Data Protection and Privacy: Risks and Solutions in the Contentious Era of AI-Driven Ad Tech

Internet Service Providers (ISPs) exponentially incorporate Artificial Intelligence (AI) algorithms and Machine Learning techniques to achieve commercial objectives of extensive data harvesting and manipulation to drive customer traffic, decrease costs, and exploit the virtual public sphere through innovative Advertisement Technology (Ad-Tech). Increasing incorporation of Generative AI to aggregate and classify collected data to generate persuasive content tailored to the behavioral patterns of users questions their information security and informational self-determinism. Significant risks arise with inappropriate information processing and analysis of big data, including personal and special data protected by influential data protection and privacy regulation worldwide. This paper bridges the inter-disciplinary gap between developers of AI applications and their socio-legal impact on democratic societies. Accordingly, the work asks how AI Behavioural Marketing poses inadequately addressed data and privacy protection risks, followed by an approach to mitigate them. The approach is developed through doctrinal research of regulatory frameworks and court decisions to establish the current legislative landscape for AI-driven Ad-Tech. The work exposes the pertinent risks triggered by algorithms by analyzing the discourse of academics, developers, and social groups. It argues that understanding the risks associated with Information Processing and Invasion is seminal to developing appropriate industry solutions through a cumulative layered approach. This work proves timely to address these contentious issues using conventional and non-conventional approaches and aspires to promote a pragmatic collaboration between developers and policymakers to address the risks throughout the AI Value Chain to safeguard individuals’ data protection and privacy rights.