Deciphering the complexities of AI ethics

As technology continues to evolve, integrating fairness, safety, inclusiveness, transparency, and accountability into the core of AI practices remains imperative for creating a responsible and ethical AI landscape

- Ashok Pandey

In a rapidly advancing era of Artificial Intelligence, ensuring responsible AI practices has become a critical focus. Karunya Sampath, Co-founder & CEO, Payoda Technologies, shares valuable insights on the pillars of responsible AI development. From addressing fairness concerns to guaranteeing safety in critical domains and promoting inclusiveness, transparency, and accountability, Sampath provides a comprehensive perspective on navigating the complex landscape of AI ethics.

▾ Ensuring Fairness in Diverse Societal Contexts

Challenge of Fairness: Ensuring fairness in AI algorithms is an ongoing challenge, particularly in diverse and evolving societal contexts. AI developers can take several measures to address this issue. One important step is to curate and preprocess training data carefully to remove any existing bias. For instance, if historical data contains gender or racial bias, developers must work to mitigate these biases to ensure fair outcomes.

Fairness-aware Techniques: