「risk」の検索結果

Assesses decision reversibility and risk at critical checkpoints. Use when a workflow reaches a high-stakes branch needing escalation check.

日本語の概要は準備中です。原文の説明を表示しています。

Use when checking a radiology or medical AI study design before drafting or submission. Reviews the analysis unit, cohort logic, leakage risks, comparator, validation strategy and reporting-guideline fit. AI-vs-expert benchmarks are /design-ai-benchmarking.

日本語の概要は準備中です。原文の説明を表示しています。

Use when running a systematic review and meta-analysis, DTA or intervention. Covers PROSPERO protocol, search, screening, extraction, risk of bias (QUADAS-3, RoB 2, ROBINS-I), bivariate/HSROC or random-effects pooling, forest plots, heterogeneity and PRISMA reporting. Topic scouting is /ma-scout.

日本語の概要は準備中です。原文の説明を表示しています。

Review an Agent Skill for valid structure, clear triggers, usable instructions, current evidence, and risky or unclear actions.

日本語の概要は準備中です。原文の説明を表示しています。

检查并修复短视频逐字稿的段落衔接、信息密度、口播节奏和观众流失风险。用户问稿子顺不顺、哪里容易被划走，或需要制作可直接拍摄的版本和标记式改稿时使用。 English: Check and improve short-video scripts for transitions, information density, spoken rhythm, and audience drop-off risk. Use when the user wants to know where viewers may leave, whether the script flows, or needs a shoot-ready or annotated revision.

日本語の概要は準備中です。原文の説明を表示しています。

GDPR Article 28(2) sub-processor approval workflow management. Covers prior specific and general authorization mechanisms, change notification procedures, objection windows, flow-down obligation enforcement, and sub-processor chain risk monitoring.

日本語の概要は準備中です。原文の説明を表示しています。

Conducts Privacy Impact Assessment for vendor and third-party data processing arrangements. Covers processor due diligence, Data Processing Agreement (DPA) requirements under GDPR Article 28, sub-processor management, cross-border vendor transfers, cloud service provider assessments, and ongoing vendor monitoring. Keywords: vendor PIA, processor assessment, DPA, Article 28, sub-processor, cloud privacy, third-party risk.

日本語の概要は準備中です。原文の説明を表示しています。

Guides privacy program effectiveness measurement including leading and lagging indicators, KPI definition, benchmarking methodology, executive reporting formats, board-level privacy dashboards, and metric-driven program improvement. Covers operational, compliance, risk, and strategic privacy metrics across the program lifecycle. Keywords: privacy metrics, KPIs, benchmarking, executive reporting, dashboard, program effectiveness.

日本語の概要は準備中です。原文の説明を表示しています。

Conducts pre-DPIA threshold screening to determine whether a full Data Protection Impact Assessment is required under GDPR Article 35. Applies the EDPB WP248rev.01 nine-criteria test, national supervisory authority blacklists, and organisational risk appetite to produce a documented screening decision. Keywords: threshold screening, DPIA trigger, pre-DPIA, WP248, Article 35(1), blacklist, screening decision.

日本語の概要は準備中です。原文の説明を表示しています。

Assesses the GDPR Article 30(5) exemption for organisations under 250 employees. Covers the three exception conditions that negate the exemption: non-occasional processing, risk to data subject rights, and special category data processing. Activate for Art. 30(5), 250 employee exemption, small business RoPA, SME exemption, occasional processing.

日本語の概要は準備中です。原文の説明を表示しています。

Implements HIPAA de-identification methods under 45 CFR §164.514(a)-(b). Covers expert determination method and safe harbor method with 18 identifiers removal, re-identification risk assessment, limited dataset requirements, and data use agreements. Keywords: HIPAA de-identification, safe harbor, expert determination, 18 identifiers, limited dataset, PHI.

日本語の概要は準備中です。原文の説明を表示しています。

Implements HIPAA breach notification requirements under 45 CFR §164.400-414. Covers individual notification within 60 days, HHS reporting thresholds (500+ immediate, under 500 annual), state attorney general notification, media notification for 500+ in a state, and breach risk assessment. Keywords: HIPAA breach notification, HHS reporting, OCR breach portal, individual notice, state attorney general.

