Protecting Privacy in the Era of Artificial Intelligence
Artificial Intelligence has emerged with real-time challenges as It has brought along with it both pros-cons, and the cons are needed to be fixed from the outset. As AI has a direct cohesion with data protection issues. If we are to cite an example that can be of an individual’s personal information which is hugely scrapped from almost all the platforms which have a colossal database. Now having cited this example invokes security issues in regard to the personal data of individuals. Whenever in recent scenarios of technological advancement any major challenges occur then we tend to be concerned for remedial measures which ultimately is the privacy of data principals.
However, these same technological innovations raise important issues, including a dilemma regarding the relation between AI and data protection laws that how can they supplement each other in sorting data related deformities. Now, this is the high time where we have both an opportunity and the obligation to examine the effectiveness of current data protection laws in light of 21st-century technological realities like challenges of AI.
While compliance with existing data protection laws is crucial, a long-lasting approach is to examine the challenges presented by AI as another wake-up call that our current approach to data protection is increasingly obsolete. Viewed in this light, it is a data protection law that must be improved if it is to protect privacy, effectively address the challenges presented by AI, and avoid creating unnecessary, bureaucratic barriers to AI’s benefits. The Five reforms appear necessary like, Shifting from Individual Consent to Data Stewardship, A More Systemic and Well-Developed utility of Risk Management, A Greater Focus on Data Uses and implications, A Framework of Harms and Transparency and Redress.
Keywords: Data protection, Artificial Intelligence, Privacy, Machine Learning, Automated facial recognition and legal ethics-AI.
Read Full paper on:-https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3560047
Author(s) – Usama Mubarak & Keyur Tripathi.