Digging deeper: AI ethics principles

AI Ethics

Joe Franklin

Associate Data Literacy and Essentials Manager, DataCamp

Meet MedTech Innovations

MedTech Innovations
- Healthcare company
- Using AI to improve patient care and uphold ethics
Personal reflections
- Consider the application of AI ethics in...
  - Personal life
  - Career
  - Known businesses

An image representing MedTech Innovation.

MedTech's AI in patient care
- Personalized treatment plans
Challenge:
- Unintentional bias in AI systems
- Potential discrimination
Principle of fairness
- Equal treatment
- Avoidance of discrimination

Checklist which specifies the action items for addressing fairness challenges.

Scenario: MedTech's AI system mistake affecting patient treatment
Principle of accountability:
- Someone should always be accountable for AI outcomes

An image illustrating the question of accountability.

Scenario: MedTech's AI system recommends a specific treatment
Challenge: Understanding why AI made the decision
Principle of transparency:
- Decisions by AI should be explainable and comprehensible
- Sharing knowledge and information across different stakeholders

Example of what information should data scientists disclose to important stakeholders.

Fairness:
- Continual testing of AI systems to detect and rectify bias
Accountability:
- Clear responsibilities defined for each AI system's outcomes
Transparency:
- Make AI systems explainable and understandable
Commitment:
- Ethical adherence builds trust, mitigates risks

Understanding & applying principles: Ensures ethical AI use
Building trust: Transparency and accountability foster patient trust
Mitigating risks: Ethical AI use reduces potential risks
Promoting AI: Transparency and knowledge-building enhances societal trust and utilization of AI

Icons illustrating that trust and understanding helps bridge AI and society.

¹ Icons made by Freepik & Smashicons from www.flaticon.com

AI Ethics