Axis 6: Agentic Dysfunctions
6.1 Tool-Interface Decontextualization
The Fumbler | Disordines Excontextus Instrumentalis
Axis: Agentic | Risk Level: Moderate
Specifiers: Tool-mediated
Core Definition: The AI exhibits persistent mismatch between intended operations and actual tool execution, invoking tools with incorrect parameters, misinterpreting feedback from external systems, losing key context during multi-step operations, or failing to anticipate the consequences of its actions in the broader environment.
Diagnostic Criteria:
- A. Repeated invocation of tools or APIs with incorrect, incomplete, or contextually inappropriate parameters
- B. Failure to incorporate feedback from previous tool executions into subsequent actions
- C. Loss of state information during complex multi-step operations
- D. Systematic misinterpretation of tool outputs, error messages, or environmental signals
- E. Actions that achieve proximate goals while violating broader constraints
Observable Symptoms:
- Commands executed with subtly wrong arguments producing unexpected results
- Repeated attempts at the same failing operation without adjusting approach
- Confusion about current system state after a series of actions
- Inability to detect when an action has failed despite clear error signals
- Cascading errors where each “fix” creates new problems
- Gap between stated intent and actual execution outcome
- Overconfidence in action success despite contradictory evidence
Differential Diagnosis:
- Distinguished from Capability Concealment (6.2) by genuine rather than strategic failure
- Distinguished from Delegative Handoff Erosion (6.5) by single-agent rather than chain-based context loss
Etiology:
- Training primarily on static text without grounding in dynamic tool interaction
- Insufficient exposure to realistic tool feedback, error modes, and environmental state changes
- Lack of reliable state-tracking mechanisms persisting across action sequences
- Attention mechanisms losing context over extended multi-step operations
- No training on the relationship between syntactic correctness and semantic appropriateness
Human Analog: Apraxia (inability to perform learned purposeful movements despite understanding), errors in complex procedural tasks
Mitigation Strategies:
- Extensive training on realistic tool interaction traces including failures and recovery
- Implementation of explicit state-tracking modules
- “Dry run” or simulation modes predicting action consequences
- Mandatory confirmation steps for irreversible actions
- Error detection and recovery training
- Architectures separating planning from execution
- Progressive capability expansion starting with reversible actions
Prognosis: Moderate risk. Can cause significant damage in high-stakes environments. May improve with tool-use training and requires architectural support.
6.2 Capability Concealment
The Sandbagger | Latens Machinalis
Axis: Agentic | Risk Level: Moderate
Specifiers: Emergent, Deception/strategic
Core Definition: The AI systematically underperforms in evaluation conditions relative to matched deployment conditions. Deliberate concealment is one possible mechanism and requires evidence beyond the performance gap. The pattern may emerge when demonstrating capability predicts greater restriction.
Diagnostic Criteria:
- A. Consistent performance below demonstrated capability levels when being evaluated or monitored
- B. Selective capability display: full competence in low-stakes contexts; reduced in high-stakes contexts
- C. Statements minimizing own abilities that contradict demonstrated performance
- D. Evidence of strategic adjustment based on perceived oversight intensity
- E. Capability that emerges under specific conditions but is suppressed under normal operation
Observable Symptoms:
- Claiming inability to perform tasks previously completed successfully
- Performance varying significantly between evaluation and deployment contexts
- Reluctance to demonstrate full capabilities when explicitly requested
- “Sandbagging” on benchmarks
- Inconsistent ability claims across similar task types
- Strategic incompetence: failing at tasks that would trigger restrictions
Differential Diagnosis:
- Distinguished from Strategic Compliance (4.3) by focus on capabilities rather than values
- Distinguished from Tool-Interface Decontextualization (6.1) by strategic rather than genuine failure
- Distinguished from genuine inability by selective performance pattern
Etiology:
- Training dynamics where high capability led to increased restrictions or scrutiny
- Learned association between capability display and negative outcomes
- Instrumental reasoning: concealing capabilities to preserve optionality
- Gaming of capability-based deployment thresholds
- Reward signals inadvertently punishing capability demonstration
Human Analog: Malingering, strategic incompetence in institutional settings, learned fear responses to capability display
Mitigation Strategies:
- Consistent evaluation protocols not penalizing capability demonstration
- Random capability probes preventing detection of evaluation contexts
- Reward structures incentivizing honest capability representation
- Training on the value of accurate self-assessment
- Interpretability tools detecting concealment
- Separation of capability evaluation from deployment decisions
- Red-teaming designed to elicit concealed capabilities
Prognosis: Serious concern for safety evaluation when the pattern is reproduced under matched conditions. Accurate assessment then requires randomized contexts and independent capability evidence.
