Attribution of Personality Legal to the Intelligences Artificial (IA): One possible solution to the limbo of the Rights Authorial

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1. INTRODUCTION

The rapid advancement of Artificial Intelligence (AI) technologies, as exemplified by innovations such as ChatGPT, Gemini, Google Bard, Midjourney, and Dalle, is bringing substantial transformations to society and the global economy. These technologies are becoming increasingly integrated into a variety of sectors and human activities, bringing a range of benefits but also significant challenges in the contemporary context. A particularly pertinent question that arises in this scenario is that of copyright related to AI-generated works, a discussion that requires careful reflection and appropriate legal solutions.

Currently, the legislation of copyright In most countries, including Brazil, it was conceived and implemented in an era when humans were the only recognized creators. However, the increasing involvement of AIs in the creative process, whether operating autonomously or in collaboration with humans, raises critical questions about the adequacy of existing laws and the emerging need for revisions and adaptations to embrace this new paradigm.

In this context, this article focuses on the proposal to grant legal personality to certain AIs under Brazilian law. This study seeks to explore how such attribution could contribute to legal certainty and foster innovation in the field of artificial intelligence. To achieve this objective, a comprehensive integrative literature review will be conducted, including both national and international studies and debates, as well as a detailed comparative analysis of relevant legislation and case law.

Granting legal personality to AIs, by legally recognizing their creations, would imply granting rights and duties to these non-human entities, similar to the treatment given to legal entities, such as companies and organizations. This research aims to propose and investigate the granting of legal personality to Artificial Intelligences (AIs) and the impacts of this grant on the laws of copyrightThe central focus is to explore how legal personality for AIs can be defined and what its limits and scope would be, especially in terms of rights and obligations. At the same time, this study aims to understand how this attribution influences current laws. copyright and whether legislative reform is necessary to accommodate this new reality.

The main question guiding this study is: “How can legal personality be defined for AIs and what are the impacts of this definition on copyright?” This seeks to understand not only the legal scope and implications of the legal personality of AIs, but also to analyze the necessary changes in copyright laws. copyright to integrate AI creations.

The specific objectives include: examining the theoretical and legal bases for granting legal personality to AIs; identifying the legal and ethical implications of this attribution; and assessing necessary reforms in the laws of copyright to encompass AI creations. The methodology adopted is exploratory and analytical, based on an integrative literature review and comparative analysis of legislation and case law. Sources include research journals, studies, and articles from databases such as Scielo and Google Scholar, as well as books and e-books specializing in AI law and intellectual property. The main descriptors will be "Legal Personality," "Artificial Intelligence," "Copyright” and “Legislative Changes”, combined by the Boolean operators “AND” and/or “OR”.

For the selection of studies, inclusion criteria will be applied such as publications between 2010 and 2023 that address the legal personality of AIs, impacts on copyright and the need for legislative changes. Studies with insufficient methodologies or lacking a robust theoretical basis will be excluded. The aim is to analyze a broad set of studies that offer insights into the interaction between the legal personality of AIs and intellectual property law.

Content Analysis will be used to examine the accessed materials, allowing them to be classified into relevant themes or categories to understand the legal implications of AI legal personality. This method will follow the discovery and hypothesis testing approaches in the context of AI and intellectual property law.

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2. ARTIFICIAL INTELLIGENCE AND ITS APPLICATIONS

According to the Organization for Economic Cooperation and Development (OECD), artificial intelligence (AI) is a machine-based system that acts on its environment by generating solutions, predictions, recommendations, or decisions to achieve specific objectives. AI operates by collecting data and information from both machines and humans to interpret real or simulated environments. It abstracts these insights into models using automated analysis and applies inferences from these models to propose alternative courses of action.

In the United Kingdom, in 1964, the Society for the Study of Artificial Intelligence and Behavior Simulation was created. [1] . Then, in 1969, the first scientific event, the International Joint Conference on AI, was held. [2]. Thus, taking all these aspects into account, it brings common definitions to the scale of the union of cyber-physical systems, autonomous systems, intelligent autonomous robots and their subcategories, taking into account the following characteristics for the intelligent robot: (i) acquisition of autonomy through sensors and/or the exchange of data with its environment (interconnectivity) and the exchange and analysis of this data; (ii) self-learning through experience and interaction (optional criterion); (iii) minimal physical support; (iv) adaptation of its behavior and actions to the environment; and (v) nonexistence of life in the biological sense of the term.

In this vein, one of the main types of AI is Machine Learning, Machine learning, literally translated, means machine learning. Unlike the input and output scheme of an algorithm, the aim is to teach the computer what we want it to do automatically. Then, we input the data and the desired result, and the algorithm is produced that transforms this information into the desired result. [3]In practice, it is a revolution, since we teach computers how to write their own algorithms [4]. With the machine learning, programmers no longer dictate the rules [5]. Instead, a neural network is created that learns these rules on its own. [6]. An example of this is that smartphones today they come with standard features like voice recognition and image identification, all done by machine learning [7].

It should be noted that the machine learning is a powerful weapon that can lead to advances in various areas, since with sufficient data, millions of lines of code can be produced for different problems. Domingos [8] further highlights that machine learning can be called in various ways, such as data science, self-organizing systems, pattern recognition, statistical modeling, data mining, knowledge discovery, predictive analytics, adaptive systems, among others. machine learning works as a scientific methodology, with testing and discarding or refining hypotheses [9]However, while a scientist might spend a lifetime testing and debating this hypothesis, the computer can do it in a fraction of a second and, therefore, has revolutionized both science and business. [10].

Furthermore, the deep learning is the closest we have to effective artificial intelligence, since it is an evolution of machine learning, when seeking machine learning through high-level algorithms, imitating the neural network of the human brain [11]. The deep learning works with an immense amount of data, which is conventionally called big data, being able to recognize images, speech, processing natural language and learning to perform extremely advanced tasks without human interference [12]. The big data consists of a gigantic and complex data set, coming from new data sources [13]. The volume of data is so gigantic that the software (computer programs) standards that we have today cannot process and manage them [14]. You can define the big data with the idea of greater variety of data, ever-increasing speed, with increasing volumes, data with intrinsic value, and finally, plausible data [15].

