{"id":157,"date":"2021-09-29T08:41:06","date_gmt":"2021-09-29T06:41:06","guid":{"rendered":"https:\/\/wpmu.mau.se\/nmict21group8\/?p=157"},"modified":"2022-05-11T14:35:37","modified_gmt":"2022-05-11T12:35:37","slug":"how-can-algorithms-big-data-and-ai-cause-biases-and-unfairness","status":"publish","type":"post","link":"https:\/\/wpmu.mau.se\/nmict21group8\/2021\/09\/29\/how-can-algorithms-big-data-and-ai-cause-biases-and-unfairness\/","title":{"rendered":"How can algorithms, big data and AI cause biases and unfairness?"},"content":{"rendered":"
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Part 02 of the learning curve about Big Data for dummys (like myself)<\/span><\/h6>\n
How can algorithms, big data and AI cause biases and unfairness?<\/b><\/h5>\n

Data reflects existing biases, unbalanced classes in training data, data that doesn’t capture the right value, data that is amplified by feedback loops, and malicious data. Let me try to explore, what that means.<\/span><\/p>\n

Now bias itself isn’t necessarily a terrible thing, our brains often use it to take shortcuts by finding patterns, but bias can become a problem if we don’t acknowledge exceptions to patterns or if we allow it to discriminate. The infographic below is showing that we\u00a0 are all biased in one way or the other. So, using data from existing biases could even spread more biases. <\/span>These biases affect belief formation, reasoning processes, business and economic decisions, and human behavior in general<\/span>. <\/span>The infographic below represents a really interesting overview of these biases.\u00a0<\/span><\/p>\n

We humans take shortcuts remembering and processing data and constructing meaning.<\/span><\/p>\n

There are 4 qualities which lead to limit every human\u2019s intelligence:<\/span><\/p>\n