Operationalizing AIMI
Unintended Consequences - AI Checklist
  • AI needs to be understood and sponsored at board level
  • Education, Training & Awareness of AI is a company wide responsibility
  • Upskilling of your workforce is an imperative for future growth
  • Ethical AI Guidelines & Guardrails should be chaired by a Multi-Stakeholder Group
  • Diversity & Inclusion should form part of every AI initiative
  • AI technology should be seamless to use for everyone and not just for the Data Science community
  • AI Regulation and Compliance are significant operational risks
  • Consumers by law are entitled to request explainable and auditable (human interpretable) decisions made by AI
  • AI Algorithms must be robust, reliable, monitored and tested throughout their existence
  • Human & Machine Bias (Fairness) go hand in hand – Eradicating bias in protected classes is hard and non-trivial
  • Monitoring of AI systems counteracts adversarial attacks on AI models, loss of data and AI business knowhow
  • Without regular AI Health checks companies are widen open to regulatory fines and significant operational risk
Rigorously Validate, Update & Monitor AI Models Pre & Post Deployment
Explain
Trace
Vulnerabilities
Testing
Action
Fairness
Imitation
Privacy
Multi-Stakeholder AI Review
Ethics
Framework
Governance
Compliance
Regulatory
Risk
Strategic AI
  • Use Case Acceptance
  • Regular Health Checks
  • Pre & Post Production Reviews
  • AI Model Monitoring
  • Guidelines / Guardrails
  • Approvals / Rejections
  • Robust / Safe
  • Explainable & Auditable
Constantly Update, Validate & Monitor AI Models