National Artificial Intelligence Policy

1.1 Talent development

The strategy aims to develop AI talent across all educational and professional levels to address a shortage of approximately 65,000 digital technology professionals annually through: promoting AI skills, knowledge and ethical understanding in schools; integrating AI into technical-professional and higher education curricula (including through public-private working groups for the 44 percent of undergraduates in technical-professional institutions); creating new certification instruments beyond traditional diplomas; upskilling all Chilean workers in AI knowledge and critical understanding; establishing specialized AI programs and cross-disciplinary integration in higher education; strengthening computer science, robotics and AI hardware education; increasing masters and doctoral graduates to at least OECD average levels; training in legal, social science, humanities, business and entrepreneurship aspects of AI; and retaining talent through competitive opportunities and international networks. The strategy coordinates talent insertion into research, private and public sectors through mechanisms such as focused doctorate scholarships, maintains a registry to quantify and project specialized talent needs across sectors, and develops talent training roadmaps that specify needs, financing instruments, required collaborations, and necessary policies and investments through permanent exercises anticipating technological scenarios.

1.2 Technological infrastructure

Chile requires technological infrastructure including connectivity, cloud platforms, data storage and high-performance computing for AI development and deployment; while the country has above 82% internet access and benefits from data centers and public-private initiatives, it faces gaps with only 57% residential internet coverage and limited connectivity in non-urban areas. The policy aims to position Chile as a southern hemisphere hub for global-standard AI infrastructure by accelerating deployment of the national connectivity system through advancing fiber optic licensing in northern and southern zones and implementing last-mile solutions and 5G to expand bandwidth access.

3.1 Ethics

Artificial intelligence poses risks to fundamental rights including dignity, privacy, freedom of expression, and non-discrimination through issues such as algorithmic bias, biometric surveillance, and labour market impacts, requiring input from affected communities particularly from underrepresented regions and groups. The policy aims to build regulatory certainty by reviewing and amending existing regulations, establishing agile institutional structures for responsible AI development with flexible frameworks and private sector collaboration, and developing guidelines from pilots and regulatory sandboxes while ensuring representation of under-represented groups including children and adolescents. Algorithmic transparency standards and recommendations are required for critical applications in state administration regarding how decision-making algorithms operate and their training data, with Chile identifying bias in algorithms and databases to mitigate risks to privacy, personal data protection, and non-discrimination while participating in international standards discussions to assert regional leadership.

3.2 Impacts on employment

Artificial intelligence is changing work and requires new competencies, with risks of job losses particularly in repetitive roles, but technology adoption is expected to create new long-term employment opportunities; Chile will conduct prospective analysis of vulnerable occupations, develop support for worker transitions, strengthen a Labor Observatory with programs including Destino Empleo to provide labor market information and training for emerging occupations, and foster technology-enabled job creation, recognizing automation risks particularly for data entry workers, data labelers, customer service staff, farmers, machine operators, and service and sales workers. The policy will establish multi-sectoral discussion forums to gather workers' expectations, concerns and perceptions regarding AI-driven workplace transformation, then study labor law and regulation for adequacy, draft modifications and new legislation aimed at worker welfare, and develop best practice guidelines for integrating AI systems during labor transition based on input from affected workers.

3.3 Consumer relations

Where providers use AI in digital commerce, they must mitigate risks including discriminatory or unjust results, lack of transparency in contracting conditions, and improper handling of personal data; inform consumers clearly and simply in comprehensible language about AI system use, personal data processing purposes, and automated decision-making processes; and ensure algorithms are explainable and fair with internal review structures preventing automated decisions that violate consumer protection legislation and enabling corrective actions when decisions fail to comply with applicable law. The policy aims to develop a digital commerce ecosystem promoting ethical and responsible AI use that is transparent, ensures fair consumer treatment, and allows adequate consumer protection oversight, enabling Chile to fully realize AI benefits in consumer relations.

3.4 Creation, intellectual and industrial property

Chile must adopt its approach to AI intellectual property rights through legal or regulatory norms while balancing progress, creators' rights, public access to knowledge, and legal certainty, considering that international consensus rejects machines as IP rights holders but countries differ on patentability standards for AI-generated works. The government commits to modernizing intellectual property systems, participating in international dialogue on AI and intellectual property through multilateral bodies, identifying how national rules impact AI adoption, and conducting inventories of creations by, for, or assisted by AI systems with forward-looking regulatory analyses covering patents, copyright especially for software and databases, and trade secrets. The government will also promote critical reflection on AI's uses and dilemmas for arts and culture, and foster research, development and innovation in AI for creative industries through training spaces and cross-sector collaboration while improving data quality and interoperability.

3.5 Cybersecurity and cyberdefence

National cyberattacks have increased in complexity and impact, with AI and emerging technologies creating new risks while also offering potential to improve speed, precision and resilience of cyberdefence operations through intrusion and fraud detection and malware analysis of large information volumes, requiring data integrity and security in AI system collection, storage, processing and transmission. The government will incorporate AI into updates of the National Cybersecurity Policy and cyberdefence policies through multi-stakeholder dialogue, analyze legal frameworks for AI in cybersecurity, promote bills including a Cybersecurity and Critical Infrastructure Framework Law and an Informatics Crimes Law, and generate recommendations for using AI to counter cyberattacks in state systems. The government will also incorporate AI training into cybersecurity policies for professionals, promote research in future technologies like quantum computing, and update the Interministerial Cybersecurity Committee to become a multi-sector space for advancing cybersecurity actions involving AI.

3.6 Género

The government recognizes gender gaps in AI research, technology and innovation stemming from biased training data and unequal development teams, and commits to promoting gender equality by establishing monitoring systems with gender indicators for AI participation, promoting women's involvement in AI sectors to reach at least the OECD average, monitoring automation's differential gender impacts, incorporating gender-differentiated risk variables into labour market forecasting, and creating guidelines recommending data practices that reduce gender biases through dataset disaggregation while respecting privacy. AI systems must be assessed throughout their lifecycle to prevent gender-based discrimination proportionate to application criticality, and gender and equity criteria will be incorporated into algorithm training with public communication of women's contributions to AI fields.