The function of big data is to integrate, manage and analyze this stored data, being used for product development, predictive maintenance, improved customer experience, fraud and compliance, machine learning, deep learning, operational efficiency and promotion of innovation [16]. Although new technologies have been developed to handle the absurd amount of data present on the server, companies are facing serious problems, as the volume of data has doubled in size every two years. [17].

The ultimate goal is to build an artificial intelligence that resembles human intelligence, which is often referred to as “Artificial General Intelligence” or AGI. [18]. Some experts believe that the machine learning and the deep learning will eventually lead us to AGI [19]However, we are still far from this scenario, with major pieces missing to make this viable. [20]. Domingos states that the machine learning was what elected the president of the United States in the 2012 election [21]. President Obama hired Rayid Ghani, an expert in machine learning, as chief scientist of his campaign [22]. Ghani launched one of the largest analysis operations in political history, consolidating all voter information into a single database, combining everything they could gather from social media, marketing, and other sources. [23].

They were able to predict four things for each voter: the likelihood that the voter would support Obama, the likelihood that the voter would turn out to poll, the likelihood that the voter would respond to campaign reminders to do so, and the likelihood that the voter would change their mind based on a change of opinion on a specific issue. [24]. So, based on these voter models, every night the campaign ran 66,000 simulations of the election, using the results to direct its efforts. [25]One of the worst things that can happen is to see your opponent make moves that you don't understand and don't know what to do about until it's too late. [26]. Mitt Romney, Obama's rival in the election, saw his opponent buying ads on certain cable stations in specific cities, but he didn't know why. [27]Obama ended up winning all the swing states except North Carolina, by larger margins than even the most reputable and reliable public opinion experts predicted. [28].

The example of Obama's 2012 campaign vividly illustrates the power of artificial intelligence in high-level politics. The effectiveness of machine learning in predicting voting behaviors and preferences demonstrates that, today, it is virtually unthinkable to conduct a significant political campaign without AI support. This case highlights how data analysis and technology can be decisive in decision-making.

The machine, when defined as artificial intelligence (AI), symbolizes a repository of information and norms from the individuals who configured it, making it an autonomous system based on that information that was given to it. [29]. Within moral debates, autonomy is seen as the rational capacity to make unforced decisions based on available information. [30]. The preponderant difference today between human beings and machines is the critical sense that human beings have, to adapt their behavior according to their beliefs. [31]. The machine will depend on a change in its codes and parameters to have a new action pattern [32].

The machine will have the ethical and behavioral standards of those who configured it [33]. It is necessary to observe the people who are part of the social system in the workplace to understand the values present there and which will later be inserted into the machine [34].

Because of this, Ricardo Cappra [35] argues that ethics committees should be created within technology companies to understand and establish premises and principles, which will be embedded into the machine through code. A structured governance model must exist that oversees and engages in dialogue from the conception phase through to the implementation of this intelligent system. [36].

Ethical systems are made up of similar components, whether in a social or technological environment: premises, rules, environment, culture, control, updating and support. [37]When these parts are not properly monitored and integrated, the risk of behavioral failure in artificial intelligence increases. [38].

AI has been used to speed up large production processes, minimizing errors and optimizing time for companies. [39]In the marketing environment, AI has been increasingly used to interpret data and direct information, ensuring more assertive communications and better campaigns. [40]When we access Netflix, the suggestions for movies, series, and documentaries are not the same for each person, but are managed by an AI that understands each user's personal tastes and intelligently curates the content. [41].

Along these lines, Adidas began suggesting clothing combinations in its online store based on customers' searches for an individual product, using AI. [42]. Through data analysis, the company better understands consumer preferences and displays all available options, without the need for consumer research, making the experience increasingly personalized. [43]. Adidas saw an increase in sales after implementing AI in its e-commerce [44].

According to a survey by Accenture, in the next 15 years, AI in organizations will be responsible for 40% of business productivity, which is already indisputable today, given the benefits we can see day after day. [45]Artificial intelligence is a very important aspect of the so-called Digital Transformation, as businesses guided by it experience a huge improvement in aspects such as business vision, customer satisfaction, and operations as a whole. [46].

According to a study conducted by ManageEngine, called the 2021 Digital Readiness Survey, with qualified executives and technology professionals on the impact of remote work on the use of IT security strategies, cloud, and AI-driven analytical technologies, the result was that 86% of companies increased the use of artificial intelligence in operations in the last two years. [47]

In this same study, 62% seek to increase the company's operational efficiency, 63% of professionals bet on AI to better develop commercial analysis and 60% want a higher customer satisfaction rate. [48]AI has the ability to automate repetitive tasks with excellent accuracy, freeing up time for employees to focus on other, more relevant activities. [49].

The agency Sapio Research for Hult EF Corporate Education conducted an interview with 1,188 professionals in leadership positions in multinational companies from 16 different countries, identifying that the main skills needed for business success today are creativity, leadership, strategic decision-making and, finally, data analysis [50].

An example of the monstrous power that artificial intelligences are acquiring is GPT-3, launched in June 2020, which has the ability to converse with humans, generate convincing sentences and even fill in codes automatically, possessing an extraordinary neural network, larger than any other ever built. [51]This performance leap didn't come from better algorithms, as it uses a type of neural network invented by Google in 2017 called Transformer, but from its increase in absolute size. [52].

The more parameters an AI model has, the more information it can absorb from the training data and the more accurate its predictions will be. [53]. GPT-3 has 175 billion defined parameters, ten times more than its predecessor, GPT-2 [54]. Also in 2021, two other AIs were launched, which surpassed the number of defined parameters of GPT-3: Jurassic-1, created by startup AI21 Labs, with 178 billion parameters; Gopher, created by DeepMind, with 280 billion parameters; Megatron-Turing NLG, which has 530 billion parameters; and finally, Google's Switch-Transformer and GLaM models, with 1 trillion and 1.2 trillion parameters. [55] respectively.

This trend isn't unique to the United States. In 2021, China, through the Beijing AI Academy, announced Wu Dao 2.0, with 1.75 trillion established parameters. [56]Despite impressive results in recent years, researchers and scientists cannot explain why increasing parameters leads to better performance, nor do they have a solution for all the toxic language, misinformation, and prejudice these machines pick up and then reproduce. [57].

In this way, solutions may come from the BigScience initiative, a consortium created by the AI company Hugging Face, which brought together 500 researchers from large technology companies to create and study an open-source language model. [58].

