The Investor's Shelf โ€” one book
Uberland

Uberland

Alex Rosenblat
2018
T3 296 pages ยท about 4h 56m to read OL21187169Wgoodreads

Field research on algorithmic management of drivers.

Summary

Alex Rosenblat, a technology ethnographer, spent four years riding with and interviewing Uber drivers across North America and studying driver forums. The book reports what she found about algorithmic management.

Her central subject is the gap between the company's characterisation of drivers as independent entrepreneurs and the control the platform actually exercises. She documents the mechanisms: the algorithm assigns work without disclosing the destination until acceptance, penalises declining rides, sets prices unilaterally and changes them, uses surge pricing displays that do not always correspond to what drivers earn, deploys behavioural prompts to keep drivers working, and deactivates drivers on the basis of passenger ratings that reflect factors including race and gender bias which the company does not correct for.

Her argument is that this constitutes management by algorithm, exercising the control an employer exercises while carrying none of the obligations, and that the entrepreneurial framing shifts responsibility for outcomes onto drivers. She also covers the company's regulatory strategy, in which it entered markets illegally and mobilised its user base politically, and the information asymmetry that prevents drivers from calculating their actual earnings net of vehicle costs. Rosenblat is critical and the drivers she reaches are self-selected toward those with grievances. The documentation of the specific algorithmic control mechanisms is the book's contribution and is unavailable elsewhere in this detail.

Key takeaways 7

  1. The platform exercises the control an employer exercises while carrying none of an employer's obligations.
  2. Drivers accept rides without knowing the destination and are penalised for declining, which removes the choice that independence implies.
  3. Surge pricing displays do not always correspond to what drivers actually earn, which is an information asymmetry rather than an error.
  4. Passenger ratings determine deactivation and reflect biases that the company does not correct for.
  5. Behavioural prompts modelled on video game design are used to keep drivers working longer than they intended.
  6. Drivers cannot easily calculate earnings net of vehicle depreciation, fuel and maintenance, which the entrepreneurial framing obscures.
  7. The company entered markets illegally and mobilised its user base politically, which Rosenblat treats as a deliberate regulatory strategy.

Who should read it

Founders and investors building platforms with worker supply who need to understand algorithmic management and the regulatory exposure it creates.

Where it sits in the reference 2

Companies
Business models

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