Shipt’s algorithm squeezed gig workers, who fought back
Shipt, a same‑day delivery service owned by Target, shifted from a transparent formula (base pay plus a percentage of cart value) to a opaque “effort-based” algorithm for paying its gig shoppers, triggering worries about hidden pay cuts and wage manipulation. Commenters argue over whether the new system fairly redistributes earnings or simply exploits information asymmetry, especially since many workers reportedly saw lower and more unpredictable pay while others gained. Broader themes include the morality and legality of black-box compensation, misclassification of gig workers as contractors, and how data-driven platforms use algorithms to maximize profit at the expense of labor transparency.
Scope of the Algorithm Change
- Many see Shipt’s move from a transparent “base + % of cart” formula to a black-box “effort-based” algorithm as a redistribution of pay, not an across-the-board cut.
- Some argue this is a rational fix to workers cherry‑picking “easy, high‑value” orders, leaving undesirable ones unfilled.
- Others stress that even if total payouts are conserved, unannounced cuts to 40% of workers are still a serious issue.
Fairness, Morality, and Power
- One camp says: if workers clearly see the offer upfront and can decline, any rate the platform sets is morally acceptable, barring outright deception.
- Critics counter that opaque rules, asymmetric information, and algorithmic targeting (e.g., offering less to those likely to accept) create exploitation, even without formal wage theft.
- Concerns about hidden discrimination and unequal pay for similar work are raised, especially with black-box algorithms.
Transparency vs. “Gaming the System”
- Strong sentiment that pay rules should be transparent, predictable, and documented so workers can verify earnings and decide whether to continue.
- Others note Shipt had been transparent, which allegedly led to “gaming” by workers; opacity can reduce loopholes but also undermines trust.
- Several argue transparency would better align incentives if the goal is genuinely to reward higher effort.
Contractor vs. Employee and Legal Grey Areas
- Debate over whether gig workers are truly independent contractors or de‑facto employees constrained by app rules.
- Examples given where contractor requirements (hours, dress code, single client, availability) can cross into illegal misclassification.
- Some say the classification distracts from the core problem: nontransparent, potentially manipulative compensation systems.
Data and Article Critique
- Multiple commenters scrutinize the wage‑change histogram:
- Point out misstatements in the article’s 40% figure and poor labeling.
- Note self‑selection bias: negatively affected workers are more likely to share data, likely skewing results downward.
- Some view the piece as a slanted “hit” that fails to prove systematic harm; others say it still reveals unacceptable opacity and unannounced pay cuts.
Broader Platform and Market Dynamics
- Discussion extends to Uber/Lyft and other platforms:
- Centralized matching and rate‑setting seen as de‑facto central planning with strong power asymmetries.
- Fears that with richer data, firms will increasingly capture maximum consumer surplus and pay workers the bare minimum.
- Proposed remedies include stronger transparency rules and privacy/data‑collection limits.