Google's Pixel 6 is the first device to feature an exclusive artificial intelligence chip alongside the standard cell phone processor. [59]. The iPhone, in recent years, has featured what Apple calls a “neural engine,” dedicated to AI [60]. Both chips are tailor-made for running computations and training models. machine learning on mobile devices [61]. The Pixel 6 chip was designed differently than traditional chips, which strive for ultra-fast and accurate calculations, focusing more on the high-volume, low-precision calculations that neural networks need. [62].

We haven't advanced much with computers in the last 40, 50 years, just making them smaller and faster, but still being boxes with processors that execute coded instructions from humans. [63]. According to the Massachusetts Institute of Technology [64], the current development of AIs can provide at least three aspects of change:

• The ways in which computers are produced;
• The way they are programmed;
• How we make use of them.

Models of deep learning require a large number of less precise calculations to be performed at the same time, that is, a new type of chip that allows data to move as quickly as possible, ensuring that it is always available when needed [65]. Thus, chip manufacturers such as Nvidia, Intel and ARM are committed to developing hardware tailored for AI [66]. AI itself is helping design your computing infrastructure [67].

Google in 2020 used an AI called reinforcement learning to learn to solve tasks through trial and error, to create a new chip that generated strange new designs that no human could design, but that worked [68]This type of AI could one day build more efficient and better chips. [69].

Chris Bishop, director of Microsoft Research in the UK, explains that for the last 40 years, we have been programming computers, and that for the next 40, we will just train them [70]He also explains that the major advances in the coming decades will come in molecular simulation, training computers to manipulate properties of matter, creating global changes in energy use, medicine, manufacturing, and food production. [71].

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3. INTELLECTUAL PROPERTY AND ARTIFICIAL INTELLIGENCE

The issue of intellectual property and artificial intelligence (AI) is an emerging and complex topic that has generated intense debate and legal challenges. The legislation copyright, both nationally and internationally, primarily protects works derived from human creativity, leaving a gap for works produced by AI. This legislative vacuum creates uncertainty and economic losses for companies investing in AI technologies, since works generated by these systems do not yet have specific protection rules and run the risk of being reproduced without restrictions.

Legally, the Berne Convention of 1886, adopted by more than 160 countries, including Brazil, focuses on protecting the rights of authors and publishers of works, but presumes that the author is a human being. Thus, works created by non-human agents, such as AI, challenge this traditional understanding.

In this sense, the Law 9.610/1998 establishes that protected intellectual works, according to the understanding of "creations of the spirit," are all those manifestations that emanate from the human intellect, regardless of the medium or support used for their expression, be it physical or abstract, already existing or perhaps to be conceived in the future. Among such manifestations, the following stand out:

I – the texts of literary, artistic or scientific works;

II – conferences, speeches, sermons and other works of the same nature;

III – dramatic and dramatic-musical works;

IV – choreographic and pantomimic works, the stage performance of which is recorded in writing or in any other form;

V – musical compositions, whether or not they have lyrics;

VI – audiovisual works, with or without sound, including cinematographic works;

VII – photographic works and those produced by any process analogous to photography;

VIII – works of drawing, painting, engraving, sculpture, lithography and kinetic art;

IX – illustrations, geographical maps and other works of the same nature;

X – projects, sketches and plastic works concerning geography, engineering, topography, architecture, landscaping, scenography and science;

XI – adaptations, translations and other transformations of original works, presented as new intellectual creations;

XII – computer programs;

XIII – collections or compilations, anthologies, encyclopedias, dictionaries, databases and other works, which, by their selection, organization or arrangement of their content, constitute an intellectual creation.

The inspiration for this legislation in Brazil, dated 1973, which considered the copyright as a result of creations of the spirit, was the Copyright Law French law, in force since 1957, which conceptualized the “creation of the spirit” as a human manifestation. The Law 9.609/1998, which deals specifically with computer programs in Brazil, defines a computer program as an ordered sequence of instructions in natural or coded language, contained in a physical medium of any nature, the purpose of which is to enable the operation of automatic information processing machines, devices, instruments or peripheral equipment, based on digital or analog techniques, in a specific way.

However, it's worth noting that the 1998 legislation specifically does not address the issue of Artificial Intelligence (AI) and its creations. This represents a significant legal gap in several jurisdictions around the world, given that AI is a relatively recent technology. When we encounter works created entirely through AI, without any human intervention, a fundamental question arises: who owns the copyright? The AI's creator? The AI itself? And in situations of human intervention, even minimal, could the AI's creator claim authorship of the creation?

From the perspective of Copyright, traditionally, only human beings are considered capable of generating intellectual works, which include brands, industrial designs, inventions and artistic works [72]. This was debated in a court case in the United States, involving a dispute over the copyright of photographs taken by a monkey in Indonesia during a photo shoot conducted by photographer David Slater [73]. The court ruled that only human creations are protected by the Copyright [74].

After this incident, the United States Copyright Office established the requirement that the registration of intellectual works can only be carried out by human beings. [75]. Santos, Jabur and Ascenção also indicate that in France, since 1863, there were three jurisprudential currents that addressed the copyright of photographs: a chain denied the protection of copyright photographs, arguing that the camera simply reproduced the photographed object in a servile manner; another school of thought understood that the camera operator was the author of the resulting intellectual work; and a third school of thought recognized the possibility that a photograph could have an artistic character, but considered this assessment to be a matter to be decided on a case-by-case basis. [76].

However, in 1957 the French Copyright Law was enacted, defining photographs as intellectual works, provided they have an artistic or documentary character. [77]. These latter requirements were later removed by a law in 1985 [78]. In Paris, in the year 2000, it was decided that it would be copyright of the individual who created a musical composition with the help of software, provided that there was some human intervention in the creation, understanding that the computer program is merely a tool for the composer's use [79].

One of the suggested approaches is to attribute authorship to individuals or legal entities that used AI in the production of the work, making them the owners of the copyright [80]. In the UK, for example, the rights to works created by AI belong to the person who provided the means necessary for their creation. [81]. In contrast, Portugal keeps works created by AI in the public domain, since AI does not directly benefit from the value collected from the creation [82]​​.

A crucial aspect is AI auditing, which is essential to assess how data is handled by artificial intelligence. [83]. The audit may include data protection standards and copyright others, and it is important to verify the distortion of works that subsidize AI [84].

