The performance of an AI system depends heavily on the underlying data used in model training, meaning that the final model will reflect biases in that data and how it was collected. A model trained on a data set with insufficient data representing minority groups will yield worse outcomes ...
we become more adept at challenging system outputs. During theCybersecurity Standuplive event, participants were encouraged to share their experiences and perspectives; they actively engaged in the conversation to foster a more inclusive and unbiased AI landscape...
AI bias is an anomaly in the output of ML algorithms due to prejudiced assumptions. Explore types of AI bias, examples, how to reduce bias & tools to fix bias.
According to NIST's Reva Schwartz, the main distinction between the draft and final versions of the publication is the new emphasis on how bias manifests itself not only in AI algorithms and the data used to train them, but also in the societal context in which AI systems are used. "Cont...
ML models should target and eliminate biases rather than exacerbate discrimination. But in order to build fair AI models, we must first build better methods to identify the root causes of bias in AI. We must understand how a biased AI model learns a biased relationship between its inputs and...
Probably better to have a known working system than one bought hasily and rushed into place.It is odd to they barely mention any AI or ML outside of face recognition despite face recognition being a small part of what is out there.All in all might be good to get you to started on ...
In “Bias in artificial intelligence algorithms and recommendations for mitigation (2023), opens in new tab/window” to which librarian Rachel Hicklen was a contributor, the authors identified five stages where bias can be introduced into an AI system: the initial research question, data collection...
Predictive policing tools—AI-powered predictive policingtools used by some organizations in the criminal justice system are supposed to identify areas where crime is likely to occur. However, they often rely on historical arrest data, which can reinforce existing patterns of racial profiling and dispr...
Intentionally inserting bias in AI Is there ever a case where IT pros would want to inject bias into an AI system? With all the talk about the dangers ofperpetuating AI bias, it may seem odd to even consider the possibility. But if one is injecting that bias to correct a...
Bias, as used in this paper, refers to the tendency toward a particular characteristic or behavior, and thus, a biased AI system is one that shows biased associations entities. In this literature review, we examine the current state of research on AI bias, including its sources, as...