Plant sentience: Time scale matters

Segundo-Ortin & Calvo (2023) have made a valuable effort in directing the discussion about plant sentience toward a strict scientific path. However, scientific endeavors must reconcile with common sense beliefs. Although nowadays people tend to accept the idea of animal sentience, this is not easily extended to plants. One reason is the difference in time scale in which phenomena occur in plants and animals; but this still does not preclude the possibility , in principle, of plant sentience in a form difficult for us to imagine

How neurons in deep models relate with neurons in the brain

In dealing with the algorithmic aspects of intelligent systems, the analogy with the biological brain has always been attractive, and has often had a dual function. On the one hand, it has been an effective source of inspiration for their design, while, on the other hand, it has been used as the justification for their success, especially in the case of Deep Learning (DL) models. However, in recent years, inspiration from the brain has lost its grip on its first role, yet it continues to be proposed in its second role, although we believe it is also becoming less and less defensible. Outside the chorus, there are theoretical proposals that instead identify important demarcation lines between DL and human cognition, to the point of being even incommensurable. In this article we argue that, paradoxically, the partial indifference of the developers of deep neural models to the functioning of biological neurons is one of the reasons for their success, having promoted a pragmatically opportunistic attitude. We believe that it is even possible to glimpse a biological analogy of a different kind, in that the essentially heuristic way of proceeding in modern DL development bears intriguing similarities to natural evolution

Neural Semantic Pointers in Context

Resolving linguistic ambiguities is a task frequently called for in human communication. In many cases, such task cannot be solved without additional information about an associated context, which can be often captured from the visual scene referred by the sentence. This type of inference is crucial in several aspects of language, communication in the first place, and in the grounding of language in perception. This paper focuses on the contextual effects of visual scenes on semantics, investigated using neural computational simulation. Specifically, here we address the problem of selecting the interpretation of sentences with an ambiguous prepositional phrase, matching the context provided by visual perception. More formally, provided with a sentence, admitting two or more candidate resolutions for a prepositional phrase attachment, and an image that depicts the content of the sentence, it is required to choose the correct resolution depending on the image's content. From the neuro-computational point of view, our model is based on Nengo, the implementation of Neural Engineering Framework (NEF), whose basic semantic component is the so-called Semantic Pointer Architecture (SPA), a biologically plausible way of representing concepts by dynamic neural assemblies. We evaluated the ability of our model in resolving linguistic ambiguities on the LAVA (Language and Vision Ambiguities) dataset, a corpus of sentences with a wide range of ambiguities, associated with visual scenes

Anti-anthropomorphism and Its Limits

There is a diffuse sentiment that to anthropomorphize is a mild vice that people tend to do easily and pleasingly, but that an adult well educated person should avoid. In this paper it will be provided an elucidation of “anthropomorphism” in the field of common sense knowledge, the issue of animal rights, and about the use of humans as a model in the scientific explanation. It will be argued for a “constructive anthropomorphism,” i.e., the idea that anthropomorphism is a natural attitude to attribute human psychological features to other individuals, no matter they are actually rational agents, or not. If we know the “grammar” of this attitude, we can avoid the risks in overestimatinasg the environmental inputs toward anthropomor-phism and, at the same time, take the heuristic advantages of anthropomor-phism in the use of human mind as a model for both everyday circumstances and scientific enterprise

Evolving Illumination Design Following Genetic Strategies

Interior lighting design is a challenging task where are involved multiple constraints that need to be optimized for producing an accurate illumination avoiding possible glare. This paper, then, takes up the issue of providing a computational tool able to produce a proper lighting plan in interior spaces for a comfortable and optimal vision in all environments, taking also into account the energy consumption as little as possible. For finding acceptable solutions we have used the metaphor of the genetic evolution in a multi-objective model, where individuals are lists of possible light sources, their positions and lighting levels. For finding acceptable solutions we have used the metaphor of the genetic evolution in a multi-objective model, where every individual is a list of light sources; their positions; and lighting levels. Further, for properly evaluating each individual, we have developed two conflicting objective functions, one for optimizing the level of brightness, and the second one for maximising the energy saving, satisfying, obviously, the additional constraints to respect the architectural structure to be lighted. From the randomly initial population of individuals generations are constructed using crossover and mutation operators, whilst the fittest offspring is preserved via an elitist Pareto-dominance selection approach. In addition to the multi-objective genetic algorithm, the 3D graphic software Blender has been used in order to reproduce the architectural space to be lighted, with the aim to evaluate then, the accuracy and uniformity of the produced lighting through a physical simulation of its brightness. The main goal of the developed tool is to provide to the designer (i.e. the decision maker) a set of interiors illumination design options, for the given environment to be lit, ensuring (i) uniform illumination distribution; (ii) accuracy of the illumination produced; (iii) avoiding harsh brightness, and glare; and (iv) low energy consumptions. Two case studies have been considered in our evaluation experiments, and for each of these the algorithm was performed on two different instances and with different types of complexity respectively

Moral dilemmas in self-driving cars

Abstract: Autonomous driving systems promise important changes for future of transport, primarily through the reduction of road accidents. However, ethical concerns, in particular, two central issues, will be key to their successful development. First, situations of risk that involve inevitable harm to passengers and/or bystanders, in which some individuals must be sacrificed for the benefit of others. Secondly, and identification responsible parties and liabilities in the event of an accident. Our work addresses the first of these ethical problems. We are interested in investigating how humans respond to critical situations and what reactions they consider to be morally right or at least preferable to others. Our experimental approach relies on the trolley dilemma and knowledge gained from previous research on this. More specifically, our main purpose was to test the difference between what human drivers actually decide to do in an emergency situations whilst driving a realistic simulator and the moral choices they make when they pause to consider what they would do in the same situation and to better understand why these choices may differs.Keywords: Self-driving Cars; Trolley Problem; Moral Choices; Moral Responsibility; Virtual Reality Dilemmi morali nelle automobili a guida autonomaRiassunto: I sistemi di guida autonomi promettono importanti cambiamenti per il futuro dei trasporti, principalmente attraverso la riduzione degli incidenti stradali. Tuttavia, vi sono preoccupazioni etiche, in particolare due questioni centrali, fondamentali per il loro sviluppo. In primo luogo, le situazioni di rischio che comportano inevitabili danni ai passeggeri e/o ai pedoni, ovvero situazioni in cui alcune persone devono essere sacrificate a beneficio di altri. In secondo luogo, l’identificazione delle parti responsabili in caso di incidente. Il nostro lavoro affronta il primo di questi problemi etici. Siamo interessati a studiare come gli umani rispondono a situazioni critiche e quali reazioni considerano moralmente giuste o almeno preferibili. Il nostro approccio sperimentale si basa sul trolley problem e sulle conoscenze acquisite da precedenti ricerche su questo ambito. Più specificamente, il nostro scopo principale è quello di testare la differenza tra ciò che i conducenti umani decidono effettivamente di fare in una situazione di emergenza, mentre guidano un simulatore realistico, e le scelte morali che compiono se posti nella stessa situazione e hanno la possibilità di decidere senza limiti di tempo. Lo scopo è inoltre comprendere come e perché queste scelte possono differire.Parole chiave: Automobili a guida autonoma; Trolley problem; Scelte morali; Responsabilità morale, Realtà virtual