F1TG 4500 - Technology for Global Challenges

From stone tools to generative AI via the printing press and the steam engine, technology is part and parcel of human development. The current Fourth Wave’ of the Industrial Revolution provides opportunities to tackle some of the most pressing global challenges facing both “Global North” and, especially so, “Global South” regions, including those reflected in the 17 SDGs such as environmental degradation, poverty and hunger, gender equality, migration, conflict and crime, and peace and justice. However, there are legitimate concerns these technologies and ‘techno-solutionism’ may hold back or reverse progress.

Building on a large body of research and practice, this seminar takes stock of how technology acts both as an effect and enabler of scientific advances and social change; it questions the ‘neutrality’ of technology according to which its effects can be positive or negative; it presents concrete examples of how data analytics and AI can foster or hinder the SDGs and inclusion; it unpacks key conditions and requirements, including related to data privacy, governance and literacy, for leveraging technology for public policy and social good.

The course relies on a combination of lectures, case-study presentations, experts’ interventions, hands-on technical tutorials, and group discussions and projects.

Learning Outcomes

• Understand and explain the meaning and implications of key concepts relevant to the course’s topic such as technological regime and change, data, data governance, data literacy, statistics, machine-learning, Artificial Intelligence (AI), generative AI, responsible and ethical AI, dis-misinformation, the SDGs, climate change, gender equality, data feminism, intersectionality…
• Understand the key opportunities, limitations, challenges, risks and requirements of using ‘new’ digital data and technologies, algorithmic decision-making support systems, machine-learning, AI, notably, for addressing global challenges;
• Design and apply concepts and tools to develop an end-to-end data-driven project to shed light on and attempt to address a social problem including through the development and communication of policy recommendations.

Professional Skills

• Critical and complex thinking: Acquire and be able to continuously develop an informed and critical understanding of the historical role of technology in social change using different social science and analytics approaches;
• Research and analysis: Undertake and synthesize research on a specific topic using different data sources including quantitative and qualitative data as well as relevant academic and ‘grey’ literature;
• Reflexivity, humility and drive: Develop the willingness and ability to leverage conceptual and analytical skills and tools and the desire to learn in a professional environment to achieve positive impact;
• Communication: Be able to convey complex hypotheses, ideas, conclusions and recommendations in clear and compelling terms, both orally and in writing;
• Team work and ethics: Be able to work on a diverse team of people on a complex problem and achieve a shared goal by leveraging individual comparative advantages and collective intelligence.

None, but interest in technology and basic statistics, econometrics and / or math skills.

The class is aimed to be participatory, interactive and versatile, relying on a combination of lectures, students’ presentations, group discussions, guest lectures and hands-on technical tutorials using real world quantitative data.

Students will be provided with or guided towards material, including readings, recording, videos and podcasts that they are expected to familiarize themselves with on their own before and between classes. Class time will be used primarily for framing presentations, group discussions, instructor-led debates guest interventions, and technical tutorials.

Each class will start with a short quiz based on the required readings and past lectures, followed by a framing presentation of the general theme or topic of the class. The rest of the class will be structured around short students’ presentations, guest lectures, group discussions and hands-on exercises including an instructor-led technical tutorial.

Feedback on quizzes and all assignments will be provided collectively and individually by the end of the semester and general feedback is provided orally on a weekly basis (individually or collectively) on methodological, theoretical, and empirical issues.

• In-class 5mn written multiple choice quizzes based on the readings; every class; worth 10% of the grade
• Individual take-home problem set handed on during class 4, due on class 8; worth 20% of the grade
• Group project with a 15mn presentation during the last class; worth 30% of the grade
• One 1.5-hour final examination; worth 30% of the grade (outside of class)
• Attendance and participation; 10% of the grade

• Attendance: 24 hours a semester / 4 hours a week for 6 weeks
• Online learning activities: 1 hour a week / 12 hours a semester
• Reading and Preparation for Class: 4 hours a week / 48 hours a semester
• Research and Preparation for Group Work: 2 hours a week / about 24 hours a semester
• Research and Writing for Individual Assessments: 3 hours a week / 36 hours a semester
• Other: Office hours as relevant