Bias is the silent killer of well-intentioned algorithms
Bias in machine learning algorithms has come under scrutiny in countless applications, underscoring how much "silent AI" has permeated so many aspects of everyday life and influenced far-reaching, sea change decisions in business and society. Well-intentioned data science warriors are working to address, correct, neutralize and eliminate bias. Attributed to a combination of human factors, bad data or a lack thereof, bias can taint predictive models and perpetuate social stereotypes by race, gender, age, location, economic status and ethnicity. E-Handbook: Machine learning and bias concerns weigh on data scientists Data scientists are forever vigilant in their desire to identify and eliminate the many forms of bias that can compromise the credibility of machine learning models. Human bias, missing data, data selection, data confirmation, hidden variables and unexpected crises can…
