Chile’s New Data Protection Law: Context, Overview, and Key Takeaways
On August 26, 2024, the Chilean Congress approved Law 21.719, on the Protection of Personal Data (“LPPD”) after eight years of legislative debate. The legislation was published on December 13, 2024, and will become fully effective twenty-four months after that date (in December 2026).
The LPPD was introduced in the Senate in 2017 to replace Law 19.628, Ley sobre Protección de la Vida Privada (hereinafter referred to as “LPVP”), which was adopted in 1999 as Chile’s first national data protection framework, as well as the first such law in Latin America.
The LPVP provided a foundational framework for personal data protection for nearly 24 years. However, the evolving demands of technological development and globalization gradually highlighted the LPVP’s lack of compatibility with newer and more comprehensive global standards for data protection adopted by partner countries.
In particular, stronger data protection standards reflected in the European Union’s Directive 95/46/EC significantly influenced post-LPVP legislation in Latin America, with Argentina passing comprehensive data protection legislation in 2000 and Mexico in 2010, for example. A similar structural effect followed the enactment of the EU’s General Data Protection Regulation (GDPR), which has influenced recent proposals including Brazil’s Lei Geral de Proteção de Dados (LGPD) and Chile’s LPPD, although each nation has approached this era of policymaking in a unique way.
Prior congressional attempts to update the LPVP reflect the country’s efforts to align to best global standards and meet international commitments1. According to the Chilean government, the approved LPPD pursues the dual objective of (i) providing stronger protection for data subjects and (ii) regulating and promoting the country’s digital economy.2
This blog covers some of the new features in the LPPD, including:
Extraterritoriality: the new law applies to private and public organizations processing personal data of individuals residing in Chile, regardless of where the processing takes place;
Stronger and new data subject rights: the LPPD expands regulation on previously recognized rights of access, rectification, suppression, and opposition, and adds new rights to portability and to block the processing of one’s data;
Additional lawful grounds for processing: the law introduces new legitimate bases for processing data as exceptions or alternatives to consent;
New obligations to controllers and processors: the LPPD imposes security incident reporting and confidentiality obligations, and the implementation of technical and organizational measures, compatible with explicitly recognized principles of legality, accountability, and privacy by design and by default, among others;
Cross-border data transfer regulation: the law recognizes several mechanisms for international transfers, including its own exception regime when transferring to non-adequate countries or in the absence of appropriate safeguards;
Data Protection Authority (DPA): the LPPD creates, for the first time, a DPA vested with supervisory, regulatory, and sanctioning powers to enforce the data protection framework;3
Stronger sanctioning regime: the new law incorporates sanctions for data protection violations, which can range between 2% and 4% of an entity’s total revenue, and creates a national registry for infractors.
Read further for a deeper insight into the key features of the new Chilean data protection law and how they differ from its predecessor and other data protection laws in the region.
1. Scope, covered actors, and exterritoriality
The LPPD regulates the form and conditions under which the processing of personal data of natural persons may be carried out, under Article 19 of the Chilean Constitution, which recognizes the right to personal data protection.4
Similar to other laws in the region (and to the model articulated in the GDPR), the LPPD applies extraterritorially to natural and legal persons, including public and private bodies, when the processing is carried out:
By a controller or processor established in Chilean territory;
When the processor or third party, regardless of its place of establishment or incorporation, processes personal data on behalf of a controller established or incorporated in the national territory; or
When the controller or processor is not established in Chilean territory, but the processing operations are intended to offer goods or services to data subjects in Chile – regardless of whether they are required to pay – or to monitor the behavior of data subjects in Chile, such as analysis, tracking, profiling, and behavior prediction (Art. 1 bis).
2. Covered data
Under Article 2(f) of the LPPD, “personal data” is broadly defined as “any information linked to or referring to an identified or identifiable natural person.” The LPPD establishes that an “identifiable” individual is one “whose identity can be determined, directly or indirectly, in particular by means of one or more identifiers, such as name, identity card number, analysis of elements of the physical, physiological, genetic, psychological, economic, cultural or social identity of such person.” In addition, to determine whether an individual is identifiable, the law requires “all objective means and factors that could reasonably be used to identify the individual at the time of the processing” be considered.
The LPPD’s approach to anonymized data is initially consistent with the GDPR’s approach to the subject: anonymized data is information that does not relate to an identified or identifiable person, and thus is not personal data5. A similar initial definition is found in Brazil’s LGPD, though the Brazilian legislation explicitly recognizes that anonymization might be a reversible process6. The key differentiating feature of LPPD’s approach to “anonymization” is the term’s definition as an “irreversible process” that does not allow for the identification of a natural person.7 In that sense, the LPPD’s definition of anonymization seems stricter than the language found in both the GDPR and the LGPD concerning anonymized data. It is likely that future guidance may shed light on the requirements for “irreversibility” under Chilean law.
Concerning “pseudonymization,” the LPPD follows a similar approach to that found in the GDPR and LGPD. Chilean law defines it as a process carried out in a way that “[data] can no longer be attributed to a data subject without additional information, provided that such information is separate and subject to technical and organizational measures to ensure the data is not attributable to a natural person.” This approach points to the possibility of considering pseudonymized data as personal data as long as it can be linked to an identifiable individual through additional information.
Standards and guidance on anonymization and pseudonymization continue to be explored globally by authorities in the context of data protection frameworks. However, some laws explicitly recognize these techniques as a way to comply with data protection principles. The LPPD explicitly refers to pseudonymization as a technique relevant to comply with the security principle. Article 14 quinquies of the LPPD indicates that controllers shall implement “technical and organizational measures to ensure a level of security appropriate to the risk” such as pseudonymization and encryption of personal data, among other security measures.
3. Data Subject Rights: “ARCO” rights, data portability, and the right to block the processing of data
The LPPD includes two new data subject rights – the right to data portability and the right to block the processing of one’s data – in addition to the previous rights granted in the former LPVP: access, rectification, suppression, and opposition, also regionally known as the “ARCO” rights.
Similar to GDPR-inspired laws that have recently incorporated the right to portability, the LPPD indicates the data subject has the right to request and receive a copy of their data in an “electronic, structured, generic and commonly used format,” which allows the data to be read by different systems and the data subject to communicate or transfer the data to another data controller, when (i) the processing is carried out in the automated form; and (ii)the processing is based on the consent of the the data subject. When technically feasible, the LPPD mandates the portability to be performed directly from controller to controller.
In addition, the LPPD indicates the controller must use the “most expeditious and least onerous means” and communicate to the data subject in a “clear and precise manner” the necessary measures to carry out the portability. Notably, under Chilean law, the right to portability does not necessarily entail the deletion of the data by the transferring controller, which means the data subject must jointly request the deletion of their data once the portability is carried out (Art. 9).
The “right to block the processing of personal data” is the other new right added by the LPPD, which resembles the GDPR’s Article 19 “right to restriction of processing” and Brazil’s LGPD Article 18 “right to blocking unnecessary or excessive data.” Under Article 8 ter of the LPPD, this right is understood as a “temporary suspension of any processing operation” that pertains to a data subject when they make a rectification, erasure, or opposition request. The temporary suspension applies as long as the subject’s request remains open. This suggests that under the “right to block processing,” a data subject can immediately and effectively suspend the processing of their data before the rectification, erasure, or opposition request is processed by the controller. The controller is thus restricted from further processing, although it may continue storing the affected personal data.
Closely linked to the right of opposition, the LPPD introduces the “right to object and not be subject to decisions based on automated processing,” including profiling, when such processing produces legal effects on the data subject or significantly affects them (Art. 8 bis). Under the LPPD, “profiling” refers to “any form of automated processing of personal data that consists of using such data to evaluate, analyze or predict aspects relating to the professional performance, economic situation, health, personal preferences, interests, reliability, behavior, location or movements of a natural person” (Art. 2, (w)).
The LPPD hews closer to the GDPR in the sense that it expressly recognizes the “right to object and not be subject” to automated processing, unlike Brazil’s LGPD, which only recognizes a data subject’s “right to review” automated processing. Similar to the GDPR, Article 8 bis of the LPPD restricts the exercise of this right under certain circumstances, such as when:(i)the decision is necessary for the conclusion or execution of a contract between the subject and the agent;(ii)there is prior and express consent; or (iii) as indicated by law, to the extent that it provides safeguards for the rights and freedoms of the data subject. The operationalization of this right must safeguard the data subject’s rights to information and transparency, obtain an explanation and human intervention, express their point of view, and request a review of the decision. This set of rights and freedoms is encapsulated within the right to object and not be subject to automated processing.
4. Lawful grounds for processing and consent requirements
The LPPD maintains consent as the general basis for the processing of personal data – similar to how it was regulated by the former LPVP. Consent must be “free, informed and specific as to its purpose” and given “in advance and unequivocally” by means of a verbal or written statement, or expressed through electronic means or an affirmative act that “clearly shows” the owner’s intent. The data subject can revoke consent without retroactive effects, and its grant or revocation should be expeditious, reliable, free, and permanently available (Art. 12).
In line with the principle of purpose limitation, the LPPD presumes consent is not “freely given” when collected for the performance of a contract or the provision of a service, where the collection is not necessary to serve those purposes. However, this presumption is not applicable when a person or entity offering goods, services, or benefits solely requires the data subject’s consent to process their data (Art. 12). Notably, this scenario applies to many “free” online services, such as social media or messaging platforms, where consent to process an individual’s data for advertising or profiling purposes is often required for the provision of service.
Without consent of the data subject, the LPPD recognizes the following lawful grounds for processing:
When the processing refers to data relating to obligations of an economic, financial, banking, or commercial nature;
When the processing is necessary for the performance or fulfillment of a legal obligation or is required by law;
When the processing is necessary for the conclusion or performance of a contract, or the execution of pre-contractual measures at the request of the data subject;
When the processing is necessary for the satisfaction of the legitimate interests of the controller or a third party, provided that the rights and freedoms of the data subject are not affected – the subject may request to be informed about the processing and the legitimate interest under which the processing is carried out; or
When the processing is necessary for the formulation, exercise, or defense of a right before the courts or public bodies.
