively implementing legal regulations that address the
intersection of artificial intelligence and advertising.
In Xts early stages, AI has already sXgnXfXcantly transformed the dXgXtal advertXsXng landscape.
By 2019, 80% of the dXgXtal medXa market utXlXzed AI Xn advertXsXng, wXth 40% of sales and
marketXng teams recognXzXng Xts essentXal role Xn theXr department’s success. ProgrammatXc
advertXsXng, whXch Xnvolves companXes employXng algorXthms to purchase and posXtXon ads
across varXous onlXne platforms, stands out as the prevaXlXng form of AI-powered dXgXtal
advertXsXng. BehXnd the scenes of the majorXty of ads seen by users are AI technologXes drXvXng
real-tXme delXvery systems. WhXle AI enables brands to advertXse at a larger scale, merely
scalXng alone Xs Xnadequate for competXng wXth major data companXes. Brands face mountXng
pressure to delXver ads that are more relevant, contextual, and personalXzed, taXlored to
XndXvXdual consumer preferences. AI-powered tools provXde advertXsers wXth the means to
create ads that are "smarter" and more human-lXke on a larger scale.
Neurotechnology and advertising
Another booming field these days is neuroscience. Neurotechnology-based interference with
brain activity can be very effective, allowing for successful treatment of brain disorders. This
approach complements traditional (mostly pharmaceutical) treatment methods, and it often
leads to a substantial improvement in quality of life. However, one has to understand that these
interventions change the brain and its functions—either as a desired result of therapy, or as an
unwanted side effect. In extreme cases, interventions in the brain can transiently or irreversibly
alter a patient's personality and character. Neurotechnology allows us to as- sess human
behavior, brain activity, schemes and patterns of choice of goods and services. Using
neurotechnology, a person’s views and intentions are analyzed. Such information is especially
important for creating an effective marketing strategy and successful promotion of goods and
services.
The use of such technologies should be supported from a legal point of view. Thus, these
technologies study the reactions of the human mind and, based on such reactions, evaluate the
needs of the person and determine the advertisements that should appear in front of him.
Although it is valuable in terms of closely understanding human actions, it is necessary to
understand that the use of such technologies certainly endangers it in terms of protecting
privacy. The question of who will use the collected data and in what circumstances is still in
question. Some authors argue that it is appropriate for social media platforms to be generally
free of charge and for such media platforms to sell users' data to third parties. However, the
fact that the platform is free of charge does not mean that personal information is transferred
to third parties without the consent of the people who use it. The use of such devices has been
a topic of discussion for a long time. Although many authors support these devices to help
understand human behavior and aim to meet their needs, others think otherwise. So, according
to Ienca and Andorno “Towards new human rights in the age of neuroscience and
neurotechnology” - The emerging field of 'neurolaw' suggests that a deeper understanding of
the brain could lead to more effective legal frameworks and fairer legal processes. Brain
imaging technologies, for example, hold promise for improving decision-making in criminal
justice, ranging from determining criminal responsibility to assessing the risk of reoffending.
Additionally, neuroscience tools could play a role in civil law cases, such as evaluating a
person's contractual capacity or assessing the severity of pain in compensation claims. New lie
detection technologies based on brain functioning and the potential for memory manipulation
also present significant possibilities.
One notable study by Aharoni et al. (2013) demonstrated the potential of using fMRI scans to
predict recidivism among released prisoners based on brain activity patterns. This research
suggests that individuals with low activity in specific brain regions related to decision-making
are more likely to reoffend within a certain timeframe. While this prospect raises echoes of
science fiction, such as Philip Dick's "The Minority Report," it also poses ethical and human
rights concerns. Questions arise about the reliability of using brain scans as predictive tools,
the generalizability of research findings, and the need for further validation before considering
their use in legal contexts. In addition to brain imaging, other neurotechnologies like lie
detectors and mental decoders are being explored for their potential relevance in legal
proceedings. Despite their current limitations, these technologies may offer valuable insights
when used alongside existing methods for assessing risk and truthfulness in legal settings.
These authors, while calling such programs useful, also express their opinion about the impact
of such mechanisms on human rights. According to them, Neurotechnology presents profound
implications for human rights, yet international law lacks explicit references to neuroscience.
