Andrés A. Ilcic

En este trabajo proponemos un recorrido por algunas de las múltiples facetas que la noción de información tuvo, tiene y tendrá en la discusión de distintos problemas filosóficos, poniendo especial atención a aquellos que han preocupado a los filósofos de la técnica, de la computación y, en particular, de la filosofía de la inteligencia artificial. En el camino prestamos atención a las oportunidades, a los desafíos y también a los peligros que las nuevas tecnologías de la información nos presentan como individuos, como sociedad y como cultura. Estas tecnologías crean nuevos espacios de interacción que ponen en jaque distintas concepciones del mundo, pero también aportan conceptos que deben incorporarse al acervo filosófico, no sólo porque pueden aportar luz a viejas discusiones sino porque consideramos que es necesaria la reflexión filosófica para orientar el curso y las consecuencias de tecnologías que, por su propia definición, intentan ocupar “espacios humanos”.

The discovery-justification distinction stands as a pivotal issue within 20th-century philosophy of science. It subtly underpins many foundational topics and concepts pertinent to our comprehension of knowledge. Thomas Kuhn's contributions are indispensable in this regard, with his critiques playing a pivotal role in shaping both his initial model of scientific progress and its subsequent revisions. Kuhn addressed this dichotomy head-on in the first of his Thalheimer Lectures, presented in 1984. In this paper, we revisit Pablo Melogno's (2019) examination of Kuhn's engagement with this theme. Concurring with Melogno, our analysis extends his interpretation by exploring Larry Laudan's objections to certain research programs focused on a logic of discovery. We further scrutinize specific assumptions about discovery heuristics that have been misinterpreted within Laudan's methodological framework, particularly the one stemming from Herbert Simon's pioneering work. By synthesizing these perspectives, we aim to set up a preliminary framework for a more refined understanding of how history and philosophy of science inform the epistemic practices of agents operating with bounded rationality.

A irrupção de múltiplas implementações de inteligências artificiais na forma de produtos no mercado trouxe à tona uma série de discussões, como o status epistemológico da computação em larga escala, os princípios econômicos e políticos que possibilitam essas implementações e as consequências que já estamos observando nos campos político, cultural e social. Nossa proposta é tratar da sobreposição entre essas abordagens com o objetivo de apontar algumas linhas que nos permitam integrar as bases epistemológicas da inteligência artificial com a filosofia da tecnologia, com a política e com a estética, a fim de propor uma agenda própria nos debates públicos.

The discovery-justification distinction stands as a pivotal issue within 20th-century philosophy of science. It subtly underpins many foundational topics and concepts pertinent to our comprehension of knowledge. Thomas Kuhn's contributions are indispensable in this regard, with his critiques playing a pivotal role in shaping both his initial model of scientific progress and its subsequent revisions. Kuhn addressed this dichotomy head-on in the first of his Thalheimer Lectures, presented in 1984. In this paper, we revisit Pablo Melogno's (2019) examination of Kuhn's engagement with this theme. Concurring with Melogno, our analysis extends his interpretation by exploring Larry Laudan's objections to certain research programs focused on a logic of discovery. We further scrutinize specific assumptions about discovery heuristics that have been misinterpreted within Laudan's methodological framework, particularly the one stemming from Herbert Simon's pioneering work. By synthesizing these perspectives, we aim to set up a preliminary framework for a more refined understanding of how history and philosophy of science inform the epistemic practices of agents operating with bounded rationality.

In 1936, Alan Turing proposed the notion of an automated machine as a model of the computation performed by a human being while only being aided by mechanical resources. Still, it seems that much more can be said about Turing’s own conception of machines in the scope of his later work, both terminologically and conceptually. In this paper we present the terms he used that refer to machines and that according to our understanding are important to give an account of Turing’s concerns and the problems he tackled with after his first recourse to the notion of machine during the late nineteen-thirties. Exploring his usage of such terms we show how it is possible to see an enlargement or extension towards a general notion of machine from the very first automated machine. At the same time, we identify in his work a modelling attitude or stance in which machines can be used as a way to understand and explain a natural or abstract phenomenon.