NSDC Data Science Flashcards – Data Science Ethics Card #5 – Algorithmic Fairness

This NSDC Data Science Flashcards series will teach you about the importance of data ethics. This installment of the NSDC Data Science Flashcards series was created by Florence Hudson and Varalika Mahajan. Recordings were done by Lauren Close, Florence Hudson, and Emily Rothenberg. You can find these videos on the NEBDHub Youtube channel.

In our digital age, algorithms shape our world. But how do we ensure fairness in these algorithms? 

First, Bias Awareness. Algorithms can sometimes make unfair decisions. Recognizing bias is like shining a light on hidden flaws. It’s crucial to identify and acknowledge biases in algorithms. Bias awareness is the first step towards fairness.

Next, data representation. Diversity in data is key. Imagine data as ingredients in a recipe. A fair algorithm requires a balanced recipe of data. Representing different perspectives will also promote fairness.

Lastly, audit and accountability. It’s like a quality check for algorithms. Independent audits help ensure fairness and compliance. Organizations should be accountable for algorithmic decisions. Audits and accountability promote trust and fairness.

By being aware of bias, using diverse data, and embracing audits, we can create algorithms that treat everyone fairly. Remember, fairness in algorithms is a cornerstone of a just digital world.

Please follow along with the rest of the NSDC Data Science Flashcard series to learn more about data science ethics.