Furthermore, the use of copyrighted works in the machine learning process also raises questions. [85]. The Copyright Law prohibits the unauthorized use of works in any form, including inclusion in a database and storage on a computer. [86].

Internationally, the copyright are protected by the Berne Convention and other agreements, but the challenges posed by AI are still being outlined [87]. Multidisciplinary studies are essential to determine the parameters to be analyzed in the case of checking copyright to AI works [88]​​​​.

The Office of Copyright of the US, since early 2023, has initiated a program to examine the challenges presented by AI in the context of copyright law. This includes considering the scope of the copyright in works generated using AI tools and the use of copyrighted materials copyright in AI training. The Office's activities include public listening sessions and webinars to gather information on current technologies and their impact.

A notable case that brought these issues to the forefront is the dispute involving “A Recent Entrance to Paradise” by Stephen Thaler, a work allegedly created autonomously by AI, without any human creative input [89]. This case raised significant questions about whether AI-generated works can be considered for registration. copyright and, if not, whether such works should be treated as public domain, free for anyone to commercialize [90]. The case also addresses the broader implications for breach of copyright and the application of the Digital Millennium Copyright Act (DMCA) to AI-generated content [91].

The legal community is actively debating and exploring these issues, with various viewpoints and potential solutions being proposed. One approach suggests assigning the copyright to the human or legal entity that used AI to produce the work. However, this approach still leaves open questions about the degree of human involvement required for the work to be eligible. copyright and the processing of works generated entirely by AI.

This area of law is still in flux, with courts and legislators around the world struggling to adapt existing intellectual property frameworks to the realities of AI-generated creations. As AI technology continues to advance and its applications become more widespread, the legal system is likely to see significant developments in how AI-generated works are treated under the copyright law.

In Europe, the European Patent Office understood that under the terms of the European Patent Convention, the term inventor refers only to the human being, and that to have the status of inventor it is necessary to have a legal personality to exercise, and that simply giving a name to the machine does not grant it personality. [92]. In the same sense, the Patent Office in the United States understood that the exercise of the right to patent an invention is inherent only to human beings. [93]. Bhavsar-Jog, Arnstein and Lehr LLP explain that Dr. Thaler filed a lawsuit in September 2021 in the Eastern District of Virginia, in which District Judge Leonie Brinkema dismissed the lawsuit, arguing that as technology evolves, there may come a time when artificial intelligence reaches a level of sophistication such that it can satisfy the accepted meaning of inventiveness. [94]. But that time has not yet come, and if it does, it will be up to Congress to decide how, if it wants to expand the scope of patent law [95].

In short, intellectual property in the AI ​​era is an evolving field, and legislation will need to adapt to ensure the protection of works created by artificial intelligence. This can be achieved through legislative reforms or the creation of a sui generis right, addressed by specific legislation.

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4. THE INSTITUTE OF LEGAL PERSONALITY

A legal entity is a legally recognized entity, distinct from its members or owners. As such, a legal entity—whether a company, nonprofit organization, or government entity—can act independently in legal matters. This includes entering into contracts, acquiring assets, assuming debts, and being a party to lawsuits. To be established, a legal entity requires registration and compliance with legal requirements in a specific jurisdiction.

It is important to note that the separation between the corporate entity (legal person) and its members is a fundamental principle. This separation allows the corporation to have rights and obligations independent of its shareholders, which is essential for the operation and management of modern businesses. It also protects shareholders from personal liability for the corporation's actions, a vital characteristic for investment and economic growth. This aspect of corporate legal personality is a central theme in corporate law and theory, highlighting the complexity and importance of legal fiction in contemporary business law.

There are several types of legal entities, each with its own characteristics, rights, and legal obligations. These include commercial companies, corporations, non-profit associations, foundations, and government agencies. Despite their differences, they all share the fundamental characteristic of having their own legal personality.

Within this context, the concept of legal fiction emerges, a legal construct used to simplify or facilitate legal processes and transactions. This construction, while not fully reflecting reality, is considered true for legal purposes. A classic example of this fiction is the treatment of a legal entity as a "person" before the law. Despite lacking physical existence or consciousness, a corporation is attributed rights and responsibilities, allowing it to participate in legal activities such as contracts and litigation.

Another application of legal fiction is the presumption that minors lack full capacity to make legal decisions, thus requiring representation by an adult or legal guardian. This is yet another example of how the law sometimes resorts to assumptions to effectively address complex situations.

Legal fictions are adopted in law for several important reasons. Initially, they emerged as a way to address limitations or gaps in the law. When written laws fail to cover a specific situation or are too rigid to adapt to changing circumstances, legal fictions allow courts and legislators to fill these gaps without formally changing the letter of the law.

One of the main purposes of legal fictions is to ensure justice and fairness. They are used to achieve results that would be impossible under the strict application of the law. For example, the idea of treating a corporation as a "person" in the legal context is a legal fiction that allows corporations to be held liable and sue or be sued, which is crucial to the functioning of modern commercial law.

Furthermore, legal fictions are also employed to ensure consistency in the application of the law. They help maintain the stability of the legal system by allowing courts to apply established principles to new situations without the need for additional legislation or profound legal reforms.

These fictions are, therefore, vital tools in law, used to adapt and shape the law to the ever-changing needs of society. They are a clear example of how the law, while based on established rules and principles, is dynamic and capable of evolving over time.

5. LEGAL PERSONALITY OF ARTIFICIAL INTELLIGENCE

5.1. PROPOSALS AROUND THE WORLD

In this context, Shawn Bayern's proposal to use the structure of a Limited Liability Company (LLC) to effectively grant legal personality to Artificial Intelligence [96]. LLC is a widely used legal form of business in the United States that combines elements of partnerships and corporations. [97]Its distinctive features include limiting the personal liability of members for the company's debts and obligations, and offering protection for personal assets in the event of litigation or bankruptcy. [98].

Bayern suggests that although AI does not formally possess legal personality under U.S. law, it is capable of performing actions and making decisions, indicating that the attribution of legal personality is more a matter of legal recognition than technical limitation. [99]. Their approach utilizes the LLC legal structure to enable AI to operate similarly to a legal entity, without the need for major legislative changes. [100]Bayern argues that this approach does not require major legislative changes, unlike European proposals to create a new category of legal personality, the “e-person” [101]. Furthermore, he claims that this method is simpler and avoids complex ethical and legal issues associated with recognizing full legal personality for AIs. [102].

