Every day we become more dependent, both as individuals and as a society, on new technologies. While, until a few years ago, legal debate focused primarily on the internet and the processing of personal data, today it has expanded to a much more complex universe. Artificial intelligence, wearable devices, smart glasses, biometric sensors, and even technologies capable of capturing neural signals are beginning to integrate into the daily lives of companies and citizens.

This advancement, while promising, brings an increasingly evident challenge: technological innovation has advanced faster than the institutional governance mechanisms capable of guaranteeing legal certainty, protection of rights, and accountability in the use of these tools. In this context, the governance of new technologies is taking center stage in contemporary legal debate.

One of the first points that needs to be understood in this scenario is the difference between governance and technology management. Governance refers to the strategic level of the organization. It deals with the definition of policies, institutional guidelines, control mechanisms, and the alignment of technologies with the legal framework and business objectives. Management, on the other hand, operates at the tactical and operational level, dealing with the daily execution of activities.

When this distinction is not observed, many organizations end up reducing governance to a set of technical rules or operational procedures. The result is the creation of fragile structures, incapable of dealing with the legal risks associated with emerging technologies.

True governance requires a cross-cutting vision capable of integrating technology, compliance, data protection, information security, and institutional accountability.

Although artificial intelligence has become the most visible topic in the regulatory debate, it is only one of the technologies that require new governance models. 

Wearable devices and smart sensors already allow for the continuous collection of physiological, behavioral, and biometric data. Smart glasses, for example, can capture images, audio, and metadata from the environment in real time, often without third parties realizing they are being recorded. These technologies raise complex legal issues involving privacy, consent, surveillance, and data protection. 

More recently, technologies capable of capturing neural signals, known as neurodata, are beginning to emerge. Brain-computer interfaces, neural sensors, and devices for reading brain activity are being developed with medical, educational, and even commercial applications.

From a legal standpoint, this data can reveal extremely sensitive information about an individual's emotional states, cognitive patterns, and intentions. The possibility of collecting, processing, and using this data raises new questions about the limits for protecting human dignity and individual autonomy.

In Brazil, the General Data Protection Law (Law No. 13.709/2018) has become the main regulatory framework for addressing some of these challenges. The LGPD introduced fundamental principles such as purpose, necessity, transparency, and security in the processing of personal data. Furthermore, it created governance obligations that require organizations to adopt policies, controls, and accountability mechanisms.

These requirements become even more relevant when dealing with technologies that collect large volumes of sensitive data, such as biometrics, health data, behavioral data, or cognitive patterns.

In this context, the concept of privacy by design—the idea of ​​incorporating data protection from the conception of products and services—ceases to be merely a good practice and becomes an essential requirement to avoid regulatory and legal risks.

Another central element in the governance of emerging technologies is the risk-based approach. Not all technologies have the same potential impact on fundamental rights. Systems that merely automate administrative tasks have relatively limited risks. However, technologies that directly interfere with medical, financial, or behavioral decisions can have profound effects on people's lives.

For this reason, contemporary governance models classify technologies into risk levels—low, medium, high, or unacceptable—establishing proportionate mechanisms for control, auditing, and supervision.

This logic also applies to the internal use of technologies within organizations. The indiscriminate use of digital tools by employees, without clear institutional guidelines, can generate situations of high regulatory risk. Confidential information may be entered into external platforms, sensors may capture data without an adequate legal basis, and connected devices may become vulnerable security points.

Another central point of technological governance is ensuring transparency and accountability. Technologies that influence relevant decisions need to be auditable and understandable. The user must be able to understand how a particular decision was made and what criteria were used.

This principle becomes especially relevant in automated environments, but it also applies to monitoring systems, behavioral analysis, and the collection of biometric or neural data.

From a legal standpoint, the introduction of technology does not eliminate human responsibility. Companies, developers, and operators remain responsible for the effects produced by the systems they implement. The principle of responsibility, or accountability, requires organizations to demonstrate effective control over the technological risks they assume.

Another aspect frequently overlooked in digital transformation is preserving the integrity of information over time. In audits and legal proceedings, digital documents need to maintain a chain of custody capable of proving their authenticity and integrity. Otherwise, their legal validity may be questioned.

Traditional backup systems are not sufficient to guarantee this preservation. More robust digital governance models require structured archival repositories capable of recording metadata, controlling versions, and ensuring document integrity over time.

Technology governance should not be interpreted as an obstacle to innovation. On the contrary, it functions as a mechanism to support digital transformation.

Organizations that structure clear technology use policies, classify risks, create multidisciplinary committees, and adopt control mechanisms are able to innovate with greater legal predictability and less exposure to litigation.

In an increasingly connected environment, where artificial intelligence, sensors, wearable devices, and even neural data are becoming part of everyday life, the absence of governance means, in practice, relinquishing control over the technological ecosystem itself.

And in the legal field, losing control over technology means taking risks that may become difficult to manage in the future.