AWS Responsible AI

Applying responsible AI

The core dimensions of responsible AI include fairness, explainability, privacy and security, robustness, governance, transparency, safety, and controllability.

No one dimension stands alone for responsible AI.

In fact, you must consider each topic as a required part for a complete implementation of responsible AI.

You'll find that considerable overlap exists between many of these topics.

Fairness and transparency are especially important for generative AI.

Fairness

Fairness is crucial for developing responsible AI systems.

With fairness, AI systems promote inclusion, prevent discrimination, uphold responsible values and legal norms, and build trust with society.

You should consider fairness in your AI applications to create systems suitable and beneficial for all.

Transparency

Transparency communicates information about an AI system so stakeholders can make informed choices about their use of the system.

Some of this information includes development processes, system capabilities, and limitations.

It provides individuals, organizations, and stakeholders access to assess the fairness, robustness, and explainability of AI systems.

They can identify and mitigate potential biases, reinforce responsible standards, and foster trust in the technology.

Accountability for generative AI outputs

The ethical impacts underscore the importance of proactive bias mitigation strategies throughout the AI development lifecycle.

Organizations must invest in diverse development teams, robust testing frameworks, and transparent reporting mechanisms to ensure their generative AI systems serve all users fairly and effectively.

Organizations are responsible for integrating AI into their operations and ensuring it is used appropriately.

Every team has a shared responsibility for generative AI outputs.

Teams should carefully consider and review information before inputting it into Generative AI systems to prevent unintentional breaches of confidentiality, data privacy, security laws, and the potential loss of intellectual property.