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.