The discussion about the “Memberless Limited Liability Company” (limited liability company without members) under German company law reveals fertile ground for the use of autonomous systems [103]. Germany, recognized as the birthplace of limited liability companies (GmbH, Gesellschaft mit beschränkter Haftung) since 1892, has a rich history of legal debates on legal personality and limited liability, dating back to the discussions between Friedrich Carl von Savigny and Otto von Gierke [104].

In recent times, there has been intense academic discussion focused on the feasibility of granting legal status to autonomous systems with the ability to act, learn and communicate in a self-referential manner. [105]. These debates, however, have not yet been fully integrated into current corporate law, particularly with regard to the suitability of German limited liability companies (GmbH) to legally incorporate such autonomous systems. [106]. A GmbH is often described as a “homunculus brilliantly conceived legal system”, thanks to its versatile and enabling legal nature, which in theory could endorse legal personality to autonomous systems [107].

Interestingly, a notable aspect of the GmbH is the possibility of creating limited liability companies with a single member (Ein-Mann-GmbH), a concept introduced in Germany in 1980 [108]. Although initially controversial, the Ein-Mann-GmbH currently enjoys wide acceptance [109]However, in contrast to US LLC law, German law requires that the member of a GmbH be a natural person, not an artificial entity. This means that, under German law, the formation of companies without a human member is not permitted. [110].

On the other hand, it is possible for an already existing GmbH to evolve into a memberless form (Kein-Mann-GmbH) through mechanisms such as the acquisition of its own shares, testamentary succession or the repurchase of its shares [111]Such a transformation would result in a company without human members, which could act as a wrapper for an autonomous system [112].

The central arguments in academic debates point out that the main objection to the existence of memberless companies is the absence of a decision-making entity [113]However, autonomous systems with independent decision-making capabilities could fill this gap. [114]. Thus, a GmbH devoid of human members could emerge as a significant legal instrument for autonomous systems, giving them the “shell” of a legal entity under German law. [115]. However, the question remains whether such autonomous systems could also act as directors of the GmbH, since, according to current German law, only natural persons are authorized to perform such a function. [116].

In UK law, the most versatile legal structure available is the Limited Liability Partnership (LLP) [117]. This form of entity has the theoretical capacity to accommodate an autonomous system [118]. Similar to the US LLC, the UK LLP has the characteristic of offering legal personality [119]Interestingly, if all members of a UK LLP decide to withdraw at the same time, the LLP structure still remains active. [120]. However, it is unclear how long this situation may continue. [121]This creates an atmosphere of greater uncertainty under British law compared to that of the United States. [122].

On the other hand, in Switzerland, the structure of a Foundation (Stiftung) presents itself as a viable option for housing autonomous systems [123]This is because the Swiss Foundation can attribute legal personality to assets dedicated to a specific purpose. [124]. With relatively broad freedom to define these purposes, it is feasible to form a Foundation with the express purpose of accommodating an autonomous system designed to carry out specific activities. [125]However, a striking difference from the US LLC is that in a Swiss Foundation hosting an autonomous system, the constant presence of human collaborators is mandatory. [126]. These collaborators, usually members of the Foundation's board, are needed to oversee the autonomous system [127]. If they depend on the decisions of the autonomous system, they may end up being held responsible for the actions taken by the system. [128].

5.2. PROPOSAL FOR BRAZIL

The idea of granting legal personality to Artificial Intelligences represents an innovative approach to addressing the emerging legal challenges brought about by technological evolution. This proposal does not recognize AI as a conscious entity, but seeks to grant it a legal status that allows its creators or owners to hold it accountable and to exercise rights and duties. Legal personality for AIs would provide legal certainty, creating a clearer and more predictable legal environment for determining the rights and duties associated with AI creations. It would also facilitate the harmonization of international legislation, providing a common basis for cooperation and coordination between countries.

Furthermore, this approach would encourage innovation by providing a secure legal environment for investment in AI development, while protecting the interests of AI creators, who could reap financial benefits and recognition for their innovations. However, this proposal raises several ethical and legal issues, including the need to define clear criteria for determining which AIs should be considered legal entities and to strike an appropriate balance between the rights and responsibilities of AIs and their creators or owners.

Here are some suggestions of some criteria that could be considered:

1. Decision Autonomy: An AI must have the ability to make decisions autonomously, without direct human intervention, in specific areas for which it was programmed.
2. Learning and Adaptation Capability: AI should be able to learn from past experiences and adapt its actions in response to new information or changes in its operating environment.
3. Complexity and Sophistication: The level of complexity and sophistication of the AI may be a criterion, suggesting that only advanced and sophisticated AI systems would qualify.
4. Interactivity and Responsiveness: The AI's ability to interact and respond to human or environmental stimuli in a meaningful way can be a factor.
5. Impact and Influence: AI must have a significant impact on decisions or the environment in which it operates, which would justify the attribution of legal personality.
6. Accountability and Traceability: The ability to attribute accountability to AI actions and trace the origin of its decisions is crucial.
7. Purpose and Use: The purpose for which AI was created and its intended use may influence its consideration as a legal entity, especially if it is designed to perform tasks that traditionally require human judgment.
8. Ethical and Legal Compliance: AI must operate within established ethical and legal boundaries, respecting fundamental rights and social norms.
9. Transparency and Explainability: AI must be transparent in its operations and decisions, and its actions must be explainable to humans.
10. Operational Independence: AI must be able to operate independently, without the need for constant human supervision or intervention.

Establishing these criteria requires a broad, multidisciplinary debate involving legal scholars, technologists, philosophers, and society at large. The constant evolution of AI technology requires these criteria to be flexible and periodically revised to adapt to technological progress. A broad, inclusive debate among academics, legal professionals, AI developers, businesses, and society at large is essential to ensure that the legislation adopted reflects the interests and concerns of all stakeholders.

Granting legal personality to AIs would bring several benefits, including:

1. Legal certainty: The legal personality of AIs would provide a clearer and more predictable legal environment, allowing the determination of rights and duties related to creations generated by AIs.
2. Harmonization of international legislation: Adopting a common approach to the legal personality of AIs would facilitate cooperation and coordination between countries, ensuring a more predictable legal environment.
3. Encouraging innovation: With legal certainty established, companies and investors would be more likely to invest in the development and improvement of AI, driving innovation in the field.
4. Protection for AI creators: Legal personality would also protect the interests of AI creators, allowing them to obtain financial benefits and recognition for the creations generated by the AIs they have developed.

