Are you based in Latin America and interested in integrating Artificial Intelligence into your business?

Generative AI (AI) is a type of artificial intelligence that has the ability to create new content based on the data it has been trained on. The AI tool trains by recognizing patterns from the data, then generates outputs using those patterns, mimicking human creativity. Those outputs include:

• Text generation, such as answers to questions, creative writing or summaries of longer texts.
• Image creation, based on textual descriptions provided as input.
• Speech synthesis, including producing human-like spoken language from written text.

Traditional AI recognizes the patterns that it has already been trained on to perform tasks like:

• Visual recognition, such as identifying faces, animals or landmarks.
• Predictions, such as stock price forecasts by applying historical patterns to new data.
• Classifications, for instance, identifying whether an email is spam.
• Data analysis, or creating analytics from large datasets, identifying trends or patterns.

The quality and accuracy of generative AI outputs depend on factors like the training data, the design of the AI model, and the complexity of the prompts provided.

AI is increasingly impacting Latin America across various sectors, including healthcare, education, finance and agriculture. The adoption and development of AI in the region are mainly driven by:

1. Economic Growth: Latin American countries are recognizing the potential of AI to boost economic growth. Governments and the private sector are both investing in AI technologies to improve efficiency, reduce costs and foster innovation.
2. Education and research: Educational institutions in countries like Argentina, Brazil, Chile and Mexico are developing AI programs, and collaborating with international organizations to enhance their teaching and research capabilities.
3. Healthcare: AI is being used to improve healthcare services, including diagnostics, treatment planning, managing patient data and predicting disease outbreaks. For instance, AI-driven platforms are helping to identify COVID-19 cases and manage healthcare resources effectively throughout the region.
4. Finance: Multiple countries in Latin America are using AI for fraud detection, credit scoring, customer service and personalized financial products. Fintech companies are particularly active in integrating AI to serve the unbanked population and enhance financial inclusion.
5. Agriculture: AI applications in agriculture are helping to increase crop yields, optimize resource use and monitor environmental conditions. Drones and AI-powered analytics are being used for precision farming and sustainable agriculture practices throughout the region.

The main challenges Latin America has faced with respect to the widespread adoption of AI in the region include:

• limited access to high-quality data
• insufficient infrastructure
• shortage of skilled professionals
• management of privacy and data security

To address the above challenges, several Latin American governments are creating policies and strategies to support AI development. For example, Brazil has launched its national AI strategy to encourage AI innovation and research, while Colombia and Mexico are also working on national AI frameworks to support AI adoption and integration.

Generative AI is rapidly transforming workplaces globally. From crafting marketing copy to designing product prototypes, generative AI tools hold immense potential for efficiency and innovation.  This power comes with inherent risks, however, such as the potential for exposure of confidential information, privacy violations, and lack of intellectual property protection. If you would like to learn how to how to optimize the value of your intellectual property, you can read Brown Rudnick’s article on the topic by clicking here.

It is key for companies that embrace generative AI to establish internal guidelines for responsible use to mitigate risks and maximize the technology's benefits. Both the company and its employees benefit greatly from having an approved roadmap, including:

• Transparency and Attribution: It is important for employees to understand the limitations of generative AI and disclose its use in outputs.  For example, it is crucial for users to know that the output generated by generative AI systems may not be considered protectable intellectual property under applicable law. Therefore, relying solely on generative AI output as the final product may not afford legal protection against unauthorized copying or use by others.  Consequently, it is good practice to clearly mark all generative AI outputs so that they can be distinguished internally from human work product.
• Data Governance: Inputting confidential information into prompts could potentially expose sensitive data to unintended parties, leading to abandonment of trade secrets, legal liabilities and breaches of confidentiality agreements.  Similarly, prompting AI tools with personally identifiable information could raise compliance issues under applicable data privacy laws aimed at protecting individuals' personal data such as the European Union General Data Protection Regulation (GDPR) and California Consumer Privacy Act (CCPA). Guidelines should establish protocols for data selection and prompting, ensuring the protection of company confidential information and personal privacy.
• Human Oversight and Accountability: Human review of AI-generated content remains crucial, with clear lines of accountability for outputs. While generative AI tools mimic human creativity, they are not necessarily factually accurate and are prone to hallucinations, or instances where AI generates information that is plausible-sounding but incorrect – one of many reasons why human review of generative AI outputs is key.
• Monitoring and Auditing: Companies should carefully choose and establish approved generative AI tools, monitor them on an ongoing basis to prevent misuse and regularly audit their generative AI tools to identify and address potential biases, or systematic errors, in the data or the applicable algorithms that can lead to inaccurate outcomes. If you would like to learn the advantages of having a compliance manual that conforms to U.S. law, you can read Brown Rudnick’s article on the topic by clicking here.

Generative AI offers endless possibilities for all kinds of businesses and governments.  By fostering a culture of responsible AI use with a written roadmap, users can unlock the full potential of generative AI while safeguarding their reputation and ensuring compliance. 

If you are interested in having a compliant generative AI program, let us know. Our team of international lawyers can assist in developing and tailoring generative AI guidelines to your business and, once developed, in training your employees and stakeholders to be aware of and comply with those guidelines.