Automation is everywhere. From robotic process automation (RPA) to AI-driven decision-making, businesses are integrating automation into their decision-making processes like never before. However, with these advancements come critical legal considerations that companies must address or face the wrath regulators—or worse, plaintiffs’ lawyers!
One general principle that businesses should understand is that automation will usually be held to a higher standard than humans. Because humans driving cars is the way it’s always been done, and self-driving cars are new and scary, self-driving cars need to be ten times safer than people before regulators will let them on the road. And even then, the liability might still be higher for self-driving cars than for people. Maybe that’s fair; maybe it isn’t. But that’s the reality.
Nearly every business wants streamlined, automated processes, but if you ever get into a situation where you are in front of a real judge or jury, and you need to defend what you’re doing, you need a human-friendly explanation for everything that you’re doing.
That’s not to say that automation isn’t worth it, but you do need to perform a different legal and risk analysis when building a business with automated processes compared to human ones.
1. Liability for Automated Decisions & Errors
When automation goes wrong, who is responsible? Businesses may face lawsuits for:
- Defective automation tools leading to financial loss.
- Automation tools that inadvertently run afoul of legal considerations.
- Errors in automated decision-making (e.g., wrongful termination, incorrect pricing, contract breaches).
- Customer-service automation failing to provide proper assistance or providing bad or misleading advice.
Key Risks:
- Automated contracts get things wrong.
- RPA bots in healthcare or finance may make critical errors affecting consumers.
- Companies may be liable for harm caused by faulty automation.
Legal Mitigation Strategies:
- Maintain human oversight over key automated decisions.
- Spot check every automated flow.
- Understand that automated processes will be held to higher standards than human ones.
- Draft liability clauses in vendor contracts when using third-party automation tools.
2. Intellectual Property (IP) & Automation Tools
Many businesses use automation tools that involve custom scripts, AI models, and proprietary software. However, legal questions arise around:
- Who owns AI-generated content?
- Are automated decisions protected by trade secrets?
- Can an AI system infringe on existing patents or copyrights?
Key Risks:
- Purely automated processes are rarely capable of copyright protection.
- Automated systems may generate content that violates copyright laws.
- AI-created software or designs may not be patentable under current IP laws.
- Businesses using third-party automation tools may infringe on software licenses.
Legal Mitigation Strategies:
- Clarify IP ownership in contracts when developing custom automation tools.
- Create hybrid systems to establish cognizable IP.
- Use properly licensed software and automation frameworks.
- Monitor AI-generated outputs for potential IP violations.
- Consult with an attorney regarding automated data collection processes such as scraping.
3. Algorithmic Bias & Discrimination
AI-powered automation is increasingly used for hiring, lending, and customer service. However, bias in AI models can lead to discrimination, violating:
- Title VII of the Civil Rights Act (US) – Workplace discrimination laws
- Fair Credit Reporting Act (FCRA) – Bias in lending automation
- Equal Credit Opportunity Act (ECOA) – Unfair automated lending decisions
Key Risks:
- AI-powered hiring tools may favor certain demographics, leading to discrimination claims.
- Automated credit scoring systems may unfairly reject applicants, resulting in lawsuits.
- Chatbots and AI-driven support may treat users differently based on personal data.
Legal Mitigation Strategies:
- Conduct regular audits of AI models to detect bias.
- Final decisions in hiring should be made by people.
- Use transparent and explainable AI rather than “black box” models.
- Implement human oversight for AI-driven decision-making.
4. Employment Law & Workplace Automation
As businesses automate tasks, employees may be affected by layoffs, changes in job roles, or new workplace surveillance tools. Legal concerns include:
- Wrongful termination lawsuits due to AI-based layoffs.
- Worker surveillance laws regulating employee tracking automation.
- Union challenges to automation replacing jobs.
Key Risks:
- Employees may sue for discrimination if AI-driven performance reviews lead to job loss.
- AI-driven monitoring tools may violate workplace privacy laws.
- Automation may trigger WARN Act (Worker Adjustment and Retraining Notification Act) obligations if layoffs affect large groups.
Legal Mitigation Strategies:
- Ensure compliance with labor laws when using AI for HR decisions.
- Avoid excessive employee surveillance, which may be illegal in some jurisdictions.
5. Data Privacy & Security Compliance
Automation often involves handling large volumes of personal data, which raises concerns under laws like:
- GDPR (General Data Protection Regulation – EU)
- CCPA (California Consumer Privacy Act – US)
- HIPAA (Health Insurance Portability and Accountability Act – US, for healthcare automation)
Key Risks:
- Automated data collection processes may capture more information than legally allowed.
- AI-driven decision-making tools may profile individuals in ways that violate privacy laws.
- Automated systems that process sensitive data may be hacked or compromised.
Legal Mitigation Strategies:
- Ensure automated data handling processes align with regulatory frameworks.
- Implement strong cybersecurity protocols to prevent data breaches.
- Provide clear user consent mechanisms and options to opt-out.
Conclusion: Balancing Automation & Legal Compliance
Obviously, automating mindless and routine processes creates business efficiencies. But judges and juries tend to look unfavorably that use automation that harms people without oversight. Balancing automated processes with human and legal oversight is the only way to engage in automation without incurring excessive levels of risk.