For decades, the answer to the question of who decides in the State was reduced to a civil servant, a leader, or a minister, but today algorithms can increasingly be included. Algorithmic systems and Artificial Intelligence are already helping to define priorities in inspections, detect fraud, organise waiting lists, allocate support, or signal risks. These are useful tools that influence people's lives, and anything that affects rights, opportunities, or duties should be subject to public scrutiny. Hence the importance of a Public Register of Algorithmic Systems and AI in the Public Sector. This is not a technological whim or bureaucratic excess, but democratic transparency applied to the 21st century. Its purpose is to allow any citizen to know which systems are being used by the State, what they are for, on what legal basis they operate, what types of data they use, and what effects they produce. If an algorithm contributes to deciding who is audited or who receives support, that cannot be an administrative secret. However, transparency does not mean irresponsible exposure, as a well-designed register distinguishes what should be public from what should be reserved. Citizens should know the purpose of the system, the responsible entity, the degree of automation, the existence of human intervention, the categories of data used, and the mechanisms for contestation. Sensitive technical details, vulnerabilities, or legitimate trade secrets should remain accessible only to control and audit entities. It is also important to explain that not all algorithms are the same. Some systems only support human decisions, others classify or prioritise processes, and others can produce automated decisions. The register should clarify the degree of human intervention involved, as a citizen has the right to know whether they are facing a technical recommendation or an automated decision. Another essential point is risk assessment. A system that organises internal schedules does not have the same impact as one that influences access to social benefits. The register should indicate the level of risk assigned and summarise impact assessments, including data protection assessments, and make public the main mitigation measures. The issue of data also requires clarity. It is not about publishing databases, but indicating which categories are used (such as tax, identification, or health data, among others), what the legal basis for processing is, and what the retention periods are. This reinforces trust and allows for informed scrutiny. Furthermore, systems are not static. They evolve, are updated, and may reveal flaws or biases. The register should include information about versions, audits conducted, aggregated performance metrics, and relevant incidents. If a significant error or important correction occurred, the public should be informed. Creating such a register is not a technical mystery. It requires a central database, a searchable portal, submission mechanisms by public entities, and legal and technical validation before publication. It requires integration with public procurement registers and inventories of personal data processing. And it requires clear governance rules to know who registers, who validates, and who oversees. But the essential aspect is not the technology; it is the democratic culture that gives it meaning. In a rule of law, power, even when exercised by code, must be visible, explainable, and contestable. Therefore, transparency today must also encompass the systems that structure decisions. Public trust arises from clarity and transparency; thus, in the age of Artificial Intelligence, democracy begins with knowing which algorithms govern us and how they do so. For all these reasons, a workshop reflecting on The Transparency of Artificial Intelligence in the Public Sector is currently taking place at Campus XXI in Lisbon, organised by APDSI - Association for the Promotion and Development of the Information Society, with the support of ARTE - Agency for the Technological Reform of the State, as part of the III Open Administration Plan.