A decision tree is a tree-like graph that can be used as an algorithm to automate decision making. Decision trees are considered human-readable. As such, they are compatible with human driven processes such as governance, ethics, law, audits and critical analysis.
Artificial intelligence is another common method of automating decisions using sophisticated tools that learn and self-improve. AI models of decision making can be based on decision trees. However, more typically they are based on statistical models that aren't easily human-readable.It is challenging to govern and manage AI decisions that can't be represented in human-readable form. Additionally, the self-improving nature of AI means that decision criteria change with time making them all the more difficult for humans to evaluate.
Generally speaking, predefined decision trees are compatible with business and legal processes. Artificial intelligence is often difficult to incorporate into processes that require human judgment.
|Decision Tree Definition||A tree-shaped graph used to determine an action or illustrate a statistical probability.|
|Artificial Intelligence Definition||Software that learns and self-improves often using statistical models that aren't easy for humans to intuitively understand.|
|Tradeoffs||Decision trees integrate well with human-driven processes.
AI decisions are potentially more optimized and dynamic as compared with predefined decision trees.AI is generally difficult for humans to govern and control due to its self-improving nature. |
|Related Concepts||Artificial IntelligenceAutomationAffective ComputingStrong Artificial IntelligenceSentiment Analysis|
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