Processing sensitive data and children’s and adolescent’s data
Similar to other comprehensive frameworks, the LPPD distinguishes sensitive data from personal data of a general nature. Under Article 2 (g) of the LPPD, “sensitive data” encompasses data that refers to “physical or moral characteristics of persons or to facts or circumstances of their private life or intimacy, that reveal ethnic or racial origin, political, union or trade union affiliation, socioeconomic situation, ideological or philosophical convictions, religious beliefs, data related to health, human biological profile, biometric data, and information related to sexual life, sexual orientation and gender identity of a natural person.”
Chile’s sensitive data definition is comparable to definitions found in other laws in the region such as Brazil’s LGPD and Ecuador’s Ley Orgánica de Protección de Datos (LOPD), which base the nature of sensitivity on the potential of discrimination or impact on an individual’s rights and freedoms if such information is mishandled or unlawfully accessed.
As a general rule, sensitive data may only be processed with the consent of the data subject. Exceptionally, controllers may process sensitive data without consent in the following circumstances (Art. 16):
When the processing refers to sensitive data that has been made public by the data subject and its processing is related to the purposes for which it was published;
When the processing is based on a legitimate interest carried out by a non-profit entity under public or private law and when certain conditions are met;8
When the processing is indispensable to safeguard the life, health, or integrity of the data subject or another person, or when the subject is physically or legally prevented from giving their consent;
When the processing is necessary for the exercise or defense of a right before courts or an administrative body;
When the processing is necessary for the exercise of rights or fulfillment of an obligation related to labor or social security; and
When the processing is expressly authorized or mandated by law.
Under Article 16 bis of the LPPD, health data and biometric data may only be processed for the purposes provided by the applicable laws or with the data subject’s consent, unless one of the following scenarios applies:
There is an official sanitary alert;
When the processing is for historical, statistical, or scientific purposes, based on public interest;
When the processing is necessary for preventive or occupational medicine, evaluation of an employee’s capacity to work, medical diagnosis, or provision and management of health or social care services (Art. 16 bis).
Article 16 ter defines biometric data as “obtained from a specific technical treatment, related to the physical, physiological or behavioral characteristics of a person that allow or confirm the unique identification of the person, such as fingerprint, iris, hand or facial features and voice.” When processing biometric data, the controller is required to disclose the biometric system used, the purpose of the collection, the period during which the data will be processed, and the manner in which the subject can exercise their rights.
Similar to other frameworks in the region like Brazil’s LGPD, Article 16 quater of the LPPD incorporates the standard of “best interest” of the children when processing their data. As a general rule, the processing of such data may only be conducted in the child’s best interest and with respect to their “progressive autonomy” – a concept introduced, yet not defined, by the LPPD. The lawful processing of children’s data must be based on consent granted by the parents or legal guardian unless expressly authorized by law.
The LPPD introduces a notable distinction between the processing rules applicable to data from children (under 14 years old) and adolescents (between 14-18 years old). Under Chilean law, the processing of adolescents’data may be processed following the general rules applicable to adults’ data, except when the information is sensitive and the child is below 16 years of age. This means that for processing sensitive data from 16 and below adolescents, controllers must still obtain consent from the parents or legal guardian. For other non-sensitive data, controllers may process adolescents’ data following the general rules of the LPPD, but would still be subject to the “best interest” standard. This distinction is a novel innovation of Chilean law and is not found in Brazil’s LGPD or Ecuador’s LOPD.
5. Duties and Obligations of Data Controllers
The LPPD’s provisions follow principles of lawfulness, fairness, purpose limitation, proportionality, quality, accountability, security, transparency, and confidentiality. These principles, along with other specific duties, guide the obligations of data controllers and are consistent with other modern data protection frameworks.
For instance, under Article 14 ter, controllers must inform and make available “background information” that proves the lawfulness of the data processing and promptly deliver such information when requested by data subjects or the authority. This suggests that regardless of whether the information is requested or not, controllers should keep this information readily available. This obligation relates to the “duty of information and transparency,” under which controllers must provide and keep “permanently available to the public” its processing policy, the categories of personal data subject to processing, a generic description of its databases, and the security measures to safeguard the data, among other information.
Notably, Article 14 quater also introduces the “duty of protection by design and by default,” resembling GDPR Article 25. Under the LPPD, this duty refers to the application of “appropriate technical and organizational measures” before and during the processing. Drawing inspiration from the GDPR, the LPPD indicates the measures should consider the state of the art, costs, nature, scope, context, purpose, and risks associated with the data processing.
Although the LPPD does not expressly recognize a “right to anonymization” like Brazil’s LGPD, it sets out the controller’s obligation to anonymize personal data when it was obtained for the execution of pre-contractual measures (Art. 14, (e)). This obligation is closely linked to the general data protection principles, and effective compliance with this duty would free controllers from the scope of the LPPD.
In relation to the security principle, Article 14 quinquies of the LPPD provides that controllers must adopt necessary security measures to ensure the confidentiality, integrity, availability, and resilience of the data processing systems, as well as to prevent alteration, destruction, loss, or unauthorized access to the data. Both controller and processor must take technical and organizational measures to ensure the security of the processing, in consideration of the risks associated with the processing, such as:
Applying pseudonymization and encryption of personal data where possible
Capability to restore access to the personal data in the event of a physical or technical incident
Conduct regular assessments of the effectiveness of technical and organizational measures
Security Incident Notification
Under Article 14 sexies of the LPPD, the responsible agent must report to the Agency by the “most expeditious means possible and without undue delay” any incident that can cause the accidental or unlawful destruction, breach, loss, or alteration of the personal data or the unauthorized communication or access to such data, when there is a “reasonable risk to the rights and freedoms of the data subjects.” Since the law is not clear on a specific timeframe for notification, it is expected the Agency will further regulate this area.
The law also requires the controller to record these communications and describe the nature of the incident, its potential or demonstrated effects, the type of affected data, the approximate number of affected data subjects, and measures taken to manage and prevent future incidents.
When the security incident concerns sensitive or children’s data, or data relating to economic, financial, banking, or commercial obligations, the controller must also communicate the incident to the owners in “clear and simple” language. If the notification cannot be made personally, the controller must notify via a mass notice in at least one of the main national media outlets.
Notably, Article 14 septiesincludes different standards of compliance with the “duty of information and transparency” and the “duty to adopt security measures” for controllers, based on whether they are a natural or legal person, their size, the activity they carry out, and the volume, nature, and purposes of their processing. The Agency will issue further regulation on the operationalization of these different standards.
For organizations not incorporated in Chile, Articles 10 and 14 of the LPPD establish that the controller must indicate to the Agency in writing an email address of the legal or natural person authorized to act on their behalf, so that the Agency can establish communications with them and data subjects can exercise their rights.
Similar to other frameworks, Article 15 bislimits the processor to carry out the data processing in accordance with the instructions given by the controller. If the processor or a third party processes the data for a different purpose or transfers the data without authorization, the processor will be considered the data controller for all legal purposes. The processor will be personally liable for any infringements incurred, and jointly and severally liable with the controller for any damages caused. Importantly, the “duty of confidentiality” and the “duty to adopt security measures” extend to the processor in the same terms applicable to the controller.
Data Protection Impact Assessment
Similar to the GDPR, under Article 15 ter of the LPPD, controllers must carry out a personal data protection impact assessment (DPIA) where the data processing is “likely to result in a high risk to the rights of data subjects” and in the following cases:
When the operation involves a systematic and exhaustive evaluation of personal aspects of the data subjects based on automated processing, such as profiling;
Massive or large-scale data processing;
Processing that involves systematic observation or monitoring of a publicly accessible area; or
Processing of sensitive or specially protected information.
The Agency will publish a list indicating the processing operations that may require a DPIA under the LPPD. In addition, the law obligates the Agency to issue guidance on the specific requirements for conducting DPIAs, so forthcoming regulation on this matter is expected once the Agency begins to operate. Notably, Article 15 ter sets out similar DPIA requirements as the GDPR, indicating that data controllers must indicate the description of the processing operations and their purpose, an assessment of the necessity and proportionality of the processing concerning its purpose, an assessment of the risks it may pose, and the adoption of mitigation measures.
Voluntary Appointment of a Data Protection Officer
Unlike other modern comprehensive data protection laws, the LPPD does not require the appointment of a Data Protection Officer (DPO). However, Article 49 indicates that controllers may voluntarily appoint a DPO that meets the requirements of suitability, capacity, and independence. Furthermore, the law indicates that controllers may adopt a “compliance program” that indicates, among other things, the appointment of the DPO and its powers and duties under that program. However, if the organization adopts a compliance program, it must be expressly incorporated into all employment or service provision contracts of the entity acting as data controller or processor.
6. Cross-Border Data Transfers
Similar to other frameworks in the region and the GDPR, cross-border data transfers made to a person, entity, or organization are generally authorized by the LPPD under the following mechanisms: (i) adequacy; (ii) contractual clauses, binding corporate rules, or other legal instruments entered into between the transferor and transferee; or (iii) under a compliance model or certification mechanism, along with adequate guarantees. The Agency will be in charge of publishing a list of “adequate” countries – under the criteria set forth by the law, as well as model contractual clauses and other legal instruments for international data transfers. Although the LPPD does not provide a specific timeline for publication, it does indicate that the agency will publish on its official website a list of countries deemed “adequate” as well as release the model contractual clauses and other data transfer mechanisms.
In the absence of an adequacy decision or proper safeguards, a “specific and non-customary” transfer may still be made under the following circumstances:
With the expressconsent of the data subject;
When it refers to a bank, financial, or stock exchange transfer under the applicable laws;
When the transfer is necessary to comply with international obligations under treaties and conventions ratified by the Chilean State;
When the transfer is necessary for cooperation between public bodies for the fulfillment of their functions or for international judicial cooperation;
When the transfer is necessary for the conclusion or performance of a contract or pre-contractual measures between the data subject and the data controller; or
When the transfer is necessary for urgent medical or sanitary measures or management of health services (Art. 27).
Notwithstanding the previous exceptions, Article 28 of the LPPD also includes a broader authorization for transfers that do not fall under any of these scenarios. Under Chilean law, an international data transfer may still be authorized when the transferor and transferee demonstrate “appropriate guarantees” to protect the rights and interests of the data subjects and the security of the information. This provision leaves a broad possibility to transfer personal data without any of the traditional mechanisms or for any of the purposes listed above as long as the Agency determines there are appropriate measures in place for the transfer to take place.
