Part 6/10:
DJ illustrates the distinction between associative and causal models using a health-related example: predicting whether a person will fall ill based on their prior visits to a doctor. While positional data may suggest that doctor visits correlate with sickness, it fails to uncover the direct causal relationship—one cannot simply interpret correlational data without a robust understanding of the underpinning causative factors.
The Proof: Why Current Technology Falls Short
In assessing why current AI agents are ineffective, the DeepMind paper lays out two proofs:
- For an agent to function optimally across a myriad of environmental shifts, it must have learned the causal dynamics of its operational environment.