Many current research trends point toward a technology of robot selfhood. The pursuit of selves for machines is motivated from a desire to equip robots with sophisticated human-like competences. Self and self-awareness constitute one of the cornerstones of consciousness, a whimsically peculiar aspect of our humanhood. While humans are the best "ground truth" we have in this respect, the best example to inspect and imitate, anthropomorphism is a procrustean path that shall be followed with care. Many attempts to create artificial selves are based on a shallow replication of biological behavioral traits; a true engineering technology of robot selves, however, must be based on a rigorous theory of consciousness, beyond humans.

A scientific, general theory of consciousness should be much more than just some “scientific progress towards understanding how consciousness can emerge form the activity of neurons and their interactions”. While the human brain is our best source of information about consciousness, the construction of a universal, general theory of consciousness is hampered by the almost absolute and excessive focus on the human brain, human cognition, and human neurophysiology. Human brains should not be the only systems we consider in work; a general theory should address at least the many other systems of interest: other kinds of animals, machines, and even social groups. In this talk I will address the emergence of a theoretical framework for Self Beyond Humans. This theoretical framework shall eventually lead to technological assets for robot selfhood to enable them to properly operate in ecological, medical, technical and economic terms in a variety of circumstances. A positive theory of self shall be centered on system functional architecture, sidetracking philosophical discussions on the nature of 'content and self' and leveraging the value of concrete topologies and measurements.

Future robots will have selves that may be enormously alien to humans; but, in a very precise sense, they will be quite similar to ours but with a deeper, purer essence, devoid of all that noise produced by biological evolution.

Get details at Reykjavik University website.

The chapter Ontology Engineering for the Autonomous Systems Domain, by Julita Bermejo–Alonso, Ricardo Sanz, Manuel Rodríguez and Carlos Hernández has been published in the book Knowledge Discovery, Knowledge Engineering and Knowledge Management.

Ontologies provide a common conceptualisation that can be shared by all stakeholders in an engineering development process. They provide a good means to analyse the domain, allowing to separate descriptive from problem–solving knowledge. Our research programme on autonomous systems considered an ontology as the adequate mechanism to conceptualise the autonomous systems domain, and the software engineering techniques applied to such systems. This paper describes the ontological engineering process of such an ontology: OASys (Ontology for Autonomous Systems). Its development considered different stages: the specification of the requirements to be fulfilled by the ontology; the extraction of the actual features needed to implement the desired requirements; the conceptualisation phase with the design decisions to integrate the different domains, theories and techniques addressed by the ontological elements; and finally, the implementation of the ontology, which integrates both ontology engineering and software engineering approaches by using UML as the implementation language.