AI's Impact on Customer Privacy Standards

AI's Impact on Customer Privacy Standards

Jodi Daniels, a privacy consultant and the head honcho at Red Clover Advisors, a women-led business enterprise focused on privacy, gets straightforward with the challenges businesses face when it comes to AI and privacy. AI, like a two-faced coin, offers immense opportunities but also poses significant risks.

One of the common problems is consumer unease about AI and data handling. But don’t lose hope! Here's what businesses must keep in mind as they delve deeper into AI, all while navigating a rapidly changing regulatory landscape. Let's dive into the good, the bad, and the ugly aspects of AI and consumer privacy expectations and what you can do about them.

Data protection laws make consumers feel more at ease sharing their info

Let's first shed some light on the privacy scene. While businesses might grumble about the constant tweaks and additions to state consumer privacy laws, there's a silver lining.

A recent Cisco survey found that aware consumers are way more confident that their data is protected (81%) compared to those unaware (44%). Additionally, 59% of consumers said they'd be more comfortable sharing data for AI applications with strong privacy laws in place. That's a win for businesses, as AI can boost customer service, personalize experiences, and drive cross- and up-selling.

However, consumers still have trust issues when it comes to AI

Remember Apple's lawsuit settlement this year over alleged privacy infringement by the Siri voice assistant dating back to 2019? It just goes to show that even with strong privacy laws, consumers remain wary about their privacy.

In fact, 68% of global consumers are still somewhat or very concerned about their privacy online, and 57% agree that AI poses a significant threat to their privacy. This has led to a confusing public perception of AI. People believe that it can benefit society, but they also think that AI poses a privacy threat.

Bridging the trust gap between consumers, privacy practices, and AI

To ease this confusing minds-thinking, businesses can alleviate customer concerns through transparent privacy programs that foster trust between the business, consumers, and the tools used.

Conduct privacy impact assessments (PIAs)

PIAs are an evaluation tool used to review a process, service, product, or feature and flag any potential privacy red flags. Many states already require PIAs for certain products, like those built for minors.

PIAs help identify risks related to the use of personal information in the context of a business activity. It's proactive and helps mitigate risks for both consumers and the company's legal liability. When evaluating AI tools, beware of these four major risk factors:

1. Type of processing
2. Type of personal data
3. Type of individual
4. Jurisdictions involved

Address AI bias

One significant concern with AI is bias. AI models often learn from large data sets, which may be full of stereotypes and inaccuracies. To protect against bias (and to protect your employees and customers), consider requiring a bias audit for any AI models you adopt.

Create an AI governance framework

With the future of AI still a mystery, that doesn't mean you should fly blind. An AI governance program sets policies, procedures, and guidelines for responsibly using AI in your organization. It aligns well with existing privacy activities.

An AI governance program should include:- A cross-departmental team with defined roles in data governance, compliance, and risk management- A comprehensive AI inventory to assess tools, usage, and risks- A third-party risk assessment of any vendor providing AI capabilities- Guidelines for governance, mapping, measuring, and managing risks- Regular risk assessments to prioritize and mitigate potential issues

Like any privacy-related activity, it's crucial to regularly train your team to ensure your approach works.

The takeaway: Responsible AI use builds trust and protects your business

Among the AI community, fear-mongering is not cool. Use AI responsibly, and you'll see benefits. Here's a quick rundown of steps to follow:

1. Conduct a PIA when considering new AI tools and use cases.
2. Identify what steps are needed to mitigate AI-related risks and obligations, such as managing bias, security concerns, or regulatory requirements.
3. Evaluate vendors thoroughly, both before adopting tools and when new features are added.
4. Provide clear communication to consumers about how your business uses AI.
5. Implement protections that put consumers in control of their personal data.

By following these steps, you won't just be protecting your business from compliance violations or reputational damage; you'll be building a stronger, more loyal customer base for years to come.

1. Jodi Daniels, a privacy consultant and the head of Red Clover Advisors, agrees that strong data protection laws can help alleviate consumers' concerns about sharing their information, as 59% of consumers claimed they'd be more comfortable sharing data for AI applications with such laws in place.
2. Jodi Daniels, a privacy consultant, acknowledges that despite the implementation of strong privacy laws, consumers continue to have trust issues regarding AI, as 68% of global consumers remain somewhat or very concerned about their privacy online, and 57% agree that AI poses a significant threat to their privacy.
3. To bridge the trust gap between consumers, privacy practices, and AI, Jodi Daniels, as a consultant, suggests implementing transparent privacy programs, such as conducting privacy impact assessments, addressing AI bias, and creating an AI governance framework, to foster trust between businesses, consumers, and the tools used.

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