Data-Driven Task

A Data-Driven Task is a decisioning task that uses sample data as its primary input to guide outcomes and decisions.

• Context:
  • Task Input: sample data, data parameters
    • Optional Input: data constraints, performance criteria
  • Task Output: data-driven decisions, data-driven insights
  • Task Performance Measure: data quality metrics, decision accuracy, computational efficiency
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  • It can range from being a Simple Data-Driven Task to being a Complex Data-Driven Task, depending on its data complexity.
  • It can range from being a Batch Data-Driven Task to being a Real-Time Data-Driven Task, depending on its temporal requirements.
  • It can range from being a Data-Driven Prediction Task to being a Data-Driven Optimization Task, depending on its task objective.
  • It can range from being a Human-Performed Data-Driven Task to being an Automated Data-Driven Task, depending on automation level.
  • It can range from being a For-Profit Org. Data-Driven Task to being a Non-Profit Org. Data-Driven Task.
  • It can range from being a Private Org. Data-Driven Task to being a Public Org. Data-Driven Task.
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  • It can generate data-driven insight task through data analysis processes.
  • It can improve decision quality through data-driven approaches.
  • It can be a member of a Data-Driven Workflow.
  • It can be supported by a Data-Driven System that implements a data-driven algorithm.
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• Examples:
  • Automated Intelligence (AI)-Requiring Tasks, such as:
    • Data-Driven Pattern Recognition Tasks, such as:
      • Data-Driven Image Recognition Task for visual pattern detection.
      • Data-Driven Speech Recognition Task for audio pattern detection.
    • Data-Driven Natural Language Tasks, such as:
      • Data-Driven Translation Task for language conversion.
      • Data-Driven Text Analysis Task for content understanding.
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  • Human-Performed Data-Driven Tasks, such as:
    • Data-Driven Expert Review Task for clinical diagnosis, where a medical professional analyzes patient data.
    • Data-Driven Strategy Planning Task for business development, where an executive uses market analysis.
    • Data-Driven Research Analysis Task for scientific discovery, where a researcher interprets experimental data.
    • Data-Driven Financial Advisory Task for investment planning, where an advisor evaluates portfolio data.
    • Data-Driven Educational Assessment Task for student evaluation, where an educator analyzes learning data.
    • ...
  • Data-Driven Hybrid Tasks (requiring both human oversight and ai support), such as:
    • Data-Driven Design Tasks, such as:
      • Data-Driven Product Design Task for product development.
      • Data-Driven Process Design Task for workflow optimization.
    • Data-Driven Evaluation Tasks, such as:
      • Data-Driven Risk Assessment Task for risk management.
      • Data-Driven Performance Review Task for performance improvement.
  • ...
• Counter-Examples:
  • Model-Driven Tasks, which rely on predefined theoretical models rather than sample data, such as:
    • Intuition-Driven Tasks, based on informal models (such as heuristic tasks).
    • Theory-Driven Tasks, based on formal models and mathematical principles.
  • Rule-Based Tasks, which use fixed business rules instead of learning from data patterns.
  • Software Programming Tasks, which involve explicit code writing rather than data-driven learning.
• See: Data-Driven Creation Task, Data-Driven Selection Task, Data-Driven Simulation Task, Data-Driven Analytics Task, Data-Driven Machine Learning Task.

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References

2017

• (Karpathy, 2017) ⇒ Andrej Karpathy. (2017). “Software 2.0." Blog post 2017-11-11
  • QUOTE: … It turns out that a large portion of real-world problems have the property that it is significantly easier to collect the data (or more generally, identify a desirable behavior) than to explicitly write the program. A large portion of programmers of tomorrow do not maintain complex software repositories, write intricate programs, or analyze their running times. They collect, clean, manipulate, label, analyze and visualize data that feeds neural networks. …

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