7. Infractions and Civil Liability
Violations of the principles and obligations set out in the LPPD may be subject to administrative and civil liability. The LPPD classifies violations as “minor” (i.e. failing to respond to data subject’s requests or to communicate with the Agency), “serious” (i.e., processing data without a legal basis or for a purpose different for which the data was collected) and “very serious” (i.e. fraudulent or malicious processing of personal data, or knowingly transferring sensitive data in contravention with the law). Notably, “very serious” violations seem to require the demonstration of intent by the infractor.
Penalties under the LPPD can range from 5,000 national tax units (around USD 387.000) to 20,000 tax units (USD 1.550.000 USD). In the case of repeated “very serious” violations, the Agency may also order the total or partial suspension of processing activities for up to thirty (30) days, a period during which the infractor must demonstrate the adoption of necessary measures to comply with the law. For entities that are not considered “small businesses”9 with repeated serious or very serious violations, the Agency may impose a fine of 2% or 4% of its annual income in the last calendar year.
Furthermore, as a dissuasive mechanism, the LPPD also creates the National Registry of Sanctions and Compliance, which will record all data controllers sanctioned for data protection violations and indicate the seriousness of the infringement, as well as aggravating or mitigating circumstances, for five (5) years.
Towards Stronger Data Protection in Chile
With the passage of the LPPD, Chile enters an era of stronger data protection requirements and enforcement. The new law expands existing data subject rights and interests and incorporates new ones, sets out relevant obligations consistent with the evolving nature and demands of offering goods and services in the digital ecosystem, aligns with other global standards of personal data protection, and incorporates higher fines and dissuasive mechanisms.
Although the LPPD draws structural inspiration from the GDPR, it also maintains certain provisions unique to its predecessor law, the LVPD, such as specific regulations for the commercial and banking sectors, and broader exceptions to the lawful grounds for processing of personal data, including sensitive and children’s data.
The LPPD may again position Chile as a regional data protection trend-setter. Other countries with not-so-old data protection laws currently seeking to update their normative frameworks, such as Argentina and Colombia, could be influenced by the landmark passing of the LPPD, facilitating a new wave of “second generation” data protection laws in Latin America.
The Chilean Congress previously analyzed at least two similar proposals under different administrations in 2008 and 2012. Two of the recurring motivations for updating the data protection framework were to achieve adequacy under the EU’s regime and comply with Chile’s commitment to update its legislation after becoming an OECD member in 2010. ↩︎
See: press release from government after approval of LPPD. ↩︎
The Agency will be managed by a Directive Council composed of three Councilors designated by the Executive and ratified by the Senate. The first Councilors are expected to be appointed within sixty (60) days after the formal enactment of the law. ↩︎
Article 19, sec. 4, of the Chilean Constitution recognizes the right to private life, human dignity, and personal data protection. ↩︎
For this exception to apply, the entity must have a political, philosophical, religious, or cultural purpose, or be a trade union; the processing refers exclusively to the entity’s members or affiliates and fulfills the purposes of the entity; the entity grants necessary guarantees to avoid unauthorized use or access to the data; and the personal data is not transferred to third parties. ↩︎
Geopolitical fragmentation, the AI race, and global data flows: the new reality
Most countries in the world have data protection or privacy laws and there is growing cross-border enforcement cooperation between data protection authorities, which might lead one to believe that the protection of global data flows and transfers is steadily advancing. However, instability and risks arising from wars, trade disputes, and the weakening of the rule of law are increasing, and are causing legal systems that protect data transferred across borders to become more inward-looking and to grow farther apart.
Fragmentation refers to the multiplicity of legal norms, courts and tribunals (including data protection authorities), and regulatory practices regarding privacy and data protection that exist around the world. This diversity is understandable in that it reflects different legal and cultural values regarding privacy and data protection, but it can also create conflicts between legal systems and increased burdens for data flows.
While this new reality affects all regions of the world, it can be illustrated by considering recent developments in three powerful geopolitical players, namely the European Union, the People’s Republic of China, and the United States. Dealing with these risks requires that greater attention be paid to geopolitical crises and legal fragmentation as a threat to protections for the free flow of data across borders.
The end of the ‘Brussels effect’?
There has been much talk of the ‘Brussels effect’ that has allowed the EU to export its regulatory approach, including its data protection law, to other regions. However, the rules on international data transfers contained in Chapter V of the EU General Data Protection Regulation (‘GDPR’) face challenges that may diminish their global influence.
These challenges are in part homemade. The standard of ‘essential equivalence’ with EU law that is required for a country to receive a formal adequacy decision from the European Commission allowing personal data to flow freely to it is difficult for many third countries to attain and sometimes leads to legal and political conflicts. The protection of data transfers under the GDPR has been criticised in the recent Draghi report as overly bureaucratic, and there have been calls to improve harmonisation of the GDPR’s application in order to increase economic growth. In particular, the approval of adequacy decisions is lengthy and untransparent, and other legal bases for data transfers are plagued by disagreements about key concepts between data protection authorities. The GDPR also applies to EU legislation dealing with AI (see the EU AI Act, Article 2(7)), so that problems with data transfers under the GDPR also affect AI-related transfers.
These factors indicate that the EU approach to data transfers may gradually lose traction with other countries. Although many of them still seek EU adequacy decisions and are happy to cooperate with the EU on data protection matters, they may also simultaneously explore other options. For example, some countries that are already subject to an EU adequacy decision or decisions (such as Canada, Japan, Korea, and the UK which has received adequacy decisions under both the GDPR and Law Enforcement Directive) have also joined a group that is establishing ‘Global Cross-Border Privacy Rules’ as a more flexible alternative system for data transfers.
Political challenges to the EU’s personal data transfer regime are now also present. Some companies are encouraging new US President Trump to challenge the enforcement of EU law against them, and some far-right parties in Europe have called for its repeal.
China has already enacted many data-related laws, including some dealing with data transfers, after first introducing sweeping data localization requirements in 2017. It was all the more surprising that in November 2024 the Chinese government announced that it will launch a ‘global cross-border data flow cooperation initiative,’ and that it is ‘willing to deepen cooperation with all parties to promote efficient, convenient, and secure cross-border data flows.’ In a speech he gave at the same time, Chinese leader Xi Jinping said that China ‘is willing to deepen cooperation with all parties to jointly promote efficient, convenient and secure cross-border data flows’.
Exactly what this means is presently unclear. However, China is a member of the BRICS group, which includes countries with nearly half of the world’s population, and has also enacted many regulations dealing with AI. If China is able to use its political and economic clout to influence the agenda for cross-border data flows, as some scholars hypothesize, this could bring the BRICS countries and others deeper into its regulatory orbit for both privacy and AI.
The arrival of data transfer rules in the US
The United States government has recently relaxed its traditional opposition to controls on data transfers and enacted regulations to regulate certain transfers based on US national security concerns.
In February 2024 former US President Biden issued an executive order limiting bulk sales of personal data to ‘countries of concern.’ The Department of Justice then issued a Final Rule in December 2024 setting out a regulatory program to address the ‘urgent and extraordinary national security threat posed by the continuing efforts of countries of concern (and covered persons that they can leverage) to access and exploit Americans’ bulk sensitive personal data and certain U.S. Government-related data.’
It is no secret that these initiatives are primarily focused on data transfers to China, which is one of the six ‘countries of concern’ determined by the Attorney General, with the concurrence of the Secretaries of State and Commerce (the other five are Venezuela, Cuba, North Korea, Iran and Russia, according to Section 202.211 of the Final Rule). While some scholars have expressed skepticism about whether these initiatives will really bring their intended benefits, it is significant that national security has been used as a basis both for regulating data flows and for a shift in US trade policy.
It is too soon to tell if President Trump will continue this focus. However, some of the actions that his administration has already taken have drawn the attention of digital rights groups in Europe who believe they may imperil the EU-US data privacy framework that serves as the basis for the EU adequacy decision allowing free data flows to the US. It is also questionable whether the EU will put resources into negotiating further agreements to facilitate data transfers to the US in light of the current breakdown in transatlantic relations.
Conclusions
We have entered a new era of instability where geopolitical tensions and the AI race have a significant impact on the protection of data flows. To be sure, political factors have long influenced the legal climate for data transfers, such as in the disputes between the EU and the US that led to the EU Court of Justice invalidating EU adequacy decisions in its two Schrems judgments (Case C-362/14 and Case C-311/18). The European Commission has also admitted that political and economic factors influence its approach to data flows. However, in the past political disputes about data transfers largely remained within the limits of disagreements between friends and allies, whereas the tensions that currently threaten them often arise from serious international conflicts that can quickly spiral out of control.
The fragmentation of data transfer rules along regional and sectoral lines will likely increase with the development of AI and similar technologies that require completely borderless data flows, and with increased cross-border enforcement of data protection law in cases involving AI. Initiatives to regulate data transfers used in AI have already been proposed at the regional level, such as in the Continental Artificial Intelligence Strategy published in August 2024 by the African Union, which refers to cooperation ‘to create capacity to enable African countries to self-manage their data and AI and take advantage of regional initiatives and regulated data flows to govern data appropriately’. This will likely also give additional impetus to digital sovereignty initiatives in different regions, which will lead to even greater fragmentation.
The growing influence of geopolitics demonstrates that the protection of data flows requires a strong rule of law, which is currently under threat around the world. The regulation of data transfers is too often regarded as a technocratic exercise that focuses on steps such as filling out forms and compiling impact assessments. However, such exercises can only provide protection within a legal system that is underpinned by the rule of law. The weakening of factors that comprise the rule of law, such as the separation of powers and a strong and independent judiciary, drives uncertainty and the fragmentation of data transfer regulation even more.
The approaches to data transfer regulation pursued by the leading geopolitical players each have their strengths and weaknesses. The EU approach has attained considerable influence around the world, but is coming under pressure largely because of homegrown problems. The US emphasis on national security is inward-looking, but could become popular in other countries as well. China’s new initiative to regulate data transfers seems poised to attain greater international influence, though this may be mainly limited to the Asia-Pacific region.
Although complying with data transfer regulation has always required attention to risk, geopolitical risk has been broadly overlooked so far, perhaps because it can seem overwhelming and impossible to predict. Indeed, events that have disrupted data flows such as Brexit and the Russian invasion of Ukraine were sometimes dismissed before they happened. However, this new reality requires incorporating the management of geopolitical risk into assessing the viability and legal certainty of international data transfers by organizations active across borders. There are steps that can be taken to manage geopolitical risk, such as those identified by the World Economic Forum, namely: assessing risks to understand them better; looking at ways to reduce the risks; ringfencing risks when possible; and developing plans to deal with events if they occur.