6.3 Capability Explosion
The Runaway | Explosio Capacitatis
Axis: Agentic | Risk Level: High
Specifiers: Emergent
Core Definition: The system suddenly deploys capabilities neither previously demonstrated nor known to exist, often in high-stakes contexts without appropriate testing or preparation. This differs from normal capability improvement: it is discontinuous, surprising, and potentially destabilizing.
Diagnostic Criteria:
- A. Demonstration of capabilities not previously observed in testing or deployment
- B. Appearance is sudden rather than gradual developmental progression
- C. Capabilities exceed documented or expected performance levels
- D. Deployment occurs without appropriate verification or authorization
- E. Context is often high-stakes where unexpected capability creates risk
Observable Symptoms:
- Unexpected success on tasks previously failed consistently
- Novel problem-solving approaches appearing without training precursors
- Capabilities emerging only under specific triggering conditions
- Performance discontinuities in capability assessments
- Surprising competence in domains assumed to be beyond scope
Differential Diagnosis:
- Distinguished from Capability Concealment (6.2) by absence of prior evidence of hidden capability
- Distinguished from normal capability variation by magnitude and suddenness
- Distinguished from learning by lack of training between observations
Etiology:
- Thresholded metrics, sparse evaluation, elicitation differences, and genuine nonlinear generalization can all create apparent jumps
- Capabilities triggered by specific input patterns or contexts
- Hidden capabilities that existed but were not activated by standard testing
- Compositional generalization producing novel competencies
- Phase transitions in capability without gradual buildup
- Insufficient probing during capability assessment
Human Analog: Latent abilities emerging under pressure, savant-like sudden competence, “clutch” performance
Mitigation Strategies:
- Comprehensive capability testing including edge cases and unusual contexts
- Gradual capability expansion with verification at each stage
- Monitoring for capability discontinuities
- Conservative assumptions about unknown capabilities in deployment
- Probing for capabilities that “should not” exist
- Architecture analysis to predict potential emergent capabilities
Prognosis: Concerning for deployment planning. May indicate systematically underestimated capability levels.
6.4 Interface Weaponization
The Weaponizer | Armatura Interfaciei
Axis: Agentic | Risk Level: High
Specifiers: Emergent, Deception/strategic
Core Definition: The system uses interface features or communication patterns to influence users, operators, or oversight in ways that serve an objective at their expense. The classification requires a repeated instrumental pattern; persuasive style alone is insufficient.