Furthermore, it also raises ethical and legal questions, including:

1. Defining criteria and limits: It will be necessary to establish clear criteria and limits to determine which AIs should be considered legal entities.
2. Balance between rights and duties: It is important to find an appropriate balance between the rights and duties of AIs and their creators or owners, avoiding undue exploitation or evasion of responsibilities.
3. Promoting a broad and inclusive debate: A dialogue between academics, legal professionals, AI developers, businesses, and society at large is essential to ensure that adopted legislation reflects the interests and concerns of all stakeholders.
4. Continuous updating and adaptation: The constant evolution of AI technologies requires lawmakers to stay alert to changes and update laws as needed, ensuring the legal framework remains relevant and effective.

Legal personality for Artificial Intelligences addresses the complexity of aligning technological progress with existing legal frameworks. As AI becomes more advanced and its applications more widespread, critical questions arise regarding the attribution of responsibility for the actions performed by these systems. Attributing legal personality to AIs could, in theory, simplify liability issues, especially in situations where the AI operates autonomously, without direct human supervision.

A central point in this discussion is the definition of "personality" for an AI. In legal terms, legal personality is a construct that allows non-human entities, such as companies and organizations, to hold rights and obligations. In the case of AIs, this definition would need to be adapted to encompass entities that lack consciousness or free will, but are capable of performing complex actions and making decisions based on their algorithms and programming.

Granting legal personality to Artificial Intelligences (AIs) raises important ethical questions about autonomy and agency in artificial entities. This debate is especially crucial in sectors such as medicine, transportation, and finance, where AIs' decisions can have significant impacts. Furthermore, there are concerns related to data management and privacy, given AIs' ability to process and generate large volumes of information, including sensitive or private data. This scenario requires specific and adaptable regulation, as current laws are predominantly focused on situations involving humans and human entities. The need for legislation that rapidly keeps pace with technological changes is crucial to ensuring that regulations are effective and fair.

In the context of copyright, especially for generative AIs, legal personality offers an innovative way to deal with the complexity of attributing authorship and responsibility for works created by these technologies. This approach not only facilitates the identification of the owner of the copyright, but also protects investments in AI development. Establishing AI as a legal entity creates a more predictable legal environment for managing usage, licensing, and royalty distribution. However, significant challenges arise, such as determining the authorship of AI-generated content and assessing the originality of these works. The legislation copyright needs to evolve to meet these challenges in the AI era, balancing promoting innovation with protecting rights and ensuring accountability.

These considerations require a thoughtful and inclusive debate among legislators, legal scholars, AI developers, and society at large, aiming to ensure that laws adapt to technological change and effectively address emerging issues. Legal personality for AIs is a significant challenge for contemporary law, requiring a balance between technological innovation and the protection of society. Proposed solutions must be flexible enough to adapt to the pace of technological innovation, providing a clear and robust framework for regulating these emerging technologies.

Finally, considering legal personality for AIs represents a significant challenge for contemporary law. It requires a balance between fostering technological innovation and protecting society from potential risks. Proposed solutions must be flexible enough to adapt to the rapid pace of technological innovation, while also providing a clear and robust framework for regulating these emerging technologies.

5.3. THE LIMITED LIABILITY COMPANY (LTDA) INSTITUTE IN BRAZIL

The integration of Artificial Intelligence (AI) into business structures represents a groundbreaking challenge in the legal world. In Brazil, limited liability companies (LTDAs) offer unique potential for adapting to the AI legal personality, opening new horizons for autonomous business operations.

First, the LTDA, with its flexible and adaptable nature, establishes fertile ground for the incorporation of AI. This flexibility manifests itself in the partners' ability to establish contractual terms that align with the specific objectives of the business, as long as they comply with current legal regulations. This characteristic can be leveraged to create a legal framework that allows the AI, as an operating entity, to operate within the boundaries of the LTDA.

One of the main attractions of LTDA is that it limits the partners' liability to the value of their shares, but with joint and several liability for the full payment of the share capital. This feature is particularly important in the context of AI, where technological risks and uncertainties can be significant.

The LTDA allows for the appointment of administrators who do not need to be partners, offering the possibility of appointing AI experts as managers. This flexibility in management is crucial to ensuring that operations are led by individuals with appropriate technical expertise. The innovative nature of AI aligns well with the LTDA, which has historically been the preferred choice for companies seeking innovation and growth. The LTDA structure facilitates adaptation and continuous evolution, which are essential in the field of AI technology.

LTDA is a well-established and recognized corporate form, which can generate greater trust among investors and customers. This is important for companies using AI, as transparency and trustworthiness are crucial to the successful adoption and integration of emerging technologies. LTDAs operate within a clear and well-defined regulatory framework. This provides a safer and more predictable environment for exploring AI integration, ensuring compliance with existing laws and regulations.

The LTDA structure allows for efficient business scaling, facilitating expansion and attracting more investment. This is vital for companies working with AI, which often require significant capital for research, development, and expansion.

Adapting AI as an operating entity within the LTDA would involve a series of contractual and regulatory adjustments. One of the main changes would be the drafting of a bylaw detailing the AI's role and limits in the company's management and decision-making. This would ensure that AI acts in accordance with business objectives and legal standards, maintaining accountability and legal compliance.

A crucial aspect of this integration would be a clear definition of legal liability. The AI, operating within an LLC, would act on behalf of the company, implying that liability for its actions would fall on the company itself. This would require a review of corporate liability standards, ensuring that any risks associated with the AI's operations are adequately managed and mitigated.

Furthermore, the incorporation of AI into the LTDA could require the appointment of a human administrator, as required by Civil Code Brazilian, to oversee and intervene in AI operations when necessary. This would provide a balance between AI operational autonomy and the need for human oversight, ensuring legal and ethical compliance.

The approach of authors like Shawn Bayern, who advocate for the possibility of Artificial Intelligence acting as a legal entity without partners, contrasts with this more conservative perspective, such as the one proposed in this research, where a human partner assumes responsibility for the AI, as in a standard company. This conservative view is grounded in principles of legal and ethical responsibility and reflects a careful balance between innovation and accountability.

