Topics of interest include (but are not limited to) the following A Testing AI applications, include (1) Methodologies for testing, verification and validation of AI applications, (2) Techniques for testing AI applications, (3) Tools and environment for automated and semi automated software testing AI applications for various testing activities and management of testing resources, (4) Specific concerns of software testing with various specific types of AI technologies, such as machine learning and data mining, genetic algorithms, multi agent systems, automatic reasoning and theorem proving, etc (5) Specific concerns of software testing for various types of AI applications B Applications of AI techniques to software testing, include (1) Machine learning applications to software testing, such as test case generation, test effectiveness prediction and optimization, test adequacy improvement, test cost reduction, etc C Data quality checking for AI applications

Topics of interest include (but are not limited to) the following A Testing AI applications, include (1) Methodologies for testing, verification and validation of AI applications, (2) Techniques for testing AI applications, (3) Tools and environment for automated and semi automated software testing AI applications for various testing activities and management of testing resources, (4) Specific concerns of software testing with various specific types of AI technologies, such as machine learning and data mining, genetic algorithms, multi agent systems, automatic reasoning and theorem proving, etc (5) Specific concerns of software testing for various types of AI applications B Applications of AI techniques to software testing, include (1) Machine learning applications to software testing, such as test case generation, test effectiveness prediction and optimization, test adequacy improvement, test cost reduction, etc C Data quality checking for AI applications

Topics of interest include (but are not limited to) the following A Testing AI applications, include (1) Methodologies for testing, verification and validation of AI applications, (2) Techniques for testing AI applications, (3) Tools and environment for automated and semi automated software testing AI applications for various testing activities and management of testing resources, (4) Specific concerns of software testing with various specific types of AI technologies, such as machine learning and data mining, genetic algorithms, multi agent systems, automatic reasoning and theorem proving, etc (5) Specific concerns of software testing for various types of AI applications B Applications of AI techniques to software testing, include (1) Machine learning applications to software testing, such as test case generation, test effectiveness prediction and optimization, test adequacy improvement, test cost reduction, etc C Data quality checking for AI applications

This book constitutes the proceedings of the First International Conference on Bridging the Gap between AI and Reality, AISoLA 2023, which took place in Crete, Greece, in October 2023. The papers included in this book focus on the following topics: The nature of AI-based systems; ethical, economic and legal implications of AI-systems in practice; ways to make controlled use of AI via the various kinds of formal methods-based validation techniques; dedicated applications scenarios which may allow certain levels of assistance; and education in times of deep learning.