With AI systems being used in practical environments, there is a concern about how they operate ethically and do not participate in biased ways. AI ethics is a relatively new field of study that is interested in defining proper approaches and tools to deal with these problems.
AI’s first major concern is bias in the service to be offered and the system to be developed. Like any technology that evolved from human society, AI can contain preexisting societal biases inherent within the developers themselves if they are not actively removed. For instance, a hiring algorithm trained using historical employment data that has gender bias will tend to rate male candidates higher than females, thus promoting discrimination. Such biases must be addressed to gain acceptance of AI-powered systems and avoid unfair consequences.
There are several techniques currently being researched and deployed to detect and reduce biases in AI models: There are several techniques currently being researched and deployed to detect and reduce biases in AI models:
- It is even better to ensure that the training data is diverse and has minimal possibility of bias because it is better to prevent models from even learning the wrong correlations in the first place. In practice, achieving a scenario where data is perfectly unbiased is…