Data is the foundation of smart cities. However, to deliver the right solutions, planners must establish sustainable data and AI technology policies.

Brilliance bias is the tendency to think of brilliance or genius as a male characteristic.

This article will look at three ways to limit data bias: collecting data from a variety of sources, ensuring data is diverse, and monitoring real world performa

Humans are naturally predisposed to some attitudes and behaviours which can close us off from good choices.

Cognitive biases are repetitive mental errors resulting from how our brains function. Due to them, we often act impulsively and that's what marketers can use.

5 main questions from a panel discussion on bias in AI. Panelists offer insights into the sources of bias, the responsibility of developers and Ai's future.

Once upon a time, there was a language model named ChatGPT, and like any curious machine, it loved to explore the vast expanse of the internet.

since it is the developers that provide the data and train the model, it is them that can cause the model to become biased (intentionally or unintentionally)

The future of Artificial Intelligence consumes our thoughts and engenders passionate debates. Theories abound, ranging from dystopian nightmares to sunlit dream

A look at how bias affects AI and how to mitigate bias in A.I.

This is an article that discusses ethical principles to reduce the fallacies of fear based thinking related to artificial intelligence.

This article explores the Mathematical details of least squares estimator in an unbiased and biased settings due to model specification errors.

Dive deep into the challenges of measuring and mitigating bias in machine learning models, the trade-offs between fairness metrics.