Job Design Visualizer for “Chaining Tasks, Redefining Work: A Theory of AI Automation”
Two-stage cost-minimization: steps → tasks (AI strategy), then tasks → jobs (job design).
Each step is executed as Manual, Automated, or Augmented.
A Manual step becomes a manual task; an Augmented step, alone or preceded by Automated steps, forms one AI chain task (length ≥ 1).
Given the task sequence from Stage 1, tasks are partitioned into jobs (one worker per job).
Each job boundary incurs a hand-off cost determined by the final step of that job.
Each step has a skill cost and a time cost for each mode of human (cMi, tMi) or AI-assisted (cAi, tAi) execution. These costs for AI-automated execution are zero. qi and tHi denote the AI's success probability and the (potential) hand-off time cost between workers.
The solver minimizes the firm's cost minimization problem, denoted in Equation 3 in the paper.
| Step | cMi ($) | tMi | cAi ($) | tAi | qi | tHi | Mode |
|---|
Each Manual step becomes a manual task with its (cM, tM); consecutive Automated steps followed by an Augmented step form one AI chain task whose skill and time costs are the augmented step's (cA, tA) and whose success probability q is the product of the constituent steps' q values. tH is inherited from the task's last step.
| Task | c ($) | t | q | tH | Type |
|---|
Each step is a rectangle: width = time, height = skill. Each job's bounding box has area = wage bill.
Hand-off rectangles appear between non-final jobs.
Automated cells use a diagonal-stripe fill — they contribute zero direct cost.
Each task is a rectangle: width = time, height = skill. Each job's bounding box has area = wage bill.
Hand-off rectangles appear between non-final jobs.
Each job is a rectangle: width = time, height = skill. Each job's bounding box has area = wage bill.
Per-job wage bills under the cost-minimizing design. The total cost equals the sum of the wage bills across all jobs.
| Job | Steps | Tasks | Σ cb ($) | Σ tb (time) | tH(Jj) | Wage Bill ($) |
|---|