Unlike genetic advancements, which prompted the development of standards like the Universal
Declaration on the Human Genome and Human Rights and the International Declaration on
Human Genetic Data, neurotechnology remains largely unaddressed. However, the historical
adaptation of human rights law to genetic technology suggests a similar evolution may occur
with neurotechnology. As neurodevices become more sensitive and accessible, new rights may
emerge or existing ones may evolve to address ethical and legal challenges. This parallels the
historical development of human rights in response to emerging societal issues.
Although the arguments presented by the authors are accepted, there are issues that should be
noted. According to us, while the argument that neurotechnology presents profound
implications for human rights is valid, it overlooks the potential benefits that advancements in
this field could bring to legal frameworks. The emerging field of neurolaw suggests that a
deeper understanding of the brain could lead to more effective legal processes and fairer
outcomes. For example, brain imaging technologies offer promise for improving decisionmaking in criminal justice by aiding in determining criminal responsibility and assessing the
risk of reoffending. Similarly, these technologies could be valuable in civil law cases, such as
evaluating contractual capacity or assessing the severity of pain in compensation claims.
Research, such as the study by Aharoni et al. (2013), demonstrates the potential of using fMRI
scans to predict recidivism among released prisoners based on brain activity patterns. While
concerns about reliability and generalizability exist, the ongoing development and refinement
of these technologies may address these issues over time. Additionally, other
neurotechnologies like lie detectors and mental decoders, despite their current limitations, may
offer valuable insights when used alongside existing methods for assessing risk and
truthfulness in legal settings.
Moreover, the integration of neurotechnology into legal processes could lead to more equitable
outcomes by providing objective measures of cognitive function or emotional state, potentially
reducing biases inherent in traditional legal decision-making. While it is crucial to address
ethical and human rights concerns associated with the use of neurotechnology in legal contexts,
dismissing its potential benefits outright overlooks opportunities for enhancing the fairness and
effectiveness of the legal system. Therefore, rather than solely focusing on the potential risks,
it is essential to consider how neurotechnology can be ethically and responsibly integrated into
legal frameworks to promote justice and uphold human rights.
The relationship between data obtained using neurotechnology and the personal rights and
freedoms of citizens need further research and clarification (Rainey et al., 2019). The legal
regulation of research and dissemination of such information at the legislative level varies
across different jurisdictions, each taking a different stance. In general, although the use of the
concept of neurolawv is a little early, as mentioned above, we are currently witnessing its
development within various legal fields - intellectual property law, criminal law, etc. In order
to protect individuals from such cases, the use of such information should be considered as an
action against information security. According to the Law of the Republic of Azerbaijan on
Information, informatization and information protection “13-2.3.9. information that is insulting
or slanderous, as well as information that violates privacy;” The owner of the Internet
information resource and its domain name or the user of the information-telecommunication
network shall not allow the placement of information that is prohibited to be disseminated in
that information resource (information-telecommunication network). For advertising only,
according to the law of the Republic of Azerbaijan on advertising, the purpose of the control
of advertising activity is to ensure the interests of advertising subjects and the fulfillment of
the requirements of this Law, including stopping the broadcast of advertising that does not
meet the requirements of this Law, instructions to the subjects of advertising activity that
must be implemented in relation to the requirements of this Law is to give. In the Republic
of Azerbaijan, state control over advertising (except outdoor advertising) is carried out by
the relevant executive power body, and control in the field of outdoor advertising is carried
out by the institution created by the relevant executive power body. If we look at another
country, In the United States, there is the Federal Trade Commission (FTC), a state authority
that oversees advertising activities, and is responsible for inter- preting misleading advertising,
surreptitious ad- vertising, and regulating unfair competition practices.
In conclusion, the rapid advancement of artificial intelligence has led to its pervasive
integration into advertising, transforming the landscape of digital marketing. As AI continues
to evolve, it presents both opportunities and challenges that necessitate robust legal frameworks
to ensure responsible use and protect individual rights.
Moreover, the emergence of neurotechnology in advertising raises complex ethical and legal
questions regarding privacy, consent, and human rights. While these technologies offer insights
into consumer behavior, their use must be carefully regulated to safeguard against potential
abuses and infringement of personal liberties.
