AI信頼性&SecurityResources
ディープフェイク検出、データプライバシー、バイアステスト、コンプライアンスフレームワーク、企業・開発者向けの責任あるAI実践。
A practical guide to spotting deepfake videos, images, and audio using both visual inspection and AI-powered detection tools.
Updated 2025-12-15
How criminals use deepfake audio and video to impersonate executives, authorize fraudulent transfers, and manipulate stock prices.
Updated 2026-01-20
Framework for organizations to prepare for, detect, and respond to deepfake attacks targeting their brand or leadership.
Updated 2025-11-08
How to ensure your AI models and data pipelines comply with GDPR requirements for data processing, consent, and the right to explanation.
Updated 2025-10-30
Best practices for collecting and using only the minimum data necessary to train effective AI models.
Updated 2025-09-15
Navigating the intersection of HIPAA compliance and AI-powered health tools, from diagnostics to patient communication.
Updated 2026-02-10
How AI-powered hiring tools can perpetuate discrimination and what companies must do to ensure fair screening.
Updated 2026-01-05
Research showing facial recognition AI performs unevenly across demographics, and technical approaches to close the accuracy gap.
Updated 2025-11-20
How AI credit scoring models can inadvertently discriminate and what regulators and lenders are doing about it.
Updated 2025-12-01
Understanding how attackers manipulate AI language models through carefully crafted inputs to bypass safety filters and extract sensitive data.
Updated 2026-02-28
How adversaries can corrupt AI models by injecting malicious data during training, and how to defend against these supply chain attacks.
Updated 2025-10-22
How attackers can reverse-engineer or clone your AI model through API queries, and strategies to prevent model theft.
Updated 2025-11-30
How tiny, imperceptible changes to images can cause AI vision systems to make catastrophically wrong predictions.
Updated 2025-09-30
A practical overview of the EU AI Act's risk-based framework, compliance timelines, and what it means for AI deployers worldwide.
Updated 2026-03-01
Step-by-step guide to establishing internal AI audit processes that satisfy regulatory requirements and build stakeholder trust.
Updated 2025-12-20
Emerging legal frameworks for AI liability, including the EU AI Liability Directive and the growing AI insurance market.
Updated 2026-01-15
How to create an effective AI ethics board that provides genuine oversight, not just corporate window dressing.
Updated 2025-10-10
How leading companies communicate their AI practices through transparency reports, and a template for creating your own.
Updated 2025-11-05
Understanding and mitigating the massive energy consumption and carbon emissions of training and running large AI models.
Updated 2026-02-05
Ensuring AI-powered products work equitably for people with disabilities, including those who rely on assistive technologies.
Updated 2025-12-10
Special considerations for AI systems that interact with or collect data from children, including COPPA compliance.
Updated 2026-01-25
Managing the risks of depending on third-party AI models and APIs that can change, disappear, or be compromised.
Updated 2025-11-15
A consumer guide to understanding how AI chatbots like ChatGPT, Claude, and Gemini handle your conversations and personal information.
Updated 2026-03-05
A curated guide to free, open-source tools for measuring and mitigating bias in your AI models.
Updated 2025-10-05
A comprehensive checklist covering all major AI regulations worldwide, including EU AI Act, NYC Local Law 144, and emerging state laws.
Updated 2026-03-10
AIセキュリティの脅威に先手を打つ
25 resources covering 6 critical categories, updated regularly.