Boje (2026) · New Mexico State University
Rate yourself on 25 items across the four XYZA dimensions plus Ghost Vortex Awareness. Your score locates you in the tesseract — and names the vortex risks you carry.
How to rate yourself: For each item, select the number that most honestly reflects your current leadership practice — not your aspirations or ideals, but what you actually do now.
There are no right or wrong answers. The inventory is most useful when answered quickly and honestly, without deliberation about what a "good leader" would say.
Rating scale:
How deliberately you set, track, and are held accountable for measurable AI performance results. High X without A = the Driving Vortex: efficiency as alibi for harm.
I set specific, measurable benchmarks for evaluating AI system performance in my organization or practice — and I review them regularly.
I hold myself directly and personally accountable for the outcomes of AI deployment decisions I authorize — not the algorithm, not the vendor, not the market.
When AI-assisted processes produce unexpected or harmful results, I conduct systematic reviews to understand what happened and document what I learn.
I establish clear, explicit criteria for what counts as success — and failure — before deploying an AI system, not after the results are in.
I can point to specific, quantifiable outcomes — both positive and negative — that AI has produced under my leadership in the past year.
How genuinely people-centered your AI governance is. High Y without structural change = the Feeling Vortex: empathy language as alibi for inaction.
I actively solicit input from the communities most affected by AI deployments — before implementing changes, not as a post-hoc consultation.
I can name the specific categories of people most likely to be disadvantaged by the AI systems I currently use or authorize.
I design AI-assisted processes so that human judgment is preserved at the most consequential decision points — hiring, firing, lending, medical, legal.
I create structured channels for AI-affected stakeholders to raise concerns — and I personally review what comes through those channels.
When AI recommendations conflict with human wellbeing, I have clear protocols for prioritizing the human dimension — and I enforce them even when it costs the organization.
How well you hold multiple possible futures simultaneously and make bets you acknowledge as uncertain. High Z without A = the Vision Vortex: futures as alibi for present harm.
I articulate at least three distinct possible futures for AI in my domain — not just the trajectory I am currently building toward.
I actively distinguish between what my AI systems are doing right now and what they are becoming — I monitor trajectory, not just current state.
I create organizational space for counter-narratives about AI direction — including narratives that challenge my own strategic vision for where AI is taking us.
I make explicit bets on AI futures that I acknowledge as uncertain — rather than presenting our current direction as inevitable or obviously correct.
I regularly imagine the scenario in which my current AI direction turns out to be seriously wrong — and I plan for that contingency as seriously as I plan for success.
The Bakhtinian nealibi v bytii: refusing every institutional alibi. This is the dimension that makes the cube into a tesseract. Your A score directly determines your Ghost Vortex Depth: GVD = 3 − (A/6.67).
When AI systems I have authorized cause harm, I acknowledge personal responsibility — rather than attributing it to the algorithm, the vendor, the market, or competitive necessity.
I resist invoking competitive necessity as an alibi for AI deployment decisions that compromise safety, equity, or the wellbeing of people my organization is supposed to serve.
I can describe, in specific terms, the ideological premises embedded in the AI systems my organization uses — not just their technical capabilities.
I have identified at least one structural mechanism — not just a policy document — that limits my own power to deploy AI without an accountability review by others.
I can name the specific alibi I am most tempted to use when AI under my leadership causes harm — and I actively work to refuse it rather than polish its wording.
Can you see whose cave you are standing in? A leader who scores high on XYZA but low on GVA may be a capable leader in human contexts but dangerously susceptible to Eidolon Vortex conditions in AI-assisted environments.
I know whose AI platform I am using and can name the leader whose character, choices, and organizational culture shaped its training data and design philosophy.
I have specifically investigated whether the AI systems I use or deploy respond differently across racial, gender, socioeconomic, or other demographic categories — and I act on what I find.
When AI gives me strategic recommendations, I ask: whose interests does this advice structurally favor? Whose interests does it structurally work against?
For high-stakes decisions, I deliberately consult AI from more than one platform — specifically choosing platforms with different organizational premises and founding leaders.
I periodically ask the AI systems I use questions they should find difficult or uncomfortable — and I deliberately notice what they avoid, deflect, or flatten.
Answer all 25 items above, then calculate your score.