Hammer or Measuring Tape? Artificial Intelligence and Justice in Healthcare.

Area of Science:

• Medical Ethics
• Health Informatics
• Artificial Intelligence

Background:

• Artificial intelligence (AI) offers significant potential for optimizing predictive models in healthcare.
• The integration of AI into medical decision-making raises ethical questions, particularly concerning the principle of justice.
• Existing ethical frameworks may not adequately address the nuances introduced by AI in healthcare.

Purpose of the Study:

• To demonstrate the need for amending the principle of justice in healthcare due to AI's impact.
• To explore how research into algorithmic fairness can inform ethical adjustments.
• To propose a combined approach using procedural methods and AI tools to enhance justice in healthcare.

Main Methods:

• Analysis of the "accountability for reasonableness" conception of justice.
• Review of research on algorithmic fairness and its implications for differential effects.
• Conceptual integration of procedural justice with AI-driven impact measurement.

Main Results:

• The procedural approach to justice is insufficiently sensitive to the differential impacts of AI on various population groups.
• Algorithmic fairness research provides methods to quantify and correct these differential effects.
• AI tools can be used to mitigate justice issues by revealing the real-world impact of distributional principles.

Conclusions:

• The principle of justice in healthcare requires adaptation to accommodate AI's influence on decision-making.
• A hybrid approach, combining procedural justice with AI-based impact assessment, is necessary for equitable healthcare.
• AI is not only a source of ethical challenges but also a tool for achieving greater fairness in medicine.