The course aims at introducing students to relevant emerging technologies for sustainability, providing a basic but in-depth conceptual understanding of Blockchain and decentralised ledgers, Machine Learning and Artificial Intelligence, Network Science with applications of IoT and 5G especially to Smart Cities and Territorial Networks, highlighting its potential applications in the social, economic and legal fields, with particular attention to the renewed sustainability challenges. Students are encouraged to apply theoretical notions in practical sessions in order to solve empirical problems through a hands-on approach with intuitive visual tools. They are also encouraged to envisage new projects involving these technologies and try to solve small real world cases of interest.

Knowledge and understanding: knowledge of the various emerging technologies and their social and legal impact. Understanding of the main paradigms of analysis and interpretation. Ability to apply knowledge: ability to analyze emerging technologies with the tools introduced and to extract synthetic knowledge to characterize their social impact. Autonomy of judgment: ability to extract 'objective' knowledge from the complexity of these technologies, as a well-founded basis to be actionable for real world projects. Communication skills: ability to present the results of the analysis both on the road graphics and public presentation in the form of short pitches. Learning skills: ability to know how to orient oneself independently and creatively in emerging technologies, to understand their structure and endless possibilities, and to extract their potential to transform our society. The only prerequisite is a genuine curiosity in understanding emergent technologies and to be passionate about learning the implications that these technologies have over society.

This course is intended to transmit sophisticated technological concepts and its implications for society in a straightforward, motivating and easy-to-understand way, avoiding at the same time unnecessary technicalities and extreme simplifications. We will explore blockchain and decentralised ledgers, machine learning and artificial intelligence, 5G and IoT, with a particular attention to the impact that all these technologies have in shaping the society we live in. At the end of the twelve weeks our students will be able to understand when emergent technologies are bringing a real added value to a specific project, and when instead they are inserted just for fashion or for “hype”, i.e. without a real need. First module The field of Machine Learning and Artificial Intelligence have a history dating back to the 1950s and in the first week of the course, after a brief historical introduction, all the basic concepts of the methodology will be introduced, which differs greatly from traditional algorithm design. In the following week the four main methodological categories will be explored: regression, classification, clustering and dimensionality reduction. Then we will explore a highly topical subject, Network Science, the currently most powerful paradigm for understanding the complex dynamics of interactions in social and economic phenomena. Networks are also a fundamental starting point to understand the shaping of Smart Cities supported by the IoT technologies. Subsequently we will lay down the theoretical foundations of Artificial Neural Networks that we will deepen in the next one talking about Deep Learning, the latest application frontier of AI in solving the most challenging problems, with performance similar to the capabilities of human thought. The last week will be dedicated to the discussion of various issues related to the impact of AI in our society, such as Explainable AI, AI Crime, ethical problems linked to these emerging technologies and finally to the creative possibilities of machines. Second Module After a brief introduction to the main concepts of programming, which will be useful throughout the course, the first six weeks of this module will be devoted to an in-depth exploration of the vast blockchain universe. Blockchain was officially invented in 2009 by Satoshi Nakamoto (which is just a nom de plume, as his/her/their real name has always been a mystery), but its origins date back to the 80’s and 90’s of the last century, when a group of people started to imagine how cryptography could allow exchange of information and creation of trust among individuals in a decentralised and private way. Blockchain is more than meets the eye, and cryptocurrencies are only the tip of the iceberg. Therefore, in order to fully understand the potential of blockchain in the first module we will delve into the concepts of competition and cooperation, of decentralisation and consensus, we will explore examples from society and from nature, to understand how players of a game can be incentivised to cooperate together for a common good without the need of a central authority. We will also learn what it means to mine a block, what is a smart contract, we will talk about Bitcoin, Ethereum and other cryptocurrencies, tokens and NFts, but always with the aim of understanding why blockchain can play a pivotal role in shaping the future of our society.

First module “On Intelligence” by Jeff Hawkins - Macmillan (book) “Superintelligence” by Nick Bostrom - Oxford (book) “Artificial Intelligence” by Alessandro Vitale - Egea (book in italian) “Computing Machinery and Intelligence” by Alan Turing - Mind (paper: https://www.csee.umbc.edu/courses/471/papers/turing.pdf, https://en.wikipedia.org/wiki/Computing_Machinery_and_Intelligence) Second module “Blockchain: Blueprint for a New Economy” by Melanie Swan (book) “The Tragedy of the Commons” by Garrett Hardin (paper) “The Evolution of Cooperation” by Robert Axelrod (book, optional)

On site lectures live exercises with students Case studies with the direct involvement of students Problem based learning Peer education

The student's knowledge will be assessed in two different ways: 1. One final project-oriented group assignment on a topic that will possible include elements of both modules and which will be proposed by the groups and have to be accepted by the teachers. 2. Two personal assignments in the form of written homework, in which the students will have to write a mini-paper for each of the two modules of the course on a specific topic assigned to each student by the teachers. The aim of the project-oriented group assignment is to give the students a way to test their capability in understanding the added value that emerging technologies can bring to a specific project. Ideally, the students should be able to point out why the projects they are working on for their assignment are only feasible with the aid of the proposed technology. The teachers will also value the capability of students to bring their own knowledge into the project, e.g., exploring the legal or the economic aspects deriving from the implementation of a given technology within the project. The project-oriented group assignment will count for 2/3 of the final grade. The aim of the personal assignment is to assess the capability of the student to explore in deeper detail a specific subject, starting from the knowledge received from the course. The form of a short mini-paper is chosen to stress the importance of expressing the concepts in a concise and understandable way (quality over quantity). The personal assignments will count for 1/3 of the final grade. Finally, at the end of each week there will be an exchange of views between the students and the teachers on the topics discussed during the week, in the form of a class debate. The students will be asked to elaborate a very short informal assignment in written or oral form, either before the class, or immediately before the debate. These oral or written elaborations will be shared with the class as a primer for the debate. These intermediate assignments and the following debate will not be evaluated, as they are intended as a moment in which students can learn together via trial and error, through direct confrontation with the class and sharing of ideas.

For the two personal assignments, the topics will be assigned by the teacher. For the group assignment, the groups will be randomly formed by the teachers and the subjects will be decided by the groups. The teacher can accept or modify the subject of the group depending on its relevance to the topics treated throughout the course.