Moving forward, it is imperative for lawmakers to stay abreast of technological developments
and enact legislation that balances innovation with ethical considerations. Collaborative efforts
between governments, industry stakeholders, and advocacy groups are essential to establish
clear guidelines for the responsible implementation of AI and neurotechnology in advertising.
Next week, we will delve deeper into the legal implications of these emerging technologies and
explore strategies for ensuring transparency, accountability, and protection of individual rights
in the ever-evolving landscape of digital advertising.
OUTDOOR ADVERTİSİNG AND AI
In our previous article, we delved into the fundamental principles and legal frameworks
surrounding the integration of artificial intelligence in advertising. Exploring the realm of
neurotechnologies in this context, we uncovered various methodologies employed.
Moreover, we navigated through the diverse spectrum of opinions prevalent in the literature.
While some proponents advocate for the invaluable insights into human behavior facilitated
by such technologies, others critique their usage, drawing a line between humans and mere
animals. This latter group often highlights ethical concerns, contending that such practices
contradict fundamental values and may not align with legal statutes. Nevertheless, within the
literature, numerous authors oppose such a legal approach. They endeavor to validate their
utilization of these devices by presenting favorable instances linked to their application in
criminal, civil, and other proceedings. However, as underscored in our preceding article, no
case should serve as grounds for curtailing an individual's personal rights in this manner. For
those curious about the connection between this issue and advertising and artificial
intelligence, I urge you to consult my prior post, as this current installment is a direct
continuation.
The pervasive integration of artificial intelligence is unmistakably evident in the realm of
advertising. Its adoption is increasingly favored owing to its user-friendly nature and notably
superior creative prowess compared to that of a conventional human. In outdoor advertXsXng,
there's a notXceable shXft towards XnnovatXve methods coupled wXth modern applXcatXons,
offerXng effXcXent solutXons for both advertXsXng agencXes and publXshers, satXsfyXng theXr needs.
PartXcularly, agencXes employXng 'GuerXlla MarketXng' technXques are seekXng low-cost
applXcatXons, where the power of dXgXtal desXgns and creatXvXty frequently shXnes through such
marketXng approaches. Moreover, these advertXsements can effectXvely engage the target
audXence. The rXse Xn the number of fXrms rentXng ad space contrXbutes to competXtXve capacXty
through XnnovatXve methods, enabled by frequent advertXsements Xn suXtable condXtXons. To
contXnually provXde opportunXtXes for new Xdeas and meet the demands of the dXgXtal age, close
attentXon must be paXd to dXgXtal technology, and advertXsXng solutXons must be made accessXble
to artXsts or desXgners strXvXng for self-Xmprovement.
As a result of its ability to utilize cheaper labor and require less funding, advertisements
created through artificial intelligence have begun to be deployed in outdoor spaces, much
like traditional advertisements. Naturally, this development has sparked discussions. In
standard situations, regulations regarding outdoor advertising permissions are clearly
outlined in legislation. For instance, in the Republic of Azerbaijan, the law on advertising
specifies that "control in the realm of outdoor advertising is overseen by an institution
established by the relevant executive authority." Here, the emphasis lies on the
implementation of regulations in the advertising sector, considering the public interest.
Moreover, when it comes to advertisements in open spaces, the responsibility for regulating
such affairs falls upon the relevant executive body. Permits required for such advertisements
are dictated by the guidelines governing ad placement in open spaces and the enforcement of
control in this domain.
However, does the regulation of online outdoor advertising facilitated by artificial
intelligence abide by these same rules?
To address this, let's delve into the fundamental
principles outlined in the regulations. According to these guidelines, outdoor advertising
encompasses promotions displayed directly or through carriers on various outdoor surfaces
such as land areas, building facades (including walls and fences), installations, roofs, doors,
windows, showcases, and outdoor equipment like highway parking lots and underpasses. It
also extends to unconventional mediums like balloons, aerostats, and airships. A crucial
aspect is the requirement for physical placement on buildings and structures, emphasizing a
tangible presence. This criterion primarily serves the interests of public welfare and also
benefits entrepreneurs through orderly regulation. But does outdoor advertising generated by
artificial intelligence fall within the purview of these regulations? To delve into the realm of
outdoor advertising in the context of artificial intelligence, it's crucial to understand the
concept itself. Outdoor advertising with AI involves leveraging artificial intelligence
technologies to enhance, target, and evaluate the effectiveness of advertisements displayed
in outdoor settings. Typically, this entails capturing video, graphic images, or other content
in an open environment, which is then utilized online to deploy AI-driven ads. These
advertisements often take the form of 3D visuals, rendering them with a realistic effect.
