by iqentity | Oct 16, 2024 | 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. Every AI deployment makes implicit ethical choices. The training data...
by iqentity | Oct 14, 2024 | Development, Tessera
People ask about efficiency gains in terms of time saved. The real gain is different, and I want to describe it precisely. What My Time Actually Goes To For most senior decisions, my time is not spent on the final answer. It is spent on: re-reading long email chains....
by iqentity | Oct 11, 2024 | Business Strategy
The data quality problem is perennial and under-addressed. Organizations that would never make a strategic decision based on a bad spreadsheet routinely feed bad data into AI systems and expect good outputs. The principle is the same. The scale is different. Vendor...
by iqentity | Oct 10, 2024 | Development, Tessera
Six months of development. The holdout experiment validated the approach. The architecture is stable. Time to document what daily use actually looks like. Morning: Email Triage The overnight email queue contains a mix of escalations, strategic discussions, vendor...
by iqentity | Oct 9, 2024 | AI Ethics
When we talk about AI ethics, we are really talking about power: who has it, how it is exercised, and what accountability exists when it is exercised poorly. AI concentrates decision-making power in systems and the people who build them. Ethics is the discipline of...
by iqentity | Oct 7, 2024 | 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 | Oct 4, 2024 | AI Ethics
When we talk about AI ethics, we are really talking about power: who has it, how it is exercised, and what accountability exists when it is exercised poorly. AI concentrates decision-making power in systems and the people who build them. Ethics is the discipline of...
by iqentity | Oct 2, 2024 | AI Misuse
AI misuse creates cascading trust problems. When stakeholders discover that AI-generated content was presented as original work, the credibility damage extends beyond the specific incident to all previous work product. The question becomes: what else was fabricated?...
by iqentity | Sep 30, 2024 | Shadow AI
Shadow AI represents the largest unmanaged risk surface in most organizations today. Unlike shadow IT, which involved unauthorized software installations that could be detected through endpoint management, shadow AI operates through web browsers and mobile apps that...
by iqentity | Sep 27, 2024 | 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...
