Building Trust in AI: Developing Guiding Principles for Ethical and Effective Implementation - American Society of Employers - Dana Weidinger

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Building Trust in AI: Developing Guiding Principles for Ethical and Effective Implementation

Rapid advancement in AI has organizations either ignoring the technology or rushing to implement it for a competitive advantage. However, implementing AI without proper guidelines regulating its use and adoption exposes organizations to risks that negatively impact organizational outcomes. Avoid adverse organizational outcomes by collaborating with organizational leaders to develop responsible AI guiding principles. 

As defined by the World Economic Forum, "Responsible AI is the practice of designing, building, and deploying AI in a manner that empowers people and businesses, and fairly impacts customers and society – allowing companies to engender trust and scale AI with confidence."

Organizational leaders should work together to create responsible AI guiding principles, ensuring alignment on ethical and legal boundaries for adopting and using AI technologies. HR teams should collaborate with leaders to identify and articulate responsible AI principles that reflect the organization's culture, values, and potential risks. By supporting responsible AI use, organizations can develop effective strategies and policies that allow them to capitalize on opportunities while managing risks effectively.

Guiding Principles include:

  • Accountability
    • All actors must be accountable for the functioning AI system.
  • Fairness & Bias Detection
    • The organization will ensure that any models/systems are fair and free from bias.
  • Data Privacy
    • Privacy values like anonymity, confidentiality, and control will guide the organization’s choice for AI model/system design.
  • Validity & Reliability
    • AI systems need to perform reliably and as expected.
  • Explainability & Transparency
    • All models/systems will provide meaningful information and be transparent and explainable to end users.
  • Safety & Security
    • All models/systems must be resilient, secure, and safe throughout their entire lifecycle.

The rationale for adopting responsible AI principles is compelling. Through modest internal efforts, organizations can establish protective measures that enhance their ability to manage the risks associated with AI implementations and optimize business outcomes.

ASE Connect

If you missed the recent webinar, AI Implementation Preparation Guide for HR, presented by McLean & Company, watch it here.

Source: McLean & Company “Develop Responsible AI Guiding Principles”



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