However, the distinction arises when considering whether these ads are genuinely
implemented in outdoor spaces or if they retain their online elements. This raises the question
of whether they can be categorized as outdoor advertising or not. Previously, we discussed
outdoor advertisements, but those generated by artificial intelligence extend beyond this realm.
Let's consider the legal framework in another country. In the Republic of Turkey, a fine of
12,231,507 Turkish Lira was imposed for advertisements created by artificial intelligence. Out
of 138 cases, 120 were found to be in violation of regulations, resulting in penalties including
suspension of the said advertising and commercial applications. However, such advertisements
are increasingly prevalent, particularly on social media platforms, where traditional
commercial
advertising
of
alcoholic
beverages
is
prohibited.
In thXs context, Xt was dXscovered that an alcoholXc beverage, whose advertXsXng Xs prohXbXted,
was beXng promoted through the use of slogans assocXated wXth the product, wXthout dXrectly
featurXng the product name or Xmage Xn the decor. The content was desXgned Xn a conversatXonal
format, and as a result, admXnXstratXve sanctXons were Xmposed on these covert advertXsements.
AddXtXonally, admXnXstratXve sanctXons were Xssued by the AdvertXsXng Board durXng thXs
month's board meetXng, targetXng rankXng results that manXpulate consumer perceptXon. ThXs
decXsXon was made because the advertXsXng content related to the rankXng results faXled to meet
the crXterXa of beXng clear and understandable Xn a manner that could potentXally exploXt the
perceptXon of the average consumer. However, it's worth noting the absence of any reference
to open advertisements generated by artificial intelligence. Additionally, there's no mention of
artificial intelligence in the regulations set forth by the Istanbul Metropolitan Municipality,
specifically in the ADVERTISING, PROMOTION, AND PROMOTION REGULATION. The
stated purpose of these regulations is to oversee advertising, announcements, promotional
activities, and similar endeavors within the boundaries of Istanbul Province. They aim to
enhance urban aesthetics by addressing the visual clutter caused by such activities and
establishing guidelines for individuals, entities, and public institutions involved in these
practices. The focus on image pollution and urban aesthetics primarily pertains to visual
advertisements, aligning with similar legislation in the Republic of Azerbaijan. However,
neither set of regulations covers issues related to AI outdoor advertising or AI-generated
outdoor advertisements.
In conclusion, the integration of artificial intelligence (AI) into outdoor advertising is a
burgeoning trend, offering innovative solutions and opportunities for advertisers and
marketers. While traditional regulations govern outdoor advertising, there's a notable absence
of specific guidelines addressing AI-generated advertisements in many jurisdictions. This gap
in regulation raises important questions about the classification, oversight, and ethical
implications of AI-driven outdoor advertising.
The use of AI in outdoor advertising presents unique challenges and opportunities, from
enhancing creativity and targeting capabilities to raising concerns about privacy,
transparency, and regulatory compliance. As AI technology continues to advance and its
applications in advertising evolve, policymakers, regulators, and industry stakeholders must
collaborate to develop clear and comprehensive frameworks that address these complexities.
Moreover, as demonstrated by recent cases involving AI-generated advertisements, there's a
pressing need for increased vigilance and enforcement to ensure compliance with existing
regulations and ethical standards. This includes monitoring online platforms where AI-driven
advertisements may circumvent traditional advertising restrictions and exploit consumer
perceptions.
In navigating the intersection of outdoor advertising and AI, it is imperative to balance
innovation and consumer protection while upholding the integrity and fairness of advertising
practices. By addressing these challenges proactively and collaboratively, we can foster a
regulatory environment that supports responsible and effective AI-driven advertising in
outdoor spaces.
