How can we ensure fairness and equity in AI for education?

Aug 8, 2023 ... Encord Active offers features to help reduce bias in datasets, allowing you to identify and address any potential biases in your data workflow. Jul 13, 2021 ... In this survey, we investigated different real-world applications that have shown biases in various ways, and we listed different sources of ... Jul 15, 2024 ... As institutions of higher education turn to AI machine learning and data-driven algorithms to make their work more efficient, a new study ... As promising as machine-learning technology is, it can also be susceptible to unintended biases that require careful planning to avoid. We argue that algorithmic bias evolves with human interaction in an iterative manner, which may have a long-term effect on algorithm performance and humans' ... Jan 31, 2018 ... This post assumes some familiarity with machine learning, and reinforcement learning in particular. If you are new to RL, I'd recommend ... Feb 4, 2021 ... Data bias in machine learning is a type of error in which certain elements of a dataset are more heavily weighted and/or represented than others ... Mar 3, 2021 ... Abstract. Western societies are marked by diverse and extensive biases and inequality that are unavoidably embedded in the data used to train ... Jul 25, 2022 ... Machine learning bias is sometimes called algorithm bias or AI bias. Predictive models may be trained on data containing human decisions or ... Detecting bias in your ML model can be done proactively or reactively, and depending on your specific case, either one is viable. Reactive bias detection ...