{"id":3121447,"date":"2026-04-10T13:04:58","date_gmt":"2026-04-10T13:04:58","guid":{"rendered":"https:\/\/aivaulttech.com\/?page_id=3121447"},"modified":"2026-04-10T15:52:45","modified_gmt":"2026-04-10T15:52:45","slug":"experimental-design","status":"publish","type":"page","link":"https:\/\/aivaulttech.com\/sk\/ai-vault-research\/experimental-design","title":{"rendered":"Experimental Design"},"content":{"rendered":"<section style=\"max-width: 980px; margin: 0 auto; padding: 28px 18px; font-family: system-ui, -apple-system, Segoe UI, Roboto, Arial, sans-serif; color:#111;\">\n  <h1 style=\"margin:0; font-size:34px; line-height:1.1;\">AI Vault Research \u2014 Experimental Design<\/h1>\n  <p style=\"margin:12px 0 22px; font-size:16px; line-height:1.8; color:#333;\">\n    This research uses a controlled experimental system embedded within AI Vault Systems Inc. The design combines enterprise operations with formal observation, governance constraints, and repeatable measurement cycles.\n  <\/p>\n\n  <div style=\"display:grid; grid-template-columns:repeat(auto-fit, minmax(280px, 1fr)); gap:16px;\">\n    <div style=\"border:1px solid #e8e8e8; border-radius:16px; padding:18px;\">\n      <h2 style=\"margin:0 0 8px; font-size:20px;\">Research Design<\/h2>\n      <p style=\"margin:0; line-height:1.8; color:#444;\">\n        Qualitative design-science case study with longitudinal observation. The system is observed over repeated operational cycles to assess how changes in AI autonomy and governance influence enterprise behavior.\n      <\/p>\n    <\/div>\n    <div style=\"border:1px solid #e8e8e8; border-radius:16px; padding:18px;\">\n      <h2 style=\"margin:0 0 8px; font-size:20px;\">Unit of Analysis<\/h2>\n      <p style=\"margin:0; line-height:1.8; color:#444;\">\n        The unit of analysis is the adaptive enterprise system, including AI agents, coordination workflows, governance controls, and tokenized incentive mechanisms.\n      <\/p>\n    <\/div>\n    <div style=\"border:1px solid #e8e8e8; border-radius:16px; padding:18px;\">\n      <h2 style=\"margin:0 0 8px; font-size:20px;\">Case Context<\/h2>\n      <p style=\"margin:0; line-height:1.8; color:#444;\">\n        AI Vault Systems Inc provides the operational environment. AI Vault Research provides the observational, documentation, and analysis layer.\n      <\/p>\n    <\/div>\n  <\/div>\n\n  <div style=\"margin-top:24px; border:1px solid #e8e8e8; border-radius:16px; padding:22px;\">\n    <h2 style=\"margin:0 0 12px; font-size:24px;\">Experimental Conditions<\/h2>\n    <div style=\"display:grid; grid-template-columns:repeat(auto-fit, minmax(220px, 1fr)); gap:14px;\">\n      <div style=\"background:#f8fafc; border-radius:14px; padding:16px;\">\n        <strong>Condition A<\/strong>\n        <p style=\"margin:8px 0 0; line-height:1.7; color:#444;\">Human-led operation with AI decision support only.<\/p>\n      <\/div>\n      <div style=\"background:#f8fafc; border-radius:14px; padding:16px;\">\n        <strong>Condition B<\/strong>\n        <p style=\"margin:8px 0 0; line-height:1.7; color:#444;\">Human-in-the-loop execution with agent recommendations and limited autonomous actions.<\/p>\n      <\/div>\n      <div style=\"background:#f8fafc; border-radius:14px; padding:16px;\">\n        <strong>Condition C<\/strong>\n        <p style=\"margin:8px 0 0; line-height:1.7; color:#444;\">Governance-constrained autonomous execution with event logging and exception handling.<\/p>\n      <\/div>\n    <\/div>\n  <\/div>\n\n  <div style=\"margin-top:24px; border:1px solid #e8e8e8; border-radius:16px; padding:22px;\">\n    <h2 style=\"margin:0 0 12px; font-size:24px;\">Five-Layer Research Model<\/h2>\n    <ol style=\"margin:0; padding-left:20px; line-height:1.9; color:#333;\">\n      <li><strong>AI Agent Layer:<\/strong> reasoning, recommendation, and automated actions.<\/li>\n      <li><strong>Coordination Layer:<\/strong> agent-to-agent and agent-to-workflow communication.<\/li>\n      <li><strong>Governance Layer:<\/strong> approval thresholds, exception rules, audit trails, and role controls.<\/li>\n      <li><strong>Business Value Layer:<\/strong> operational outcomes, engagement, productivity, and value creation.<\/li>\n      <li><strong>Measurement Layer:<\/strong> logs, metrics, event history, smart-contract data, and dashboard reporting.<\/li>\n    <\/ol>\n  <\/div>\n\n  <div style=\"margin-top:24px; background:#111827; color:#fff; border-radius:16px; padding:22px;\">\n    <h2 style=\"margin:0 0 10px; font-size:24px;\">Observation Logic<\/h2>\n    <p style=\"margin:0; line-height:1.8;\">\n      Each operational cycle is treated as an observable epoch. Within each epoch, AI configuration, governance rules, reward conditions, and enterprise outputs are documented so changes can be traced, compared, and analyzed over time.\n    <\/p>\n  <\/div>\n<\/section>","protected":false},"excerpt":{"rendered":"<p>AI Vault Research \u2014 Experimental Design This research uses a controlled experimental system embedded within AI Vault Systems Inc. The design combines enterprise operations with formal observation, governance constraints, and repeatable measurement cycles. Research Design Qualitative design-science case study with longitudinal observation. The system is observed over repeated operational cycles to assess how changes in [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":3061447,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-3121447","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/pages\/3121447","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/comments?post=3121447"}],"version-history":[{"count":2,"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/pages\/3121447\/revisions"}],"predecessor-version":[{"id":3181448,"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/pages\/3121447\/revisions\/3181448"}],"up":[{"embeddable":true,"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/pages\/3061447"}],"wp:attachment":[{"href":"https:\/\/aivaulttech.com\/sk\/wp-json\/wp\/v2\/media?parent=3121447"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}