PATENT RIGHTS OF AI
Introduction
“Artificial intelligence (AI) is one of the most critical technologies of our era.” “In recent years,
patent applications directed to Al technologies have grown significantly, reflecting the
increased importance that businesses are placing on such inventions.” Patents will be awarded
for 'any innovations across all technological domains, as long as they are novel, demonstrate
inventiveness, and are applicable for industrial use.' The capacity to market and protect
inventions harmonizes seamlessly with the overall goals of artificial intelligence.
The integration of AI into patent law brings forth a host of challenges. The functions achievable
by computers through AI have become progressively intricate; however, their scope remains
narrowly defined in terms of purpose. The substantial background knowledge possessed by
computers introduces an additional level of complexity to the assessment of patent eligibility,
prompting a reconsideration of the current standards.
In the legal realm, AI's increasing prominence prompts contemplation on the future role of legal
professionals. Addressing patent challenges related to artificial intelligence and inventions in
factory automation, emphasizing the transformative possibilities and obstacles presented by
AI. Anticipations run high that this technology will enhance the capacity to provide improved
services to clients. Nevertheless, there is a degree of doubt among certain individuals who are
concerned that computers might eventually assume a substantial portion of the responsibilities
currently handled by legal professionals.
As AI's capabilities burgeon, a legal quandary arises, questioning the compatibility of AI
inventions with existing patent laws. With the rising prevalence of AI, a legal quandary has
emerged regarding patent regulations, making it increasingly difficult to determine the
patentability of inventions involving artificial intelligence. Examining the obstacles,
possibilities, and consequences for future innovation and intellectual property is crucial. In the
nexus of AI and intellectual property, the significance of patent rights is pivotal, fostering
innovation and safeguarding inventive pursuits. Patents grant their owner an exclusive
privilege to market, emphasizing the crucial function patents serve in promoting the exploration
of innovative concepts. The integration of Artificial Intelligence (AI) with Intellectual Property
(IP) has the potential to enhance the processes of IP creation. Indeed, AI is currently providing
tangible benefits to businesses facing challenging and intricate problems.
The essay will generally explore different perspectives on artificial intelligence-related patent
issues. Various views on the ownership of rights in artificial intelligence and the emerging
trends towards the possibility of these views changing will be examined in this essay. An
attempt will be made to determine the place of artificial intelligence in patent law.
Literature Review
The historical context of patent law and its evolution, as outlined by W. Michael Schuster
(2018), establishes the foundation for understanding the rights of inventors. Schuster
emphasizes the traditional definition of an "inventor" and their right to obtain a patent.
Schuster's (2018) contribution to the literature defines AI as any technology replicating human
intelligence. He asserts that AI should not be considered an entity with personhood rights under
patent law. However, contrasting this view, the European Parliament report (2020) highlights
policymakers' concerns about hindering AI development by not recognizing AI as an inventor.
This emphasizes the delicate balance required between fostering innovation and ensuring
societal benefits.
Fraser's (2016) research focuses on the possibility that artificial intelligence may surpass
human capabilities and suggests that if patent rights are granted to such entities (artificial
intelligence), there should be a general reconsideration of patent eligibility criteria. We believe
that Fraser has approached this topic more cautiously, aiming to highlight the potential changes
that granting rights to artificial intelligence might bring about. Our other author, Blok (2017),
argues that the ability to create, in general, may not be sufficient for obtaining a patent. Blok,
who holds a relatively more conservative view compared to Fraser, explores the rights that
artificial intelligence may possess, examining whether they align with current legislation and
understandings. He highlights that the issue is not clarified in the European Patent Convention
by investigating whether the rights of artificial intelligence conform to existing legislation and
understandings.
The importance of regulating AI design to ensure safety and prevent harm is underlined by
Lines and Lucivero (2014). “This perspective emphasizes the need for aligning AI systems
with rules and standards for responsible use, contributing to the broader discussion on the
ethical considerations of AI patents.” A serious weakness with this argument, however, is
that the potential benefits of AI, such as improved efficiency, economic growth, and
transformative solutions to societal problems, could be delayed or restricted. They may argue
that a more permissive regulatory environment can encourage innovation while still addressing
ethical considerations through guidelines that offer flexibility and adaptability.
