Description: Utilitarianism is a normative ethical theory that holds that the best action is the one that maximizes utility, understood as general well-being or happiness. This ethical philosophy focuses on the consequences of actions, evaluating their morality based on the results they produce. In this sense, utilitarianism seeks the greatest good for the greatest number of people, promoting the idea that decisions should be made considering their impact on collective happiness. Among its main characteristics are the pursuit of maximizing utility, considering all those affected by an action, and evaluating long-term consequences. This theory has influenced various areas, from ethics in technology to resource management, where optimization and efficiency are fundamental. In the context of artificial intelligence, utilitarianism raises questions about how algorithms can be designed to maximize human well-being, which involves a deep analysis of ethics and bias in artificial intelligence models. In summary, utilitarianism provides a valuable framework for evaluating ethical decisions in an increasingly complex and technological world.
History: Utilitarianism was developed in the 18th and 19th centuries by philosophers such as Jeremy Bentham and John Stuart Mill. Bentham, in his work ‘An Introduction to the Principles of Morals and Legislation’ (1789), proposed that the morality of an action is measured by its ability to generate pleasure and avoid pain. Mill, in his book ‘Utilitarianism’ (1863), refined these ideas, arguing that not all pleasures are equal and that some are more valuable than others. Over the years, utilitarianism has evolved and has been the subject of criticism and debate, especially regarding its application in politics and economics.
Uses: Utilitarianism is used in various fields, including ethics, economics, politics, and artificial intelligence. In ethics, it is applied to evaluate moral decisions and public policies, aiming to maximize social welfare. In economics, it is used to analyze resource efficiency and the distribution of well-being. In artificial intelligence, it is considered when designing algorithms that must make decisions impacting people, seeking to minimize biases and maximize benefits.
Examples: A practical example of utilitarianism in action is the evaluation of public health policies, where measures are sought to maximize the health and well-being of the population as a whole. Another example is the use of algorithms in technology platforms that prioritize content that generates greater satisfaction among users, even if this may lead to the spread of biased or harmful information. In the field of artificial intelligence, recommendation systems can be designed to optimize user experience based on utilitarian principles.
