Essays

The architecture of meaning: How the tools we build shape what we think is possible

Tillich’s Ultimate Concern and the Idol of Productivity

Paul Tillich defined idolatry as elevating a finite thing to ultimate significance. When 61% of technology workers measure self-worth by productivity, productivity has become the industry's idol.

Ethics of AI-Assisted Decision Making in Government

Six government AI systems reviewed, none meeting transparency standards required of equivalent human processes. Public systems demand higher ethical standards, yet the opposite is often true.

The Absurdity of Optimizing Deprecated Systems

The average enterprise system lives 6.2 years before deprecation. Camus's absurdism reveals that meaning in engineering comes not from permanence but from the quality of the work itself.

Data Privacy Engineering Is a Data Engineering Discipline

Implementing tokenization and differential privacy at the pipeline level reduced PII exposure incidents by 89% while adding less than 3% to processing time.

The Ethics of AI Art Is a Labor Economics Problem

An estimated 26% of commercial illustration work has been displaced by AI image generation since 2023, with losses concentrated among early-career artists. This is a labor economics problem, not a copyright debate.

The Difference Between Data and Evidence

In a review of 30 data-driven proposals, 22 presented data as evidence without the analytical chain from observation to inference. The gap is analytical rigor.

The Regulatory Gap Between AI Capability and Governance

The average gap between AI capability deployment and regulatory response is 26 months. During that gap, organizations have a moral obligation to self-govern rather than exploit the vacuum.

Designing systems for resilience, not optimization

Red Teaming AI Systems Is Not Optional

Only 4 of 23 AI systems evaluated had undergone adversarial testing. Untested systems averaged 3.7 exploitable vulnerabilities including prompt injection and data extraction paths.