Understanding AI model bias
In this section, we unpack the potentially devastating issue of AI model bias, a prevalent pitfall that, if overlooked, can skew financial trades, investments, or analysis, leading to poor financial decisions and potential monetary losses. This section stresses the importance of comprehending, quantifying, and addressing bias in AI models, underlining how unchecked bias could erode investor trust and propagate inaccuracies in predictions. By exposing the complexities of AI model bias, we provide the necessary tools for developing more fair, reliable, and ethically-sound AI-driven financial strategies, thereby empowering you to avert unnecessary financial risks. An AI model is considered biased when it systematically and unfairly discriminates against certain groups or outcomes based on specific attributes, such as race, gender, or age. Bias in AI models often occurs due to the presence of biased data used during training, flawed model assumptions, or other...