1. General Legal Framework
1.1 General Legal Background Framework
There is no specific AI law in Mexico. However, a number of Mexican laws – for example, the Data Protection Law (Ley Federal de Proteccio?n de Datos Personales), the Consumer Protection Law (Ley Federal de Protección al Consumidor) and the Economic Competition Law (Ley Federal de Competencia Económica) – contain provisions regulating certain aspects of AI use.
In April 2023, the Mexican Senate created the National Alliance for Artificial Intelligence (Alianza Nacional de Inteligencia Artificial, or ANIA), the purpose of which is to recognise and fortify the AI ecosystem in Mexico by seeking a legal basis for proposing and creating regulatory frameworks specifically for AI.
2. Industry Use of AI and Machine Learning
2.1 Industry Use
During the COVID-19 pandemic of 2020, companies in Mexico developed accelerated solutions based on AI. An increasing number of companies now use AI, a practice that is transforming the way in which companies operate ? from the communication they have with their clients, to their network security management.
Important AI and machine-learning initiatives are being discussed in the Mexican Chamber of Commerce and are anticipated in the following industries:
- media and advertising;
- health and medical services;
- hardware and software services; and
- banking and financial services.
However, as is the case for many cross-border companies, Mexican companies must overcome significant challenges in order to fully adopt AI. These barriers preventing the integration of AI include a lack of knowledge, lack of adequate strategies, and lack of data – not to mention the costs and time required for implementation.
3. Legislation and Directives
3.1 Jurisdictional Law
As explained in 1.1 General Legal Background Framework, there is no specific legislation regulating AI in Mexico. Mexico is a civil law jurisdiction and therefore, as a rule, relies on common civil law and practice when observing general obligations, liability and responsibility. Certain legal statutes and regulations also apply to AI, such as the aforementioned Data Protection Law and the Consumer Protection Law and its regulations, respectively.
3.2 EU Law
3.2.1 Jurisdictional Commonalities
The matter is not applicable in this jurisdiction.
3.2.2 Jurisdictional Conflicts
The matter is not applicable in this jurisdiction.
3.3 US State Law
The matter is not applicable in this jurisdiction.
4. Judicial Decisions
4.1 Judicial Decisions
As of May 2023, there have been limited judicial decisions specifically addressing Generative AI and its implications for IP rights in Mexico. However, in cases involving AI, Mexican courts have relied on existing IP laws and principles.
4.2 Technology Definitions
There are no standardised definitions for AI in judicial decisions. However, for the purposes of this article, the authors shall adopt what has been used to define AI during commercial chambers debates with Mexican government officials – ie, "Artificial Intelligence" refers to the group of digital technologies that enable machines to perform complex tasks that typically require human intelligence. It can be divided into two main fields:
- Artificial General Intelligence (AGI) – machines capable of fully replicating human intellectual capabilities and even exhibiting traits of consciousness; and
- specific AI (or Artificial Narrow Intelligence (ANI)) – technologies and techniques (such as data mining, deep learning, machine learning, or artificial neural networks) that are used to perform specific actions and are already in the initial stages of use.
5. AI Regulatory Regimes
5.1 Key Regulatory Agencies
In Mexico, multiple regulatory agencies have a role in AI oversight, including:
- the National Institute of Transparency, Access to Information and Protection of Personal Data (Instituto Nacional de Transparencia, Acceso a la Información y Protección de Datos Personales, or INAI), which is responsible for data protection and privacy rights;
- the Federal Telecommunications Institute (Instituto Federal de Telecomunicaciones, or IFT), which regulates telecommunications and media that may intersect with AI applications;
- the Federal Consumer Protection Agency (Procuraduría Federal del Consumidor, or PROFECO), which protects consumer rights and investigates unfair trade practices related to AI applications; and
- the Federal Economic Competition Commission (Comisión Federal de Competencia Económica, or COFECE), which ensures fair competition in the market and may address anti-competitive behaviour related to AI.
5.2 Technology Definitions
Although regulatory agencies in Mexico have recognised the importance of AI, there are no specific definitions used by each agency, so it may vary. Please refer to 4.2 Technology Definitions.
5.3 Regulatory Objectives
Regulatory agencies seek to prevent harms associated with AI, including data privacy violations, unfair trade practices, anti-competitive behaviour, and potential risks to consumer rights and safety. Additionally, they aim to promote the responsible and ethical use of AI, encourage innovation, protect personal data and privacy, ensure fair competition, and safeguard consumer rights and safety.
