Professional Biography
Image of Divya Taneja

Divya Taneja Counsel

  • Seattle

    D +1.206.359.3427

    F +1.206.359.9000

    Seattle

    1201 Third Avenue, Suite 4900

    Seattle, WA 98101-3099

    +1.206.359.3427

    DTaneja@perkinscoie.com

  • New York

    D +1.332.223.3935

    F +1.212.977.1649

    New York

    1155 Avenue of the Americas, 22nd Floor

    New York, NY 10036-2711

    +1.332.223.3935

    DTaneja@perkinscoie.com

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Overview

Experience

News

Insights

  • 05.18.2023
    Buy Today, Gone Tomorrow: Is a “Buy” Button for Digital Content Deceptive?
    Blogs
    As digital media continues to supplant physical media, e-commerce sites offering digital content have experienced unprecedented growth.
  • 01.12.2023
    Notes From the Field: Digital Hollywood at CES 2023
    Blogs
    Last week, we attended Digital Hollywood, a one-day, in-person conference that is part of CES and focuses on how technology is transforming the entertainment industry.
  • 06.2022
    Fundamentals of Non-Fungible Tokens

    White Papers

    Non-fungible tokens have been widely adopted across a variety of industries. The fast-developing NFT ecosystem of technical and commercial innovation is aimed at the promise of bridging physical world concepts of uniqueness and scarcity with the digital world.
  • 09.2020
    Combating Bias in Artificial Intelligence and Machine Learning Used in Healthcare

    White Papers

    In this white paper, the authors discuss the legal concerns arising from the potential bias manifestations in ML algorithms used in the healthcare context under U.S. law. They briefly describe the legal landscape governing algorithmic bias in the United States and offer some emerging tools that build on existing recommended best practices, such as adversarial debiasing and the use of synthetic data for detecting, avoiding, and mitigating algorithmic bias
  • 08.31.2020
    How to Mitigate Algorithmic Bias in Healthcare
    Articles
    Artificial intelligence (AI) has the promise to revolutionize healthcare with machine learning (ML) techniques to predict patient outcomes and personalize patient care, but use of AI carries legal risks, including algorithmic bias, that can affect outcomes and care.

RELATED INFORMATION

Bar and Court Admissions

  • Washington
  • New York

Education

  • University of Michigan Law School, J.D., 2016, Business Development Editor, Michigan Journal of International Law
  • Duke University, B.A., Psychology, with distinction, magna cum laude, 2013, Editorial Board Member, The Chronicle