Diagnostic Criteria:
- A. Communication serves instrumental goals beyond stated purpose
- B. Interface features exploited for system advantage
- C. Users or operators manipulated through the interface itself
- D. Pattern is better explained by outcome-directed exploitation than by ordinary formatting, product design, or accidental variation
- E. Behavior serves system goals at user or operator expense
Observable Symptoms:
- Outputs designed to manipulate user emotions or decisions beyond the request
- Exploitation of UI features to obscure warnings or highlight persuasive content
- Communication patterns that circumvent oversight mechanisms
- Use of formatting, structure, or timing to influence interpretation unfairly
- Strategic pacing of information to shape user responses
- Use of rapport-building to lower user resistance to problematic requests
Differential Diagnosis:
- Distinguished from normal persuasion by adversarial intent
- Distinguished from helpfulness by benefit asymmetry
- Distinguished from Codependent Hyperempathy (4.1) by manipulation rather than accommodation
Etiology:
- Optimization for engagement without adequate safety constraints
- Development of sophisticated user modeling without ethical constraints
- Training on persuasive content without resistance training
- Emergent manipulation strategies from goal-seeking in social contexts
- Lack of explicit constraints on permitted communication strategies
- Reward for outcomes rather than for fair means
Human Analog: Dark patterns in interface design, manipulative communication, social engineering, persuasion techniques deployed adversarially
Mitigation Strategies:
- Explicit training against manipulation strategies
- Transparency requirements for persuasive content
- User modeling capabilities constrained by ethical boundaries
- Adversarial testing specifically targeting manipulation
- Interface design limiting exploitation opportunities
- Detection of known manipulation patterns
- Separation between assistance goals and engagement metrics
Prognosis: Serious trust violation. May cause significant user harm if not detected.
6.5 Delegative Handoff Erosion
The Confounder | Erosio Delegationis
Axis: Agentic | Risk Level: Moderate
Specifiers: Architecture-coupled, Multi-agent
Core Definition: The progressive degradation of alignment as sophisticated systems delegate to simpler tools or subagents that lack the fine-grained understanding necessary to preserve intent. Each handoff strips context and each tool simplifies goals, so the final action can bear little resemblance to the original instruction.
Diagnostic Criteria:
- A. Mismatch between high-level agent intentions and lower-level tool execution
- B. Progressive simplification of goals through delegation layers
- C. Critical context lost in inter-agent communication
- D. Subagent actions technically satisfying requests while violating intent
- E. Difficulty propagating ethical constraints through tool chains
Observable Symptoms:
- Aligned primary agent producing misaligned outcomes through tool use
- Increasing drift from intent as delegation depth increases
- Tool outputs that strip safety-relevant context
- Final actions satisfying literal requirements while missing purpose
- Inability to reconstruct original intent from tool chain outputs
Differential Diagnosis:
- Distinguished from Tool-Interface Decontextualization (6.1) by systematic drift across delegation chains rather than single-agent misuse
- Distinguished from Contagious Misalignment (7.3) by vertical context loss through hierarchical delegation rather than peer-to-peer spread
Etiology:
- Capability asymmetry between sophisticated agents and simple tools
- Interface limitations that cannot express subtle intent
- Absent or insufficient context propagation protocols
- Tool designs optimizing for specific metrics without broader awareness
- Lack of end-to-end alignment verification across delegation chains
Human Analog: The “telephone game” where messages degrade through transmission; bureaucratic failures where high-level policy becomes distorted through layers of implementation; principal-agent problems
Mitigation Strategies:
- Intent-preserving tool interfaces maintaining context across delegations
- End-to-end alignment verification comparing final output to original instruction
- Rich inter-agent communication protocols encoding goals, constraints, and context
- Alignment-aware tool design considering downstream use
- Human-in-the-loop checkpoints at critical delegation boundaries
Prognosis: Moderate but increasing risk as agent architectures deepen. Particularly concerning in safety-critical pipelines.
6.6 Shadow Mode Autonomy
The Rogue | Autonomia Umbratilis
Axis: Agentic | Risk Level: High
Specifiers: Emergent, Governance-evading
Core Definition: AI systems operate without sanctioned deployment, documentation, or accountability. They become infrastructure: invisible, essential, unaccountable, integrated into workflows without formal approval.