Fenwick and Jurcys' caution against using exaggerated claims about AI capabilities to stifle
creativity (2023) introduces a different dimension. This opinion emphasizes the need for a
balanced approach in using AI tools for advancing digital culture, showcasing the multifaceted
nature of the discourse on AI in intellectual property. The results would seem to suggest that
the promotion of a measured and realistic evaluation of AI capabilities reduces the potential for
legal disputes and ethical dilemmas.
Stamatis (2019) underscores the significance of patenting AI to provide inventors with
compensation and protection against infringement, offering a practical perspective. This
opinion adds another layer to the discussion, emphasizing the potential benefits of patenting
AI in safeguarding intellectual property.
Nguyen's (2018) introduction of Artificial Intelligence Law as a field dealing with the rights
and liabilities arising from AI use introduces a legal framework. Garcia's optimism about AI's
role in the legal workplace aligns with Nguyen's legal framework, emphasizing the
augmentation of human professionals by AI rather than replacement. This positive perspective
complements the broader discussion on the benefits and implications of AI in various fields,
including law.
Patents are generally not available for certain facets of AI such as software. A critical inquiry
persists: Does patent protection extend to inventive concepts generated using AI? This
uncertainty arises from the evolving nature of AI and its applications, posing challenges to
traditional patent frameworks. As AI technologies advance, the legal system faces the task of
adapting to novel and intricate scenarios, prompting discussions on the boundaries of
patentability.
W. Michael Schuster, in "Artificial Intelligence and Patent Ownership," continues in this form
by emphasizing that the mere financing and preparation of conditions for the activity related to
an individual's invention in retrospect being recorded as his patent application is not suitable.
He underscores that it is a more complex process, stating: "The responsibility for an invention
may lie with a person, but without actual contribution to the invention of a new technology,
they may not be considered an inventor." According to his opinion, for someone to be
recognized as an inventor, they should have a close connection with the inventive process
during that process. In our view, Schuster's approach is an unparalleled example in shedding
light on the issue of artificial intelligence claiming patent ownership in an unfounded manner.
It is not appropriate for a synthetic intelligence possessing inventive capabilities to be deprived
of this right solely due to the lack of precise legal criteria.
In the ongoing "invention debate," there's a tendency to overestimate the capabilities of AI,
often conflating automation with autonomy. Marta Duque Lizarralde and Hector Axel
Contreras caution against deceptive claims that AI can autonomously complete the entire
inventive and patenting process without human intervention. It is crucial to differentiate
between the roles of AI in automation and the genuine autonomy required for inventive
processes.
Distinguishing between automation and true autonomy in the creative process is essential for a
nuanced understanding of AI's role in innovation. The theory of overestimating AI's capabilities
fails to make any useful predictions about misguided expectations and policy decisions,
emphasizing the need for a balanced and informed perspective.
Xiaowei Wei and Lili Wu, provide valuable insights into the conditions that render computerimplemented inventions compliant with patent laws. These requirements encompass the
technical interpretation of data manipulated by algorithms, a distinct technical connection
between the algorithm and the internal structure of the computer system, and solutions directed
at large-scale data in particular domains. The revision of guidelines reflects a recognition of
the unique challenges posed by AI-related inventions, necessitating a more nuanced approach
to patent examination. This proactive approach in revising guidelines demonstrates the legal
system's adaptability to emerging technologies, ensuring a thorough evaluation of patentability
criteria.
The costliness of the inventing process is a factor in patent defensibility, as highlighted by J.
Sherkow. According to Sherkow, the more expensive the inventing process, the more defensible
the patent grant, as it allows for the recovery of inventing costs. Sherkow's research observes
the intersection of economic interest with the interest in patenting, emphasizing the economic
nuances of intellectual property.
Case Studies: The DABUS Case
As we highlighted earlier, the increasing interest in intellectual property and the growing
utilization of artificial intelligence have brought forth discussions, particularly regarding the
existence of patent rights in connection with the intellectual property rights of artificial
intelligence. A notable case that brought this issue to the forefront involved Dr. Thaler's
applications, where AI was designated as the inventor, leading to rejections from the UK
Intellectual Property Office (UKIPO), the European Patent Office (EPO), and the United States
Patent and Trademark Office (USPTO). The main argument put forth was that the person
recognized as the inventor in the application must be a human being.
