• Skip to main content
  • Skip to secondary menu
  • Skip to primary sidebar
  • Skip to footer
Montreal AI Ethics Institute

Montreal AI Ethics Institute

Democratizing AI ethics literacy

  • Articles
    • Public Policy
    • Privacy & Security
    • Human Rights
      • Ethics
      • JEDI (Justice, Equity, Diversity, Inclusion
    • Climate
    • Design
      • Emerging Technology
    • Application & Adoption
      • Health
      • Education
      • Government
        • Military
        • Public Works
      • Labour
    • Arts & Culture
      • Film & TV
      • Music
      • Pop Culture
      • Digital Art
  • Columns
    • AI Policy Corner
    • Recess
    • Tech Futures
  • The AI Ethics Brief
  • AI Literacy
    • Research Summaries
    • AI Ethics Living Dictionary
    • Learning Community
  • The State of AI Ethics Report
    • Volume 7 (November 2025)
    • Volume 6 (February 2022)
    • Volume 5 (July 2021)
    • Volume 4 (April 2021)
    • Volume 3 (Jan 2021)
    • Volume 2 (Oct 2020)
    • Volume 1 (June 2020)
  • About
    • Our Contributions Policy
    • Our Open Access Policy
    • Contact
    • Donate

Research summary: Comparing Privacy Law GDPR Vs CCPA

August 17, 2020

Summary contributed by Sundar Narayanan, Director at Nexdigm and ethics & compliance professional.

*Authors of full paper & link at the bottom


Mini-summary: The paper is a summary of key similarities and distinctions between GDPR and CCPA. The paper analyses these similarities and distinctions in areas including scope, definitions, legal, rights and enforcement areas. 

The scope is fairly inconsistent, definitions are fairly consistent, legal grounds are inconsistent, rights are fairly consistent in some cases and enforcement is inconsistent. These analyses are based on the regulations themselves.


Full summary:

The paper details out the key differences between the two regulations. The similarities and differences are classified in the following areas:

  1. Scope
  2. Definitions
  3. Legal Basis
  4. Rights
  5. Enforcement

Scope: The section covers personal scope, territorial scope and material scope. 

AspectDegree of similarityRemarks
Personal scopeFairly inconsistentBoth apply to natural persons. CCPA applies to only residents and only for profit entities unlike GDPR which applies to even non profit entities
Territorial scopeFairly inconsistentCCPA stresses on doing business in california, while GDPR is applicable for companies outside EU also to the extent they have access to data of data subjects from EU
Material scopeFairly consistentDefinitions of personal data and processing have similarities. CCPA has exclusions for medical info, info regarding clinical trials etc, unlike GDPR which does not have such differences

Definitions: The section covers the key definitions including personal data, pseudonymisation, controllers, processors etc

AspectDegree of similarityRemarks
Personal dataFairly consistentBoth have consistent definitions of personal info and do not apply to anonymised/ de identified data. CCPA does not apply to publicly available information, unlike GDPR. Similarly, GDPR prohibits processing of special categories of personal data, unlike CCPA, which does not have such definitions
PseudonymisationFairly consistentBoth have consistent definitions of Pseudonymisation. CCPA defines that reidentification is not required if information to link the same as personal information not maintained, unlike GDPR
Controllers & processorsFairly consistentBoth have consistent definitions including data processor/ service provider, binding / written contracts,right to deletion and misuse of personal info. GDPR imposes obligations of privacy impact assessment, appointing DPO and notification of breaches, which are not there clearly in CCPA 

Legal: This section deals with legal grounds for processing

AspectDegree of similarityRemarks
Legal groundsInconsistentGDPR limits data controllers from processing data when there is a legal ground (consent, contractual obligation etc) for it, unlike CCPA, which requires consent when there is a financial incentive out of the personal info 

Rights: This section covers right to erasure, right to be informed right to object and right of access

AspectDegree of similarityRemarks
Right to erasureFairly consistentBoth have the scope that extends beyond data collectors to third parties to whom data is sold or passed on, expresses that the right is free of cost and mandates mechanisms for compliance. However both regulations have differences in lead time to respond to such requests. 
Right to be informedFairly consistentBoth mandate that data controllers cannot process data for purposes for which it is collected. 
Right to objectFairly inconsistentRight to opt out in CCPA is an absolute right and cannot be withdrawn. Further in CCPA the right is limited to selling or disclosing of the data and not for processing unlike GDPR.
Right of accessFairly inconsistentBoth express that the businesses must have in place mechanisms to enable such requests. CCPA has limitation of time of data collected (12 months), unlike GDPR
Right not to be discriminatedInconsistentCCPA provides that consumers must not be discriminated against for exercising their rights including being denied goods or services, charged differential prices or providing different quality of service. Such provision does not exist in GDPR
Right to data portabilityFairly consistentBoth reflect that the data shall be portable in readily usable format free of charge

