In “Weapons of Math Destruction”, by Cathy O’Neil, the bias behind machine learning and its algorithms are exposed and elaborated on by providing various examples seen in cases across the country. The main areas covered in the book include opacity and scaling of the models, unfairness, and corruption behind the creation of the models. O’Neil further elaborates throughout the book how these algorithms and the biases that come with them have led to hundreds of people falling victim when the models were originally intended to bring efficiency to the world and makes jobs easier for others, when some of the models do the exact opposite.
As someone new to the field of data science, this book was eye-opening to see the negative impacts algorithms can bring to others. When first learning about data science, it is preached how beneficial it can be and the how it is contributing to furthering the different industries. After reading “Weapons of Math Destruction”, a new perspective is gained making those who plan on going into the field of data science more educated on the dangers of algorithms, which will help instill better practices among individuals to incorporate when working with machine learning models to try and eliminate bias.