Algorithms, Bias, and Fairness: Keynote and Film Screening of Coded Bias (2020)

TitleTimeRoomTeacher
Algorithms, Bias, and Fairness: Keynote and Film Screening of Coded Bias (2020)12.02.2025 15:00 - 18:00 (Wed)Campus Neuherberg, building 23, room 001 (Auditorium)Niki Kilbertus
Course Information
Course Mode: 
Offline/In Person
Language: 
English
Number of credit hours: 
3.00
Approval required: 
No
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Description
Description: 

We are excited to invite you to an engaging and thought-provoking event featuring a keynote address on Fairness in Machine Learning followed by a screening of the documentary Coded Bias (2020).

Keynote: Fairness in Machine Learning (3.00 - 4.30 pm)
How does machine learning impact social justice, equality, and discrimination? In this keynote, Niki Kilbertus will explore the role of machine learning in automated decision-making and its consequences in critical societal contexts. By diving into real-world scenarios, we will uncover how data-driven algorithms can perpetuate unfair outcomes—sometimes without individuals' knowledge or consent.
The talk will then broaden its perspective, reflecting on how machine learning can both sustain systemic inequalities and offer opportunities to combat discrimination. Ultimately, the keynote will address the importance of considering the entire life cycle of machine learning models to tackle societal challenges and promote fairness.

Film Screening: Coded Bias (2020) (4.30 - 6.00 pm)
Following the keynote, we will screen Coded Bias, a powerful documentary that explores how algorithmic biases in artificial intelligence systems affect real people and society at large. Directed by Shalini Kantayya, the film reveals the unintended consequences of machine learning and the need for ethical frameworks to govern its use.

Join us for an evening of critical insights, lively discussions, and an inspiring exploration of the intersection of technology and fairness. Don’t miss this opportunity to learn, reflect, and engage with one of the most important issues of our time.

Condition to Participate: 

Please mind the booking and unbooking periods. This event is open to external participants. 

Course Fee in Euros: 
€0.00
Target Group(s): 
Doctoral Researcher
Postdocs
Course Topic(s): 
Communication and Social Skills
Professional Skills
Organizing Institute/ Unit: 
Scientific Talent and Career Development (SPR)
Trainer Information
Trainer (Internal/External): 
Internal

Niki Kilbertus is an Assistant Professor for "Ethics in Systems Design and Machine Learning" at the Technical University of Munich and leads the Reliable Machine Learning group at Helmholtz Munich. His research focuses on causality, reliability, and the development of socially beneficial machine learning systems. Niki holds a PhD in Machine Learning from the University of Cambridge and the Max Planck Institute for Intelligent Systems. During his PhD, he gained hands-on experience through internships at Google, DeepMind, and Amazon, building on his strong foundation in mathematics and physics.

Capacity
1/-
Minimum Number of Participants: 
15

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