Regulatory Compliance in the Age of AI

Is the AI solution you’re using compliant with industry regulations?

AI tools are transforming businesses and introducing new efficiencies across industries. But with the benefits come a few new challenges.

The regulations surrounding AI are changing almost as fast as AI itself. AI regulations in the U.S., especially, aren’t fully settled yet.

However, the regulations around discrimination, data privacy, and security haven’t changed much, and they apply to anyone using AI.

This article highlights some common regulatory missteps businesses make when giving AI access to their data.

Mistake 1: Allowing AI Bias to Creep In

AI is not traditional software, and treating it as such can lead to overlooking the necessary fairness checks that AI requires. AI learns from data, and without proper oversight, it may produce unintentionally biased results.

The Equal Employment Opportunity Commission (EEOC), which enforces federal anti-discrimination laws, plays a key role in regulating AI’s impact, particularly in employment contexts. AI tools that influence hiring, promotions, or employee evaluations need to be carefully scrutinized for compliance with laws that protect against discrimination based on race, gender, age, disability, and other protected characteristics.

The EEOC has pointed out that even seemingly neutral AI systems can inadvertently lead to biased outcomes. For example, a resume-screening tool might reject applicants with certain speech patterns due to a disability, or facial recognition software might inaccurately identify employees based on skin tone, leading to discrimination.

Such biases can violate the spirit and letter of federal employment laws. Businesses using AI in employment-related decisions must be especially vigilant in assessing their models to avoid discrimination, whether intentional or accidental.

Mistake 2: Overpromising What AI Can Deliver

In 2024, the FTC filed a case against a company that promised consumers easy money through AI-powered online storefronts. The tools were advertised as highly advanced, with claims that users could generate thousands in passive income.

However, according to the FTC, the reality was far from what was promised, and the scheme ended up costing consumers millions. While the case is still ongoing, it represents that when businesses make exaggerated claims about what AI can do, especially in ways that influence consumer decisions, they can expect regulators to step in.

The FTC’s involvement is part of a broader trend of increasing regulatory attention on AI, especially when it comes to consumer protection.

Mistake 3: Overlooking Data Privacy and Consent

In the United States, data privacy regulations like HIPAA and the California Consumer Privacy Act (CCPA) are setting the stage for a more rigorous approach to data protection. These laws require businesses to obtain clear and affirmative consent from users before collecting or processing their data, particularly when it’s sensitive.

Consumers have the right to know exactly what data is being collected, and to request its deletion.

In Europe, the General Data Protection Regulation (GDPR) takes things a step further. It requires explicit consent before collecting personal data and gives consumers the right to access their data, correct it, or have it erased. GDPR also puts a strong emphasis on businesses being transparent about how data is used. Even if a company isn’t based in Europe, if it handles data from EU consumers, it must comply with GDPR.

GDPR has become the global standard for data privacy. Even if a company isn’t directly subject to GDPR, adopting similar practices can help meet growing data protection requirements everywhere.

To manage data privacy and stay compliant, businesses should focus on three key actions:

• Obtain Clear Consent: Always ensure that consumers understand what data is being collected and why. Provide them with a simple way to give consent, and make it easy for them to withdraw it at any time.
• Use Anonymization: When possible, anonymize or de-identify data to reduce the risk of exposing personal information. This practice strengthens data security and also aligns with privacy standards.
• Be Transparent About Data Practices: Keep consumers informed about how their data is being used. Transparency builds trust and ensures compliance with data protection laws like HIPAA, GDPR, and CCPA.

Mistake 4: Assuming Your AI Vendor Handles Compliance

When companies adopt third-party AI tools or partner with AI vendors, it’s easy to assume that the vendor will take care of compliance. However, this is a dangerous assumption.

Third-party AI tools do not absolve businesses of their responsibility to comply with regulations. Even if an AI vendor offers a seemingly compliant solution, the ultimate responsibility still lies with the business using the tool.

AI systems can have significant legal and ethical implications. If something goes wrong, such as a privacy breach or a biased decision made by the AI system, the business using the tool, not just the vendor, could face legal consequences.

What to Verify in Vendor Agreements

It’s essential to include compliance-related clauses in vendor agreements to ensure both parties are aligned on legal and regulatory responsibilities. Make sure that your AI partner provides clear documentation of their compliance processes, such as:

Data handling practices: How does the vendor collect, store, and process data, and are these practices compliant with relevant laws like HIPAA, GDPR, or CCPA?

Security protocols: What security measures are in place to protect sensitive data and prevent breaches?

Audit rights: Does the vendor allow regular audits of its AI systems to ensure compliance with regulations and identify potential risks or biases?

Liability clauses: What happens if the AI system causes harm or fails to comply with regulations?

Due Diligence Questions to Ask Your AI Vendor

When selecting an AI vendor, it’s critical to ask the right questions to ensure they’re committed to compliance. Here’s a quick list of due diligence questions to ask your AI partner:

• How do you ensure your AI models are free from bias?
• What data privacy measures do you implement to comply with regulations like HIPAA, GDPR, CCPA, or others?
• Can you provide transparency into the decision-making process of the AI system?
• What steps do you take to protect sensitive data and maintain security?
• How often do you audit your AI systems for compliance and fairness?
• In the case of a data breach or AI failure, what is your protocol for handling the issue and informing clients?

Regulation Is Not the Enemy of Innovation

Many believe that compliance holds back innovation, but the truth is, smart compliance is actually one of the best ways to stay ahead. When businesses build AI systems that meet both legal and ethical standards from the beginning, they reduce the risk of costly penalties and, at the same time, they earn the trust and loyalty of their customers.

The laws are constantly changing, and the best way to stay ahead is to be proactive. A focus on compliance now can save you time and money and potentially damage your reputation down the road.

If you operate in a regulated industry, Taazaa’s AI teams can help you assess your readiness and build ethical, compliant AI solutions that work for your business. Contact us today to learn more.