The Moral Machine experiment, conducted by researchers at MIT and other institutions, aimed to explore global moral preferences regarding autonomous vehicle (AV) decisions in unavoidable accident scenarios. By collecting 40 million decisions from over 2.3 million people across 233 countries, the study sought to understand the ethical principles that should guide machine behavior. The findings revealed strong preferences for sparing human lives, more lives, and younger individuals, while weaker preferences included sparing women and pedestrians. Individual variations in these preferences were observed, but no demographic factors changed the direction of any preference. Cross-cultural differences were also identified, with three major clusters of countries showing distinct moral preferences. These differences correlated with modern institutions and deep cultural traits. The study emphasized the need for global, harmonious, and socially acceptable principles for machine ethics, as AVs will soon be prevalent on roads. The experiment highlighted the importance of public morality in AI ethics and the challenges of achieving universal agreement on ethical principles. The results underscore the complexity of moral decision-making in AV contexts and the necessity for inclusive public consultations to shape ethical guidelines. The study also noted the limitations of its data, including self-selection bias, and the need for further research to address the complexities of AV dilemmas. Overall, the Moral Machine experiment provided valuable insights into global moral preferences and the challenges of developing universally accepted ethical principles for AI.The Moral Machine experiment, conducted by researchers at MIT and other institutions, aimed to explore global moral preferences regarding autonomous vehicle (AV) decisions in unavoidable accident scenarios. By collecting 40 million decisions from over 2.3 million people across 233 countries, the study sought to understand the ethical principles that should guide machine behavior. The findings revealed strong preferences for sparing human lives, more lives, and younger individuals, while weaker preferences included sparing women and pedestrians. Individual variations in these preferences were observed, but no demographic factors changed the direction of any preference. Cross-cultural differences were also identified, with three major clusters of countries showing distinct moral preferences. These differences correlated with modern institutions and deep cultural traits. The study emphasized the need for global, harmonious, and socially acceptable principles for machine ethics, as AVs will soon be prevalent on roads. The experiment highlighted the importance of public morality in AI ethics and the challenges of achieving universal agreement on ethical principles. The results underscore the complexity of moral decision-making in AV contexts and the necessity for inclusive public consultations to shape ethical guidelines. The study also noted the limitations of its data, including self-selection bias, and the need for further research to address the complexities of AV dilemmas. Overall, the Moral Machine experiment provided valuable insights into global moral preferences and the challenges of developing universally accepted ethical principles for AI.