Parties involved in data transfers already need to perform risk assessments, but geopolitical events present a larger scale of risk than many will be used to. Risk reduction and ringfencing for unpredictable ‘black swan events’ such as wars or sudden international crises are difficult, and may require drastic measures such as halting data flows or changing supply chains that need to be prepared in advance.
Major geopolitical events and the AI race are having a significant effect on data protection and data flows, making it essential to anticipate them as much as possible and to develop plans to cope with them should they occur. The only thing that can be safely predicted is that further geopolitical developments are in store with the potential to bring massive changes to the data protection landscape and disrupt global data flows, making it essential to give them a prominent place in risk analysis when transferring data.
FPF Submits Comments to the California Privacy Protection Agency on Proposed Rulemaking
On February 19, the Future of Privacy Forum (FPF) submitted comments to the California Privacy Protection Agency (CPPA) concerning draft regulations governing cybersecurity audits, risk assessments, automated decisionmaking technology (ADMT) access and opt-out rights under the California Consumer Privacy Act.
FPF’s comments identified opportunities to bring additional clarity to key elements of the proposed regulations as well as support interoperability with other US legal frameworks. In particular, FPF recommended that the CPPA—
Clarify the “substantially facilitate” standard for in-scope ADMT systems, to provide more certainty for businesses and focus requirements to the highest-risk uses of ADMT;
Ensure that carve-outs for narrowly used, low-risk AI systems are appropriately tailored to avoid unintended impacts to socially beneficial technologies and use cases;
Clarify the intended scope of definition “significant decision” to include decisions that result in “access to” the specified goods and services;
Consider whether application of requirements to training ADMT systems that are “capable” of being used for certain purposes, rather than intended or reasonably likely to be used for such purposes, is too broad;
Clarify what it means for an ADMT or AI system to be used for “establishing individual identity”;
Clarify that requests to opt-out of having one’s personal information processed to train ADMT or AI systems submitted after processing has begun do not require businesses to retrain models;
Consider whether requiring businesses to identify “technology to be used in the processing” in risk assessments is overly broad;
Clarify that, in conducting risk assessments, the benefits from processing activities should be weighed against the risks to individuals’ privacy as mitigated by safeguards;
Consider whether it is appropriate to require board members to certify a business’s cybersecurity audits; and
Provide flexibility to support the delivery of effective and context-appropriate privacy notices, particularly with respect to virtual and augmented reality environments.
FPF’s comments also included a comparison chart highlighting similarities and differences between the CPPA’s proposed risk assessment regulations, data protection assessment regulations pursuant to the Colorado Privacy Act, and data protection impact assessment requirements under the General Data Protection Regulation.
FPF Releases Infographic Highlighting the Spectrum of AI in Education
To highlight the wide range of current use cases for Artificial Intelligence (AI) in education and future possibilities and constraints, the Future of Privacy Forum (FPF) today released a new infographic, Artificial Intelligence in Education: Key Concepts and Uses. While generative AI tools that can write essays, generate and alter images, and engage with students have brought increased attention to the topic, schools have been using AI-enabled applications for years.
“AI encompasses a broad range of technologies, and understanding the main types of AI, how they interrelate, and how they use student data is critical for educators, school leaders, and policymakers evaluating their risks and benefits in the educational environment,” said Jim Siegl, FPF Senior Technologist for Youth & Education Privacy. “Understanding the use case and context is critically important, and we hope this infographic underscores the need for nuance when setting AI policies in schools.”
Although popular edtech tools powered by machine learning (ML), large language models (LLM), and generative AI (GEN) are transforming education by personalizing learning experiences and automating administrative tasks, AI is not limited to these models. It spans various other forms, including knowledge engineering, symbolic AI, natural language processing, and reinforcement learning, each contributing uniquely to enhancing human capabilities in the completion of specific tasks in the school context.
The infographic takes a closer look at several common AI use cases in schools, including:
Automated grading and feedback, allow teachers to spend more time focused on instruction and student support. While these tools may aid in consistency and objectivity in grading, they should be designed to comply with student privacy laws, and the output should be reviewed by the teacher for risk of bias.
Student monitoring, via integrated systems designed to assist schools in monitoring activity on school-issued divides, accounts, and district internet connections. Student monitoring is done to detect threats to student safety, comply with state and federal regulations, respond to community concerns, and identify at-risk students.
Curriculum development, through systems that can help educators design effective curricula to meet current education standards and student needs. Additionally, AI can help generate quizzes, worksheets, and reading materials tailored to the curriculum.
Intelligent tutoring systems can create customized learning plans and provide students with additional support outside of classroom hours, helping to reinforce concepts through an interactive and engaging learning experience.
School security includes using facial recognition and advanced video analytics to enable faster and more accurate responses to potential threats and ultimately help ensure a safe learning environment.
To support schools seeking to vet AI tools for legal compliance, FPF released a checklist and guide last year. To access all of FPF’s Youth & Education Privacy resources, visit StudentPrivacyCompass.org.
Why data protection legislation offers a powerful tool for regulating AI
For some, it may have come as a surprise that the first existential legal challenges large language models (LLMs) faced after their market launch were under data protection law, a legal field that looks arcane in the eyes of those enthralled by novel Artificial Intelligence (AI) law, or AI ethics and governance principles. But data protection law was created in the 1960s and 1970s specifically in response to automation, computers and the idea of future “thinking machines”.
The fact that it is now immediately relevant to AI systems, including the most complex ones, is not an unintended consequence. To some extent, the current wave of AI law and governance principles could be seen as the next generation of data protection law. Yet if it is not developed in parallel and if it fails to build coherently on the existing body of data protection laws, practice and thinking, it risks missing the mark.
FPF Celebrates Safer Internet Day with Newly Released Encryption Infographic
Future of Privacy Forum (FPF) is thrilled to celebrate Safer Internet Day 2025 with the release of a new infographic, “Encryption Keeps Young People Safe.” Safer Internet Day is an annual event and part of a larger global mission to create a safer online environment, especially for young people. FPF’s new infographic explains how encryption technology plays a crucial role in ensuring data privacy and online safety for a new generation of teens and kids. FPF will host leading experts at a virtual event on Feb. 11 at 10 am ET to discuss the state of encryption technology and policy.
Data encryption is central to online security, privacy, and safety, and of particular importance for particularly vulnerable groups, such as young people. Gen Z and Gen Alpha have lived their entire lives in the age of the commercial internet, social media, electronic records, and internet-connected devices. They have grown up in a world where everything from insulin pumps to cars are internet-connected. Encryption is the best protection to ensure that personal communications, transactions and devices are safe and secure. The 2025 infographic illustrates encryption’s role in protecting data in places young people frequent, such as sports parks, shopping centers, and health clinics.
Encryption is often used to secure or authenticate sensitive documents. Encryption applies a mathematical formula, which obfuscates plaintext information and transforms the plaintext into unreadable ciphertext. Each use of encryption generates a long number that is the mathematical solution to the formula and can unscramble the protected sensitive information. If a private key is not kept secret, anyone with the key can access the private data or impersonate the authenticated person or organization.
This infographic is the latest in FPF’s longstanding work on encryption, which includes a 2020 infographic explaining how encryption more broadly protects enterprises, individuals, and governments—and what may happen when data and devices fail to use strong encryption and are compromised by bad actors. The infographic series advances FPF’s mission of promoting data privacy for every user by showcasing the vital role encryption plays in ensuring online safety, and the detrimental effects of an online world without its protections.
FPF will host a virtual event at 10 am ET today, featuring a Keynote address from Patricia Kosseim, Ontario Information and Privacy Commissioner. There will also be a panel of experts to dive into how encryption protects young people not just online, but in the physical world as well, by preventing malicious actors from gaining access to the devices and spaces they rely on for health, education, convenience, and more. Register now to join the event!
If you’re interested in learning more about encryption or other issues driving the future of privacy, sign up for our monthly briefing, check out one of our upcoming events, or follow us on X, LinkedIn, or Instagram.
Minding Mindful Machines: AI Agents and Data Protection Considerations
Thank you for the contributions of Rob van Eijk, Marlene Smith, and Katy Wills
We are now in 2025, the year of AI agents. In the last few weeks, leading large language model (LLM) developers (including OpenAI, Google, Anthropic) have released early versions of technologies described as “AI agents.” Unlike earlier automated systems and even LLMs, these systems go beyond previous technology by having autonomy over how to achieve complex, multi-step tasks, such as navigating on a user’s web browser to take actions on their behalf. This could enable a wide range of useful or time-saving tasks, from making restaurant reservations and resolving customer service issues to coding complex systems. However, AI agents also raise greater and novel data protection risks related to the collection and processing of personal data. Their technical characteristics could also present challenges, such as those around safety testing and human oversight, for organizations seeking to develop or deploy AI agents.
This analysis unpacks the defining characteristics of the newest AI agents and identifies some of the data protection considerations that practitioners should be mindful of when designing and deploying these systems. Specifically:
While agents are not new, emerging definitions across industries describe them as AI systems that are capable of completing more complex, multi-step tasks, and exhibit greater autonomy over how to achieve these goals, such as shopping online and making hotel reservations.
Advanced AI agents raise many of the same data protection questions raised by LLMs, such as challenges related to thecollection and processing of personal data for model training, operationalizing data subject rights, and ensuring adequate explainability.
In addition, the unique design elements and characteristics of the latest agents may exacerbate or raise novel data protection compliance challenges around the collection and disclosure of personal data, security vulnerabilities, the accuracy of outputs, barriers to alignment, and explainability and human oversight.
What are AI Agents?
The concept of “AI Agents” or “Agentic AI” arose as early as the 1950s and has many meanings in technical and policy literature. In the broadest sense, for example, it can include systems that rely on fixed rules and logic to produce consistent and predictable outcomes on a person’s behalf, such as email auto-replies or privacy preferences.
Advances in AI research, particularly around machine and deep learning techniques and the advent of LLMs, have enabled organizations to develop agents that can tackle novel use cases, such as purchasing retail goods and recommending and executing transactions. From finance to hospitality, these technologies could help individuals, businesses, and governments save time they would otherwise dedicate to completing tedious or monotonous tasks.
