The importance of educating the next generations in the understanding of the fundamentals of the upcoming scientific and technological innovations that will force a broad social and economical paradigm change can not be overstressed. One such breakthrough technologies is Artificial Intelligence (AI), specifically machine learning algorithms. Nowadays, the public has little understanding of the workings and implications of AI techniques that are already entering their lives in many ways. We aim to achieve widespread public understanding of these issues in an experiential learning framework. Following a design based research approach, we propose to implement program coding scaffoldings to teach and experiment some basic mechanisms of AI systems. Such experiments would be shedding new light into AI potentials and limitations. In this paper we focus on innovative ways to introduce high school students to the fundamentals and operation of two of the most popular AI algorithms. We describe the elements of a workshop where we provide an academic use-create-modify scaffolding where students work on the Scratch partial coding of the algorithms so they can explore the behavior of the algorithm, gaining understanding of the underlying computational thinking of AI processes. The extent of the impact on the students of this experience is measured through questionnaires filled before and after participation in the workshop. Preliminary experiments offer encouraging results, showing that the workshop has differential impact on the way students understand AI.

The integration of Artificial Intelligence (AI) tools and techniques has provided a significant advance in drone technology. Besides the military applications, drones are being increasingly used for logistics and cargo transportation, agriculture, construction, security and surveillance, exploration, and mobile wireless communication. The synergy between drones and AI has led to notable progress in the autonomy of drones, which have become capable of completing complex missions without direct human supervision. This study of the state of the art examines the impact of AI on improving drone autonomous behavior, covering from automation to complex real-time decision making. The paper provides detailed examples of the latest developments and applications. Ethical and regulatory challenges are also considered for the future evolution of this field of research, because drones with AI have the potential to greatly change our socioeconomic landscape.