August 8, 2024

From Theory to Practice: How to Address Algorithmic Bias

Experience algorithmic bias firsthand: A unique, immersive learning workshop. This workshop is limited to 35 participants. Click the register button below to join the waitlist.

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AI bias arises from human decisions and the data used to train algorithms. This data, reflecting human biases and subjective views, is not neutral. As a result, AI can inherit these biases.

For instance, facial recognition software trained mostly on white faces performs better on white faces. Similarly, the Amazon hiring algorithm perpetuated gender biases due to biased training data. Even efforts to eliminate explicit bias can fail because proxy variables may still result in discriminatory outcomes.

While achieving completely bias-free AI may be unrealistic, we can focus on identifying and addressing known biases and remaining vigilant about hidden ones. This is where Alix Rübsaam expansive and immersive AI Bias workshopplays a crucial role.

In this workshop, participants will:

  • Identify and Analyze Bias: Learn how design decisions impact algorithm outcomes and understand mechanisms leading to unintended AI outcomes.
  • Simulation Experience: Make decisions about training and designing algorithms in a real-world technology simulation.
  • Advocate for Responsible AI: Build more socially responsible algorithms and identify ways to create responsible AI
  • Familiarization: Gain experience with the design, implementation, and use of automated decision-making algorithms and Machine Learning systems.
  • With over 1,500 participants from diverse backgrounds and 40+ countries, Alix and Ty Henkaline’s AI Bias Workshop emphasized the impact of who is at the table in shaping AI outcomes.

    About the facilitator

    Alix Rübsaam

    Alix Rübsaam is a visionary in the field of AI and bias mitigation. With a background in creating immersive learning experiences, she co-created the AI Bias Workshop with Ty Henkaline. Her dedication to developing inclusive technology and educating others on the implications of bias in algorithms has made a significant impact in the industry. Currently, she's the VP of Research, Expertise & Knowledge at Singularity University.

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