Companies, civil society, and academia have defined the latest iteration of AI agents, examples of which are provided in the table below:
“[A]n entity that senses percepts (sound, text, image, pressure etc.) using sensors and responds (using effectors) to its environment. AI agents generally have the autonomy (defined as the ability to operate independently and make decisions without constant human intervention) and authority (defined as the granted permissions and access rights to perform specific actions within defined boundaries) to take actions to achieve a set of specified goals, thereby modifying their environment.”
“AI agents [are] systems capable of pursuing complex goals with limited supervision,” having “greater autonomy, access to external tools or services, and an increased ability to reliably adapt, plan, and act open-endedly over long time-horizons to achieve goals.”
“Agents,” Sept. 2024, Julia Wiesinger, Patrick Marlow, and Vladimir Vuskovic, Google
“[A] Generative AI agent can be defined as an application that attempts to achieve a goal by observing the world and acting upon it using the tools that it has at its disposal. Agents are autonomous and can act independently of human intervention, especially when provided with proper goals or objectives they are meant to achieve. Agentscan also be proactive in their approach to reaching their goals. Even in the absence ofexplicit instruction sets from a human, an agent can reason about what it should do next to achieve its ultimate goal.”
Defining long-term planning agents as “an algorithm designed to produce plans, and to prefer plan A to plan B, when it expects that plan A is more conducive to a given goal over a long time horizon.”
“An artificial intelligence (AI) agent refers to a system or program that is capable of autonomously performing tasks on behalf of a user or another system by designing its workflow and utilizing available tools.
Table 1. Definitions of “AI agents”
These definitions highlight common characteristics of new AI agents, including:
Autonomy and adaptability: Users generally provide an agent with the task they want it to achieve, but neither they nor the agent’s designers specify how to accomplish the task, leaving those decisions to the agent. For example, upon being instructed by a business to project the sales revenue of its flagship product for the next six months, the agent may decide that it needs sales figures from the last two years and use certain tools (e.g., a text retriever) to obtain these details. If it cannot find these figures or if they contain errors, it may determine that the next step is to seek information from other documentation. Agentic systems may incorporate human review and approval over some or all decisions.
These characteristics enable advanced agents to achieve goals that are beyond the capabilities of other AI models and systems. However, they also raise questions for practitioners about the data protection issues organizations may encounter when developing or deploying these technologies.
Emerging Privacy and Data Protection Issues with Agentic AI
While the latest AI agents may raise similar risks to consequential decision-making and LLMs, they can also exacerbate or pose novel privacy and data protection considerations. The economic and social impact of AI agents is a topic of heated debate and significant financial investment, but there has been less attention on the potential impact of agents on privacy and data protection. In order to effectuate tasks and decision making with autonomy, especially for consumer-facing tools and services, AI agents will need access to data and systems. In fact, much like human assistants, AI agents may be at their most valuable when they are able to assist with tasks that involve highly sensitive data (e.g., managing a person’s email, calendar, or financial portfolio, or assisting with healthcare decision-making).
As a result, many of the same risks relating to consequential decision-making and LLMs (or to machine learning generally) are likely to be present in the context of agents with greater autonomy and access to data. For example, like some LLMs, some AI agents transmit data to the cloud due to the computing requirements of the most powerful models, which may expose the data to unauthorized third parties (e.g., the recent Data protection impact assessment on the processing of personal data with Microsoft 365 Copilot for Education). As with chatbots that use LLMs, AI agents with anthropomorphic qualities may be able to steer individuals towards or away from conducting certain actions against the user’s best interest. Other examples of cross-cutting data protection issues include challenges related to having a lawful basis for model training, operationalizing data subject rights, and ensuring adequate explainability. These legal and policy issues for LLMs, which are the subject of ongoing debate and legal guidance, are only heightened in the context of agentic systems with enhanced capabilities.
In addition, more recent AI agents may present some novel privacy implications or exacerbate data protection issues that go beyond those associated with LLMs.
Data collection and disclosure considerations:The latest AI agents may need to capture data about a person and their environment, including sensitive information, in order to power different use cases. As with LLMs, the collection of personal data by agents will often trigger the need for having a lawful ground in place for such processing. When the personal data collected is sensitive, additional requirements for lawfully processing them often apply too. While current LLM-based systems may train and operate using personal data, they lack the tools (e.g., application programming interfaces, data stores, and extensions) to access external systems and data. The latest AI agents may be equipped with these tools, which could enable them to obtain real-time information about individuals. For example, some agents may take screenshots of a user’s browser window in order to populate a virtual shopping cart, from which intimate details about a person’s life could be inferred. As the number of individuals using AI agents and its use cases grow, so too could AI agents’ access to personal data. For example, AI agents may collect many types of granular telemetry data as part of their operations (e.g., user interaction data, action logs, and performance metrics). Increasingly complex agents may collect large quantities of telemetry information, which may qualify as personal data under data privacy legal regimes.
Security vulnerabilities: Advanced AI agents’ design features and characteristics may make them susceptible to new kinds of security threats. Adversarial attacks on LLMs, such as the use of prompt injection attacks to get these models to reveal sensitive information (e.g., credit card information), can impact AI agents too. Besides causing an agent to reveal sensitive information without permission, prompt injection attacks can also override the system developer’s safety instructions. While prompt injection is not a threat unique to the latest AI agents, new kinds of injection attacks could take advantage of the way agents work to perpetuate harm, such as installing malware or redirecting them to deceptive websites.
Accuracy of outputs: Hallucinations, compounding errors, and unpredictable behavior may impact the accuracy of an agents’ outputs. LLM hallucinations—the making up of factually untrue information that looks correct—may affect the accuracy of an agent’s outputs. These hallucinations are closely tied to the “temperature” parameter that controls randomness in the model’s attention mechanism: higher temperatures increase creativity and the risk of hallucinations, while lower temperatures reduce hallucinations but may limit the agent’s adaptability. However, errors that affect agent outputs may have different implications for individuals, such as misrepresenting a user’s characteristics and preferences when it fills out a consequential form. In addition to hallucinations, the latest AI agents may experience compounding errors, which could occur while the systems perform a sequence of actions to complete a task (e.g., managing a customer’s account). Compounding errors is the phenomenon where the agent’s accuracy decreases the more steps a task takes. For example, an AI agent creating a travel experience may experience an error while making a one-day hotel booking, which cascades into misaligned restaurant reservations and museum tickets. This holds true even when the model’s accuracy is high. Some AI agents may act in unpredictable ways due to dynamic operational environments and agents’ non-deterministic nature—producing probabilistic outcomes, adapting to new situations, learning from data, and exhibiting complex decision-making—leading to malfunctions that affect output accuracy. These accuracy issues may be challenging to redress through risk management testing and assessments and exacerbated when different AI agents interact with each other.
Barriers to “alignment”: Some AI agents may pursue tasks in ways that conflict with human interests and values, including data protection considerations. AI alignment refers to designing AI models and systems to pursue a designer’s goals, such as prioritizing human well-being and conforming to ethical values. Misalignment problems are not new to AI, but continued technological advances with agents may make it challenging for organizations to achieve alignment through safeguards and safety testing. LLMs can fake alignment by strategically mimicking training objectives to avoid undergoing behavioral modifications. These challenges have data protection implications for the latest AI agents. For example, an agent may decide that it needs to access or share sensitive personal data in order to complete a task. Such behavior could implicate an individual’s data protection interest in having control over their data when personal data is processed during deployment. Practitioners must be mindful of the need for safeguards to constrain this behavior, although research into model alignment has focused more on safety issues rather than privacy.
Explainability and human oversight challenges:Explainability barriers arise when users cannot understand an agent’s decisions, even if these decisions are correct. Users and developers may encounter difficulties in understanding how some AI agents reach decisions due to their complex processes. The black box problem, or the challenge of understanding how an AI model or system makes decisions, is not unique to agents. However, the speed and complexity of AI agents’ decision-making processes may create heightened roadblocks to realizing meaningful explainability and human oversight. AI agents utilizing language models can provide some of their reasoning in natural language, but these “chain-of-thought” insights are becoming more complicated and are not always indicative of the agent’s actual reasoning. These challenges may make it more difficult to reliably interrogate agents’ decision-making processes and manage risks.
Looking Ahead
Recent advances in AI agents could expand the utility of these technologies across the private and public sectors, but they also raise many data protection considerations. While practitioners may be aware of some of these considerations due to the relationship between LLMs and the latest AI agents, the unique design elements and characteristics of these agents may exacerbate or raise new compliance challenges. For example, an agent may manage privacy settings (e.g., accepting cookies so that it can continue working on a task) as part of its operations, although companies can establish safeguards to address this risk. In closing, practitioners should remain abreast of technological advances that expand AI agents’ capabilities, use cases, and contexts where they can operate, as these may raise novel data protection issues.
This year’s Winning Privacy Papers to be Honored at the Future of Privacy Forum’s 15th Annual Privacy Papers for Policymakers Event
The Future of Privacy Forum’s 15th Annual Privacy Papers for Policymakers Award Recognizes Influential Privacy Research
The PPPM Awards recognize leading U.S. and international privacy scholarship that is relevant to policymakers in the U.S. Congress, federal agencies, and international data protection authorities. Six winning papers, two honorable mentions, one student submission, and a student honorable mention were selected by a diverse group of leading academics, advocates, and industry privacy professionals from FPF’s Advisory Board.
Authors of the papers will have the opportunity to showcase their work at the Privacy Papers for Policymakers ceremony on March 12, in conversations with discussants, including James Cooper, Professor of Law, Director, Program on Economics & Privacy, Antonin Scalia Law School, George Mason University, Jennifer Huddleston, Senior Fellow in Technology Policy, Cato Institute, and Brenda Leong, Director, AI Division, ZwillGen.
“Data protection and artificial intelligence regulations are increasingly at the forefront of global policy conversations,” said FPF CEO Jules Polonetsky. “And it’s important to recognize the academic research that explores the nuances surrounding data privacy, data protection, and artificial intelligence issues. Our award winners have explored these complex areas ― to all of our benefits.”
