Legal, Moral, and Ethical Implications of Machine Learning

Abstract

Machine learning (ML) algorithms can help to distill vast quantities of information to support decision making. However, ML also presents unique legal, moral, and ethical concerns - ranging from potential discrimination in personnel applications to misclassifying targets on the battlefield. Building on foundational principles in ethical philosophy, this Institute for Defense Analyses presentation summarizes key legal, moral, and ethical criteria applicable to ML and provides pragmatic considerations and recommendations. Addressing core legal and ethical concerns requires linking the ultimate action that an analysis plans to support with each step of the analysis. For instance, what data are appropriate to consider? Are the algorithm and the subsequent analysis effective for supporting the action? This presentation also highlights implementation steps to maintain responsible machine learning and artificial intelligence at both the organizational level and the level of individual workers and analysts.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 2022
Accession Number
AD1210693

Entities

People

  • Alan B. Gelder

Organizations

  • Institute for Defense Analyses

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Accountability
  • Algorithms
  • Artificial Intelligence
  • Civil Rights
  • Discrimination
  • Ethics
  • Executives
  • Human Rights
  • Law
  • Learning
  • Life Cycles
  • Machine Learning
  • Personnel Management
  • Philosophy
  • Special Forces
  • Training
  • Transparencies

Readers

  • Emergency Management and Homeland Security.
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy
  • AI & ML - Neural Networks