Cognitive Science

The scientific and technological upheavals of the 20th Century and the questions and difficulties that went along with them (climate change, nuclear energy, GMO, etc.) have increased the necessity of thinking about and formalizing technoscientific progress and its consequences. Expert evaluations and ethics committees today cannot be the only legitimate sources for understanding the social acceptability and desirability of this progress. Responsibility must be shared out on a wider scale, as much in society as in the process of research and innovation projects. This book presents the main works of Responsible Research and Innovation (RRI) from a moral responsibility point of view, for which it calls upon no fewer than 10 understandings to bring out those which are positive and to support an interpretive and combinatory pluralism. In this sense, it demonstrates moral innovation. It analyzes numerous cases and proposes perspectives that are rarely discussed in this emerging field (current practices of ethical evaluation, concerns of the integrity of research, means for participatory technological evaluation, etc.). It contributes to the pledges of RRI, which largely remains theoretically undetermined even though it reorganizes the relationships between science, innovation and society.

Natural Language Processing (NLP) is a scientific discipline which is found at the intersection of fields such as Artificial Intelligence, Linguistics, and Cognitive Psychology. This book presents in four chapters the state of the art and fundamental concepts of key NLP areas. Are presented in the first chapter the fundamental concepts in lexical semantics, lexical databases, knowledge representation paradigms, and ontologies. The second chapter is about combinatorial and formal semantics. Discourse and text representation as well as automatic discourse segmentation and interpretation, and anaphora resolution are the subject of the third chapter. Finally, in the fourth chapter, I will cover some aspects of large scale applications of NLP such as software architecture and their relations to cognitive models of NLP as well as the evaluation paradigms of NLP software. Furthermore, I will present in this chapter the main NLP applications such as Machine Translation (MT), Information Retrieval (IR), as well as Big Data and Information Extraction such as event extraction, sentiment analysis and opinion mining.