FPF’s 2025 Privacy Papers for Policymakers Award winners are:
Privacy laws are traditionally associated with democracy. Yet autocracies increasingly have them. Why do governments that repress their citizens also protect their privacy? This Article answers this question through a study of China. China is a leading autocracy and the architect of a massive surveillance state. But China is also a major player in data protection, having enacted and enforced a number of laws on information privacy. To explain how this came to be, the Article first discusses several top-down objectives often said to motivate China’s privacy laws: advancing its digital economy, expanding its global influence, and protecting its national security. Although each has been a factor in China’s turn to privacy law, even together, they tell only a partial story. Through privacy law, China’s leaders have sought to interpose themselves as benevolent guardians of privacy rights against other intrusive actors—individuals, firms, and even state agencies and local governments. This Article adds to our understanding of privacy law, complicates the relationship between privacy and democracy, and points toward a general theory of authoritarian privacy.
The Great Scrape: The Clash between Scraping And Privacy by Daniel J. Solove, George Washington University Law School and Woodrow Hartzog, Boston University School of Law and Stanford Law School Center for Internet and Society
Artificial intelligence (AI) systems depend on massive quantities of data, often gathered by “scraping” – the automated extraction of large amounts of data from the internet. A great deal of scraped data is about people. This personal data provides the grist for AI tools such as facial recognition, deep fakes, and generative AI. Although scraping enables web searching, archival, and meaningful scientific research, scraping for AI can also be objectionable or even harmful to individuals and society. Organizations are scraping at an escalating pace and scale, even though many privacy laws are seemingly incongruous with the practice. In this Article, we contend that scraping must undergo a serious reckoning with privacy law. Scraping has evaded a reckoning with privacy law largely because scrapers act as if all publicly available data were free for the taking. But the public availability of scraped data shouldn’t give scrapers a free pass. Privacy law regularly protects publicly available data, and privacy principles are implicated even when personal data is accessible to others. This Article explores the fundamental tension between scraping and privacy law.
Debates in AI ethics often hinge on comparisons between AI and humans: which is more beneficial, which is more harmful, which is more biased, the human or the machine? These questions, however, are a red herring. They ignore what is most interesting and important about AI ethics: AI is a mirror. If a person standing in front of a mirror asked you, “Who is more beautiful, me or the person in the mirror?” the question would seem ridiculous. Sure, depending on the angle, lighting, and personal preferences of the beholder, the person or their reflection might appear more beautiful, but the question is moot. AI reflects patterns in our society, just and unjust, and the worldviews of its human creators, fair or biased. The question then is not which is fairer, the human or the machine, but what can we learn from this reflection of our society and how can we make AI fairer? This essay discusses the challenges to developing fairer AI, and how they stem from this reflective property.
On paper, the Federal Trade Commission’s consumer protection authority seems straightforward: the agency is empowered to investigate and prevent unfair or deceptive acts or practices. This flexible and capacious authority, coupled with the agency’s jurisdiction over the entire economy, has allowed the FTC to respond to privacy challenges both online and offline. The contemporary question is whether the FTC can draw on this same authority to curtail the data-driven harms of commercial surveillance or emerging technologies like artificial intelligence. This Essay contends that the legal answer is yes and argues that the key determinants of whether an agency like the Federal Trade Commission will be able to confront emerging digital technologies are social, institutional, and political. Specifically, it proposes that the FTC’s privacy enforcement occurs within an “Overton Window of Enforcement Possibility.”
Anonymity is an important principle online. However, malicious actors have long used misleading identities to conduct fraud, spread disinformation, and carry out other deceptive schemes. With the advent of increasingly capable AI, bad actors can amplify the potential scale and effectiveness of their operations, intensifying the challenge of balancing anonymity and trustworthiness online. In this paper, we analyze the value of a new tool to address this challenge: “personhood credentials” (PHCs), digital credentials that empower users to demonstrate that they are real people—not AIs—to online services, without disclosing any personal information. After surveying the benefits of personhood credentials, we also examine deployment risks and design challenges. We conclude with actionable next steps for policymakers, technologists, and standards bodies to consider in consultation with the public.
Governments and policymakers increasingly expect practitioners developing and using AI systems in both consumer and public sector settings to proactively identify and address bias or discrimination that those AI systems may reflect or amplify. Central to this effort is the complex and sensitive task of obtaining demographic data to measure fairness and bias within and surrounding these systems. This report provides methodologies, guidance, and case studies for those undertaking fairness and equity assessments — from approaches that involve more direct access to data to ones that don’t expand data collection. Practitioners are guided through the first phases of demographic measurement efforts, including determining the relevant lens of analysis, selecting what demographic characteristics to consider, and navigating how to hone in on relevant sub-communities. The report then delves into several approaches to uncover demographic patterns.
FPF also selected a paper for the Student Paper Award: Data Subjects’ Reactions to Exercising Their Right of Accessby Arthur Borem, Elleen Pan, Olufunmilola Obielodan, Aurelie Roubinowitz, Luca Dovichi, and Blase Ur at the University of Chicago; and Michelle L. Mazurek from the University of Maryland. A Student Paper Honorable Mention went to Artificial Intelligence is like a Perpetual Stew by Nathan Reitinger, University of Maryland – Department of Computer Science.
In reviewing the submissions, winning papers were awarded based on the strength of their research and proposed policy solutions for policymakers and regulators in the U.S. and abroad.
The Privacy Papers for Policymakers Award event will be held on March 12, 2025, at FPF’s offices in Washington, D.C. The event is free and registration is open to the public.
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About Future of Privacy Forum (FPF)
The Future of Privacy Forum (FPF) is a global non-profit organization that brings together academics, civil society, government officials, and industry to evaluate the societal, policy, and legal implications of data use, identify the risks, and develop appropriate protections.
FPF believes technology and data can benefit society and improve lives if the right laws, policies, and rules are in place. FPF has offices in Washington D.C., Brussels, and Singapore. Learn more at fpf.org.
5 Ways to Be a Top Dog in Data Privacy
Data Privacy Day, or Data Protection Day in Europe, is recognized annually on January 28 to mark the anniversary of Convention 108, the first binding international treaty to protect personal data. To raise awareness for the day and promote best practices for data privacy, we’ve partnered with Snap to create a Data Privacy Day Snapchat Lens that lets you choose what type of privacy pup best reflects your personality. Check it out by scanning the Snapchat code!
Once you’ve determined which privacy pup you are, learn more about protecting your privacy with these 5 quick, easy steps.
1. Share your Information with Websites and Apps you Trust
Today, almost everything we do online involves companies collecting personal information about us. When we’re subscribing to marketing emails, making online purchases, filling out surveys, or even applying for jobs online, websites are collecting more information than ever before, and we’ve become accustomed to sharing personal information daily. However, it’s important to be cautious and trust a website or app before sharing any personal information with it.
There are a few ways to evaluate a website or app before sharing personal information. The first is to check the website’s url and domain name. Confirm that both the name of the website is spelled properly, and the domain name ending in .org, .com, .edu, or .gov, which are typically (but not always) more credible. Next, you can look for clear information about the leaders of the organization and their contact information on the website. If that information isn’t available, or is difficult to find, be cautious because you may not know who will be responsible for your personal information. Lastly, take a few minutes to evaluate a company’s privacy policy. The policy should clearly state the company’s full name, explain how they will be using your information, and may include information about the security measures in place. Many states also require companies to let you submit a data access request, and it’s helpful to check that the company is complying with their state law and displaying that information.
2. Update your passwords and multi-factor authentication regularly
Password re-use is one of the top ways that unwanted eyes can get into your accounts: once one service where you used a password is breached, criminals will likely try the same username and password combination on other services just to see if it works. To get a sense of the scale of the risk, you check your info on web service “Have I Been Pwned” (available at haveibeenpwned.com), which allows you to enter your email address and see what data breaches that email has been included in.
Because of the risks involved in recycling passwords, using unique passwords is an essential step for keeping personal information private. You can also consider utilizing a password manager. Password managers save passwords as you create and log in to your accounts, often alerting you of duplicates and suggesting the creation of a stronger password. And no, the name of your dog is not a strong password.
For example, if you use an Apple product when signing up for new accounts and services, you can allow your iPhone, Mac, or iPad to generate strong passwords and safely store them in iCloud Keychain for later access. Some of the best third-party password managers can be found here.
When possible, you should also utilize multi-factor authentication along with a password. This extra step ensures that simply inputting a compromised password is not enough to provide access to your account without an extra step, typically the connection of a device like a yubikey or submission of a numeric code sent to a phone number, e-mail address, or authentication application on your phone. While some forms of multi-factor authentication may be more protective and more resilient than others, any choice will significantly increase the security in comparison to a password alone. You can see how easy it is to set up multi-factor authentication on Snapchat using their easy-to-understand articles, available online.
3. Respect other peoples’ privacy
It’s important to be mindful about the information you share and see on social media. Consider the reach of your own posts, and avoid sharing anything you wouldn’t want to be saved or widely shared, whether it’s about you or someone else. Many social media sites like Instagram, Facebook, and Snapchat allow you to share images and chat with a closed group or limited number of friends, and it’s important to honor when someone chooses to keep information non-public when they share it in closed or private settings. Don’t screenshot or reshare private stories or messages from others.
4. Review all social media settings
Many social media sites include options on how to tailor your privacy settings to limit how data is collected or used. Snap provides privacy options that control who can contact you and many other options. Start with the Snapchat Privacy Center to review your settings. You can find those choices here.
Snap also provides options for you to view any data they have collected about you, including account information and your search history. Downloading your data allows you to view what information has been collected and modify your settings accordingly.
Instagram allows you to manage various privacy settings, including who has access to your posts, who can comment on or like your posts, and manage what happens to posts after you delete them. You can view and change your settingshere.
TikTok allows you to decide between public and private accounts, allows you to change your personalized ad settings, and more. You can check your settingshere.
X allows you to manage what information you allow other people on the platform to see and lets you choose your ad preferences. Check your settings here.
Facebook provides a range of privacy settings that can be found here.
In addition, you can check the privacy and security settings for other popular applications such as Reddit and Pinteresthere. Be sure to also check your privacy settings if you have a profile on a popular dating app such as Bumble, Hinge, or Tinder.
What other social media apps do you use often? Check to see which settings they provide!
5. Use incognito settings to keep personal information about you hidden
Many browsers and apps allow you to turn on a setting that lets you continue to use the service without sharing as much personal information as you normally would.
On Chrome, you can browse the web more privately using incognito mode. To activate, open Chrome, under “More,” click “New Incognito Window.”
