Table 2.

Comparative analysis of prominent ethical decision-making models in AI.

Authors	Model/concept	Key components	Strengths	Weaknesses/criticisms
Jones (1991)	Issue-Contingent Model	Effect concentration, proximity, extent of consequences, probability of effect, social consensus, temporal immediacy	Comprehensive Supported by research	Descriptive, not prescriptive Lacks focus on judgment
Bartlett (2003)	Ethical Model Review	Ecological validity Balance between individual/social context Focus on real-life decision processes	Real-world application Balance between context/cognition	Descriptive approach Lacks prescriptive guidance
Kelley and Elm (2003)	Critique of Jones’ Model	Organizational factors Focus on moral intensity and context	Highlights organizational role Context-driven insights	Descriptive Limited prescriptive focus
Cottone and Claus (2000)	Integrated Ethical Decision-Making	Combines theoretical and practical approaches	Bridges theory and practice	May lack specificity in certain contexts
Chorus (2015)	Discrete Choice Analysis	Utilizes statistical models to analyze moral decision-making	Provides a quantitative approach to ethics	May oversimplify complex moral dilemmas
Rosenberg and Schwartz (2019)	Problem-Solving Approach	Emphasizes multiple behaviors and outcomes in ethical situations	Offers a structured approach to complex decisions	May add complexity; less empirical support
Board BAC (2020)	BACB Ethical Decision-Making Model	Nine-step process including identifying ethical issues and evaluating options	Comprehensive framework for behavior analysts	Complexity may hinder practical application