Privacy & Ethical Considerations

 

While artificial intelligence brings innumerable benefits and promises of a technologically advanced future, it poses numerous challenges too. As we’ve touched upon in previous chapters, one of the common challenges is bias and fairness. The concept of bias refers to an unfair and prejudicial inclination or favor towards or against a person or group. In the context of AI, the concern is that prediction models, particularly those involved in decision-making processes, inadvertently replicate and amplify biases present in the training data or the biases of their human creators, leading to unfair outcomes.

These biases can manifest in numerous ways, from racial and gender bias in facial recognition software to socioeconomic bias in credit scoring models. Bias has substantial real-world implications as it can lead to systematic discrimination, marginalization of certain groups, and exacerbation of societal inequalities. This poses not...