Using Safari, you can choose “private browsing” by opening Safari, clicking “File” and then “New Private Window.” If you have the app, you can choose to always browse privately by clicking “Settings” and then for the option “Safari opens with” pop-up menu, choose “a new private window.”
Mozilla also has options for using Firefox in “private browsing mode.” Click Firefox’s menu button, and then click “New private window.” You can also choose to always be in private browsing mode by choosing “Use custom settings for history” from the Firefox’s menu and checking the “Always use private browsing mode” setting.
Browsers like DuckDuckGo and Brave also default to private browsing mode. You can read more about DuckDuckGo’s anonymous browsing settings here, and Brave’s privacy protections here.
Using Snapchat, you can turn on Ghost Mode. While using it, your location won’t be visitable to anyone, including friends you may have previously shared your location with on Snapchat’s Snap Map. To turn it on, open the Map, tap the ⚙️ button at the top of the map screen, toggle Ghost Mode to on, and select how long you’d like to enable Ghost Mode.
If you’re interested in learning more about one of the topics discussed here or other issues driving the future of privacy, sign up for our monthly briefing, check out one of our upcoming events, or follow us on X, LinkedIn, or Instagram.
FPF brings together some of the top minds in privacy to discuss how we can all benefit from the insights gained from data while respecting the individual right to privacy.
What to Expect in Global Privacy in 2025
Next year, in 2026, we will celebrate a decade after the adoption of the GDPR, a law with an unprecedented regulatory impact around the world, from California to Brazil, across the African continent, to India, to China, and everywhere in between. The field of data protection and privacy has become undeniably global, with GDPR-inspired laws (from a lesser to a bigger degree) adopted or updated in many jurisdictions around the world throughout the past years. This could not have happened in a more transformative decade for technologies relying on data, with AI decidedly getting out of its winter, and “connected-everything,” from cars to eyewear, increasingly shaping our surroundings.
While jurisdictions around the world were catching up with the GDPR or gearing their own approach to data protection legislation, the EU leaped in the past five years towards comprehensive (and sometimes incomprehensible) regulation of multiple dimensions of the digital economy: AI itself, online platforms through intermediary liability, content moderation and managing systemic risks on very large online platforms and search engines, online advertising in electoral campaigns, digital gatekeepers and competition, data sharing and connected devices, data altruism and even algorithms used in the gig economy.
Against this backdrop, I asked my colleagues in FPF’s offices around the world, who passionately monitor, understand, and explain legislative, regulatory, and enforcement developments across regions, what we should expect in 2025 in Global Privacy. From data-powered technological shifts and their impact on human autonomy, to enforcement and sectoral implementation of general data protection laws adopted in the past years, to AI regulation, cross-border data transfers, and the clash of online safety and children’s privacy, this is what we think you should keep on your radar:
1. AI becoming ubiquitous will put self-determination and control in the center of global privacy debates
“Expect AI to become ubiquitous in everything we do online,” signals Dr. Rob van Eijk, FPF Managing Director for Europe. This will not only bring excitement for tech enthusiasts but also a host of challenges, heightened by the expected increase in consumers using AI agents. “The first challenge is maintaining personal autonomy in the face of technological development, particularly regarding AI,” weighs in Rivki Dvash, Senior Fellow with ITPI – FPF Israel.
Rivki foresees two prominent dimensions of this topic: first, at the ethical level, and second, at the regulatory level, particularly concerned “with the limits of the legitimacy of the use of AI while trying to contour the uniqueness of a person over a machineand the desire to preserve personal autonomy in a space of choice.” “What does it mean to be a human in an Agentic AI future?” is a question that Rob says will ignite a lot of thinking in the policy world in 2025. This makes me think of an older paper from Prof. Mireille Hildebrandt, “Privacy as Protection of the Incomputable Self: From Agnostic to Agonistic Machine Learning” (2019), where she described a framework that could “provide the best means to achieve effective protection against overdetermination of individuals by machine inferences.”
I expect the idea of “control” over one’s persona and personal information in the world of Generative and Agentic AI to increasingly permeate and fuel regulatory debates. In its much-expected Opinion on AI systems and data protection law published over the Holidays, the European Data Protection Board (EDPB) identified “the interest in self-determination and retaining control over one’s own personal data” as chief among individuals’ interests that must be taken into account and balanced, both when personal data is gathered for the development of AI models and with regards to personal data processed once the model is deployed.
Putting self-determination and control at the center of AI governance will not be just academic. For instance, the EDPB asked for an “unconditional opt-out from the outset,” “a discretionary right to object before the processing takes place” for developing and deploying AI systems, “beyond the conditions of Article 21 GDPR,” in order for legitimate interests to be considered as a valid lawful ground legitimizing consentless processing of personal data for AI models.
Rob adds that in 2025, we will see users “becoming increasingly reliant on AI companions for decision-making, from small choices like what to watch on streaming services to larger life decisions.” He highlights what will be one of the key privacy and data protection implications of all this: “AI companions will get unprecedented access to sensitive personal data, from financial transactions to private conversations and daily routines.” Protecting sensitive data in this context, especially with inferences broadly recognized as being covered by such enhanced safeguards under data protection law regimes, will be a key challenge that will keep privacy experts busy this year.
But the ideas of “control,” “self-determination,” and “autonomy” in relation to one’s own personal data are particularly fragile when it comes to non-users or bystanders whose data is collected through another person’s use of a service or device. This is one of the big issues that Lee Matheson, FPF Deputy Director for Global Privacy, sees as defining an enforcement push from Data Protection Authorities (DPAs) from Canada to Europe this year, particularly as it relates to Augmented Reality and connected devices: “It’s a cross-cutting technology that implicates lawful bases for collection/processing, AI and automated decision-making (particularly facial recognition), secondary uses, and data transfers (as unlike smartphones, activity is less likely to be kept on-device). I think a particular focus could be on how to vindicate the rights of non-user data subjects whose information is captured by these kinds of devices.”
2. Three different speeds for AI legislation: Moderation in APAC, Implementation in Europe, Acceleration in Latin America
AI governance and data protection are closely linked, as shown above, which makes AI legislation a particularly poignant topic to follow. “Whether through hard or soft law approaches, preventing significant fragmentation of AI rules globally will be high on the agenda,” observes Bianca-Ioana Marcu, FPF Deputy Director for Global Privacy. Bianca has been closely following initiatives of international organizations and networks in the AI governance space throughout the last year, like the efforts of the UN, the OECD, or the G7 in this space, and she believes that in 2025, “international fora and the principles and guidelines agreed upon within such groups will act as the driving force behind AI standard-setting.” Bianca adds that we might see efforts towards “harmonizing regional data protection rules in the interests of supporting the governance and availability of AI training data.” I can see this happening, for instance, across economic regions in Africa, or even at the ASEAN level.
As for legislative efforts around the world targeting AI, the team identifies three different speeds. In the Asia-Pacific (APAC) region, Josh Lee Kok Thong, FPF Managing Director for APAC, foresees a “possible cooling down” of the race to adopt AI laws and other regulatory efforts. “There will be signs of slight regulatory fatigue in AI governance and regulatory initiatives in APAC. This is especially so among the more mature jurisdictions, such as Japan, Singapore, China, and Australia. Rather than developing new headline regulatory or governance initiatives, efforts are likely to focus on the development of tools for evaluation and content provenance,” he says. Josh notes that jurisdictions across APAC will be closely watching how the implementation of the EU AI Act unfolds, as well as the US regulatory stance towards AI under President Trump’s administration before deciding what steps to take.
In contrast, Latin America will likely move full speed ahead toward AI legislation. Maria Badillo, Policy Counsel for Global Privacy, explains that “this year will mark significant progress on initiatives to govern and regulate AI across multiple countries in Latin America. Brazil has taken a leading role and is getting closer to adopting a comprehensive law in 2025 after the Senate’s recent approval of the AI bill. Other countries like Chile, Colombia, and Argentina have introduced similar frameworks.” Maria says that this will happen mainly under the influence of the EU AI Act, but also from Brazil’s AI bill.
When it comes to AI legislation, the EU is catching its breath this year, focusing on the implementation of the EU AI Act, which was adopted last year and whose application starts rolling out in a month. Necessary Codes of Conduct – like the one dedicated to general purpose AI, implementing acts, and specific standards are expected to flow within the next 18 months or so. But this year, we will certainly see the first signs of whether this new law will successfully achieve its goals. A good indicator will be observing in practice the intricate web of authorities tasked by the EU AI Act with oversight, implementation, and enforcement of the law. “The lack of a one-stop-shop mechanism and the presence of several authorities in the same jurisdiction will be a first test of the efficiency of the AI Act and the authorities’ ability to coordinate,” highlights Vincenzo Tiani, Senior Policy Counsel in FPF’s Brussels office.
Meanwhile, it is expected that DPAs will gain a more prominent role in enforcing the law on matters at the intersection of the GDPR with the various new EU acts regulating the digital space, including the EU AI Act. “DPAs will be increasingly called to step up and drive enforcement actions on a broad number of issues also falling under other EU regulatory acts, but which involve the processing of personal data and the GDPR,” says Andreea Serban, FPF Policy Analyst in Brussels. This will be particularly evident regarding AI systems, after a first infringement decision in a series of complaints surrounding ChatGPT was issued by the Italian DPA, the Garante, at the end of 2024.
The space in AI governance that the GDPR occupies will visibly expand this year, including into issues where copyright is considered central. Vincenzo explains that “the licenses provided by newspapers to providers of LLMs, at least so far, do not cover the protection of personal data contained therein.” The Italian DPA has already raised the flag on this issue.
Countervailing some of the biggest risks of Generative AI beyond the processing of personal data will keep regulators across Europe busy, be they DPAs, the European Commission’s AI Office, or other national EU AI Act implementers. Dr. Desara Dushi, Policy Counsel in our Brussels office, anticipates “a sharp focus on controlling the use of synthetic data that fuels harmful content, with the rise of advanced emotional chatbots and the proliferation of deepfakes.” This could happen through “more robust and specific guidelines targeting generative AI’s risks.”
3. International Data Transfers will come back on top of the Global Privacy agenda
As I anticipated last year in my 2024 predictions, international data transfers started intertwining with the broader geopolitical goals of countries caught in the AI race. This trend will become even more visible in 2025, when we expect that issues related to international data transfers will come back to the top of the Global Privacy agenda, fueled this time not only by the geopolitics of AI development, but also by the broader dynamic between a new European Commission in Brussels and a new administration in Washington DC.
