The advent of artificial intelligence has assumed prominence amongst all industries and various facets of people's personal lives. The integration of AI in education has been inevitable, given the significance and role of information, knowledge production and administration in the sector. This is especially so as its capabilities entail replicating higher-order thinking. Besides assisting in the education process, it also brings the element of real-life relevance, allowing education to be imparted against the backdrop of the evolving world due to the same AI. It tends to have implications on the subject matter that needs to be imparted, which tends to be something that constantly needs to answer the question of "Why and how is this particular subject matter relevant for learning?". This induces policy-makers and educational institutions to rethink what they need to impart as knowledge, the area of matter, and the manner of thinking to be emphasised. This is because educa
New A.I. regulations aim for ethical use and privacy protection. The E.U.'s GDPR safeguards data and restricts harmful automated decisions. It states that people can't face impactful choices made solely by AI, though some exceptions exist. While A.I. has benefits, oversight is needed to uphold rights and prevent unintended harm. GDPR also introduces mandatory Data Protection Impact Assessments for organizations to evaluate the risks of new projects, including those using AI. These assessments determine when high-risk A.I. systems should be subject to further regulation. Impact assessments require documenting the automated decision-making process, assessing necessity and proportionality, and mitigating potential risks. [1] . The United States lacks a singular regulation like GDPR but instead relies on a sectoral approach. For example, the Fair Credit Reporting Act requires explainable credit scoring algorithms and gives consumers access to their credit data [2] . The Equal Cre