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Baukasten:Algorithmic Bias – Life with Artificial Intelligence – digital

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Algorithmic Bias – Life with Artificial Intelligence – digital

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Through this building block participants develop sensitivity towards using and living with artificial intelligence (AI). They get the ability to reflect on daily AI usage as well as develop an awareness regarding the challenges and problems we are facing when using AI systems.

Participants understand the different use cases of artificial intelligence in their daily life, which can be unexpected in some cases. Also they get a brief idea of how artificial intelligence systems work and that they are able to fail. This building block gives different examples of AI being subjective and discriminating. AI very much depends on the people setting it up as well as the training data provided and so it remains biased in many cases. In the follow-up tasks examples are given to handle the difficulties programming AI.

The building block includes a theoretical part for preparation, to ensure that participants have a basic understanding of artificial intelligence. After that, participants will discuss the consequences and problems of AI usage. Finally, they will brainstorm ideas on how these problems can be prevented and how society and individuals should deal with them.

Title
Algorithmic Bias – Life with Artificial Intelligence – digital
Topic
Thinking about the impact especially biases in AI systems have on humanity such as the impact humanity has on AI systems.
Type
Digital
Keywords
AI systems, bias, training datasets, high tech
Competences
perspective-taking, anticipation, gaining interdisciplinary knowledge, dealing with incompleteness and overcomplexity, motivation, reflecting principles, acting independently
Forms of Learning
cooperative, fact-oriented
Methods
experiencing unexpected situations (Google/ Bing search), evaluate different use cases, group discussion, reflecting group discussion, personal reflection
Group Size
>2
Duration
30 minutes
Material and Space
E-learning unit based on information material and videos about algorithmic bias
Quality
good - building block developed by participants in Berlin
Semester
Winter Semester 2020/21