Unpacking the blackbox: Transparency

AI Ethics

Joe Franklin

Llama Enthusiast

Black-box nature

  • AI implementations are often black boxes
  • A black box in AI:
    • Known inputs and outputs

              A flowchart illustrating the black-box nature.

AI Ethics

Ambiguousness is non-ideal

  • Ambiguity in AI: Ethical challenge
  • Question of trust:
    • Can we validate AI decisions without understanding them?
  • Transparency:
    • Making an AI's decision-making process understandable
  • Example:
    • Factors in AI sales model

Sticky notes illustrating the factors in AI sales model.

AI Ethics

Throughout the AI life cycle

  • Transparency in AI involves all stages of the AI life-cycle
  • Purpose:
    • Understand the workings of the AI system
    • Gauge comfort level with its operation

The stages of AI life cycle.

AI Ethics

A deciding factor

  • Current state:
    • Transparency in AI is uncommon
    • Hesitation in AI adoption
  • Future implications:
    • Transparency will become a deciding factor in users' choice of AI systems
  • Actionable:
    • Organizations should prioritize transparency

An icon depicting a girl in hesitation.

1 Icon made by Eucalyp from www.flaticon.com
AI Ethics

Openness is key

  • Openness about AI challenges and learnings is key
  • Transparency encourages innovation in AI
  • It leads to more advanced, reliable AI systems

An icon illustrating that openness is the key to transparency.

1 Icon made by Freepik from www.flaticon.com
AI Ethics

Embracing transparency in AI

  • Transparency in AI can be intimidating but is beneficial for businesses

 

  • Transparency leads to predictable regulations and public perception

 

  • Companies can compete based on strengths, culture, customer relationships rather than secrecy

A flowchart illustrating the benefits brought by embracing transparency.

AI Ethics

Let's practice!

AI Ethics

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