5.4 Enforcement Actions
Even though debates concerning AI are increasingly common, as yet there have been no significant precedents or regulatory actions with regard to imposing fines or sanctions exclusively for AI-related matters in Mexico. The government is actively working across its three branches (judicial, legislative and executive) to develop an AI strategy aimed at regulating its use and penalising any misuse. A common denominator is that self-regulation will not suffice for the phenomenonal impact of AI on day-to-day life.
6. Proposed Legislation and Regulations
6.1 Proposed Legislation and Regulations
As of May 2023, there is only one initiative in Mexico to introduce a new law to regulate AI. This proposed law ? known as the "Law for the Ethical Regulation of Artificial Intelligence for the Mexican United States" (Ley para la Regulación Ética de la Inteligencia Artificial para los Estados Unidos Mexicanos) – defines AI as "the scientific discipline that involves creating computer programmes capable of performing operations comparable to those carried out by the human mind, such as learning or logical reasoning".
The main objective of this initiative is to establish structures and ethical standards for the development, research, and use of AI in Mexico. It also aims to establish and regulate a Mexican Council for Ethics in Artificial Intelligence and Robotics.
As regards regulations from government authorities outside Mexico, their impact on businesses in Mexico would depend on whether these businesses are subject to such foreign regulations. The impact of these regulations would be determined by their specific provisions and requirements, which might include compliance obligations, data protection requirements, or restrictions on certain AI applications. Additionally, if businesses operating in Mexico are organised under the laws of another jurisdiction, they would need to assess the compatibility of the foreign regulations with the local legal framework. This process may require adapting their practices to comply with both sets of regulations. Extraterritorial regulation is common in certain areas such as anti-corruption, AML and data privacy. Regulations on AI are expected to follow the path of cross-border compliance regimes.
7. Standard-Setting Bodies
7.1 National Standard-Setting Bodies
In Mexico, the development and adoption of AI-related standards are influenced by various factors. Mexico has been actively working on the formulation of a national AI strategy to promote the responsible and ethical use of AI.
Additionally, different industries in Mexico are subject to sector-specific regulations that can impact the utilisation of AI. In the healthcare sector, for example, the Federal Commission for Protection against Sanitary Risks (Comisión Federal para la Protección contra Riesgos Sanitarios, or COFEPRIS) and the Federal Institute for Access to Information and Data Protection (Instituto Nacional de Transparencia, Acceso a la Información y Protección de Datos Personales, or INAI) oversee the implementation of AI in medical applications to ensure patient safety and privacy. They play a crucial role in developing regulations and guidelines concerning the use of AI, particularly in relation to personal data and privacy.
Although Mexico may currently lag behind in these matters, there is an expectation that Mexico will align with international best practices and collaborate with international organisations to address AI-related challenges and establish appropriate standards that comply with national laws and regulations. This will certainly be part of future sections in the free trade agreements currently in place between Mexico and other jurisdictions.
7.2 International Standard-Setting Bodies
In Mexico, businesses are encouraged to adopt and adhere to international AI standards to enhance their competitiveness and facilitate international trade. Notwithstanding the foregoing, conflicts may arise when international AI standards conflict with specific legal provisions in Mexico. Therefore, companies must ensure compliance with national regulation, even if it differs from international one.
8. Government Use of AI
8.1 Government Use of AI
The Mexican government has been exploring the uses of AI in several practice areas.
Facial recognition technology (or facial recognition systems) use AI algorithms to analyse and identify individuals based on their facial features. These systems have been implemented in Mexico for various purposes, including law enforcement, border control, and surveillance. Facial recognition raises concerns about mass surveillance, potential misuse of personal data, and the risk of false identifications. There are concerns that these systems may lead to an invasion of privacy, as individuals can be tracked and monitored without their consent or knowledge.
Furthermore, biometric systems such as fingerprint or iris scanners use unique physical or behavioural characteristics to identify individuals. They are used in various contexts, including for identification by government services, border control, and law enforcement. The collection and storage of biometric data raise concerns about data security and the potential for misuse or unauthorised access. There is a need for robust security measures that protect the integrity and confidentiality of biometric data in order to prevent identity theft or unauthorised use.
It is worth noting that the implementation and specific use cases of AI by the Mexican government for civil law purposes has been in constant legislative evolution for the past decade.
