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Bias can emerge from many factors, including but not limited to the design of the algorithm or the unintended or unanticipated use or decisions relating to the way data is coded, collected, selected or used to train the algorithm. For example, algorithmic bias has been observed in search engine results and social media platforms.
For example, technologies that use algorithms to detect skin cancer have been found to be less accurate for people with darker skin, while a liver disease detection algorithm was found to ...
The inductive bias (also known as learning bias) of a learning algorithm is the set of assumptions that the learner uses to predict outputs of given inputs that it has not encountered. [1] Inductive bias is anything which makes the algorithm learn one pattern instead of another pattern (e.g., step-functions in decision trees instead of ...
Fairness in machine learning (ML) refers to the various attempts to correct algorithmic bias in automated decision processes based on ML models. Decisions made by such models after a learning process may be considered unfair if they were based on variables considered sensitive (e.g., gender, ethnicity, sexual orientation, or disability).
In marking down many individual students to prevent high grades increasing overall, the algorithm did exactly what the government wanted it to do. Here are the biased algorithms the UK government ...
Several users posted a lot of photos to show that in an image that has people with different colors, Twitter chooses to show folks with lighter skin after cropping those images to fit its display ...
[14] [15] For example, boosting combines many "weak" (high bias) models in an ensemble that has lower bias than the individual models, while bagging combines "strong" learners in a way that reduces their variance. Model validation methods such as cross-validation (statistics) can be used to tune models so as to optimize the trade-off.
The Health Information National Trends Survey reports that 75% of Americans go to the internet first when looking for information about health or medical topics. YouTube is one of the most popular ...