A practical approach for implementing sustainable, responsible and ethical AI - CANCELED
With growing regulations and societal expectations around responsible AI, developers are facing increasing demand to build AI solutions that are not only powerful but also sustainable, responsible, and ethical. Looking for practical tools and methodologies to integrate these values into your solutions? In this class, you'll discover how to identify and address issues in the data and classification pipeline while putting responsible AI ethics into practice.
Praktische info:
Inschrijven?
- Voorwaarden: A basic background in Data Science and Machine Learning. Experience with coding and basic knowledge of Python, scikit-learn, and Pandas. Bring you own computer.
- Prijs: €145
georganiseerd door:
Leertraject
Programme
09:30 Introduction to the problem
- Tour de table
- Introduction to a common decision support problem. The dataset is provided.
10:00 Challenge! Can you find the solution?
11:00 Can we find the solutions in the group?
- Guidance by tutor
- Different approaches of the students are discussed
12.00 Lunch break
13:00 Overview of common techniques to address sustainability, responsibility and ethics in AI
15:00 Exercises to put the theory in practice
16:30 Evaluation: did you reach the aimed-for result?
17:00 Wrap-up & further reading to keep learning
Key features
- Practical AI problem-solving: You’ll work on a simulated real-life challenge, allowing you to familiarise yourself with possible ethical issues in very common decision support systems.
- Hands-on experience: Tackle fairness issues in the dataset, identify biases, and explore the environmental impact of AI models.
- Legal & societal compliance: Prepare for stricter AI regulations by mastering fairness metrics, identifying proxy variables, and ensuring your models are interpretable and unbiased.
- Empowering exercises: Through interactive exercises, you’ll apply the concepts you’ve learned and explore how to create AI systems that are not just efficient but also transparent and responsible. Learning doesn't stop at the end of this workshop: you will leave with a reading list that encourages you to become even more proficient in these techniques.
Lesgever/spreker
Leticia Arco García
Leticia Arco received the B.Sc. and M.Sc. degrees in Computer Science from the Central University of Las Villas, Cuba, in 2001 and 2005, respectively. In 2009 she obtained the Ph.D. degree in Informatics from the Central University of Las Villas, Cuba, in collaboration with the Universities of Magdeburg and Oldenburg, Germany. From 2001 to 2018, she was a Researcher and an Assistant Professor at the Artificial Intelligence Lab, Computer Science Department, Central University of Las Villas, Cuba., and a guest researcher at the Hasselt University and Vrije Universiteit Brussel, Belgium. She is currently a Postdoctoral Researcher with the Artificial Intelligence Lab, Vrije Universiteit Brussel, Brussels, Belgium. She leads the research efforts in the AI applied team led by Prof. Loeckx. Her main research interests include conversational analysis, machine learning, data science, and responsible AI.
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