The growing intersection of AI use with many and varied aspects of business and society makes navigating the complex web of compliance a significant challenge. The information below provides a brief, strategic guide to managing compliance in the AI era, focusing on aligning AI practices with legal, ethical, and regulatory standards.
The Compliance Landscape
Compliance with existing and emerging AI rules, guidelines, policies, and laws involves understanding national and international data protection laws, such as the California Consumer Privacy Act (CCPA), the European Union’s General Data Protection Regulation (GDPR) and Artificial Intelligence Act (EU AI Act), as well industry-specific regulations, organizational policies, and generally accepted ethical standards. Businesses must be aware of how all of these directives can or will affect AI usage by employees, customers, and other stakeholders, how they can or will affect business practices and protocols, where they will be in effect geographically, and, last but certainly not least, which measures need to be adopted to ensure compliance and when that must happen.
In addition to all that, there is the clear expectation that providers of AI-dependent tools of every sort will understand that AI compliance encompasses a broad spectrum of considerations, from data privacy and security to ethical, culturally sensitive or at least culturally aware, and safe use of their AI products–and foreseen misuse. Staying abreast of evolving directives like those mentioned above and others is absolutely critical for businesses creating, supporting, or deploying AI technologies. The ramifications for not doing so will put a damper on your day in the best case and put your company underwater in the worst.
Develop a Compliance-Centric AI Strategy
The best things every AI-utilizing organization can do to future-proof itself against compliance issues include the following:
- Conduct a comprehensive risk assessment: No company can possibly understand the potential AI compliance risks it faces without one. The key to this is comprehensive; it must involve assessing the effects of internal decisions about AI-related privacy, fairness, and transparency.
- Embed compliance-centric considerations into every step of the AI development lifecycle: Doing so from the outset of AI project planning is critical. This means designing AI systems with regulatory requirements in mind–right up there with functionality, performance, reliability, etc.
- Do not ignore the ethical aspect of the product, service, or solution: Beyond legal compliance, ensuring that AI systems adhere to accepted or, in some cases stated, ethical standards is key to maintaining public trust and brand integrity.
- Train your people: Equip your workforce, including those external teams that might resell, install, or otherwise work with your AI solution, with the necessary knowledge about AI compliance. Conduct regular training sessions and workshops to ensure the organization as a whole has a compliance-first mindset.
Leverage Technology
You’re an AI company! Use the resources at hand! Utilize AI tools and other novel technologies to monitor compliance, which will streamline and optimize the process, making it more cost-efficient and less prone to human error. Our CalypsoAI SaaS-enabled security, orchestration, and compliance platform is designed and built to provide AI security for an organization’s digital infrastructure at the user and group level, certainly. But in doing so, it also provides the capacity to ensure the organization as a whole remains safe from challenges, including those resulting from being out of compliance.
Full observability allows security teams to see what models are doing in real time, enabling them to detect anomalous activity and deter threats that could otherwise lead to data breaches or adversarial attacks on models. Customizable audit scanners give admins the ability to establish thresholds for terminology and topics in prompts and responses that could lead to bias, toxicity, and other unacceptable practices.
Navigating compliance in the AI era requires a strategic approach that integrates legal, ethical, and regulatory considerations into every aspect of your AI system or solution. By prioritizing risk assessment and comprehensive data governance, embedding compliance into AI development and deployment, focusing on ethics, and leveraging technology, businesses can successfully manage the complexities of AI compliance.
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