Research on computational models of scientific discovery investigates both the induction of descriptive laws and the construction of explanatory models. Although the work in law discovery centers on knowledge‐lean approaches to searching a problem space, research on deeper modeling tasks emphasizes the pivotal role of domain knowledge. As an example, our own research on inductive process modeling uses information about candidate processes to explain why variables change over time. However, our experience with IPM, an artificial intelligence system that implements this (...) approach, suggests that process knowledge is insufficient to avoid consideration of implausible models. To this end, the discovery system needs additional knowledge that constrains the model structures. We report on an extended system, SC‐IPM, that uses such information to reduce its search through the space of candidates and to produce models that human scientists find more plausible. We also argue that although people carry out less extensive search than SC‐IPM, they rely on the same forms of knowledge—processes and constraints—when constructing explanatory models. (shrink)

When philosophers discuss the possibility of machines making scientific discoveries, they typically focus on discoveries in physics, biology, chemistry and mathematics. Observing the rapid increase of computer-use in science, however, it becomes natural to ask whether there are any scientific domains out of reach for machine discovery. For example, could machines also make discoveries in qualitative social science? Is there something about humans that makes us uniquely suited to studying humans? Is there something about machines that would bar them from (...) such activity? A close look at the methodology of interpretive social science reveals several abilities necessary to make a social scientific discovery, and one capacity necessary to possess any of them is imagination. For machines to make discoveries in social science, therefore, they must possess imagination algorithms. (shrink)

El papel de las emociones en los procesos de toma de decisiones racionales es un hecho demostrado. Al mismo tiempo, el paradigma de la mente extensa resulta útil en el planteamiento de los mecanismos cognitivos implícitos en la ciencia moderna, una e-ciencia altamente computerizada y robotizada, con múltiples elementos procedentes de la Inteligencia Artificial. Por ello, el análisis de modos eficientes de interacción entre seres humanos y entidades artificiales pasa por el estudio de las emociones sintéticas, desde la idea de (...) los robots sociales o los entornos afectivos. El presente artículo analiza estos fenómenos y plantea una pionera propuesta de desarrollo de las investigaciones en esta área. (shrink)