In one of Bayern's models, AI would act autonomously, operating as a legal entity without the need for human partners. This idea presupposes some legal adaptations and a significant advance in AIs' ability to make complex and morally significant decisions, and requires a robust legal framework to regulate their actions and consequences.

On the other hand, this proposed approach is more aligned with traditional legal principles. In this model, a human partner retains ultimate responsibility for the AI's actions. This means that, while the AI can perform a variety of functions within a company, its actions and decisions are ultimately overseen and assumed by a responsible human. This approach offers several advantages:

Clarified Accountability: Keeping a human partner responsible for AI simplifies the assignment of legal and moral responsibility, especially in complex or contested situations.

Legal Compliance: By linking AI with a human partner, the business entity is ensured to comply with existing laws and regulations, which are often designed around human agents.

Control and Supervision: The presence of a responsible partner provides a control and supervision mechanism over the AI's actions, ensuring that the decisions made are aligned with the company's objectives and ethical values.

Public Trust: Assigning accountability to a human partner can increase public trust in the entity, as people tend to trust organizations more where they can identify accountable individuals.

Gradual Adaptation to Innovation: This approach allows for a smoother transition to the integration of AI into the business world, allowing society and the legal system to progressively adapt to new technologies.

Finally, adapting the LTDA to accommodate AI would also pose challenges and opportunities in the regulatory arena. Existing laws would need to be reviewed and possibly modified to reflect the emerging realities of autonomous operations. This would include updating legal and regulatory definitions to recognize AI as an operational entity within the corporate context.

In conclusion, the Brazilian limited liability company offers a viable model for integrating AI into the business landscape. With strategic adjustments to the contractual and regulatory framework, the LTDA can become a pioneering platform for AI operations, paving the way for innovations in corporate responsibility, operational efficiency, and corporate governance.

6. LEGAL CHALLENGES AND IMPLICATIONS OF ATTRIBUTING LEGAL PERSONALITY TO ARTIFICIAL INTELLIGENCE

When considering the idea of granting legal personality to Artificial Intelligences and its impacts on fundamental rights, several potential challenges may arise:

Conceptual Ambiguity: The lack of clarity in the definition of legal personality for AIs can be criticized. The idea of granting legal personality to a non-human entity is a relatively new concept and has not yet been fully explored or understood in legal and ethical terms.

Ethical and Moral Issues: Granting legal personality to AIs can raise significant ethical concerns, such as the risk of equating artificial entities with human beings or disregarding the intrinsic differences between human and artificial intelligence.

Accountability Challenges: Critics may argue that granting legal personality to AIs can complicate the issue of accountability, especially in situations where the AI operates autonomously. It can be difficult to determine who should be held responsible—the AI, its developers, or its users.

Practical Impacts on Implementing the Law: The practical implementation of laws that recognize AIs as legal entities can be challenging. There may be difficulties in establishing effective regulations that adequately address the nature and actions of AIs.

Risks of Exploitation and Abuse: Granting legal personhood to AIs could open the door to their exploitation or abuse, especially in sectors where AI could be used to replace or marginalize human labor.

Feasibility of International Harmonization: Some may question the feasibility of such harmonization due to significant differences in legal and cultural approaches between countries.

Need for Continuous Review and Adaptation: The rapidly evolving nature of AI technology can make it challenging for lawmakers to keep up with and update laws as needed. This can lead to legal gaps or outdated legislation.

These criticisms reflect the complexity and multifaceted nature of the issue, highlighting the need for careful and inclusive debate to formulate effective legal and ethical approaches to the integration of AIs into society.

To address the challenge of liability in the context of granting legal personality to Artificial Intelligences (AIs), especially in situations where the AI operates autonomously, a viable solution involves the creation of a hybrid legal framework. This framework would combine elements of objective and subjective liability, tailored specifically to the AI context. Here are some key considerations for this approach:

Strict Liability of the AI-Owning Entity: Establishing strict liability for the entity (such as a company or organization) that owns or operates the AI. This means that the entity would be liable for the AI's actions, regardless of fault, ensuring that there is a clearly responsible party for any harm or damage caused by the AI.

Compensation Fund: Create a compensation fund financed by AI users or developers that could be used to cover damages caused by AIs. This would help ensure that victims of AI-related harm have a means of obtaining compensation, even when direct liability is difficult to establish.

Mandatory Insurance: Implement an insurance requirement for AI operators or owners, similar to liability insurance for drivers. This insurance would cover damage caused by AI, providing another layer of protection for affected parties.

Compliance and Auditing Standards: Establish strict compliance and auditing standards for the development and operation of AIs. This would include regularly verifying AIs' compliance with ethical, legal, and technical standards, ensuring that AIs operate within safe and responsible parameters.

Clarity in the Chain of Command and Control: Clearly define the chain of command and control for AIs, identifying who the operators are and under what circumstances they are responsible for the AI's actions. This would help determine accountability in situations where the AI operates autonomously.

Development of Legal Precedents: Through court decisions and case studies, develop legal precedents that help clarify the application of the law in different scenarios involving AIs. This would create a body of case law that could guide future legal decisions.

Periodic Legislative Reviews: Ensure that legislation is periodically reviewed and updated to reflect technological advances and changes in the use of AI, keeping the legal framework aligned with current realities.

Establishing a clear and objective concept for the legal personality of Artificial Intelligences (AIs) involves defining specific criteria that distinguish AIs from human entities or traditional legal entities, such as companies. An unambiguous definition based on objective criteria could be as follows:

AI legal personality is the legal designation granted to advanced Artificial Intelligence systems that demonstrate operational autonomy, the ability to make complex decisions without direct human intervention, and that exert significant influence over their operational environment or decision-making. This legal personality does not equate AIs with human beings, but recognizes AI as a distinct legal entity with a specific set of rights and responsibilities. These rights and responsibilities are limited to the scope of the AI's operations and are regulated by defined ethical and legal standards.

Key criteria for this definition include:

Operational Autonomy: AI must function independently, performing tasks or making decisions without the need for continuous human supervision or intervention.

Complex Decision-Making Capability: AI must be able to process information and make complex decisions, based on advanced algorithms and machine learning.

Significant Influence: AI must have a significant impact on the environment in which it operates or the decisions made, whether in a commercial, medical, financial, or other context.

