Resources

Assessing Potential Future AI Risks, Benefits, and Policy Imperatives OECD

AI, Risk Management, Technical and Organisational Measures (TOMs)

Reducing Risks Posed by Synthetic Content by NIST

AI, Risk Management, Technical and Organisational Measures (TOMs)

CAIDP Responds to Outcome of U.S. Convening of AI Safety Institutes

AI, Risk Management, Technical and Organisational Measures (TOMs)

Guidelines on Securing AI Systems by The Cyber Security Agency of Singapore (CSA)

AI, Risk Management, Specific processing situations

Case C‑21/23 CJEU (full text in german)

Controllers and Processors, Data Breaches, Health Data, Lawfulness of Processing, Principles, Sensitive Data

Press Release No 159/24 on Judgment of the Court in Case C-21/23 CJEU

Controllers and Processors, Data Breaches, Health Data, Lawfulness of Processing, Principles, Sensitive Data

Cyber Threat Modelling for Risk Assessment by CSB

Risk Management, Technical and Organisational Measures (TOMs)

Chief Information Security Officer_ HANDBOOK

Risk Management

“AI & Algorithmic Risks Report” by Dutch Data Protection Authority

AI, Risk Management, Specific processing situations

NIST Special Publication NIST SP 800-221A_Information and Communications Technology (ICT) Risk Outcomes Integrating ICT Risk Management Programs with the Enterprise Risk Portfolio

Risk Management

Artificial Intelligence and Machine Learning in Health Care and Medical Sciences Best Practices by Pitfalls Gyorgy J. Simon Constantin Aliferis Springer

AI, Health Data, Principles, Sensitive Data, Specific processing situations

National Strategy to Advance Privacy-Preserving Data Sharing and Analytics by the EO by the US President

Anonymisation, Controllers and Processors, Technical and Organisational Measures (TOMs)

DRAFT RISK ASSESSMENT REGULATIONS FOR CALIFORNIA PRIVACY PROTECTION AGENCY

Risk Management

Case C 683-2021

Data Controller, Data Processors, Joint Controllers

Guidelines for evaluating differential priavacy gurantees by NIST

Anonymisation, Controllers and Processors, Technical and Organisational Measures (TOMs)

Practice Guide to Anonymising Personal Data

Anonymisation, Controllers and Processors

Public Benefit and Privacy Panel for Health and Social Care (Guidance for applicants)

Health Data, Principles, Sensitive Data

C-272/19

Access Requests (DSAR), Data Controller, Data Subjects Rights, Definitions

C-319/20

Representation of data subjects

Effective Cyber Risk Management: A best practice governance guide for digitally secure and resilient organisations by Governance Institute of Australia

Risk Management, Technical and Organisational Measures (TOMs)

Case C‑461/22 CURIA

Data Controller, Definitions

Artificial Intelligence and Algorithms in Risk Assessment by the European Labour Authority

Risk Management

Case 4:23-cv-01110-P AHA v. Bacerra

Health Data, Principles, Sensitive Data

Generative Artificial Intelligence Risk Assessment by State of California Department of Technology

AI, Risk Management, Specific processing situations

Opinion 39/2021 on whether Article 58(2)(g) GDPR could serve as a legal basis for a supervisory authority to order ex officio the erasure of personal data, in a situation where such request was not submitted by the data subject |EPDB

Data Controller, Data Subjects Rights, Definitions

EDPB-EDPS Joint Opinion 1/2022 on the Proposal for a Regulation of the European Parliament and of the Council amending Regulation (EU) 2021/953 on a framework for the issuance, verification and acceptance of interoperable COVID-19 vaccination, test and recovery certificates (EU Digital COVID Certificate) to facilitate free movement during the COVID-19 pandemic |EPDB

Health Data, Principles, Sensitive Data

EDPB-EDPS Joint Opinion 03/2022 on the Proposal for a Regulation on the European Health Data Space

Health Data, Principles, Sensitive Data

Personal data breaches in the health sector: how to avoid them (and how to deal with them when they happen) by the UK ICO

Data Breaches, Health Data

Practice Guide to Anonymising Personal Data by Stiftung Dateschutz

Anonymisation

Fashion ID, 29 July 2019, C-40/17, ECLI:EU:C:2019:629

Data Controller, Data Processors

Unabhängiges Landeszentrum für Datenschutz Schleswig-Holstein v Wirtschaftsakademie Schleswig-Holstein GmbH, in the presence of Facebook Ireland Ltd (Case C-210/16).

Data Controller

GUIDE TO BASIC ANONYMISATION | PDPC Singapore

Anonymisation

Guidance on Anonymisation and Pseudonymisation | Irish DPC

Anonymisation

Opinion 05/2014 on Anonymisation Techniques | WP216

Anonymisation

UK MRC Identifiability, anonymisation and pseudonymisation

Anonymisation

Guidelines 07/2020 on the concepts of controller and processor in the GDPR

Data Controller, Data Processors, Definitions

Guidelines 04/2020 on the use of location data and contact tracing tools in the context of the COVID-19 outbreak

Health Data

Guidelines 03/2020 on the processing of data concerning health for the purpose of scientific research in the context of the COVID-19 outbreak

Health Data

Rules of Procedure by EDPB on the cooperation and respective roles of national SAs and the EDPB Secretariat regarding the submission of complaints in the redress mechanism available to EU individuals in relation to alleged violations of U.S law with respect to their data collected by U.S. authorities competent for national security

Adequacy Decisions, Data Transfers, Risk Management

Artificial Intelligence Risk Management Framework by NIST: Generative Artificial Intelligence Profile

AI, Risk Management, Specific processing situations

Building a Cybersecurity and Privacy Learning Program | NIST | Initial Public Draft

Data Breaches, Employment, Risk Management, Technical and Organisational Measures (TOMs)

Anonymisation: managing data protection risk code of practice | UK ICO

Anonymisation

Spanish AEPD: 10 MISUNDERSTANDINGS RELATED TO ANONYMISATION

Anonymisation

Board of Directors Handbook for Cloud Risk Governance | Google

Risk Management

The EDPB data protection guide for small business

AI, Risk Management

Approach to Data Spaces from GDPR Perspective (AEPD)

Data Spaces, Risk Management