How AI can help app developers keep up with changing regulations [Q&A]
A changing regulatory landscape can prove difficult for app developers as they need to make sure they remain compliant and keep up with evolving rule sets.
We spoke to Pedro Rodriguez, head of engineering at AI-powered compliance intelligence platform Checks, to find out how AI can help mobile app developers to handle data responsibly and keep up with ever-changing global regulations,
BN: Privacy regulations like GDPR and CCPA are constantly evolving. How can AI help mobile app developers keep up with these changes?
PR: Advanced AI Large Language Models (LLMs) have the capacity to facilitate rapid regulatory compliance for app developers. By analyzing app data, privacy policies and app interactions, AI can help quickly identify compliance gaps as regulations evolve. Rather than pour over lengthy legal documents, developers can get AI-powered assessments on how new policies apply to their apps. This allows them to make any necessary changes faster and with greater accuracy.
In the past, leveraging AI required deep technical expertise. However user-friendly interfaces from companies like Google and Open AI have lowered the barrier to access. Developers can now tap into powerful AI capabilities through simple websites and plugins. An emerging marketplace of integrations is also making compliance-focused AI more readily available. Regulatory complexity will only increase, but AI helps give developers an easy way to stay up-to-date.
With advanced large language models, compliance is no longer a burden but a competitive advantage. AI-assisted tools equip developers with the speed and accuracy needed to turn evolving privacy regulations into an opportunity.
BN: What kind of insights can AI models provide to app developers about their apps? For example, can it identify where data is being sent and how it's being used?
PR: Tools fueled by advanced AI models like LLMs help app developers gain unparalleled insights into their app's data practices. By analyzing app code and behavior, LLMs can identify precisely how user data is collected, transmitted, and utilized. Developers simply provide the AI-based tool with access to the app codebase and activity logs. The AI-based tool can then detect data types, pinpoint data flows, and assess usage contexts. For example, it can flag when personal data is being sent to third-party services or used for advertising.
Unlike static code analysis, LLM-based tools, like Bard and Vertex AI Codey APIs, interpret code dynamically. This allows a more nuanced understanding of real-world data handling. These tools can even recommend security and privacy best practices tailored to an app's specific data types and flows.
In the past, custom AI development was needed to achieve such detailed app insights. However, accessible AI interfaces now put robust audit capabilities in developers' hands. AI equips developers with the tools to make the technology fueling their apps transparent, ethical, and compliant by default. These safeguards become powerful tools as users demand privacy more often. With AI-based insights, developers can remain competitive and build user trust.
BN: What are the most common challenges app developers run into with privacy and compliance and how can AI alleviate them?
PR: App developers face numerous challenges when it comes to privacy and compliance. With the proliferation of SDKs and third-party libraries, the ecosystem has become extremely fragmented. Developers often incorporate a mix of analytics tools from different vendors into their apps, making it difficult to keep up with varying data collection practices, consent requirements, and security protocols.
Constantly evolving regulations like GDPR and CCPA, and new regulations from across the US and around the globe, further complicate compliance efforts. Large teams spend countless hours manually analyzing endpoints and auditing data flows to identify compliance gaps. This manual process does not efficiently scale as new policies emerge and developer stacks rapidly change.
AI-powered solutions like Checks are emerging to help alleviate these pain points. Rather than rely on manual reviews, there are solutions that can automatically analyze app behavior and data flows to surface insights and potential compliance issues. It equips developers with a scalable way to gain visibility into their compliance posture amidst constantly shifting privacy regulations and tooling options.
By leveraging AI to automate audits and surface actionable insights, developers can incorporate privacy and compliance into their workflows. Instead of playing catch-up, developers can adopt a proactive approach aligned with the developer community's growing desire for more transparent and compliant data practices. Compliance no longer needs to be an afterthought given the right technology support.
BN: As head of engineering, what excites you most about leveraging AI for regulatory compliance in the app development space?
PR: What excites me most is the tremendous pace of the technological advancement in AI. In just the past eight months, we've seen incredible progress in AI capabilities. This is fostering an ecosystem where companies can now build tailored solutions for specific verticals, including app development.
Solutions that were once just a part of the imagination are becoming reality; assisting developers to build software faster and unlocking opportunities for non-engineers to become app creators. AI is truly democratizing software development.
At the same time, governments are investing heavily in privacy regulations worldwide. Pairing advanced AI with this growing compliance focus is a powerful combination that can make the app ecosystem better and safer.
On the Checks team at Google, our mission centers on leveraging AI to tackle regulatory and platform compliance for app developers. We are at the forefront of rapid AI advancements and real-world use cases that were inconceivable just months ago. This gives us a front-row seat to trailblaze compliance solutions that reduce developer burdens.
It's an exciting time to steer AI toward addressing the pressing needs of the app development community while helping to protect user privacy. We're living in an era where AI can drive meaningful progress on issues like compliance that once seemed intractable.
BN: What trends are you seeing in terms of how data regulations differ between regions? How does your platform account for these regional nuances?
PR: Previously, the industry took a global approach with regulations such as GDPR and CCPA becoming the benchmark for privacy. But now we see that certain states and certain countries are also creating their own frameworks. There are data sensitivities that differ across jurisdictions and there are certain regions where certain topics are more sensitive.
There is a need for a holistic approach to providing a solution in this space that supports as many customers as possible and protects the largest number of app users. At the same time, we need to build technology that can keep pace with the increasing number of policies and regulations, so companies have access to tools now to help them manage the larger scope of requirements.
A lot of focus has been put on privacy and compliance in the mobile space, but privacy and compliance specifically for AI is emerging as a compelling need. As companies rush to implement AI amidst minimal governance, we have an obligation to expand our compliance solutions to encompass resources that promote principled development.
While regulations lag, companies like Checks sit at the center of pressing discussions around AI compliance. We recognize AI's exponential pace requires proactive frameworks to steer developers towards ethical choices, even amidst ambiguity.
By promoting not just AI compliance, but ethically principled compliance, we can move the industry forward responsibly during this critical growth juncture.