The increasing prominence of AI systems calls for urgent integration of diversity and inclusion (D&I) principles to achieve unbiased outcomes. Lack of practical guidance may perpetuate biases and marginalize underrepresented groups.
Inconsistencies in interpreting and applying ethical AI principles, coupled with a lack of diversity in perspectives and underrepresentation from the Global South, raise concerns about the effectiveness of current guidelines.
Implementing ethical principles in AI is challenging due to the absence of proven methods, common norms, and legal accountability. Focus on algorithmic decision-making overlooks operational aspects leading to issues like 'ethics washing' and corporate secrecy.
Debate on AI ethical guidelines' effectiveness and practical applicability is ongoing. Munn highlights the ineffectiveness of current AI ethical principles in mitigating biases in AI systems.
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