Ethical, Legal and Governance Challenges of AI Implementation in Education and Enterprises

Abstract

The rapid application of artificial intelligence (AI) in schools and organizations has impacted the process of decision-making, performance measurement and value addition. In post-secondary education, AI-powered learning analytics is increasingly being employed to support outcome-oriented education. In organizations, AI solutions are being employed to enhance organizational operation, employee management and organizational-level decision-making. Nevertheless, emerging parallel to these advances, ethical, legal and governance (ELG)-related challenges have appeared to have immense potential to become important considerations for systematic and evidence-based analysis, rather than simply normative discussion (Floridi et al., 2018; Mittelstadt et al., 2016). This chapter applies a data-driven model for analysis of ethical, legal and governance-related concerns emerging due to the employment of AI within schools and organizations. This research avoids literature-based discussion for its focus by applying hypothetical but realistic primary research data to test concerns regarding privacy, bias, transparency, regulatory compliance and maturity in a governed context. Based on business enterprises and colleges, the chapter applies structured synthetic data in the application of comparative, correlational and descriptive analytics to uncover quantifiable risk exposure and governance readiness scores (Kshetri, 2021; Raji et al., 2020). This chapter is an application of pattern identification in the quantification of ethical risk vulnerabilities, regulatory issues of compliance and governance inadequacies in sectors through the application of tables, analytics and text analysis (Jobin et al., 2019).