Responsible (use of) AI

Area of Science:

• Artificial Intelligence (AI) Ethics
• Human-Computer Interaction
• AI Safety and Governance

Background:

• Traditional philosophical definitions of ethics applied to human behavior face challenges when extended to artificial intelligence (AI).
• Attributing inherent ethical characteristics to AI can foster unrealistic expectations and potential risks.
• A shift towards researching the practical, ethical application of AI throughout its lifecycle is necessary.

Purpose of the Study:

• To highlight the difficulties in applying human ethical frameworks directly to AI.
• To advocate for a research agenda focused on the responsible development and deployment of AI.
• To propose key areas for advancing ethical AI practices.

Main Methods:

• The study advocates for a proactive research approach rather than reactive ethical considerations.
• It emphasizes a multi-faceted strategy encompassing education, transparency, design, and operational monitoring.
• The authors propose five key research directions for ethical AI.

Main Results:

• Directly applying human ethics to AI is fraught with challenges due to AI's nature.
• Five critical research areas are identified: AI ethics education, model transparency (model cards/datasheets), human-centered design, runtime assurance, and human-AI co-creation.
• These areas aim to foster responsible AI development and deployment.

Conclusions:

• AI cannot be inherently "ethical" in the human sense; focus must be on ethical use and development.
• Implementing transparency, human-centered design, and runtime assurance are crucial for mitigating AI risks.
• Continued research in these five areas is essential for ensuring AI systems align with human values and societal good.