The rapid advancement of AI and its applications, including facial recognition and biometrics, may outpace existing regulations. Mexico has privacy laws in place to protect individuals' personal information, such as the Federal Law on Protection of Personal Data Held by Private Parties (Ley Federal de Protección de Datos Personales en Posesión de los Particulares) and the Federal Law on Protection of Personal Data Held by Obliged Entities (Ley General de Protección de Datos Personales en Posesión de Sujetos Obligados). However, there is a need for comprehensive and up-to-date legislation to address the specific challenges posed by AI and its impact on privacy.
8.2 Judicial Decisions
AI has contributed to evidence-based policy-making in judicial decisions and civil law matters. By analysing large datasets and identifying trends and patterns, the government can gain insights into issues such as crime rates, legal compliance, or areas requiring legislative intervention. No judicial decision has been resolved using AI, per se; however, AI has provided support in certain trials.
8.3 National Security
AI has been used in Mexico surveillance systems to monitor public spaces, borders, or critical infrastructure, as facial recognition technology can assist in identifying individuals of interest within airports or enhancing border security. AI helps analyse vast volumes of data ? including communications, online content, or sensor data ? to identify potential security threats.
Mexico has used AI aimed for national security within the following areas of practice.
- Cybersecurity and defence ? AI plays a significant role in cybersecurity by identifying and responding to potential cyberthreats as well as developing proactive defence mechanisms to protect critical infrastructure and sensitive data from cyber-attacks.
- Counterterrorism efforts ? AI can support counterterrorism efforts by analysing intelligence data (including textual documents, images, and videos) to uncover patterns and connections between individuals or organisations involved in terrorist activities or drug cartels.
9. Generative AI
9.1 Generative AI
Generative AI can be used to generate realistic and convincing fake content, including text, images, and videos. This raises concerns about the potential spread of misinformation and disinformation, which can have significant societal and political implications. Researchers and organisations are working on developing methods to detect and counteract AI-generated misinformation ? for example, fact-checking techniques and digital forensics tools.
Likewise, AI technologies have the potential to disrupt labour markets and lead to job displacement or changes in work dynamics. Legal frameworks should address the social and economic implications of AI adoption, ensuring that appropriate measures are in place to:
- protect workers' rights;
- provide adequate training and reskilling opportunities; and
- promote a just transition.
10. AI in the Practice of Law
10.1 Uses of AI in the Practice of Law
AI has assisted legal professionals in conducting research and analysing vast amounts of legal information. Natural Language Processing (NLP) techniques can be used to extract relevant case law, statutes, and legal opinions, thereby providing lawyers and judges with valuable insights to support their decision-making processes. Likewise, AI-powered technologies such as machine learning algorithms can be employed to automate the review and analysis of legal documents. This can help streamline administrative processes, improve efficiency, and reduce the time and resources required for tasks such as contract review and the drafting and translation of due diligence legal documents.
AI algorithms can be trained on historical legal data to predict case outcomes, thereby assisting lawyers and judges in assessing the strengths and weaknesses of a case. This can help inform legal strategies, identify patterns, and potentially improve the overall administration of justice. The government leverage AI to develop chatbots or virtual assistants that are capable of providing legal information and guidance to citizens. These AI-powered systems can interact with users, answer frequently asked questions and provide initial legal advice, thus making legal information more accessible to the public.
10.2 Ethical Considerations
AI may impact ethical margins at an individual level, in terms of consent and autonomy, and at a societal level with regard to employment and transparency. However, when it comes to the practice of law, the ethical issues surrounding AI are complex and multifaceted. The following are among the key ethical considerations arising in relation to AI from a legal perspective.
- Privacy and data protection ? AI often relies on large amounts of personal data to function effectively. Legal frameworks need to ensure that AI systems respect individuals' privacy rights, including the collection, use and storage of personal data. Adequate safeguards should be in place to protect sensitive information and prevent unauthorised access or misuse.
- IP and ownership ? AI raises questions regarding IP rights and ownership of AI-generated outputs. Legal frameworks should consider issues related to copyright, patentability, and ownership of AI-generated works or inventions. Additionally, ethical considerations may arise in cases where AI systems generate content that could infringe on the privacy or IP rights of others.
- Confidentiality and veracity ? confidentiality agreements may be breached or violated by providing confidential information to certain AI instruments. Violating a confidentiality agreement in Mexico can be considered a criminal act. Nothing the AI is told remains confidential and, as such, it is important to provide very generic elements rather than privileged information. However, it is also necessary to confirm the veracity of the information. Not everything AI systems assure may be up-to-date or correct. Lawyers must always corroborate the information.
