RESUMO
Esta cronología es una idea del psicoanalista e investigador francés Théo Lucciardi y fue publicada originalmente en el número 3 de la revista LAPSUS NUMÉRIQUE. Su autor ha preparado esta versión actualizada a 2023 especialmente para este número de Aesthethica. La secuencia, que va desde la invención de la rueda hasta la IA generativa, permite detenernos en los grandes hitos del desarrollo científico tecnológico y a la vez advertir ve el grado de aceleración de la última década. Se pueden reconocer allí varios de los temas que integran la agenda contemporánea en materia de bioética y que están presentes en este número de la revista. Algunos de ellos son cruciales para la lectura ético-analítica que proponemos, como la vigencia de la lógica booleana, la actualización del Test de Turing o el porvenir de la IA y el Chat GPT
This chronology is an initiative of the French psychoanalyst and researcher Théo Lucciardi and was originally published in number 3 of the LAPSUS NUMÉRIQUE magazine. Its author has prepared this updated version to 2023 especially for this issue of Aesthethica. The sequence, which goes from the invention of the wheel to generative AI, allows us to stop at the great milestones of technological scientific development and at the same time notice the degree of acceleration of the last decade. Several of the issues that make up the contemporary agenda in bioethics and that are present in this issue of the magazine can be recognized there. Some of them are crucial for the ethical-analytical reading that we propose, such as the validity of Boolean logic, the updating of the Turing Test or the future of AI and Chat GPT
Assuntos
História Antiga , História do Século XXI , Pesquisa Científica e Desenvolvimento Tecnológico , Inteligência Artificial , CronologiaRESUMO
Logic models of signaling pathways are a promising way of building effective in silico functional models of a cell, in particular of signaling pathways. The automated learning of Boolean logic models describing signaling pathways can be achieved by training to phosphoproteomics data, which is particularly useful if it is measured upon different combinations of perturbations in a high-throughput fashion. However, in practice, the number and type of allowed perturbations are not exhaustive. Moreover, experimental data are unavoidably subjected to noise. As a result, the learning process results in a family of feasible logical networks rather than in a single model. This family is composed of logic models implementing different internal wirings for the system and therefore the predictions of experiments from this family may present a significant level of variability, and hence uncertainty. In this paper, we introduce a method based on Answer Set Programming to propose an optimal experimental design that aims to narrow down the variability (in terms of input-output behaviors) within families of logical models learned from experimental data. We study how the fitness with respect to the data can be improved after an optimal selection of signaling perturbations and how we learn optimal logic models with minimal number of experiments. The methods are applied on signaling pathways in human liver cells and phosphoproteomics experimental data. Using 25% of the experiments, we obtained logical models with fitness scores (mean square error) 15% close to the ones obtained using all experiments, illustrating the impact that our approach can have on the design of experiments for efficient model calibration.
RESUMO
Los motores de búsqueda son objetos culturales que presentan, como toda herramienta destinada a la organización y circulación de la información, desafíos de carácter semiótico y epistémico así como sesgos ideológicos. El presente artículo analiza el modo en que alumnos de escuela primaria conceptualizan el modo de funcionamiento de un buscador que usan asiduamente. La perspectiva teórica adoptada considera los aportes de la tradición sociohistórica vigotskiana y del constructivismo relacional piagetiano. El diseño metodológico se inscribe en un estudio cualitativo de casos en el que se emplean dos instrumentos de recolección: observaciones de clase (en el aula y en la sala de informática), y entrevistas clínico-críticas posteriores. Los resultados evidencian que en situaciones didácticas donde el buscador se convierte en objeto de análisis, los alumnos toman conciencia de que la construcción de las palabras clave los ubica en una situación de escritura para un "lector robot" que no coopera en la interpretación. Ante este problema, se proponen usar una sintaxis en la que las palabras se enlazan con signos diversos a los que adjudican funciones vinculadas con sus conocimientos del lenguaje natural. La contradicción se produce porque los motores de búsqueda utilizan una lógica más próxima a las matemáticas
Search engines are cultural objects which represent semiotic and epistemological challenges as well as ideological bias, like every tool destined to the organization and circulation of information. This article analyzes the conceptualizations of elementary school students about a search engine that frequently used. The adopted theoretical perspective considers both the contribution of the Vigotskian sociohistorical tradition and the Piagetian relational constructivism. The methodological design consisted of a qualitative study of cases. Two data collection instruments are used: observations in the classroom and in the computer lab and post-clinical-critical interviews. The results show that in those didactic situations where the search engine becomes an object of analysis, the students develop awareness of the fact that the construction of keywords places them in a writing situation for a "robot reader" that does not cooperate in the interpretation. In view of this problem, they propose to use a syntax in which the words connect with different signs. But the students give to these signs functions linked with their own knowledge of the natural language. The contradiction occurs because the search engines use logic close to the mathematical languages