Artificial Intelligence in the Workplace

The use of AI in employment settings raises several legal and ethical concerns that employers must consider to avoid legal ramifications. These concerns primarily revolve around issues of bias, discrimination, data privacy, transparency, and accountability.

Below are key areas where AI could present legal challenges:

1. Discrimination and Bias

• Title VII of the Civil Rights Act of 1964: AI tools used in hiring, promotions, or other employment decisions may inadvertently discriminate based on race, gender, or other protected characteristics if they rely on biased data.
• The Americans with Disabilities Act (ADA): AI systems must accommodate candidates with disabilities, ensuring that the tools are accessible and do not create barriers in the workplace.
• The Equal Employment Opportunity Commission (EEOC) has issued guidance on the use of AI, emphasizing the potential risks of perpetuating discrimination. If an AI tool results in a disparate impact on a protected group, employers could face liability. Removing questions that ask for data about protected classes and ensuring that AI tools measure only abilities necessary for the job are two effective ways to minimize exposure.

2. Data Privacy and Security

• General Data Protection Regulation (GDPR): In the European Union, AI tools must comply with GDPR regulations regarding the collection, storage, and use of personal data. Employees and job applicants must be informed about how their data is being used, and they have the right to request deletion or correction. US companies can be subject to the GDPR if they process or control data from EU residents. In addition, websites that provide goods or services to EU citizens or collect their personal information must comply with the GDPR.
• Employers must also ensure that AI systems handling personal data are secure and do not expose the organization to data breaches or violations of privacy rights.

3. Algorithmic Transparency and Accountability

• Explainability: AI decision-making processes must be explainable, particularly in contexts like hiring, promotion, or termination. If an adverse employment decision is made based on an AI tool, the employer may be required to explain how the decision was reached.
• Fairness in Algorithms: Employers are responsible for ensuring that AI algorithms are fair, meaning that they do not treat similarly situated individuals differently without justification.
  Automated Decision Systems Laws: Some jurisdictions are moving toward regulating automated decision systems (ADS). New York City, for example, has introduced legislation that requires AI used in hiring to undergo bias audits and notification to candidates when AI is used.
• Automated Decision Systems Laws: Some jurisdictions are moving toward regulating automated decision systems (ADS). New York City, for example, has introduced legislation that requires AI used in hiring to undergo bias audits and notification to candidates when AI is used.

4. Liability and Accountability 

• Employers could face legal challenges if AI systems make decisions that are unlawful or violate employment laws. It is important for organizations to establish human oversight over AI tools to ensure that employment decisions are lawful and based on the facts of each individual situation.
• Delegation of Responsibility: Even if AI tools are developed by third-party vendors, employers remain responsible for ensuring that these tools comply with employment laws. Thus, indemnification and due diligence on AI providers are crucial.

5. Worker Monitoring and Privacy

• Electronic Communications Privacy Act (ECPA) and similar state laws may limit the extent to which AI can be used to monitor employee activities. Employers must balance their need for monitoring productivity with respect for employee privacy.
• Excessive surveillance or intrusive AI monitoring systems may also lead to claims of privacy violations or constructive discharge if employees feel they are being forced to resign due to unreasonable monitoring.
  

Key Mitigation Steps:

• Bias Audits and Testing: Regularly audit AI systems to ensure that they do not produce biased or discriminatory outcomes.
• Transparent Policies: Implement clear policies on the use of AI in employment decisions and communicate them to employees and applicants.
• Human Oversight: Ensure that human judgment plays a significant role in decisions, particularly for actions like hiring or firing.
• Legal Compliance Reviews: Work with legal experts to review AI systems for compliance with employment and data protection laws.

Employers must balance the efficiency gains from AI with compliance and ethical considerations to avoid legal consequences. For assistance in this evolving area, please contact attorney Mike Briach, 440.930.4001 or mbriach@dooleygembala.com.