Addressing these ethical issues requires a multiphase approach involving legislation, regulations and international co-operation. Legal frameworks should aim to strike a balance between fostering AI innovation on one hand and ensuring ethical practices, protecting fundamental rights, and mitigating potential harm on the other.
11. Theories of Liability
11.1 Theories of Liability
In Mexico, the theories of liability for personal injury or commercial harm resulting from AI technologies can be understood within the framework of existing legal principles such as tort law and contractual liability. Requirements for imposing civil liability and resulting damages in Mexico:
- direct causal link;
- breach of duty or obligation; or
- amount of damages, which in certain cases is a separate incidental procedure involving expert witnesses.
In Mexico, liability issues related to AI technologies are still evolving and legal frameworks may adapt in order to address the unique challenges posed by AI. The specific requirements for imposing liability can vary depending on the facts of each case, judicial interpretations, and potential legislative developments.
12. General Technology-Driven AI Legal Issues
12.1 Algorithmic Bias
Bias in algorithms refers to the presence of systematic errors in the predictions generated by the algorithms. Legally, bias in algorithms intersects with laws and regulations that prohibit discrimination and promote equality. Legal concerns include equal protection (algorithms must not discriminate against individuals or groups based on protected characteristics) and privacy and data protections (algorithms should respect privacy rights and comply with data protection regulations when processing personal data).
Mexico has no laws or regulations that address bias in algorithms, but can refer to the following:
- the EU's General Data Protection Regulation (GDPR) (includes the right to an explanation when algorithms impact individuals);
- the USA's Algorithmic Accountability Act (proposed legislation that would require companies to assess and mitigate bias in their algorithms and provide transparency in automated decision-making processes); and
- the EU's Ethical Use of Artificial Intelligence Act (proposed regulatory framework that aims to address the ethical aspects of Al, including transparency, accountability and non-discrimination).
Bias in algorithms can create significant risks for consumers in various domains, such as:
- hiring and employment;
- financial services (when algorithms are used in loan approvals or insurance pricing); and
- the criminal justice system (when algorithms are used in sentencing).
Companies can face potential liability for algorithmic bias in discrimination lawsuits and regulatory actions, as regulatory agencies may impose fines or sanctions on companies that violate relevant laws and regulations related to bias in algorithms. The technology industry has recognised the importance of addressing bias in algorithms and several initiatives have emerged, such as:
- diversity and inclusion (promoting diversity within AI development can help identify and mitigate against biases during algorithm design);
- ethical guidelines that emphasise fairness and transparency; and
- R&D for mitigating bias.
12.2 Data Protection and Privacy
In terms of data protection, personal data subject to Al technology and AI-enabled business practices presents a number of risks and issues, including:
- invasion of privacy;
- security vulnerabilities that increase the risk of data breaches and cyber-attacks;
- lack of transparency concerning how the personal data is processed; and
- limitation of individuals' control over their own information.
Nonetheless, the use of AI in processing personal data leads to some benefits, such as personalised services, healthcare advancements, and enhanced user experience. Improved efficiency is an obvious additional bonus, as Al-powered data analytics can automate tasks and make predictions based on large datasets.
Database breaches present risks such as data exposure, financial losses, and misuse of information. Protection against database breaches offers a number of benefits beyond simply enhancing data protection and privacy. It can improve the reputation of and trust in an organisation, as a result of demonstrating a commitment to data security and privacy – not to mention compliance with regulations. Protecting databases against breaches helps organisations comply with data protection laws, thereby avoiding legal consequences and reputational damage.
Processing personal data and machine-generated data without direct human supervision can lead to unintended consequences and the lack of human oversight mean there can be a lack of accountability. However, the absence of human supervision allows for faster and scalable operations that enable organisations to handle large volumes of data and provide real-time answers). Processing data in this way also facilitates unbiased decision-making and the discovery of new patterns and insights that may not be apparent to humans.
12.3 Facial Recognition and Biometrics
The use of facial recognition and biometric information raises legal issues related to jurisdictional consent rules, given that companies must comply with specific consent requirements. The GDPR in the EU, for example, requires explicit consent for processing biometric data. In the USA, different states have implemented their own regulations on biometric data privacy. The Illinois Biometric Information Privacy Act imposes strict requirements with regard to obtaining consent and providing notice when collecting biometric data.
