Legal aspects of use artificial intelligence in business

Artificial intelligence (AI) is becoming an integral part of modern business, providing new opportunities to optimize processes, improve customer service and increase competitiveness. However, with the growing use of AI, complex legal issues related to ethics, privacy and liability also arise. International law firm Antwort Law offers an overview of the legal aspects of using AI in business and recommendations for their effective regulation.

Key legal aspects of using AI

1. Ethics and liability are central issues in the context of AI, and companies must take into account ethical principles when developing and implementing AI systems, including transparency, fairness and non-discrimination. Legally, this requires the creation of an internal policy that regulates ethical standards and procedures for evaluating AI solutions.

Example: in 2018, studies showed that Google's facial recognition algorithms exhibit bias, recognizing white people better than dark-skinned people, which led to accusations of discrimination and damaged the company's reputation. In response, Google has had to develop and publish a set of principles governing the use of AI, implement processes to regularly audit and test its AI algorithms for bias, and launch training programs for its developers and employees to raise their awareness of bias issues and teach them how to develop ethical AI systems.

2. Privacy and data protection: Using AI often involves processing large amounts of data, including personal data, and companies are therefore required to comply with data protection laws such as the GDPR in Europe and the CCPA in California. This includes ensuring consent for data processing, anonymizing data, and respecting the rights of data subjects.

Example: Facebook has been repeatedly criticized for violating user privacy, and the Cambridge Analytica scandal, in which millions of users’ data was used without their consent, resulted in huge fines and reputational damage. As a result, Facebook was forced to review its privacy policies and improve data protection measures.

3. Intellectual property: This concerns both the creation of AI technologies and the use of their results. Companies must protect their AI developments with patents, copyrights, and trade secrets, and manage ownership issues of AI results, such as authorship and patentability.

Example: IBM actively patents its AI developments, protecting innovations in machine learning and natural language processing. In 2020, IBM received more than 9,000 patents, many of which were related to AI. This allows the company to protect its developments and strengthen its position in the market.

Legal challenges and solutions

1. All AI technologies used by a company must be transparent and auditable to eliminate bias and ensure fairness, which from a legal point of view requires disclosing how the algorithms work and ensuring that they can be verified for compliance with the law.

Example: Microsoft has implemented an audit system for its AI algorithms to eliminate bias and ensure fairness. The company has developed special tools to check algorithms for discrimination and regularly publishes reports on the results of these checks.

We help companies develop procedures for auditing and certifying their AI models. This includes creating internal AI ethics committees and engaging external experts for independent assessment.

2. The use of autonomous systems (robots and unmanned vehicles) requires a clear definition of responsibility for their actions. Legislation in many countries is still being developed, but companies must already provide insurance and liability mechanisms to minimize risks.

Example: Tesla is actively developing and implementing autonomous driving technologies, but accidents involving Tesla autopilots raise questions about liability. In response, Tesla has developed insurance programs for its customers and improved systems for monitoring and controlling the operation of autopilots.

3. The conclusion of smart contracts and the automation of transactions using AI require special attention to legal aspects, since companies must ensure that such contracts comply with legal standards for further recognition in court. Security and fraud protection issues must also be taken into account.

Example: The Ethereum platform provides the ability to create and execute smart contracts, but hacks and bugs in smart contract code have caused significant losses to users. As a result, Ethereum developers are constantly working to improve the security and reliability of their platform.

4. Using AI on a global scale requires compliance with international norms and standards. Companies should be aware of international agreements and standards that govern the use of AI, such as the recommendations of the Organisation for Economic Co-operation and Development (OECD) and the International Organization for Standardization (ISO).

Example: Siemens, which operates internationally, adheres to ISO standards and OECD recommendations to ensure that its AI solutions comply with international regulations, thereby avoiding legal issues and building trust with customers worldwide.

AI legislation continues to evolve, with new regulations and standards expected regarding ethics, privacy, and liability. For example, the EU is actively working on creating legislation regulating the use of AI: in 2021, the European Commission presented a draft AI law that includes strict requirements for transparency, security, and liability. Accordingly, companies operating in the EU market should be prepared for these changes and begin adapting their processes now.

Antwort Law recommends that companies carefully analyze the legal aspects of using AI, implement reliable data protection and liability mechanisms, and consult with legal experts. This will allow you to not only ensure compliance with the law, but also to use the potential of AI as efficiently and safely as possible.

Lidia Ivanova

International lawyer
Antwort Law