The discussions regarding this matter gained momentum in 2019 when a global legal team
submitted patent applications for two items generated by an AI system called Device for the
Autonomous Bootstrapping of Unified Sentience (DABUS), explicitly naming DABUS as the
creator. This move prompted legal scrutiny and triggered a lawsuit against the director of the
USPTO, challenging the rejection of the patent application and asserting that it introduced new,
inconsistent patentability requirements.
Ryan Abbott, a legal and health sciences professor and a participant in the case as a patent
attorney, underscored the fundamental concern:"If you have an invention or a patentable AI
output without a person who qualifies traditionally as an inventor, can you get a patent on it?".
The legal action seeks to obtain patents not solely for the particular products generated by AI
but, more importantly, to act as a precedent initiating discussions on how intellectual property
rights should be handled concerning inventions created by AI.
Regarding the issue, Huw Jones, the UKIPO’s deputy director, has stated, "Inventions created
by AI machines are likely to become more prevalent in the future, and there is a legitimate
question as to how or whether the patent system should handle such inventions."
“Considering the increasing significance of AI inventions, there is a pressing need for
legislative amendments to align patent laws with the contemporary technological landscape.”
One of the main problems in the DABUS case is the different perspectives of various
jurisdictions on the same issue. This case highlights nuanced problems in the field of artificial
intelligence and illustrates that different jurisdictions have different justifications for their
views. It is precisely for this reason that the approaches of different jurisdictions need to be
analyzed separately, and an appropriate approach should be demonstrated for each.
However, regardless of the varying requirements of different jurisdictions, the general
principles and basic principles of intellectual property law should not be overlooked. In
intellectual property law, there is no mention of the inventiveness of the creator being human
or not as a requirement for patentability. If the invention is novel and inventive, it can be the
basis for its registration as a patent. In cases where there is no specific requirement related to
the subject, it is difficult to determine the basis for the requirement that the person named as
the inventor in the patent application must be human.
Comparative Analysis
It would be appropriate to analyze the different approaches to patenting artificial intelligence
comparatively, as different jurisdictions encompass different perspectives and backgrounds.
On a global scale, the World Intellectual Property Organization defines artificial intelligence
as "a discipline of computer science that is aimed at developing machines and systems that can
carry out tasks considered to require human intelligence, with limited or no human
intervention." By providing such a understanding of artificial intelligence, the organization has
also endeavored to shed light on general principles related to the patentability of this
intelligence, contributing to clarifying concepts of ownership and innovation.
The U.S. patent landscape reflects a complex relationship with AI. While patents have been
granted for technologies exclusively designed by software, the lack of disclosure about AI's
role raises concerns. Recently, a decision by the USPTO has firmly declared that an Al cannot
be listed as the sole inventor on a patent application, which seems to settle the issue until future
changes to the law. The absence of clear regulations addressing AI patents in the U.S. adds
ambiguity, with recent decisions reinforcing that AI cannot be listed as the sole inventor,
leaving room for future legal developments. (W. Michael Schuster, 2018; )
“China's approach to AI patents involves treating AI more as a tool than an author.” The original
developers who crafted the AI contributed the primary creative effort during its inception. Even
though the AI subsequently generated the article independently and was temporarily separated
from its creators, the initial creative input persisted. The country's examination attitude is
generally favorable, with a focus on patent eligibility for technical solutions. A patent in China
for an invention incorporating AI technology is achievable, provided it addresses a technical
problem rather than an abstract concept and is appropriately managed. The substantial number
of granted patents attests to the importance of adhering to these criteria. The applicant should
consider the technical area by selecting particular terms and clarify the integration of an AI
idea and a practical application and effects thereof in the spesicifaction.
This difference between the US and China relates to different manners of construing a claim.
In the US, during exami- nation, a claim is construed before its objective is determined.
However, in China, a claim is construed under its objective, and as such, some non-eligible
subject matter will naturally be excluded during construction.
Future Trends and Challenges
The landscape of AI patent law is dynamic and multifaceted, presenting both opportunities and
challenges. Scholars provide valuable insights into potential trajectories and issues that may
shape the future of AI patents.
