RT Journal Article
T1 Machine Ethics: Do Androids Dream of Being Good People?
A1 Génova Fuster, Gonzalo
A1 Moreno Pelayo, Valentín
A1 González Martín, M. Rosario
AB Is ethics a computable function? Can machines learn ethics like humans do? If teaching consists in no more than programming, training, indoctrinating¿ and if ethics is merely following a code of conduct, then yes, we can teach ethics to algorithmic machines. But if ethics is not merely about following a code of conduct or about imitating the behavior of others, then an approach based on computing outcomes, and on the reduction of ethics to the compilation and application of a set of rules, either a priori or learned, misses the point. Our intention is not to solve the technical problem of machine ethics, but to learn something about human ethics, and its rationality, by reflecting on the ethics that can and should be implemented in machines. Any machine ethics implementation will have to face a number of fundamental or conceptual problems, which in the end refer to philosophical questions, such as: what is a human being (or more generally, what is a worthy being); what is human intentional acting; and how are intentional actions and their consequences morally evaluated. We are convinced that a proper understanding of ethical issues in AI can teach us something valuable about ourselves, and what it means to lead a free and responsible ethical life, that is, being good people beyond merely "following a moral code". In the end we believe that rationality must be seen to involve more than just computing, and that value rationality is beyond numbers. Such an understanding is a required step to recovering a renewed rationality of ethics, one that is urgently needed in our highly technified society.
PB Springer
SN 1353-3452
YR 2023
FD 2023-03-23
LK https://hdl.handle.net/10016/38545
UL https://hdl.handle.net/10016/38545
LA eng
NO This work has been supported by the Madrid Government (Comunidad de Madrid-Spain) under the terms of the Multi-Annual Agreement with UC3M in the line of Excellence of University Professors (EPUC3M17), and in the context of the V PRICIT (Regional Programme of Research and Technological Innovation). This research has received funding also from the RESTART project – “Continuous Reverse Engineering for Software Product Lines / Ingeniería Inversa Continua para Líneas de Productos de Software” (ref. RTI2018-099915-B-I00, Convocatoria Proyectos de I + D Retos Investigación del Programa Estatal de I + D + i Orientada a los Retos de la Sociedad 2018, grant agreement nº: 412122; and from the CritiRed project – “Elaboración de un modelo predictivo para el desarrollo del pensamiento crítico en el uso de las redes sociales”, Convocatoria Retos de Investigación del Ministerio de Ciencia, Innovación y Universidades (2019–2022), ref. RTI2018-095740-B-I00.
DS e-Archivo
RD 30 jun. 2024