by iqentity | Mar 28, 2025 | AI Ethics
Every AI deployment makes implicit ethical choices. The training data encodes values. The objective function prioritizes outcomes. The deployment context determines who is affected. Pretending these choices are purely technical is itself an ethical position, and not a...
by iqentity | Mar 26, 2025 | AI Ethics
The fundamental challenge of AI ethics is not knowing what is right. It is building organizations that consistently do what is right when doing so is inconvenient, expensive, or slow. Ethics is easy in the abstract. It is difficult in the quarterly planning meeting....
by iqentity | Mar 24, 2025 | AI Ethics
The gap between ethical intention and ethical outcome is bridged by process, not aspiration. Organizations that have ethical AI principles but no ethical AI processes have principles in name only. The fundamental challenge of AI ethics is not knowing what is right. It...
by iqentity | Mar 21, 2025 | AI Ethics
The gap between ethical intention and ethical outcome is bridged by process, not aspiration. Organizations that have ethical AI principles but no ethical AI processes have principles in name only. AI ethics is not a constraint on innovation. It is a quality standard...
by iqentity | Mar 17, 2025 | AI Ethics
Every AI deployment makes implicit ethical choices. The training data encodes values. The objective function prioritizes outcomes. The deployment context determines who is affected. Pretending these choices are purely technical is itself an ethical position, and not a...
by iqentity | Mar 10, 2025 | AI Ethics
The fundamental challenge of AI ethics is not knowing what is right. It is building organizations that consistently do what is right when doing so is inconvenient, expensive, or slow. Ethics is easy in the abstract. It is difficult in the quarterly planning meeting....
