The Future of AI: Neat or Scruffy?

Bernardo Gonçalves, Fabio Gagliardi Cozman

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva


The “neat” and “scruffy” portraits have long been painted to describe viewpoints, styles of reasoning and methodologies in AI research. Essentially, the neats defend techniques based on first principles and grounded in mathematical rigor, while the scruffies advocate diversity within cognitive architectures, sometimes meant to be models of parts of the brain, sometimes just kludges or ad-hoc pieces of engineered code. The recent success of deep learning has revived the debate between these two approaches to AI; in this context, some natural questions arise. How can we characterize, and how can we classify, these positions given the history of AI? More importantly, what is the relevance of these positions for the future of AI? How should AI research be pursued from now on, neatly or scruffly? These are the questions we address in this paper, resorting to historical analysis and to recent research trends to articulate possible ways to allocate energy so as to take the field to maximal fruition.

Idioma originalInglés
Título de la publicación alojadaIntelligent Systems - 10th Brazilian Conference, BRACIS 2021, Proceedings, Part 2
EditoresAndré Britto, Karina Valdivia Delgado
EditorialSpringer Science and Business Media Deutschland GmbH
Número de páginas16
ISBN (versión impresa)9783030916985
EstadoPublicada - 2021
Publicado de forma externa
Evento10th Brazilian Conference on Intelligent Systems, BRACIS 2021 - Virtual, Online
Duración: 29 nov. 20213 dic. 2021

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen13074 LNAI
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349


Conferencia10th Brazilian Conference on Intelligent Systems, BRACIS 2021
CiudadVirtual, Online


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