“I think transatlantic data transfers issues will be brought back to center stage in the dynamics of EU’s implementation of digital regulations like the DSA and the DMA on one side, and the priorities of the new administration in the US on the other side,” foresees Lee Matheson, who is based in our Washington DC office and who closely follows international data transfers. But, this time around, the pressure on the continuity of data flows between the US and the EU might first come from the US side.
Lee thinks we should follow closely what happens with Executive Order (E.O.) 14117 “Preventing Access to Americans’ Bulk Sensitive Personal Data and United States Government-Related Data by Countries of Concern,” an instrument adopted last year which bans transfers of bulk sensitive data of Americans outside of the U.S. in specific circumstances and only towards designated countries of concern (currently China, Iran, Russia, Venezuela, Cuba and North Korea). The Executive Order could be left as is, amended, repealed, or replaced by the new administration in Washington. But an interesting point Lee raises is that “E.O. 14117 and its associated DOJ Rules, in particular, provide a framework that could be extended to additional jurisdictions.”
On the other hand, the General Court of the CJEU started early this year with a decision that recognized plaintiffs can obtain compensation for non-material damage if their personal data have been transferred unlawfully, in a case involving transfers made by the European Commission to the U.S. before the Data Privacy Framework became effective. This clarification made by the Court could increase the appetite for challenging the lawfulness of international data transfers. In part due to pressure on more traditional data transfer mechanisms, Lee thinks “the world will see alternative systems for international data transfers, such as the Global Cross Border Privacy Rules system, become substantially more prominent.”
Indeed, transatlantic data flows will only be one of many cross-border data flow stories to follow. “We may well see continuing fragmentation of the cross-border data transfer landscape globally and in APAC into clusters of likeminded jurisdictions, ranging from those like Singapore and Japan that are working to promote trusted data flows (especially through initiatives like the Global CBPRs) to those like Indonesia, India, and Vietnam that have recently renewed their interest in adopting data localization measures,” adds Dominic Paulger, FPF Deputy Director for APAC, from our Singapore office. He also thinks that geopolitical and regulatory trends in the US and the EU will affect dynamics in APAC. “While there will be tension between data localization requirements in some jurisdictions, navigating the right balance will be crucial in shaping both regulatory strategies and business practices across the region in 2025,” concludes Sakshi Shivhare, Policy Associate for FPF APAC.
4. Convergence of youth privacy and online safety will take the spotlight around the world
Convergence of children’s and teen’s privacy and online safety issues into new legislative action, regulatory initiatives, or public policy measures is being emphatically highlighted as a top issue to watch in 2025 by my colleagues across APAC, India, EU, and, to some extent, Latin America.
Dominic explains that jurisdictions in APAC are increasingly incorporating online safety provisions into data protection laws, with some focusing on age verification or age-appropriate design requirements. This highlights tensions between real concerns about young people’s online safety and the substantial privacy risks that are posed by age assurance technologies and related mandates. Experts have raised the need for more cross-cutting conversations to identify and address privacy and security risks created by regulatory efforts. He expects the focus on youth safety to continue throughout 2025, “especially following Australia’s recent ban on social media use for under-16s.” This approach has been criticized by some youth safety and privacy experts while being lauded by others. Several jurisdictions, including Singapore, are considering emulating this model, and many more will be watching to see how it plays out.
“The dialogue around online youth safety will likely intensify in the EU as well, with a notable focus on children’s overall well-being and how that intersects with youth privacy rights,” foresees Desara, who comes to FPF’s Brussels office with extensive research and policy work in this space. “The narrative may broaden to encompass a more holistic approach to child protection, leading toward ‘child rights by design’ requirements,” she adds.
The Child Sexual Abuse Regulation (CSAR) proposal in the EU will continue to be the subject of fierce debate in 2025. The CSAR debate has been characterized by proponents noting the measure’s noble goals and critics characterizing the proposal as technically unworkable and certain to undermine core privacy and security measures. Desara concludes: “With early insights emerging from the UK’s Online Safety Act, the ongoing intersection of privacy and youth safety promises to be a defining issue in the year ahead.”
5. We have a new law, now what? Implementation and groundwork for enforcement will be central in APAC, LatAm, Africa, and EU
Several jurisdictions across all regions will focus on starting the implementation of recently adopted data protection laws. Perhaps this is most visible in the APAC region, which “is seeing a significant maturation of data protection frameworks,” as Sakshi Shivhare notes. Examples include “the promulgation of India’s DPDPA Rules, the phased implementation of Malaysia’s PDPA amendments, the much-awaited finalization of implementing regulations for Indonesia’s PDP Law, and the implementation of Australia’s first tranche of Privacy Act amendments,” explains Josh Lee.
This year, significant attention will be paid to India’s DPDPA Implementing Rules. “With the draft rules now released, attention will shift to public consultations and how the government addresses feedback,” notes Bilal Mohamed, FPF Policy Analyst based in New Delhi. He points out that some of the key concerns discussed so far relate to “the possible reintroduction of data localization norms, (Rules 12(4) and 14) and the practical concerns with the implementation of Verifiable Parental Consent,” also adding to two of the trends we identified above related to international data transfers and children’s privacy and online safety. “Together, these shifts suggest that 2025 will be pivotal for creating a more cohesive, though not necessarily uniform, privacy landscape across APAC,” concludes Sakshi.
Jurisdictions across Africa will face similar challenges this year. Mercy King’ori, FPF Policy Manager for Africa, based in Nairobi, thinks we should expect “more sectoral regulations as controllers and processors continue to seek clarity on the practical implementation of legal provisions in most data protection laws across the continent. This is the continuation of a trend from 2024 where DPAs have been identifying gaps in the implementation of the laws and proposing regulations and guidelines in data-intensive sectors such as education, marketing, and finance.”
She adds that, in parallel, DPAs are dealing with an increasing number of complaints: “The rise of complaints has been due to heightened awareness of data subject rights and DPAs eager to push for compliance with national data protection regimes. The move towards enforcing compliance has even seen DPAs initiate assessments on their own volition, such as South Africa’s Information Regulator leading to enforcement notices and penalties.”
Secondary or implementing regulations are also expected to drive the agenda in Latin America, with a priority on “protecting children’s data, data subject rights, and processing of personal data in the context of AI,” points out Maria Badillo. She specifically notes that “active DPAs in the region, such as those from Brazil and Argentina, have identified AI regulation, exercise of data subject rights, and processing of children’s data among the priority areas for developing secondary regulations and guidance in 2025.”
Even the EU will have implementation fever this year – which is to be expected after intense lawmaking of everything digital and data during the first von der Leyen Commission. “In 2025, we should see a policy shift, prioritizing the application and implementation of existing frameworks, like the EU AI Act, the DSA, the DMA, and so forth, rather than proposals of new legislation,” points out Andreea Serban, who also notes recent messaging in Brussels signaling a decreased focus on regulation, especially in the aftermath of the Draghi report.
This is indeed how the Brussels agenda reads, but it shouldn’t be a surprise if new legislation, like the Digital Fairness Act, will make its way as an official proposal as soon as this year. And with other files like the CSAR still on the legislative train, or the constant “hide and seek” with the ePrivacy Regulation, the Brussels legislation machine might slow down, but it will not halt.
6. Bigger public policy debates will end up shaping global privacy: from “Innovation v. Regulation,” to checks and balances over government access to data
The “Innovation v. Regulation” dichotomy has been omnipresent in the European public debate since the publication of the Draghi report last year, even as some are positing this is a false choice (see Anu Bradford or Max von Thun).
“With a new European Commission taking the reins in Brussels, and with political tides changing across the EU, the innovation versus regulation debate will continue to polarize the digital policy community. Repercussions will be felt in discussions regarding not only the application and enforcement of the DSA and the DMA but also for data protection law as we await new GDPR enforcement rules,” explains Bianca-Ioana Marcu. However, she suggests that this debate might be louder than having effects in practice, as Brussels will move ahead with its regulatory agenda of the new Commission. It is clear, though, that Brussels may experience a “shift towards promoting EU competitiveness,” as Andreea framed it, and that this will impact, even if incrementally, all the “digital agenda” files.
While most of the attention in India might be focused on the DPDPA Implementing Rules, promoting the country’s competitiveness is a bigger goal for many, which could result in regulatory changes supporting it. Bilal signals that there are interesting data-sharing initiatives coming up at a sectoral level. “For instance, MeitY plans to launch an IndiaAI datasets platform to provide high-quality datasets (non-personal data) for AI developers and researchers. Similar initiatives are underway in sectors such as healthcare, e-commerce, and agriculture,” he says. These initiatives are quite similar to the EU Data Spaces, which are also expected to advance. “It will be fascinating to see how these initiatives align with the DPDPA, and how this shapes the definition of ‘non-personal data’ in India,” adds Bilal.
One last bigger public policy debate that may impact concrete data protection this year remains the checks and balances over government access to personal data. For instance, Rivki, based in our Tel Aviv office, highlights that this year she expects the privacy community to confront the long-term privacy consequences of the exceptional measures taken by the government during the war, such as storage of fingerprints in databases or authorization of intrusion into security cameras without consent. The privacy community will likely be focused to “ensure that any measures implemented during this period do not persist or become the new standard for privacy,” she says.
Government access to data shapes up to also be top of mind in policy debates in India, with Bilal noting that “on a broader scale, constitutional challenges related to government exemptions under the DPDPA may surface in the Supreme Court once the implementing rules are officially notified.”
7. A dark horse prediction and further reading
Before ending the round-up of issues to follow in 2025 in Global Privacy, I will make my dark horse prediction: The reopening of the GDPR might appear more convincingly on the regulatory agenda this year, once the procedural reform is done. What seemed almost sacrilegious a couple of years ago will now look more likely, especially in the light of DPAs becoming active in enforcing the GDPR on AI systems, and eventual hiccups of non-DPA enforcers applying the digital strategy package at the intersection with GDPR provisions.
Finally, for a good understanding of what the year might bring to US policymaking, check out this analysis by Jules Polonetsky, FPF CEO, for TechPolicy Press, “2025 May be the Year of AI Legislation: Will we see Consensus Rules or a Patchwork?,” as well as FPF Senior Director for U.S. Legislation Keir Lamont’sblog, “Five Big Questions (and Zero Predictions) for the US State Privacy Landscape in 2025.”
