W4323064579 Working papers AI × management and organizations

Regulating Algorithmic Management: A Blueprint

Jeremias Adams-Prassl · Halefom H. Abraha · Aislinn Kelly-Lyth · M. Six Silberman · Sangh Rakshita

Also recorded as: doi:10.2139/ssrn.4373355 · ssrn:4373355

ssrn abstract page · 2023-03-04

Recorded claims
1
coded from the inspected source
Evidence classes
1
ssrn-abstract-page
Recorded limitations
3
stated, never hidden

From the hash-bound evidence releases

Recorded claims

Each claim states what the inspected source says, at the recorded location—bounded by its scope and graded by its confidence. Nothing here is a synthesis across works.

The article identifies privacy harms, information asymmetries, and loss of human agency as regulatory gaps in automated employer functions, and proposes prohibitions, purpose limits, information rights, human review, consultation, and impact assessment as governance responses.

confidence: high ssrn-abstract-page apw-e1-ssrn-backfill

Scope: Legal-policy blueprint covering employer functions from hiring through termination; no empirical sample, study period, or statistical denominator

Structured relationships

In-corpus citations

Only source-supplied cites relationships whose two endpoints are admitted are shown. Invocation evidence remains a separate relationship.

Cites (0)

No in-corpus outgoing citation is available in the current enrichment coverage.

Cited by (0)

No in-corpus incoming citation is available in the current enrichment coverage.

Boundaries

Limitations & independence

Recorded at coding time, carried with the work forever. A claim without its limits is not evidence.

Recorded limitations

  • Abstract-level evidence only; full text and PDFs were not inspected.
  • The proposed safeguards are policy designs; the abstract reports no implementation test or causal evaluation.
  • The abstract does not specify a common jurisdictional baseline for every proposed safeguard.

Source independence

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