Privacy laws, data protection laws and consumer protection laws may apply to the use of facial recognition technology. Violations can result in legal consequences and damage to a company's reputation. Industry-specific risks for companies using facial recognition primarily involve regulatory violation. Mexico is no exception and non-compliance with consent rules, data protection requirements or privacy laws when using AI in connection with facial recognition technologies can lead to penalties, legal actions, and reputation damage.
12.4 Automated Decision-Making
Automated decision-making technology, also known as constant AI, is a crucial element. As such, companies in Mexico must disclose the use of automated decision-making systems to individuals.
There are no Mexican regulations concerning the use of chatbots as a substitute for services rendered by natural persons, nor the disclosure of AI use. However, the performance and accuracy of chatbots may be regulated to ensure that they meet certain standards and do not mislead consumers. The disclosure of Al use must be transparent in order to build trust and ensure consumer protection.
Various technologies can be used to make undisclosed suggestions or manipulate consumer behaviour. Personalisation algorithms analyse user data to make suggestions based on individual preferences, whereas targeted advertising tailors marketing messages to specific individuals or groups.
12.6 Anti-competitive Conduct
The use of Al technology for price-setting raises several competition and antitrust issues that should be carefully considered, including:
- the lack of transparency;
- tacit collusion;
- market concentration if certain firms gain a competitive advantage through their superior algorithms or access to large datasets; and
- predatory pricing strategies.
13. Sustainability and Climate Change
13.1 Sustainability and Climate Change
Al has a significant role to play in combating climate change and can be used in the following ways:
- AI contributes to climate modelling and prediction;
- Al can optimise the integration and management of renewable energy sources into existing power grids;
- Al algorithms can identify energy-saving opportunities; and
- Al can assess climate risk and develop adaptation strategies.
The development of industry standards is crucial for ensuring the responsible and ethical use of Al in addressing climate change.
14. AI in Employment
14.1 Hiring Practices and Termination of Employment Practices
The automated phases of employee hiring and termination of employment often involve the use of various technologies – for example, an Applicant Tracking System (ATS), which is software that automates the hiring process by collecting and filtering job applications. These systems use algorithms to scan resumes, identify relevant keywords and rank candidates based on predetermined criteria.
The benefits to employers include:
- efficiency (an ATS can handle a large volume of applications);
- standardisation; and
- improved matching (ATS algorithms can help identify candidates with skills and qualifications that match the job requirements).
Employers must ensure that automated termination processes do not discriminate against employees based on protected characteristics; otherwise, they are potentially at risk of being held liable for discriminatory practices. If the algorithms or data used in the process introduce bias, there is a risk of violating anti-discrimination laws.
14.2 Employee Evaluation and Monitoring
The evaluation of employee performance and the monitoring of employee work have become sophisticated, owing to the advancement of technology. Employees' work is now evaluated and monitored via email, instant messaging apps, project management software, and videoconferencing apps ? along with time-tracking and productivity software to track the time employees spend on tasks and projects. All this technology allows for more frequent feedback, which facilitates continuous improvement and growth.
Remote work technologies enable employees to work from any location, thereby providing flexibility and work?life balance opportunities. However, employees also face potential harms, such as invasion of their privacy and burnout from the stress of being constantly monitored and evaluated.
There are potential legal risks concerning data protection and privacy, owing to the constant monitoring of employees and their information. In addition, the evaluation should not discriminate against employees based on protected characteristics.
15. AI in Industry Sectors
15.1 Digital Platform Companies
AI is used by digital platform companies to analyse user data in order to provide personalised experiences ? for example, recommending food choices ? based on preferences and past behaviour. Companies also use AI to adjust pricing based on demand and supply patterns. The use of AI must comply with applicable labour and employment laws, such as the Mexican Federal Labour Law (Ley Federal del Trabajo). Compliance with data protection regulations is crucial to safeguard user privacy.
15.2 Financial Services
There are limited regulations in Mexico for the use of Al by financial services companies. Specifically, the Law to Regulate Financial Technology Institutions (Ley para Regular las Instituciones de Tecnología Financiera, or LRITF) – also known as the "Fintech Law" ? contains certain provisions requiring financial technology services companies to disclose how AI is used in their operating process. Al has been used in operations to evaluate credit ratings and for risk management in fraud detection. Al algorithms are used in personalised customer service and for automated trading and investment strategies.