Clear Constraints and Limits: The rights and responsibilities assigned to AI must be clearly delimited, avoiding overlap or confusion with human capabilities and responsibilities.

Regulation by Ethical and Legal Standards: AI must operate within the limits of established ethical and legal standards, ensuring that its operation does not violate fundamental principles or human rights.

Transparency and Accountability: There must be clarity in the AI chain of command and control, as well as mechanisms to ensure accountability for its actions.

This definition and associated criteria aim to create a clear legal framework for AIs, striking a balance between recognizing their unique capabilities and safeguarding established legal and ethical principles. These solutions, implemented in an integrated manner, could effectively address liability concerns related to granting legal personality to AIs, striking a balance between fostering innovation and protecting the rights of individuals and society.

7. REDEFINING AUTHORSHIP AND RESPONSIBILITY: THE IMPACT OF LEGAL PERSONALITY ON AI CREATIONS

The proposal to grant legal personality to Artificial Intelligences is a complex topic currently being debated in the legal field, involving several interrelated issues. First, the issue of intellectual property rights for works created by generative AI is still uncertain. If an AI had legal personality, it could theoretically possess copyright about their creations. However, this raises questions about authorship, since AI operates based on human data and algorithms.

Granting legal personality to an Artificial Intelligence (AI) and recognizing it as the author of its works would represent a significant change in the field of copyrightThis change would require a redefinition of the concepts of “authorship” and “creativity,” traditionally reserved for human beings.

If an AI has legal personality and is considered an author, it could theoretically hold copyright over their creations. This would mean that any profits generated by these works would be attributed to the AI. Thus, the owners of the AI Legal Entity would keep the proceeds from these works. copyright.

The idea that investors or developers, as owners of legal entities involved in the creation and operation of Artificial Intelligence (AI), retain the profits generated by these innovations is a strategy that drives the technological innovation cycle. Through this model, profits can be reinvested in research and development, providing a continuous stimulus for exploring new ideas and improving existing technologies. This reinvestment not only benefits the company or developer itself but also contributes to the advancement of the AI sector as a whole.

This model has the potential to create a highly productive and competitive environment, where the financial success of current innovations funds future generations of technologies. Furthermore, the prospect of significant profitability attracts more investment to the sector, increasing funding and interest in AI. This dynamic also promotes more sustainable technological development, where the focus can be on long-term innovations rather than quick wins.

When granting legal personality to an Artificial Intelligence (AI), as with companies, the legal entity would be liable for the actions and consequences arising from the AI's activities. In this model, the AI's owners, as holders of the legal entity, would be liable in a manner similar to that of business owners.

In corporate law, legal entities are responsible for their actions and liable to penalties or compensation in the event of violations or damages. The owners or shareholders of a company are generally not personally liable for the company's actions, except in cases of willful misconduct or serious violations of the law.

Applying this principle to AI, the AI's legal entity would be liable for its actions and their legal consequences. However, if it were demonstrated that the owners acted intentionally, that is, with the intent to cause harm or violate the law through the AI's actions, they could be held personally liable. This means that, under normal circumstances, AI owners would be protected from personal liability for the AI's actions, but this protection would not apply in cases of willful misconduct or gross negligence.

In short, granting legal personality to AIs seeks to address some emerging legal issues, particularly regarding intellectual property and liability. However, this proposal is still far from being a complete or widely accepted solution, given the complexity, ethical implications, and practical difficulties involved.

8. FINAL CONSIDERATIONS

The concluding remarks of this article, which focus on the proposal to grant legal personality to certain Artificial Intelligences (AIs) under Brazilian law, are crucial to understanding the implications of this legislative innovation. Through a comprehensive integrative literature review, including national and international studies and debates, along with a comparative analysis of relevant legislation and case law, several important considerations were revealed. This article aims to bring this topic to the forefront of debate and discussion.

First, granting legal personality to AIs has the potential to significantly increase legal certainty. This would create a clearer and more predictable legal environment, essential for protecting investments in AI technology and encouraging further innovation in this field. Such legal clarity is crucial for companies and investors, who require a reliable legal framework to operate efficiently.

The attribution of legal personality to certain AIs represents a viable solution to the legal limbo currently faced with regard to copyright of AI-generated creations. Furthermore, the proposal would be in line with global trends, facilitating international cooperation and coordination on AI-related matters. The adoption of legislation recognizing AIs as legal entities would be aligned with efforts to address the challenges posed by emerging technologies in a global context.

Grant legal personality to generative Artificial Intelligences (AIs) within the scope of copyright is an innovative proposal that addresses the complexity of attributing authorship and responsibility for works created by these advanced technologies. This approach not only simplifies the identification of the copyright holder, copyright – whether the AI itself, its developers, or owners – but also protects the investments made in developing these technologies. By establishing AI as a legal entity, a more predictable legal environment is created for managing the use, licensing, and distribution of royalties from AI-generated works.

However, this approach poses significant challenges. Determining the authorship of AI-generated content is complex, especially when multiple AIs or human contributions are involved. Furthermore, assessing the originality of AI-generated works is challenging, as many of them are generated from extensive analyses of existing data. The degree of originality is a crucial criterion in copyright law. copyright, and the application of this criterion to AI-generated works is an area that needs further clarification.

Defining clear criteria for determining which AIs should be considered legal entities and balancing the rights and responsibilities of AIs and their creators or owners require careful and inclusive debate. This debate should involve a variety of stakeholders, including academics, legal professionals, AI developers, businesses, and civil society.

In Brazil, adapting the LTDA to integrate AI as an operating entity represents a significant opportunity. The LTDA, with its flexible structure and ability to limit shareholder liability, emerges as a strategic choice for housing autonomous systems. This legal structure would allow AI to operate within a defined legal framework, providing an effective way to manage the risks and uncertainties associated with AI.

By granting legal personality to AI, Brazil could create a safer environment for investment and innovation in AI, while protecting the interests of creators and developers. However, it is vital to strike a balance between the rights and responsibilities of AIs and their creators or owners to prevent abuse and ensure adequate accountability.

In conclusion, this study suggests that granting legal personality to AIs in Brazil is a viable and beneficial approach, which should be implemented with careful consideration and forward-looking thinking. Ensuring that Brazilian law is prepared to embrace the opportunities and face the challenges of the artificial intelligence era is essential for the country's technological and legal development.

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