In recent decades, society has been transformed by impactful technological advances. From the popularization of the internet to the proliferation of mobile devices and the rise of Artificial Intelligence (AI), these innovations have redefined how we live, work, and communicate.
Technological advancements have driven the development of new industries, changed business models, and even altered social paradigms. Consequently, society is adapting to an ever-evolving landscape shaped by the rapid technological evolution.
In this context, AI emerges as an essential tool for the development and improvement of organizations. Through AI, companies can automate processes, efficiently analyze large volumes of data, and make more accurate and informed decisions. Additionally, it enables the creation of innovative products and services, boosting competitiveness and the ability of organizations to adapt in a constantly changing business environment.
It is worth noting that AI is a field of computer science that focuses on developing computational systems capable of performing tasks that would normally require human intelligence. This includes functions such as learning, reasoning, problem-solving, pattern recognition, natural language understanding, and decision-making.
AI uses algorithms and machine learning models to analyze large volumes of data, learn from them, and make predictions or take actions based on that learning.
However, while providing significant advances, persistent concerns arise related to relevant topics such as privacy and personal data protection, intellectual property, and competitive issues related to the use of AI.
Its rapid expansion raises complex ethical and legal questions, requiring the implementation of appropriate policies and regulations to ensure safety and integrity in its use.
Thus, we can highlight some challenges arising from the intersection between the use of AI and data protection legislation, such as the European GDPR and the Brazilian LGPD. For example, the excessive data collection necessary for the effective training and functioning of AI systems raises concerns about the adequacy of processing this personal data.
We can also highlight that the operationalization of the principles established in GDPR and LGPD, such as the principle of data quality, directly impacts the need for precision and reliability of the algorithms used by artificial intelligence. Additionally, ensuring compliance with data subjects’ rights can be complex due to the nature of the processed data.
Regarding third-party Intellectual Property, its use generally requires authorization, but there are exceptions, especially for non-commercial purposes. In this context, how can we reconcile this need with the use of third-party content by AI systems to train their algorithms?
Some argue that the content serves only as input for learning, similar to what humans do without authorization. However, intellectual property holders state that this use is illegal, especially to create derivative commercial content. This debate is further complicated by the diversity of laws and jurisprudence in different countries. The answer depends on the origin of the material, its use, and an analysis of the results generated by the AI system and the relevant jurisdiction.
In turn, when we talk about competitive aspects, we highlight that the rapid development and implementation of AI systems have profoundly impacted the competitive dynamics in various sectors, including those undergoing digitalization.
This raises important questions, especially regarding merger and acquisition analysis, where authorities have expressed concerns about the intensive use of AI by large technology companies, potentially creating competitive advantages or barriers to entry for smaller competitors.
There are also concerns about the possible use of AI algorithms to coordinate prices, forming algorithmic cartels and, more worryingly, algorithmic discrimination, where marketplace platforms may favor their own products to the detriment of competitors.
Antitrust authorities have adapted, including using AI, to identify and punish such practices. These issues have received national and international scrutiny, with authorities and regulators closely examining these practices.
In this sense, it is essential to adopt a structured approach to the use of AI and carefully consider the legal issues involved.
This implies evaluating not only the potential benefits but also the legal risks and responsibilities associated with the implementation and operation of AI systems. By doing so, organizations can—and should—ensure compliance with relevant laws and regulations, as well as promote an ethical and responsible approach to the development and use of this innovative technology.
Acting proactively on these issues to ensure that AI is developed and applied ethically, transparently, and responsibly, maximizing its benefits while minimizing potential risks and negative impacts is fundamental.
Thus, adopting robust compliance policies is necessary, providing clear guidelines and control mechanisms to ensure that the implementation and use of AI in companies align with established ethical and legal principles.
Does it make sense for corporations to have institutional AI policies among those that must be followed by their employees? It seems so.
These regulations should cover everything from data collection and processing to intellectual property protection and the promotion of fair competition, among others.
Thus, the integration between compliance and AI should go hand in hand, providing legal security and ensuring the effectiveness of processes.
This synergy not only strengthens regulatory compliance but also makes organizations more competitive, combining technological innovation with legal and ethical responsibility.