The use of Al in healthcare is subject to regulations aimed at ensuring patient safety, privacy, and ethics. Potential risks associated with the use of Al in healthcare include patient treatment errors and hidden bias in training data. Data use and sharing of personal health information are crucial for training machine-learning algorithms; however, they raise concerns about patient privacy and cybersecurity.
Robotic surgery is a reality in almost every corner of the world, including Mexico. While offering advantages like precision and safety, robotic surgery also presents challenges related to surgeon training, potential errors and ethical considerations. Machine learning plays a key role in digital healthcare, including diagnostic support, personalised medicine, imaging, predictive analytics, and population health management.
Centralised electronic health record systems have strengths in terms of accessibility and data integration. Weaknesses include data breach concerns and lack of interoperability. Data use and data sharing in the machine-learning context are subject to data protection law in Mexico.
The use of AI as a software for health purposes is not regulated ? even though AI can be an integral part of a medical device. In most cases, AI is part of a separate process that captures and processes medical device data output. NLP plays a vital role in analysing insights from textual medical data.
Regulatory schemes involved in common use scenarios include privacy regulations and rules governing patient consent for data use.
16. Intellectual Property
16.1 Applicability of Patent and Copyright Law
The legal landscape and framework surrounding AI-generated inventions and works is still evolving in Mexico.
It is important to note that opinions on these matters vary. Some argue that AI systems should be recognised as inventors or authors, as they can exhibit a level of autonomy and creative output. Advocates of this perspective highlight the potential of AI to generate novel and inventive solutions or produce creative works beyond human capacity. They argue that attributing inventorship or authorship to AI technology could encourage innovation and creativity.
To date, no clear consensus or widely accepted legal position has emerged on whether AI can be recognised as an inventor or author. The question involves complex considerations such as legal doctrine, policy goals, ethical implications, and potential impacts on the legal framework surrounding IP rights.
16.2 Applicability of Trade Secret and Similar Protection
AI-related IP is protected by copyright, patents, trade marks, and design rights. Contractually, trade secrets related to AI technologies can be subject to non-disclosure agreements, employee and contractor agreements, licensing agreements, and data usage and privacy policies.
Under Mexican law, trade secret and confidentiality agreements can always be used to protect any aspect of AI that cannot be protected through the traditional means of protecting IP.
It is important to consider that legal counsel is essential to determine the most appropriate IP protection strategy and ensure compliance with relevant regulations.
16.3 AI-Generated Works of Art and Works of Authorship
The scope of IP protection for works generated by AI has evolved to include:
- copyright ownership (some jurisdictions have debated whether Al can be considered a legal author and when the Al works should be entitled to copyright protection);
- the human inventive and creative input;
- the use of AI as a tool of assistance used by human creators to facilitate the creative process;
- legal and policy discussions regarding a potential change to copyright laws to accommodate Al-generated works and clarify their ownership; and
To date, no clear consensus or widely accepted legal position has been adopted in Mexico on how IP protection must be applied in connection with AI-generated artworks.
- the rights and limitations associated with the use of Al technologies;
- the copyrights considerations;
- the specific licences for use and restrictions; and
- the limitations on the commercial use of the works.
17. Issues for In-House Attorneys
17.1 AI Issues for In-House Attorneys
When it comes to their company's use of AI technologies, in-house attorneys should focus on statistical information related to work volume and cost-based analysis. Data privacy and security are relevant to in-house compliance teams, as well as compliance training tools. In-house attorneys should address IP considerations such as patent protection, trade secrets, copyright issues and licensing agreements. They also need to be aware of ethical considerations and frameworks for the responsible use of Al technologies in back-office operations and IT toolkits.
18. Advising Corporate Boards of Directors
18.1 Advising Directors
There are several key issues that should be addressed when advising the board of directors. Boards must ensure that proper data privacy and security measures are in place to protect sensitive information collected and processed by Al systems, while also ensuring transparency, accountability, and regular audits to mitigate the risks of bias. The authors have noticed that boards are delegating an AI taskforce to specific committees in order to anticipate how AI will benefit company's performance. At the same time, certain contingencies need to be addressed as part of the overall risk-management scenarios. Boards need to be aware of the legal and regulatory landscape in order to establish mechanisms for oversight and ensure accountability. Regular reporting can help mitigate risks and ensure proper governance of Al initiatives.
Originally published by Chambers and Partners.
The content of this article is intended to provide a general guide to the subject matter. Specialist advice should be sought about your specific circumstances.