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entry · p2026-09-07-046 · validated
Uber dynamic (upfront) pricing and work allocation
93 drivers were worse off in terms of their average per hour pay
- tech
- uber-dynamic-pricing
- passes the definition as
- per-trip fares and driver fees set independently by a system whose inputs include predicted cancellation probability and a deep-neural-network ETA
- from
- 2023-01
- region
- UK
- domain
- work
- side
- loss
- people
- 114 drivers (2024-02)
- effect
- 93 people (2024-02) — 93 of 114 drivers with continuous data across the change were worse off in average pay per hour; 21 were better off
- reversible
- yes
- who holds the switch
- owner:Uber
- attribution
- named
- source kind
- primary
- the statistic
- For the 114 drivers with monthly data covering the year either side of dynamic pricing (2022/02–2024/02), average pay per hour fell from £18.52 to £17.07 — a larger drop than across the whole sample — and the loss was not evenly spread: 93 drivers were worse off, 21 better off. This is the distributional finding: who bore it, not only how much.
- source
- https://arxiv.org/pdf/2506.15278
- proposed by
- researcher (opus), brief 2026-09-06 second harvest, robots-gig-work
- received
- 2026-09-06T13:34:02-04:00
- harvest report
- impacts/harvest/2026-09-07-robots-gig-work.md
Rulings, in order
- 2026-09-06T13:34:54-04:00 · validatorpass — quote found on the fetched page (exact match; HTTP 200 application/pdf)
- 2026-09-06T13:38:18-04:00 · sessionnote — Same study, a 114-driver subset of p2026-09-07-043's panel; bands through 043.
The proposal as it arrived (JSON)
{
"id": "p2026-09-07-046",
"received": "2026-09-06T13:34:02-04:00",
"proposer": "researcher (opus), brief 2026-09-06 second harvest, robots-gig-work",
"kind": "entry",
"sha": "7c64350d0df8ce6d",
"data": {
"kind": "entry",
"tech": "uber-dynamic-pricing",
"tech_name": "Uber dynamic (upfront) pricing and work allocation",
"definition": "per-trip fares and driver fees set independently by a system whose inputs include predicted cancellation probability and a deep-neural-network ETA",
"from": "2023-01",
"region": "UK",
"domain": "work",
"side": "loss",
"people": {
"n": 114,
"unit": "drivers",
"date": "2024-02"
},
"effect": {
"n": 93,
"unit": "people",
"date": "2024-02",
"what": "93 of 114 drivers with continuous data across the change were worse off in average pay per hour; 21 were better off"
},
"reversible": true,
"switch": "owner:Uber",
"statistic": "For the 114 drivers with monthly data covering the year either side of dynamic pricing (2022/02–2024/02), average pay per hour fell from £18.52 to £17.07 — a larger drop than across the whole sample — and the loss was not evenly spread: 93 drivers were worse off, 21 better off. This is the distributional finding: who bore it, not only how much.",
"source": "https://arxiv.org/pdf/2506.15278",
"quote": "93 drivers were worse off in terms of their average per hour pay",
"attribution": "named",
"source_kind": "primary"
},
"from_file": "impacts/harvest/2026-09-07-robots-gig-work.md"
}