日本語の概要は準備中です。原文の説明を表示しています。

Executes breach notification under HIPAA Breach Notification Rule (45 CFR 164.400-414). Covers 60-day individual notification, HHS/OCR reporting for breaches of 500+ individuals (immediate) and under 500 (annual log), state attorney general notification, media notification for 500+ in a single state, and breach risk assessment using the four-factor test. Keywords: HIPAA, breach notification, PHI, HHS, OCR, covered entity, business associate.

日本語の概要は準備中です。原文の説明を表示しています。

Guides internal privacy audit program design and execution including risk-based audit planning, scope definition, fieldwork procedures, finding classification, evidence gathering, remediation tracking, and management reporting. Covers audit universe definition, annual audit plan, working papers, and closure verification. Keywords: internal audit, privacy audit, fieldwork, remediation, findings, audit plan.

日本語の概要は準備中です。原文の説明を表示しています。

Guides privacy impact assessment for emerging technologies including IoT, blockchain, AR/VR, quantum computing, and digital twins. Covers risk identification methodology, proportionality assessment, and technology-specific privacy challenges. Activate when evaluating new technology adoption, innovation projects, or emerging tech procurement. Keywords: PIA, emerging technology, IoT, blockchain, AR/VR, quantum computing, digital twins, innovation privacy.

日本語の概要は準備中です。原文の説明を表示しています。

Manages the organisational DPIA register tracking all Data Protection Impact Assessments across the enterprise. Covers DPIA lifecycle management, status tracking, review scheduling, Art. 35(11) periodic reassessment, and supervisory authority reporting. Implements a centralised register linking DPIAs to RoPA entries, risk registers, and mitigation plans. Keywords: DPIA register, DPIA tracking, Art. 35(11), review schedule, DPIA lifecycle, centralised register, DPIA portfolio management.

日本語の概要は準備中です。原文の説明を表示しています。

Conducts a Data Protection Impact Assessment for automated decision-making and profiling systems under GDPR Article 35(3)(a), covering algorithmic transparency, meaningful human oversight, contestation mechanisms, and Art. 22 safeguards. Activate for DPIA automated decision, profiling DPIA, algorithmic impact assessment, Art. 35(3)(a), ADM risk assessment queries.

日本語の概要は準備中です。原文の説明を表示しています。

Guides conversion of gap analysis findings into phased implementation plans with milestones and risk-based prioritisation. Activate when building compliance programmes or allocating privacy budgets. Keywords: remediation roadmap, implementation plan, phased approach, prioritisation.

日本語の概要は準備中です。原文の説明を表示しています。

Complete guide to LINDDUN privacy threat modeling methodology covering seven threat categories: Linking, Identifying, Non-repudiation, Detecting, Data Disclosure, Unawareness, and Non-compliance. Includes DFD-based analysis, threat tree catalogs, mitigation mapping to privacy design patterns, and step-by-step process.

日本語の概要は準備中です。原文の説明を表示しています。

Cloud service provider privacy assessment framework. Covers ISO 27018 cloud privacy controls, CSA STAR certification, SOC 2 Type II evaluation, shared responsibility model mapping, data residency verification, and cloud-specific privacy risk analysis.

日本語の概要は準備中です。原文の説明を表示しています。

Guide for obtaining explicit consent for international data transfers under GDPR Article 49(1)(a). Covers informed consent requirements including risks of transfers without adequacy decisions or appropriate safeguards, specific destination country disclosure, and the narrow scope of derogation-based transfers.

日本語の概要は準備中です。原文の説明を表示しています。

Assesses AI bias risks for GDPR Art. 9 special category data and AI Act Art. 10 data governance. Covers fairness metrics, bias detection methods, mitigation strategies, and documentation requirements for protected characteristics. Keywords: AI bias, special category, fairness metrics, discrimination, Art. 9, Art. 10.

日本語の概要は準備中です。原文の説明を表示しています。

Determines controller-processor relationships for AI services and conducts privacy due diligence. Covers SaaS AI (processor), embedded AI (joint controller), API-based AI (assessment framework), and vendor risk assessment. Keywords: AI vendor, controller-processor, due diligence, SaaS AI, joint controller, Art. 28.

日本語の概要は準備中です。原文の説明を表示しています。

Managing privacy risks from AI-driven inferences about individuals including derived data classification, profiling under GDPR Art. 22, inference accuracy obligations, and controlling automated personality/behaviour predictions. Keywords: AI inference, derived data, profiling, automated predictions, GDPR.

日本語の概要は準備中です。原文の説明を表示しています。