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Artificial intelligence (AI) decision-support tools challenge responsibility by obscuring "decision ownership." This makes it difficult to attribute value judgments reflected in AI-assisted choices, focusing on attributability over accountability.

Keywords:
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Area of Science:

  • Philosophy of Technology
  • Artificial Intelligence Ethics
  • Human-Computer Interaction

Background:

  • Traditional AI responsibility discussions focus on autonomous systems like robots.
  • Most current AI functions as decision-support tools, analyzing data for human users.
  • Existing frameworks struggle to assign accountability for AI-driven actions.

Purpose of the Study:

  • To explore the unique challenges artificial intelligence (AI) decision-support tools pose to responsibility.
  • To introduce the concept of "decision ownership" in the context of AI.
  • To differentiate the problem of attributability from accountability in AI-assisted decision-making.

Main Methods:

  • Analysis of philosophical literature on responsibility and its facets.
  • Examination of AI as a decision-support tool, not an autonomous agent.
  • Distinguishing between AI providing recommendations versus descriptive information.

Main Results:

  • AI decision-support tools create a novel challenge related to "decision ownership."
  • It is difficult to attribute value judgments to human agents when using AI tools.
  • The primary issue is one of attributability (who made the value judgment) rather than accountability (who is to blame).

Conclusions:

  • AI decision-support tools complicate the attribution of responsibility beyond traditional accountability concerns.
  • Understanding AI's impact on decision ownership is crucial for ethical AI development.
  • The challenge extends to AI providing recommendations and mere descriptive information.