HU Berlin Lecture Series on AI: David Stillwell (Cambridge)
IZBF Lecture Series 2020 "Machine Learning / Intelligent Data Analysis"
Dr. David Stillwell, Lecturer in Big Data Analytics and Quantitative
Social Science, Academic Director - The Psychometrics Centre, Cambridge
University Judge Business School
Abstract: Many researchers, including myself (e.g. Kosinski, Graepel
& Stillwell, 2013), have published papers showing that
psychological traits like personality and intelligence can be
predicted from the digital footprints people leave behind when they
use online services like social media. Should this capability be
used in practice, and if so under what conditions? The Facebook
Cambridge Analytica scandal clearly demonstrates that the public is
uneasy when they feel their data was misused, but on the other hand the
public also likes their data to be used to personalise recommendations
and services. This session will introduce the big data
psychometrics technology and will then encourage debate on its
application by organisations.
NEXT:
Fri, 20 March 2020, 16.00 – 17.30 Uhr
"Combining Mobile Sensing and Machine Learning for Psychological
Assessment"
Dr. Clemens Stachl, Media and Personality Lab, Stanford University
*Venue* Humboldt-Universitaet zu Berlin, Unter den Linden 6, 10117 Berlin,
Senatssaal (1st floor)
*Abstract* The increasing digitization of our society radically
changes how scientific studies are being conducted in the field.
In the social sciences, the analysis of online repositories,
digital footprint data, and data from in-vivo high-frequency mobile
sensing now allows for the investigation of formerly intangible
psychological constructs. In contrast to past possibilities these methods
enable fine-grained, longitudinal data collections in the wild, at large
scale. The combination with state of the art machine learning
methods, provides a perspective for the direct prediction of
psychological traits and behavioral outcomes from these data. In my talk I
will give an overview on latest studies combining machine learning with
mobile sensing. In particular, I will highlight findings with regard
to psychological assessment and discuss the limitations of current
approaches. Consequently, I will introduce some of my own work and provide
an outlook perspective on where these developments could take the field.
Mon, 26 October 2020, 16.00 – 17.30 Uhr
„Lehrende, Lernende und Künstliche Intelligenz: Wie kann eine fruchtbare
Interaktion im Klassenraum von morgen aussehen?“ (Teachers, students and
artificial intelligence: What can a fruitful interaction in the classroom
of tomorrow look like?)
Prof. Dr. Nikol Rummel, Pädagogische Psychologie, Institut für
Erziehungswissenschaft, Ruhr-Universität Bochum
*Venue* Humboldt-Universitaet zu Berlin, Unter den Linden 6, 10117 Berlin,
Senatssaal (1st floor)
Organizers:
The Interdisciplinary Center for Educational Research (IZBF),
Humboldt-Universitaet zu Berlin, regularly invites renowned experts to
present theories, methods and findings from the field of educational
research. The lectures are open to the public and are aimed equally at
science, educational policy and educational practice. Machine Learning
(ML), Data Science and Artificial Intelligence (AI) are no longer future
topics. Artificial intelligence and data science are considered to be
central trends and currently important topics that are also increasingly
finding applications in educational contexts.