Enforcement: This section covers monetary penalties and civil remedies for individuals

AspectDegree of similarityRemarks
Monetary penaltyInconsistentThe penalties are varied with CCPA defining it at a violation level, while GDPR expresses it as a proportion of overall turnover.
Civil remediesInconsistentCCPA allows the remedy only when non-encrypted or nonredacted personal information is subject to an unauthorized access, unlike GDPR which can get triggered for any violation. 

Original paper by:

  • DataGuidance: Alice Marini, Alexis Kateifides, Joel Bates
  • Future of Privacy Forum: Gabriela Zanfir-Fortuna, Michelle Bae, Stacey Gray, Gargi Sen
  • Link to paper: https://arxiv.org/ftp/arxiv/papers/2006/2006.16179.pdf
Want quick summaries of the latest research & reporting in AI ethics delivered to your inbox? Subscribe to the AI Ethics Brief. We publish bi-weekly.

Primary Sidebar

🔍 SEARCH

Spotlight

This image is a collage with a colourful Japanese vintage landscape showing a mountain, hills, flowers and other plants and a small stream. There are 3 large black data servers placed in the bottom half of the image, with a cloud of black smoke emitting from them, partly obscuring the scenery.

Tech Futures: Crafting Participatory Tech Futures

A network diagram with lots of little emojis, organised in clusters.

Tech Futures: AI For and Against Knowledge

A brightly coloured illustration which can be viewed in any direction. It has many elements to it working together: men in suits around a table, someone in a data centre, big hands controlling the scenes and holding a phone, people in a production line. Motifs such as network diagrams and melting emojis are placed throughout the busy vignettes.

Tech Futures: The Fossil Fuels Playbook for Big Tech: Part II

A rock embedded with intricate circuit board patterns, held delicately by pale hands drawn in a ghostly style. The contrast between the rough, metallic mineral and the sleek, artificial circuit board illustrates the relationship between raw natural resources and modern technological development. The hands evoke human involvement in the extraction and manufacturing processes.

Tech Futures: The Fossil Fuels Playbook for Big Tech: Part I

Close-up of a cat sleeping on a computer keyboard

Tech Futures: The threat of AI-generated code to the world’s digital infrastructure

related posts

  • Going public: the role of public participation approaches in commercial AI labs

    Going public: the role of public participation approaches in commercial AI labs

  • Research summary: Roles for Computing in Social Change

    Research summary: Roles for Computing in Social Change

  • The State of AI Ethics Report (Volume 6)

    The State of AI Ethics Report (Volume 6)

  • The State of AI Ethics Report (Volume 5)

    The State of AI Ethics Report (Volume 5)

  • Intersectional Inquiry, on the Ground and in the Algorithm

    Intersectional Inquiry, on the Ground and in the Algorithm

  • Unsolved Problems in ML Safety

    Unsolved Problems in ML Safety

  • Embedding Values in Artificial Intelligence (AI) Systems

    Embedding Values in Artificial Intelligence (AI) Systems

  • Ethics and Governance of Trustworthy Medical Artificial Intelligence

    Ethics and Governance of Trustworthy Medical Artificial Intelligence

  • The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization

    The Challenge of Understanding What Users Want: Inconsistent Preferences and Engagement Optimization

  • Use case cards: a use case reporting framework inspired by the European AI Act

    Use case cards: a use case reporting framework inspired by the European AI Act

Partners

  •  
    U.S. Artificial Intelligence Safety Institute Consortium (AISIC) at NIST

  • Partnership on AI

  • The LF AI & Data Foundation

  • The AI Alliance

Footer


Articles

Columns

AI Literacy

The State of AI Ethics Report


 

About Us


Founded in 2018, the Montreal AI Ethics Institute (MAIEI) is an international non-profit organization equipping citizens concerned about artificial intelligence and its impact on society to take action.

Contact

Donate


  • © 2025 MONTREAL AI ETHICS INSTITUTE.
  • This work is licensed under a Creative Commons Attribution 4.0 International License.
  • Learn more about our open access policy here.
  • Creative Commons License

    Save hours of work and stay on top of Responsible AI research and reporting with our bi-weekly email newsletter.