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Member rate £492.50
Non-Member rate £985.00
Save £45 Loyalty discount applied automatically*
Save 5% on each additional course booked
*If you attended our Methods School in July/August 2023 or February 2024.
Date: Monday 29 July – Friday 2 August 2024
Time: 10:00 – 13:00 CEST
elizaveta.kuznetsova@weizenbaum-institut.de
Weizenbaum Institute for the Networked Society
Experience an interactive online learning environment with this immersive course that harnesses state-of-the-art pedagogical tools. This course is tailored for a demanding audience of researchers, professional analysts, and advanced students, and is limited to a maximum of 20 participants to ensure that our instructors can focus on the specific needs of each individual.
With the rise of generative AI researchers need new methods to study social phenomena on emerging digital platforms. Algorithm audit is a methodology that can help understand biases generated or perpetuated by algorithms. Potential case applications include studies of gender bias or distribution of misinformation.
This course introduces you to social science driven auditing of generative AI with a focus on practical application. It covers a range of topics, including different approaches to auditing generative AI, from manual to automated data collection, data wrangling and descriptive statistics, quantitative and qualitative content analysis with a particular focus on code book design. While statistical evaluations will be discussed, the course places less emphasis on statistical analysis.
The course offers ample space for developing your own projects and experimenting with the research design. Given that generative AI is a new technology, methods require continuous adjustment adjusted to the evolving applications. Our emphasis will be precisely on that aspect.
Elizaveta Kuznetsova leads a Research Group on ‘Platform Algorithms and Digital Propaganda’ at the Weizenbaum Institute in Berlin.
Her research lies at the intersection of political and communication science. Her primary focus is on algorithms, digital propaganda, international media, and generative AI. Elizaveta has a particular affinity for mixed methods research.
She holds a PhD in International Politics from City, University of London and is former fellow at the Davis Center, Harvard University and at the Center for the European Studies at Boston University. She also occasionally engages in journalism work.
An overview of the methodology and potential applications for specific research questions. Starting with a brief outline of the concepts and literature, we will discuss potential case studies that might be relevant for your research.
During this session, you will be introduced to the most important step – designing an audit specific to research questions. We will focus on formulating research queries and prompts.
We will focus on various methods of collecting data, from front end manual collection to using an API.
In this session, we will introduce qualitative analysis of the collected data, designing a code book, and performing intercoder reliability tests.
You will merge coded data with the original database and generate descriptive plots. We will also discuss possible options for further statistical tests.
The course consists of asynchronous pre-class activities like assigned readings and pre-recorded videos. The participants will meet daily for 3-hour live Zoom sessions to discuss the theory and the application of the method. The course will incorporate individual projects, short individual presentations, group work, and discussions. These learning activities use various online applications that facilitate collaboration and interaction with the course material.
The instructor will also conduct live Q&A sessions and offer designated office hours for one-to-one consultations.
Prior experience in mixed method research as well as a solid understanding of social science research methods and designs is recommended for this course. Familiarity with Python, content analysis, discourse analysis, and basic statistics are desirable but not essential. A genuine enthusiasm for discovering innovative methods and exploring diverse approaches while maintaining a spirit of fun and out-of-the-box thinking is essential.
As a participant in this course, you will engage in a variety of learning activities designed to deepen your understanding and mastery of the subject matter. While the cornerstone of your learning experience will be the daily live teaching sessions, which total three hours each day across the five days of the course, your learning commitment extends beyond these sessions.
Upon payment and registration for the course, you will gain access to our Learning Management System (LMS) approximately two weeks before the course start date. Here, you will have access to course materials such as pre-course readings. The time commitment required to familiarise yourself with the content and complete any pre-course tasks is estimated to be approximately 20 hours per week leading up to the start date.
During the course week, you are expected to dedicate approximately two-three hours per day to prepare and work on assignments.
Each course offers the opportunity to be awarded three ECTS credits. Should you wish to earn a 4th credit, you will need to complete a post-course assignment, which will involve approximately 25 hours of work.
This comprehensive approach ensures that you not only attend the live sessions but also engage deeply with the course material, participate actively, and complete assessments to solidify your learning.
This course description may be subject to subsequent adaptations (e.g. taking into account new developments in the field, participant demands, group size, etc.). Registered participants will be informed at the time of change.
By registering for this course, you confirm that you possess the knowledge required to follow it. The instructor will not teach these prerequisite items. If in doubt, please contact us before registering.