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Privacy and Data Protection in the Public and Private Sector in the AI ​​Era Focusing on Profiling in Business and Investigative Processes

  • Legal Theory & Practice Review
  • Abbr : LTPR
  • 2025, 13(2), pp.221~262
  • Publisher : The Korea Society for Legal Theory and Practice Inc.
  • Research Area : Social Science > Law
  • Received : May 7, 2025
  • Accepted : May 23, 2025
  • Published : May 31, 2025

Lee Keon Su 1

1백석대학교

Accredited

ABSTRACT

Profiling through AI prediction is the output result of AI that learned big data, and is used in various fields such as advertising, insurance, talent introduction, and crime prevention. The advantages of AI prediction and profiling can be summarized as follows. First, objective and precise prediction and analysis are possible. AI prediction and profiling can perform objective and high-precision prediction or analysis without relying on human intuition or experience. By doing this, I can more accurately understand the relationships between things and future trends. We can expect convenience and improved management efficiency for both businesses and consumers. AI prediction and profiling have advantages for both businesses and consumers. Through this, I can expect improved management efficiency such as cost reduction and increased sales. The following can contribute to solving social issues. AI prediction and profiling also have advantages for society as a whole. AI prediction and profiling can potentially contribute to solving various tasks such as early detection and treatment of diseases, optimal placement and training of talent, and prevention and countermeasures for crimes. However, the problems of AI prediction and profiling can be summarized as follows: There is a concern that an individual's privacy or right to self-determination may be violated. First, AI prediction and profiling may violate an individual's privacy or right to self-determination. For example, profiling by AI may promote discrimination or prejudice. If AI’s accountability and transparency are insufficient, trustworthiness and ethics can be compromised. Next, AI predictions and profiling can be compromised if AI’s accountability and transparency are insufficient. Therefore, trust in AI’s predictions or analysis can be reduced, or it can lead to incorrect judgments or actions. Since AI profiling is based on data, human subjectivity is not reflected. Finally, since AI predictions and profiling are based on data, human subjectivity is not reflected. And the ultimate decision must be made by a human. The following countermeasures can be considered for the problems of AI predictions and profiling. In order to secure responsibility and transparency for AI, AI algorithms and learning data must be open or subject to verification or audit by a third party. In order to appropriately utilize AI profiling, AI predictions or analyses must be treated as reference information, and the final decision must be made by a human. AI prediction and profiling are technologies that can be effectively utilized in the business field, but at the same time, they can affect individuals and society. When utilizing AI prediction and profiling, it is important to understand its advantages and disadvantages and take appropriate measures. AI prediction and profiling will improve through cooperation between humans and AI.

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