AI is widely recognized a technology with the potential to undermine various domains of human life. It has the potential to change the way we commute, labor, create and consume media, and interact. The fields which it can reform are unlimited. For the law, it brings many challenges. These problems, even if dealt with by other fields of law, necessarily impact how parties interact in their civil law relationships. For example, if a company employs AI to draft a contract it offers its consumers, it may reduce its transaction costs. It may need fewer employees to perform these tasks. By using appropriate prompts, it’s AI can not only provide a standard form of contract, but it can create terms that are more favorable for the company, based on the analysis of the customer’s data. Or, more radically, it may decide not to consider the credit application submitted by an applicant based on the analysis of their data. As evidence suggests, AI is prone to making mistakes in such contexts and even to making decisions based on the applicant’s race, gender, or other identity markers. A company that uses AI may therefore reduce its transactional costs and potentially expose its customers to unfair and biased treatment.

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Understanding AI and the Current Legal Landscape

  • Nasir Muftić

摘要

AI is widely recognized a technology with the potential to undermine various domains of human life. It has the potential to change the way we commute, labor, create and consume media, and interact. The fields which it can reform are unlimited. For the law, it brings many challenges. These problems, even if dealt with by other fields of law, necessarily impact how parties interact in their civil law relationships. For example, if a company employs AI to draft a contract it offers its consumers, it may reduce its transaction costs. It may need fewer employees to perform these tasks. By using appropriate prompts, it’s AI can not only provide a standard form of contract, but it can create terms that are more favorable for the company, based on the analysis of the customer’s data. Or, more radically, it may decide not to consider the credit application submitted by an applicant based on the analysis of their data. As evidence suggests, AI is prone to making mistakes in such contexts and even to making decisions based on the applicant’s race, gender, or other identity markers. A company that uses AI may therefore reduce its transactional costs and potentially expose its customers to unfair and biased treatment.