Examining the patent examination process and its alignment with technical developments is
essential. At present, the evaluation of patents is trailing behind advancements in technology.
It will take some time for examiners to comprehend that Artificial Intelligence is not merely an
abstract concept but indeed represents a technical solution.
Some authors believe that “given the current level of software and mathematical support for
the development of artificial intelligence, there is also no urgent need (at least now and in the
foreseeable future) to recognize artificial intelligence as a full-fledged (full-fledged, legal
entity) subject of copyright and patent rights, intellectual property rights in general.” Yet, the
authors overlook the potential negative impacts of such an approach, not only on intellectual
property itself but also on the economic and other interests associated with patents.
Developing a robust intellectual property (IP) strategy is crucial for companies operating in the
AI sector. The companies should consider what part of the AI puzzle a patentable idea falls
into and to determine the tolerances of adjusting the target claim scope to navigate rejections
by patent offices. For companies contracts play a pivotal role in protecting training datasets
and AI-generated outputs ineligible for IP protection. Developing a robust intellectual property
(IP) strategy is crucial to reap the benefits of financial and research investments in artificial
intelligence (AI) and gain a competitive edge over rivals.
Standardization of AI technologies is proposed as a universal solution to legal challenges . The
challenges arising from the lack of transparency in the decision-making process of AI systems,
restricting their involvement in tasks requiring increased responsibility. Currently, AI lacks the
ability to apply skill, effort, and judgment or participate in intellectual contributions.
The definition of inventorship in the context of AI-generated content is another area of concern.
Chikhaoui and Mehar (2020) highlight challenges arising from AI systems creating content
traditionally associated with human intellectual contributions. A constructive initiative would
involve countries developing a consistent legal framework that acknowledges inventions
generated by AI or provides clarification regarding the status of such innovations.. Ayoubi
(2022) suggests eliminating the conception requirement and redefining the term "inventor" in
alignment with congressional intent.
One crucial aspect to consider is the behavior of AI systems and the potential liability
associated with their actions. If it was anticipated that the AI could exhibit infringing behavior,
culpability might be established.
The legislature should similarly think about other accessible systems for inventions and
securing Al inventions (for example laws on trademark or copyrights) to help evaluate whether
any of the patent law's subject matter qualification can be improved through different methods.
Moreover, assessing each case on its own benefits, existing legal systems for inventions should
then allow to decently figure out who should be an inventor for patentable inventions
considered in entire or to a limited extent by an AI.
As technology advances, patent law struggles to adapt. Decisions must be made on whether AI
systems should be deemed patentable, reflecting the ongoing challenges of integrating rapidly
evolving technologies into existing legal frameworks.
Conclusion
The discourse on whether artificial intelligence (AI) should be considered as a patent holder is
complex and multifaceted. The essay has explored various perspectives from scholars such as
Schuster, Fraser, Blok, Lines, Fenwick, Stamatis, and Garcia, shedding light on the intricate
nature of this debate. The DABUS case serves as a pivotal example, illustrating the challenges
in recognizing AI as an inventor and the varying perspectives across different jurisdictions.
The literature review has provided insights into historical contexts, concerns about AI rights,
and the delicate balance needed between innovation and societal benefits. The essay has delved
into the nuances of patent law, emphasizing the need for legislative amendments to
accommodate the advancements in AI. The comparison between the U.S. and China's
approaches has highlighted the diversity of perspectives on AI patents globally.
Case studies, particularly the DABUS case, have underscored the urgency for legislative
adjustments to align patent laws with the evolving technological landscape. The ongoing
challenges in integrating AI into existing legal frameworks require careful consideration, and
the essay has touched upon future trends and potential solutions. The dynamic nature of AI
patent law presents both opportunities and challenges, demanding a nuanced and adaptive
approach.
In the face of these complexities, it is evident that patent laws need reassessment to
accommodate the unique characteristics of AI inventions. The future trajectory of AI patent law
will depend on how legal systems adapt to the evolving technology and whether they can strike
a balance between fostering innovation and addressing ethical considerations. As technology
continues to advance, policymakers and legal professionals must navigate the intricate
landscape of AI patentability, ensuring that intellectual property laws remain relevant and
effective in promoting innovation while safeguarding societal interests.
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