COURSE DESCRIPTION
In this course, participants are introduced to key notions and concepts evolving in sustainability science that are relevant to all, independent to one's work or field of interest. After having completed the course, participants will have a better understanding of the vocabulary used today and should demonstrate the ability to reflect critically to integrate different perspectives of environmental, social, and economic sustainability to their specific area of interest or research.
Throughout the course, links are made to the Agenda 2030 for Sustainable Development, as our current global road map towards sustainability, and how new approaches and solutions are emerging to describe, understand and address key sustainability challenges. Put simply, the overall aim is to give participants the knowledge and confidence needed to present and discuss ideas with others by applying methods, concepts and the vocabulary exemplified in the course with a more holistic view on the sustainability agenda across topics and disciplines.
The course is designed as 5 modules:
The first module presents essential concepts within sustainability science, and methods used to describe, frame, and communicate aspects of sustainability. We look at key questions such as what we mean with strong or weak sustainability, resilience, tipping points and the notion of planetary boundaries. We also look at some techniques used of envisioning alternative futures and transitions pathways.
The second module is all about systems thinking and how systemic approaches are applied today to achieve long-term sustainability goals. Your will see what we mean with systems thinking and how systems thinking, and design is applied in practice to find new solutions.
The third module touches upon drivers for a sustainable future, namely links to economy and business with an introduction to notions of a circular economy, and also policy and regulatory frameworks. We introduce the basics of transformative policy frames and how they are designed and applied through several real-case examples.
The fourth module discusses the links between innovation and sustainability, highlighting approaches for technological, social, institutional, and financial innovations. Some examples (or cases) aim to show how different actors across society balance in practice the need for innovative approaches for social, environmental, and economic sustainability.
The fifth and last module provides general insights on how we work with models to create various scenarios that help us identify solutions and pathways for a more sustainable world. Three main dimensions are addressed namely climate and climate change, nature and biodiversity, and the importance of data and geodata science to support spatial planning and sustainable land use.
The aim of this course is to give students insight about certification and about what it means to certify/self-assess safety- critical systems with focus on software system and to create a safety case, including a multi-concern perspective when needed and reuse opportunities, when appropriate.
Do you want to be efficient, effective and minimize waste by learning and implementing lean production tools? This course provides insight into the demands and challenges posed by competitive production in industrial production systems and develops your ability to participate in and to drive improvement work. The course focuses on efficient lean production. Through theory and project work, you will learn useful techniques, methods and strategies. You will obtain the necessary knowledge and training to carry out value stream mapping and other forms of improvement work. The course offers current and competitive knowledge through its close links with our successful research and partner companies. It provides basic knowledge and understanding of the modern view of lean production in industrial activity.
Answer Set Programming (ASP) is a declarative programming paradigm designed within the field of Artificial Intelligence (AI), and used to solve complex search-problems. The declarative nature of ASP allows one to encode a problem by means of logic. In this way, unlike in imperative programming approaches, there is no need to design an algorithm as a solution for the given problem. In this sense, ASP is comparable with SAT-based encoding or constraint satisfaction problems. However, due to its stable-model semantics, ASP provides a richer representation language useful to handle uncertain situations more effectively for real world scenarios. The advantages of declarative programming together with non-monotonic nature of ASP in handling uncertainties have recently made ASP more attractive both for academia and industry. This course focuses on formalizing and solving various search problems in planning, scheduling and system configuration in ASP.
ROS (Robot Operating System) is a common set of tools used in academia to do research within autonomous systems. It shortly provides a middleware for handling communication, as well as interfacing sensors and actuators, visualization, simulation and datalogging and infrastructure where it is easy to share your own methods and algorithms. The latter has allowed a large set of different of state-of-the-art research approaches to be readily available for downloading. Due to its popularity it is also getting more widespread in the industrial community, especially in R&D. This course will give you hands-on experience how to utilize these tools and apply them to a problem of your choice.
As AI systems become more common and expand their abilities, the decisions they made have a crucial impact on society as a whole. Whether they are designed to recommend content or product online, to assist judges or physicians in their decision-making, or to decide how to distribute mortgages or video surveillance cameras, these systems can have a crucial and lasting impact on all of us. For this reason, it is of paramount importance that those in charge of designing such systems work toward ethical and responsible systems. This course covers the theoretical and practical aspects of normative ethics and how they apply to AI systems, discuss how AI systems can become biased, as well as how to prevent and correct possible bias. Through concrete examples, case studies, and project, this course aims at raising awareness on the problem of ethical AI as well as giving the students practical experience on how to ensure ethical and responsible development of AI systems in their everyday work. This course is given on-line with three mandatory Zoom-meetings. This course is directed towards working professionals.
The course is part of the programme MAISTR (hh.se/maistr) where participants can take the entire programme or individual courses. The course is for professionals and is held online in English. Application is open as long as there is a possibility of admission. The courses qualify for credits and are free of charge for participants who are citizens of any EU or EEA country, or Switzerland, or are permanent residents in Sweden. More information can be found at antagning.se. About the course Critical design and practical ethics for AI, 3 credits Who is this course for? Artificial Intelligence (AI) is being increasingly implemented and used in society today. It has already proven to have an impact on the individual, organization and society, and this impact will most likely only increase. Therefore, it is important to understand the ethical issues that may arise from use of AI, as well as to adopt a critical stance to the technology’s impact. The course introduces critical and ethical issues surrounding data and society, to train the student to problematize and reason about artificial intelligence (AI). You are most likely a designer, innovator, or product manager that works with digital services and products. What will you learn from this course? The course deals with different perspectives on AI and its real and potential effect on organizations and society. The course is based on five different perspectives on AI: accountability, surveillance capitalism, power and bias, sustainability, and trust. The course material consists of recent and relevant literature on the impact of, and critical perspectives on AI. Active discussions founded in different ethical perspectives are also an important part of the course. What is the format of this course? This course is primarily self-paced, with a few synchronous meetings. Most activities are based on the student’s having consumed specified material beforehand, such as video lectures, podcasts, articles, and books. Active discussions, both in online forums and during synchronous meetings, are an important part of the course.