COMPUTER FUNDAMENTALS

Detailed explanation-1: -In general terms, blackbox machine learning refers to machine learning models that give you a result or reach a decision without explaining or showing how they did so. The internal processes used and the various weighted factors remain unknown. In other words, there is a lack of transparency in this technology.

Detailed explanation-2: -Artificial intelligence and bias Typically these bias outputs follow classical societal biases like race, gender, biological sex, nationality or age. Bias in AI algorithms can emanate from unrepresentative or incomplete training data or the reliance on flawed information that reflects historical inequalities.

Detailed explanation-3: -Machine learning bias generally stems from problems introduced by the individuals who design and/or train the machine learning systems. These individuals could either create algorithms that reflect unintended cognitive biases or real-life prejudices.