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Carolin Böke

Analytics Consultant · SAP

2 activities
Caroline CHOPINAUD

Caroline CHOPINAUD

Directrice Générale · HUB FRANCE IA

2 activities
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Caroline Stanford

Microsoft

2 activities
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Activities & events

Title & Speakers Event
Event EMPOWERMENT of WOMEN in TECH: 10th ANNIVERSARY of WOMEN in BIG DATA 2025-10-24
Panel: The Future of Tech 2025-10-24 · 19:30
Kendy Rannenberg – Manager Business Dev. CE @ Databricks
What is driving your daily business and WHY Women in Big Data Berlin? 2025-10-24 · 18:45
Carolin Böke – Analytics Consultant @ SAP , Amy Raygada – Data consultant; Founder @ Thoughtworks
Big Data
Event Building Better Software: A Journey through AI Ethics & Data Integrity in Design 2024-03-12
Navigating AI Ethics in Software Design 2024-03-12 · 18:00
Camila Lombana Diaz – AI ethics expert

Abstract: Given the potential for AI systems to cause harm when not properly designed and regulated, understanding AI ethics is crucial. It aids in identifying potential risks and developing strategies to mitigate them, thereby minimizing negative consequences such as biases, discrimination, and privacy violations associated with AI deployment.

So, what exactly is AI ethics at SAP? And how is this emerging field being operationalized? What should AI professionals understand about the ongoing discourse to empower individuals and organizations to anticipate and proactively address future challenges? This ensures that AI development and deployment aligns with societal values and norms.

AI/ML SAP
Data is emotional - The influence of bias hidden in our data 2024-03-12 · 18:00
Carolin Böke – Analytics Consultant @ SAP

Abstract: We rely on data for everything and assume that algorithms will give us the correct answer to everything. In this session, we will explore the concept of data bias and its impact on our understanding and perception of the world. Data bias refers to the hidden influences and prejudices that can be present in the data we collect and analyze. It can occur due to various factors, such as the way data is collected, the sample size, or the inherent biases of the people involved in the process. You will learn how data bias can affect our lives in various domains. By relying on biased data, we risk perpetuating unfair practices and reinforcing existing inequalities. When thinking about data it is crucial to recognize and address data bias to ensure fairness and accuracy in our analyses.
Showing 4 results