1,721,013 research outputs found
Turing's Vision. How AI is Shaping the World
No full textChat-GPT, humanoid robotics, and self-driving cars are just a few of the things that are changing our everyday lives. The rapid advancement of AI is eroding one by one all the cornerstones considered unique of human nature: language, consciousness, creativity, and moral responsibility. The book argues that the revolution we are facing is driven by Alan Turing's "vision". This vision rests on the idea that intelligence is not an intrinsic property of human beings, but is a way in which matter is functionally organized and an attribute we are naturally inclined to ascribe to certain entities. For decades we have pretended that this idea does not have the corrosive power that it actually does, perhaps more so than the Copernican and Darwinian revolutions. But now, given the achievements of new forms of computing based on deep learning and predictive coding, the most common intuitions can no longer avoid the dangerous Turing idea.
The book is intended for scholars, researchers, and readers intrigued by the intersections across disciplines interested in understanding the philosophical, ethical, and social implications of Artificial Intelligence and its impact on human nature
Neural Semantic Pointers in Context
Get PDFResolving 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
How Neurons in Deep Models Relate with Neurons in the Brain
Get PDFIn 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
Resolving Linguistic Ambiguities by Visual Context
No full textResolving linguistic ambiguities is a crucial type of inference in several aspects of language, communication in the first place, and in the grounding of language in perception. This task is frequently called for in human communication and, in many cases, it cannot be solved without additional information about an associated context. In this paper we focus on the contextual effects of visual scenes on semantics, investigated using neural computational simulation. Specifically, 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, we address the problem of selecting the interpretation of the sentence matching the context provided by visual perception, choosing 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
Moral reasoning and automatic risk reaction during driving
No full textRecent advances in autonomous vehicles promise to revolutionize the transportation system. This perspective has led to new research on a number of open questions, such as how the self-driving system should behave in unavoidable crash situations. Our study aims to contribute to this investigation. In most ongoing research, this question is presented as a moral dilemma, drawing on established research on the trolley dilemma. However, more recent studies have shifted the focus from morality to risk analysis. We investigated the dual contribution of moral judgment and risk analysis in subjects facing dangerous situations. To this end, we use virtual reality to recreate a driving situation that allows subjects to immerse themselves in the road environment. Our results show a strong dissociation between quick decisions, when risk analysis seems to suggest the best choice, and conscious decisions, when proper moral judgment is at stake
Evaluating mentalization during driving
No full textThe development of artificial intelligence promises important future changes from a social point of view. In particular, the emerging self-driving cars allow today to plan a future where traffic flow will greatly improve, and car accidents will be continuously decreasing. However, we should expect a period when full or partial autonomous vehicles and ordinary cars coexist, during which it would be essential to fully understand the cognitive processes used by ordinary people when driving. We identify as a crucial aspect the shift between quick and automated reactions, and the resort to mentalizing, costly social processes, sometimes necessary to predict intentions of other road users. In our experimental design we investigate the main precursors of mindreading, that is, eye contact and shared attention. We believe that a better understanding of this twofold mecahnisms involved in driving could be used to improve advanced driver assistance systems
Integrating human acceptable morality in autonomous vehicles
No full textOur study aims at progressing the assessment of the moral behaviour of human drivers. It is a felicitous coincidence that psychological and philosophical research into human morality has been dominated by thought experiments, resembling vehicles facing emergency situations. These thought experiments involve a running trolley, and have been used to contrast different moral principles, especially deontology versus utilitarianism. We designed an ecologically valid trolley-like dilemma with the help of virtual reality, aimed to understand the moral behavior of human subjects when facing a car accident situation. We report and comment on early results of our first tests
Moral dilemmas in self-driving cars
Get PDFAbstract: 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
Revising Conceptual Similarity by Neural Networks
Get PDFSimilarity is an excellent example of a domain-general source of information. Even when we do not have specific knowledge of a domain, we can use similarity as a default method to reason about it Similarity also plays a significant role in psychological accounts of problem solving, memory, prediction, and categorisation. However, despite the strong presence of similarity judgments in our reasoning, a general conceptual model of similarity has yet to be agreed upon. In this paper, we propose an alternative, unifying solution in this challenge in concept research based on the recent Eliasmith's theory of biological cognition. Specifically we introduce the Semantic Pointer Model of Similarity (SPMS) which describes concepts in terms of processes involving a recently postulated class of mental representations called semantic pointers. We discuss how such model is in accordance with the main guidelines of most traditional models known in literature, on the one hand, and gives a solution to most of the criticisms against these models, on the other. We also present some preliminary experimental evaluation in order to support our theory and verify whether similarities derived by human judgments can be compatible with the SPMS
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