How to establish AI ethics

Artificial intelligence operates in accordance with its design, development, training, tuning, and application. AI ethics is fundamentally about constructing an ethical framework and setting up guardrails that permeate every phase of an AI system’s lifecycle.

Organizations, governments, and researchers are actively collaborating to develop comprehensive frameworks to address current AI ethical concerns and to shape the future trajectory of the field. While these guidelines are continually being refined and structured, there is a growing consensus on the importance of incorporating the following principles:

Governance: Governance is the strategic oversight that an organization exercises over the AI lifecycle, encompassing internal policies, processes, personnel, and systems. It ensures that AI systems operate in alignment with the organization’s principles and values, meet stakeholder expectations, and comply with relevant regulations.

Principles: An organization’s approach to AI ethics can be guided by principles that can be applied to products, policies, processes, and practices throughout the organization to help enable trustworthy AI. These principles should be structured around and supported by focus areas, such as explainability or fairness, around which standards can be developed and practices can be aligned. When AI is built with ethics at the core, it holds the potential to profoundly impact society for the better. We’ve already begun to witness this in its integration into critical areas of healthcare, such as radiology. The conversation around AI ethics is not only important but essential for appropriately assessing and mitigating possible risks related to AI’s uses, beginning right from the design phase.