Fundamental principles of AI ethics
The AI revolution has brought with it a series of ethical challenges that shape our world in profound and complex ways. Issues such as data privacy, algorithmic bias, and the potential for AI to perpetuate or even exacerbate social inequalities are at the forefront of these challenges.
Algorithmic bias refers to systematic errors in AI systems that lead to unfair outcomes, often disadvantaging certain groups. For example, a hiring algorithm that consistently rejects candidates from a particular demographic group demonstrates algorithmic bias.
Social inequalities involve disparities in access to resources and opportunities among different social groups, which AI can inadvertently amplify if not carefully managed. For instance, AI systems used in loan approvals might deny loans disproportionately to certain racial groups if trained on biased historical data.
This chapter embarks on an essential journey to understand how AI ethics is not only...
