• Skip to main content
  • Skip to primary sidebar
  • Skip to footer
  • Core Principles of Responsible AI
    • Accountability
    • Fairness
    • Privacy
    • Safety and Security
    • Sustainability
    • Transparency
  • Special Topics
    • AI in Industry
    • Ethical Implications
    • Human-Centered Design
    • Regulatory Landscape
    • Technical Methods
  • Living Dictionary
  • State of AI Ethics
  • AI Ethics Brief
  • 🇫🇷
Montreal AI Ethics Institute

Montreal AI Ethics Institute

Democratizing AI ethics literacy

Green Lighting ML: Confidentiality, Integrity, and Availability of Machine Learning Systems in Deployment

July 19, 2020

Get the paper in PDF formDownload

Authors: Abhishek Gupta, Erick Galinkin

Abstract

Security and ethics are both core to ensuring that a machine learning system can be trusted. In production machine learning, there is generally a hand-off from those who build a model to those who deploy a model. In this hand-off, the engineers responsible for model deployment are often not privy to the details of the model and thus, the potential vulnerabilities associated with its usage, exposure, or compromise.

Techniques such as model theft, model inversion, or model misuse may not be considered in model deployment, and so it is incumbent upon data scientists and machine learning engineers to understand these potential risks so they can communicate them to the engineers deploying and hosting their models. This is an open problem in the machine learning community and in order to help alleviate this issue, automated systems for validating privacy and security of models need to be developed, which will help to lower the burden of implementing these hand-offs and increasing the ubiquity of their adoption.

Get the paper in PDF formDownload
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

Canada’s Minister of AI and Digital Innovation is a Historic First. Here’s What We Recommend.

Am I Literate? Redefining Literacy in the Age of Artificial Intelligence

AI Policy Corner: The Texas Responsible AI Governance Act

AI Policy Corner: Singapore’s National AI Strategy 2.0

AI Governance in a Competitive World: Balancing Innovation, Regulation and Ethics | Point Zero Forum 2025

related posts

  • Response to the European Commission’s white paper on AI (2020)

    Response to the European Commission’s white paper on AI (2020)

  • Anthropomorphized AI as Capitalist Agents: The Price We Pay for Familiarity

    Anthropomorphized AI as Capitalist Agents: The Price We Pay for Familiarity

  • AI and Marketing: Why We Need to Ask Ethical Questions

    AI and Marketing: Why We Need to Ask Ethical Questions

  • AI Ethics: Inclusivity in Smart Cities

    AI Ethics: Inclusivity in Smart Cities

  • The Ethics of AI in Medtech: A Discussion With Abhishek Gupta

    The Ethics of AI in Medtech: A Discussion With Abhishek Gupta

  • What has been published about ethical and social science considerations regarding the pandemic outbr...

    What has been published about ethical and social science considerations regarding the pandemic outbr...

  • The Canada Protocol: AI checklist for Mental Health & Suicide Prevention

    The Canada Protocol: AI checklist for Mental Health & Suicide Prevention

  • On the Construction of Artificial Moral Agents Agents

    On the Construction of Artificial Moral Agents Agents

  • How Kathleen Siminyu created Kenya’s go-to space for Women in Machine Learning

    How Kathleen Siminyu created Kenya’s go-to space for Women in Machine Learning

  • 3 activism lessons from Jane Goodall you can apply in AI Ethics

    3 activism lessons from Jane Goodall you can apply in AI Ethics

Partners

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

  • Partnership on AI

  • The LF AI & Data Foundation

  • The AI Alliance

Footer

Categories


• Blog
• Research Summaries
• Columns
• Core Principles of Responsible AI
• Special Topics

Signature Content


• The State Of AI Ethics

• The Living Dictionary

• The AI Ethics Brief

Learn More


• About

• Open Access Policy

• Contributions Policy

• Editorial Stance on AI Tools

• Press

• Donate

• Contact

The AI Ethics Brief (bi-weekly newsletter)

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.


Archive

  • © MONTREAL AI ETHICS INSTITUTE. All rights reserved 2024.
  • 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.