The mapping of existing as well as upcoming regulatory obligations provides a roadmap for businesses to understand the compliance expectations of major global regulators from AI developers and deployers. Businesses must begin to develop technical capabilities, policies and procedures to ensure they can continue to develop and use AI systems and models while avoiding potential legal pitfalls which may arise in the future.
PrivacyOps is the perfect solution for the organizations aiming to achieve AI governance. It refers to the combination of philosophies, practices, automation, and orchestration that increases an organization’s ability to comply with a myriad of laws and regulations reliably and quickly. It evolves an organization from traditionally manual methods across various functional silos to full automation in a cross-functional collaborative framework.
With its proven value for the organizations in relation to global comprehensive privacy laws compliance, the PrivacyOps – the AI-powered robotic automation framework – is the best approach to achieve the complex AI governance without having to fear liabilities and regulatory risks.
Let’s look into some of the steps PrivacyOps can help automate and ensure compliance with global AI regulations and achieve AI governance.
Step 1: Classify AI systems and Assess risks using Automated Assessments
Automated Assessments can help organizations assess the risks of their AI systems at pre-development, development and post-development phases and document mitigations to the risks.
Step 2: Secure AI systems using Automated Data Security and Data Access Governance
Automated Data Security controls can help organizations ensure that there are proper safeguards to protect AI systems and the data involved from security threats and unauthorized access.
Step 3: Monitor and clean input data using Data Mapping and Sensitive Data Intelligence
Automated data mapping and sensitive data intelligence can help organizations catalog training data in order to ensure bias removal, anonymization, removal of sensitive personal data, removal of obsolete data as well as ensure the data is accurate and minimized as per applicable data protection standards.
Step 4: Disclose AI systems related details to data subjects using Privacy Notice Creation & Management
Automated privacy notice creation and management can help organizations publish AI systems related disclosures to data subjects in their privacy notices with explanations of what factors will be used in automated decision-making, the logic involved and the rights available to data subjects.
Step 5: Obtain consent and honor opt-outs from data subjects using automated consent management
Automated consent management can help organizations obtain data subjects’ consent for automated decision-making or provide data subjects the right to opt-out of their personal data being used by AI systems at the time of collection of their personal data.
Step 6: Fulfill Data Subject Rights using automated Data Subjects Rights Fulfillment
Automated data subjects’ rights fulfillment allow organizations honor data subjects’ rights to access their personal data which has been processed by the AI system, the logic involved and the outputs it created based on the process. It also allows organizations to honor individuals’ requests to delete their personal data from AI data systems, opt-out and appeal any decision made by an AI system or obtain human intervention.
Step 7: Demonstrate Compliance and Audit using Data Mapping and Sensitive Data Intelligence
Automated Data Mapping can help organizations monitor AI systems by allowing them to know what personal data/sensitive personal data is fed into the AI system, show that it is complying with its intended logical parameters and bias removal mechanisms, demonstrate compliance to regulators, produce ROPAs and maintain event logs.
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