Data Ethics – Navigating the Ethical Landscape of Emerging Technologies

Course title:

DATA ETHICS
NAVIGATING THE ETHICAL LANDSCAPE OF EMERGING TECHNOLOGIES

Interactive Online Course and Book 

Learn at your own pace: Our self-paced online course and interactive book provide a comprehensive introduction to data ethics.
Engage with real-world examples: Explore case studies and practical scenarios to understand how data ethics applies in various contexts.
Test your knowledge: Interactive quizzes and exercises help reinforce your learning.
COURSE DESCRIPTION:

Deep tech refers to technologies that are based on cutting-edge scientific principles and have the potential to revolutionize various aspects of our lives. However, the development and deployment of these technologies raise a host of ethical concerns, such as fairness, bias, privacy, and accountability. This course will provide a comprehensive overview of the ethical issues surrounding deep tech, empowering students to make informed decisions about the development and use of these powerful technologies.

In addition, most deep tech innovation is inspired by different science fiction books and movies, and the ethical concerns and philosophy of the authors of these works. In this perspective the ideas and visions of Isaac Asimov, Arthur C. Clarke, George Orwell, Aldous Huxley and many more are integrated in the course content and work as a framework for the course. This in order to give support for learning about the EU AI Act and the Asilomar AI Principles.

As deep tech innovations continue to transform our world, it is crucial to consider the ethical implications of these technologies. This course will provide a comprehensive overview of the ethical considerations surrounding deep tech, including topics such as algorithmic bias, privacy, artificial intelligence and autonomy, and the responsible development and deployment of deep tech. Furthermore, how all this impacts society and people at an individual level.

TARGET AUDIENCE:
This course is designed for anyone interested in learning about the ethical implications of deep tech, with special focus on deep tech students, professionals within deeptech, as well as policymakers. Basic knowledge of deep tech is required, but no prior knowledge of ethics is required.

COURSE OBJECTIVES:
By the end of this course, students will be able to:

• Define deep tech and explain its potential impact on society
• Identify key ethical issues surrounding deep tech, such as fairness, bias, privacy, and accountability
• Analyze real-world examples of how deep tech has been used ethically and unethically
• Develop a framework for making ethical decisions about the development and use of deep tech
• Advocate for responsible and ethical development of deep tech
• Understand the fundamental concepts of deep tech and its impact on society
• Identify and analyze the ethical challenges posed by deep tech
• Apply ethical principles to real-world case studies of deep tech applications

COURSE STRUCTURE:
The course will consist of six lessons, each covering a specific topic related to deep tech and ethics. Each module will include a mix of readings in an interactive book with interactive case studies and hands-on exercises. It will also include literature, advanced scenario-based learning and lectures.

Assessment: Quiz tests and assignments,

Final project: Develop a plan for the ethical development and deployment of a deep tech application, a plan that to a large extent can be developed during the course.

 

Added 10/02/2025:

1. Develop knowledge and understanding of at least one field of science, engineering, and/or computer science, with an emphasis on learning about deep tech innovations in the field(s) and their application to complex real-world challenges.

Data ethics is a field with ties to many academic disciplines. Here are a few of the most prominent:

Computer Science and Information Science: These fields are central to data ethics because they deal with the technical aspects of data collection, storage, processing, and analysis. Understanding algorithms, databases, and data security is crucial for evaluating the ethical implications of data use. All this constitutes the core of what the student learns in the course, both in theory and practice.

Philosophy: Philosophy provides the theoretical frameworks for understanding ethical concepts like privacy, fairness, accountability, and responsibility. It helps in examining the moral implications of data practices and developing ethical guidelines. To learn what these terms mean within the field of data ethics in theory and practice is one of the main pillars of the course. And how these are implemented in different forms of established frameworks like the Asilomar AI Principles.

Social Sciences (Sociology, Anthropology, Psychology): These disciplines help understand how data practices impact individuals, groups, and societies. They provide insights into how data can influence behavior, perpetuate biases, and affect social structures. In the course the student learns about the impact and practices in real world scenarios.

Law: Legal frameworks are essential for regulating data use and protecting individual rights. Data ethics intersects with legal fields like privacy law, intellectual property law, and human rights law. In the course the focus is especially directed on the EU AI Act and EU GDPR.

Business and Economics: Data is increasingly valuable in the business world. Data ethics is relevant to understanding responsible data use in marketing, advertising, and decision-making. The course explores the ethical considerations in developing and using deep tech, focusing on real-world challenges and the ethical frameworks for decision-making, through interactive case studies and hands-on exercises.

This is not an exhaustive list, as data ethics has implications for virtually every field that generates or uses data. As data becomes more central to our lives, the importance of data ethics across all disciplines will only continue to grow.

2. Develop entrepreneurial skills and competences, exploring the processes by which scientific and engineering deep tech solutions can be commercialised, and understanding relevant concepts such as intellectual property, market dynamics and funding mechanisms.

Although the course doesn’t explicitly focus on commercialization, it indirectly contributes to developing entrepreneurial skills by teaching students how to navigate the ethical landscape of deep tech. This includes understanding the impact of data ethics when it comes to market dynamics during development, launch and maintaining the deep tech product or service. Here the main focus is directed on the entrepreneur’s and other stakeholders decision-making when it comes to ethical considerations. All these are crucial aspects of commercializing deep tech solutions.

3. Encourage an interdisciplinary approach, exploring how different fields intersect and how experts in different academic and business domains collaborate to create innovative solutions.

The course encourages interdisciplinary thinking that highlights the connection between humanities and deep tech innovation. It also emphasizes the importance of considering societal and individual impacts, promoting a broader perspective. Where these basic visions then are put into practice in simulations and other interactive exercises. With the purpose of improving entrepreneurial skills by e.g. practicing decision-making that balances business and ethical concerns in working life scenarios.

4. Incorporate challenge-based and creative learning, in which learners apply domain knowledge and skills to real-world problems, with the aim of designing and developing novel solutions.

The inclusion of interactive case studies, hands-on exercises, and a final project where students develop a plan for ethical deep tech deployment fosters challenge-based and creative learning. This encourages students to apply their knowledge to real-world scenarios and design innovative solutions.

5. Include a focus on skills relevant for working in deep tech (e.g. research skills, team-working, networking, digital skills, critical thinking, etc.).

The course promotes essential skills for deep tech careers. Research skills developed through readings and analysis and critical thinking is central to ethical decision-making. Additionally, the focus on communication and advocacy skills prepares students for leadership roles in the field.

6. Promote reflection on the nature of deep tech: how it is defined and understood, its ethical implications and societal impact (e.g. addressing issues such as privacy, security, and environment).

The course explicitly addresses the ethical implications and societal impact of deep tech. It dedicates lessons to privacy, AI ethics, and responsible development, encouraging students to reflect on the broader consequences of technological advancements.