AI’s legal landscape: As artificial intelligence continues to revolutionize industries, companies face a growing array of legal challenges and considerations when implementing AI strategies.
- The Copyright Alliance reports over two dozen AI-related lawsuits in the US alone, highlighting the legal complexities surrounding AI adoption.
- In September, the Federal Trade Commission took enforcement action against companies for making deceptive claims and promising false business results using AI hype and technology.
Key legal factors for AI implementation: Business leaders and owners must carefully consider five critical legal aspects before rolling out broad AI strategies across their organizations.
- Technology evaluation: Assessing compatibility and integration: Companies need to evaluate their existing IT infrastructure’s compatibility with current and future AI systems.
- This involves examining infrastructures, workflows, data handling procedures, and customer interactions that AI might affect.
- Businesses must ensure that AI solutions can seamlessly integrate into their current software ecosystems and maintain service quality without violating privacy agreements.
- Scalability of AI solutions should also be considered during the evaluation process.
- Regulatory compliance: Navigating a complex and evolving landscape: Companies must stay informed about federal, state, and international regulations governing AI use.
- Europe’s GDPR and the European Union’s AI Act have specific stipulations concerning automated decision-making procedures, which apply to most AI systems.
- Several US states are developing their own AI regulations, adding to the complexity of compliance.
- Businesses should design robust compliance frameworks that can adapt to evolving regulations, potentially requiring periodic audits and specialized compliance officers.
- Data and security protections: Safeguarding sensitive information: Companies must prioritize data security when adopting AI technologies.
- A clear understanding of data storage locations, encryption methods, and access controls is essential.
- Jake Heller, a lawyer and AI product manager at Thomson Reuters, emphasizes the need for stringent data privacy and security measures, comparable to those in legal practices.
- Companies should inquire about data breach protocols and confirm that AI providers’ security practices meet industry standards.
- Implementing clear data governance policies, including data classification, access controls, and periodic security audits, is crucial.
- Data training risks: Managing AI’s learning capabilities: The self-learning abilities of AI systems present potential liabilities that business leaders must address.
- Companies need to understand precisely how their data are used by AI systems, especially in sensitive domains like healthcare and finance.
- Negotiating terms of data usage with AI providers is essential, including whether providers retain rights to use the data for improving their own AI models.
- Exploring technical options like differential privacy can help protect individual data while allowing meaningful analysis.
- Intellectual property issues: Navigating ownership and copyright concerns: Content created through AI raises complex questions about intellectual property rights.
- Ownership of AI-generated works remains a contentious issue, with potential claims from various parties involved in the AI creation process.
- Companies should apply existing intellectual property protection policies to their AI platforms and clearly specify ownership of AI-generated works in contracts with providers.
- Businesses must be aware of potential copyright infringement issues if AI systems are trained on copyrighted material.
The evolving regulatory landscape: Despite the growing need for AI regulations, progress in establishing legal guardrails has been slow.
- California Governor Gavin Newsom recently vetoed the first major piece of legislation aimed at establishing legal guardrails for AI usage of certain copyright materials and the creation of deepfakes.
- As AI capabilities continue to advance rapidly, business leaders must cautiously navigate the implementation of AI within their organizations, balancing innovation with legal compliance and risk management.
5 Critical AI Legal Issues Every Business Must Navigate
