Value group classifier model for ethical decision-making

Abstract

Decision-makers refer to ethics or moral philosophy during times of ethical dilemma. Dilemmas are situations of inner conflict, which require a methodical approach. Diversity in viewpoints on moral decisions ensures there cannot be a fixed solution for ethical dilemmas as in the case of numerical problems. Existing ethical and sustainable decision models for businesses are not automated because of a lack of a comprehensive list of dilemmas. To resolve this gap, an AI model was trained to classify all dilemmas into three value groups by using a support vector classifier (SVC). The model provided scaffolding to the ethical decision-maker by suggesting relevant human values applicable to the dilemma. The design works on the ethical theory of stakeholder management, which includes sustainable business goals. The study was conducted with 30 students and 30 adults to identify their dilemmas. The dilemma dataset was used to train an ethical decision-support tool, called the value group classification (VGC) model. The model achieved a score of 0.52 on performance. The VGC model overcomes the black-box biases of similar machine-learning models by allowing human autonomy in ethical decisions.