Are Algorithms Biased by Design?

The video discusses the process of determining trending topics on Facebook, highlighting the three-layer system involving algorithms and human decision-making. It addresses concerns about bias, particularly regarding conservative news, and emphasizes the role of human influence in algorithm design. The discussion extends to media bias and its impact on algorithms, with a focus on data selection and inherent biases. The video concludes by questioning the possibility of creating non-biased algorithms.

What is the role of the algorithmic personalized ranking in trending topics?

• To detect potential trending topics

• To manually select trending topics

• To remove irrelevant topics

• To create new topics for users

How does the algorithmic ranking process address potential bias against conservative news?

• By applying a conservative penalty

• By ensuring a mix of different types of news

• By excluding conservative news

• By prioritizing entertainment news

What is a common misconception about algorithms according to the transcript?

• They are always biased

• They can solve all problems magically

• They require no human input

• They are only used for trending topics

What challenge is associated with defining what is relevant in algorithmic processes?

• Relevance is determined by user clicks

• Relevance is not important

• Relevance is easy to define

• Relevance is always subjective

What example is given to illustrate potential bias in algorithms?

• Trending topics on social media

• Recidivism rate predictions

• Weather forecasting

• Search engine results

What factor can influence the outcome of an algorithm?

• The speed of the internet

• The type of data selected

• The color of the interface

• The number of users online

Can algorithms be completely unbiased?

• Yes, if coded correctly

• No, because they reflect human biases

• No, because they are inherently flawed

• Yes, if they use enough data