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Causal AI for government agencies

Governments need AI systems that stakeholders understand and can interact with, that make fair recommendations, and that are dependable during periods of seismic change or disruption. Major government agencies trust Causal AI with all aspects of their decision-making processes.

Top of mind for our government agency clients

  1. Policymaking under severe uncertainty.
  2. Global supply chain disruption.
  3. Climate risk.
  4. Demand for cost-effective technology solutions. 
  5. Current AI solutions are flawed and lack trustworthiness.

Causal AI use cases government agencies are benefitting from

  • Simulate the impact of policies before implementing them, reducing the need for costly trial-and-error experimentation or randomized controlled trials. 
  • Assess the impact of policies by applying counterfactual analysis to compute what would have happened under an alternative policy intervention. 
  • Enable policymakers convey background information and context to aid the modelling process, with human-in-the-loop modelling. 
  • Generate explainable glass-box models with behavior that can be anticipated ahead of time with confidence.
  • Build models that promote fair policy-making and eliminate algorithmic bias.
  • Encode models with high-level constraints, objectives, KPIs (autoKPI™),  and domain knowledge. 
  • Build models that dynamically update as conditions on the ground change. 
  • Simulate the impact of budgetary decisions via intervention-design modelling.
  • Estimate demand with intelligent forecasts that are robust to minor disruptions and adaptive to major crises. 
  • Produce reliable predictions under extreme uncertainty and volatility, with regime-invariant causal models.
  • Integrate domain expertise to factor in government agency’s constraints and goals.
  • Intelligent price forecasting, that includes price elasticity of demand modelling via intervention-analysis — a signature capability of Causal AI. 
  • Purchasing power analytics to optimize price negotiations.
  • Causal modelling that is robust to minor supply-chain disruptions and adaptive to extreme volatility.

Augment your decision-making capabilities today

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