<?xml version="1.0" encoding="UTF-8"?>
<oembed>
  <version>1.0</version>
  <type>link</type>
  <title>EQ-08: Human Review Stabilization &amp; Shared Attention Capacity (Bartolucci &amp; Vivo; Wang et al., 2026) (South Korea COO Practice) | ANDYGROVE.SYSTEMS</title>
  <author_name>ANDYGROVE.SYSTEMS Continuing Professional Development &amp; Operations Research Collective</author_name>
  <author_url>https://andygrove.systems/education</author_url>
  <provider_name>ANDYGROVE.SYSTEMS — High Output Operations &amp; Fresh Preprints Upskilling Hub</provider_name>
  <provider_url>https://andygrove.systems</provider_url>
  <cache_age>86400</cache_age>
  <thumbnail_url>https://andygrove.systems/og-card.png</thumbnail_url>
  <thumbnail_width>1200</thumbnail_width>
  <thumbnail_height>630</thumbnail_height>
  <url>https://andygrove.systems/south-korea/eq-08</url>
  <description>EQ-08 (Human Review Stabilization &amp; Shared Attention Capacity (Bartolucci &amp; Vivo; Wang et al., 2026)) applied by IE/OR specialists in South Korea: t_rev + p_err · t_fix &lt; t_manual,   α_AI &gt; α_crit,   and   λ_esc + λ_clarify &lt; N_H · r_H. Agents speed up a workflow only if review + error-repair time beats manual execution, AI-eligible task share exceeds α_crit, and combined escalation + clarification arrivals stay strictly below human capacity N_H r_H. | Fresh Preprints: https://andygrove.systems/preprints | 42-Hr CPD Hub: https://andygrove.systems/education (Independent platform; not affiliated with Intel Corporation or the Grove family)</description>
</oembed>