Publications

In this paper I argue that the answer is no, for no context-dependent feature can play a significant role in solutions to the frame problem, and that is the case of emotions. Abstract The frame problem, a long-standing issue in Artificial Intelligence (AI), revolves around determining the relevance of information in an ever-changing array of contexts, posing a formidable challenge in modeling human reasoning. The purpose of this paper is to explore the hypothesis that emotions are able to solve, or at least enable a substantial step towards a solution....

This is my PhD’s dissertation. I try to account for the relevance sensitivity presented in a core human cognitive capacities, which is commonsense. Roughly, that’s the capacity to zero in on what’s relevant within an open-ended set of contexts in a non circular way (after all, what’s relevant is context dependent). The key idea is that relevance sensitivity is a kind of cognitive technology (a cognitive gadget, as Cecilia Heyes would put it) that relies heavily on culturally established elements....

Here we argue for a conception of structural representations grounded in isomorphism as an alternative for linguistic representations grounded in causal correlation. We show that this conception can satisfy requirements such as Ramsey’s job description challenge and avoid the so called Hard problem of content and remain compatible with 4E cognition. We also argue that deciding whether a given cognitive capacity or performance is representational is a matter of empirical research on a case by case basis....

In this paper I argue that the problem of algorithmic bias should not be handled as a technical issue. There’s no such thing as a bias free AI model or system. What we have are sets of desirable and undesirable biases, and populating these sets should be done through public debates, rather than “technical” indoors decision. Abstract Artificial intelligence (AI) techniques are used to model human activities andpredict behavior. Such systems have shown race, gender and other kinds of bias, whichare typically understood as technical problems....

This is my Masters dissertation about the frame problem of Artificial Intelligence. The core claim of this work is that the problem (conceived as a problem about relevance) is neither computational nor representational in nature. It plagues every contemporary explanatory framework. In particular, one does not simply get rid of the frame problem by (e.g.) adopting a 4EA perspective. Abstract Context sensitivity is one of the distinctive marks of human intelligence....