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AI ethics is a crucial consideration. The goal is to help clients implement ethical AI that is socially responsible, aligns to moral values, and earns community trust.
AI ethics is a crucial consideration. The goal is to help clients implement ethical AI that is socially responsible, aligns to moral values, and earns community trust.
Risk Assessment
Risk Assessment
Identifying potential risks and harms associated with the client's intended AI systems, including bias, discrimination, privacy breaches, and safety issues.
Principles Development
Principles Development
Guiding the creation of ethical AI principles aligned to the client's brand, values and industry standards. This shapes an ethical framework.
Policy Formulation
Policy Formulation
Recommending comprehensive policies and guidelines governing ethical data collection, model development, and usage protocols to embed ethics.
Governance Definition
Governance Definition
Designing cross-functional governance structures, committees and review boards to oversee ethical AI practice.
Process Integration
Process Integration
Developing processes like ethical reviews, algorithm audits, external oversight mechanisms to continually assess AI ethics.
Training and Awareness
Training and Awareness
Conducting training across the organization on ethical AI considerations and ensuring human review of automated decisions.
Vendor Assessment
Vendor Assessment
Evaluating 3rd party vendor solutions for alignment with the client's ethical principles and risk tolerance.
Communications
Communications
Advising the client on transparent communication of its ethical AI commitments to build trust with stakeholders.
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