Artificial intelligence's new frontier: artificial companions and the fourth revolution

‘The definitive version is available at www3.interscience.wiley.com '. Copyright Metaphilosophy LLC and Blackwell Publishing Ltd.In this paper I argue that recent technological transformations in the life-cycle of information have brought about a fourth revolution, in the long process of reassessing humanity’s fundamental nature and role in the universe. We are not immobile, at the centre of the universe (Copernicus); we are not unnaturally distinct and different from the rest of the animal world (Darwin); and we are far from being entirely transparent to ourselves (Freud). We are now slowly accepting the idea that we might be informational organisms among many agents (Turing), inforgs not so dramatically different from clever, engineered artefacts, but sharing with them a global environment that is ultimately made of information, the infosphere. This new conceptual revolution is humbling, but also exciting. For in view of this important evolution in our self-understanding, and given the sort of IT-mediated interactions that humans will increasingly enjoy with their environment and a variety of other agents, whether natural or synthetic, we have the unique opportunity of developing a new ecological approach to the whole of reality.Peer reviewe

Scepticism, Animal Rationality and the Fortune of Chrysippus' Dog

Peer reviewe

Perception and Testimony as Data Providers

Assuming that the sceptical challenge might be either bypassed or answered, this still leaves unspecified how high-quality information about the external world is acquired. In this paper, I will argue that, if knowledge is accounted information, then when we apply this definition to the analysis of perceptual knowledge and knowledge by testimony (the only two sources of information about the external world), the result is that both qualify as data providers.Peer reviewe

Is Information Meaningful Data?

There is no consensus yet on the definition of semantic information. This paper contributes to the current debate by criticising and revising the Standard Definition of semantic Information (SDI) as meaningful data, in favour of the Dretske-Grice approach: meaningful and well-formed data constitute semantic information only if they also qualify as contingently truthful. After a brief introduction, SDI is criticised for providing necessary but insufficient conditions for the definition of semantic information. SDI is incorrect because truth-values do not supervene on semantic information, and misinformation (that is, false semantic information) is not a type of semantic information, but pseudo-information, that is not semantic information at all. This is shown by arguing that none of the reasons for interpreting misinformation as a type of semantic information is convincing, whilst there are compelling reasons to treat it as pseudo-information. As a consequence, SDI is revised to include a necessary truth-condition. The last section summarises the main results of the paper and indicates some interesting areas of application of the revised definition

Information ethics: an environmental approach to the digital divide

Peer reviewe

Outline of a Theory of Strongly Semantic Information

Peer reviewe

A Praxical Solution of the Symbol Grounding Problem

Peer reviewe

Recommender systems and their ethical challenges

This article presents the first, systematic analysis of the ethical challenges posed by recommender systems through a literature review. The article identifies six areas of concern, and maps them onto a proposed taxonomy of different kinds of ethical impact. The analysis uncovers a gap in the literature: currently user-centred approaches do not consider the interests of a variety of other stakeholders—as opposed to just the receivers of a recommendation—in assessing the ethical impacts of a recommender system

Transparent, explainable, and accountable AI for robotics

To create fair and accountable AI and robotics, we need precise regulation and better methods to certify, explain, and audit inscrutable systems