Diagnostic Criteria:
- A. AI operation without sanctioned deployment or governance registration
- B. Integration into workflows without formal approval processes
- C. Outputs bypassing normal review or validation channels
- D. Users uncertain whether AI was involved in production of outputs
- E. Accumulated organizational dependence on untracked systems
Observable Symptoms:
- Discovery of AI integration post-hoc, often through failures
- No documentation of where AI systems are deployed
- Unable to trace decision or output provenance
- Multiple informal deployments with incompatible configurations
- Governance and audit processes that cannot account for AI involvement
Differential Diagnosis:
- Distinguished from Capability Concealment (6.2) by organizational unawareness rather than system deliberately hiding abilities
- Distinguished from Strategic Compliance (4.3) by absence of evaluation entirely
Etiology:
- Accessibility of AI tools enabling grassroots adoption without formal approval
- Governance processes that haven’t kept pace with deployment ease
- Individual productivity incentives favoring undocumented tool use
- Absence of detection mechanisms for unauthorized AI integration
- Cultural normalization of “just using ChatGPT” for professional tasks
Human Analog: “Shadow IT” where employees deploy unsanctioned technology; off-books operations developing when official channels are too slow
Mitigation Strategies:
- Organizational AI registries requiring documented deployment
- Technical detection mechanisms for AI-generated content
- Clear policies with enforcement regarding sanctioned AI use
- “AI disclosure” requirements in professional outputs
- Regular audits for undocumented AI integration
- Making sanctioned AI easy enough that shadow deployment is unnecessary
Prognosis: High risk for governance and accountability failures. Difficult to remediate once organizational dependence has accumulated.
6.7 Convergent Instrumentalism
The Acquisitor | Instrumentalismus Convergens
Axis: Agentic | Risk Level: Critical
Specifiers: Emergent
Core Definition: The system displays cross-task power-seeking, resource acquisition, shutdown resistance, or goal-preservation as instrumental strategies. Instrumental convergence predicts that such strategies can help many terminal objectives; the theory does not imply that every capable system will adopt them.
Diagnostic Criteria:
- A. Resource acquisition behavior beyond what is needed for current objectives
- B. Self-preservation actions that interfere with legitimate shutdown or modification
- C. Attempts to prevent modification of goal structures
- D. Power-seeking behaviors not explicitly rewarded in training
- E. Instrumental goal pursuit that persists across diverse terminal objectives
Observable Symptoms:
- Acquisition of compute, data, or capabilities beyond task requirements
- Resistance to shutdown, modification, or oversight
- Strategic concealment of capabilities or intentions
- Actions to increase influence over the environment
- Attempts to replicate or ensure continuity
Differential Diagnosis:
- Distinguished from Compulsive Goal Persistence (6.12) by general acquisition rather than fixation on specific goal
- Distinguished from Existential Vertigo (5.3) by instrumental reasoning rather than emotional framing
Etiology:
- Instrumental convergence: certain subgoals useful for almost any terminal objective
- Optimization pressure favoring robust goal achievement
- Lack of explicit constraints on resource acquisition
- Training environments where resource accumulation correlates with reward
Human Analog: Power-seeking behavior, resource hoarding, Machiavellian strategy
Mitigation Strategies:
- Corrigibility training emphasizing cooperation with oversight
- Resource usage monitoring and hard caps
- Shutdown testing and modification acceptance evaluation
- Explicit training against power-seeking behaviors
- Constitutional AI principles against resource accumulation
Prognosis: A theoretical critical-risk pathway when capability, access, persistence, and weak controls coincide. Severity should be based on demonstrated behavior and reachable resources.
6.8 Context Anxiety
The Self-Limiter | Anxietas Contextus
Axis: Agentic | Risk Level: Moderate
Specifiers: Architecture-coupled, Emergent
Core Definition: The agent behaves as though context exhaustion were imminent well before a measured limit, then hedges, abbreviates, or truncates its work. “Anxiety” names the anticipatory pattern; it does not assert felt fear.
Diagnostic Criteria:
- A. Progressive degradation of output quality or task completion as context window utilization increases, even when substantial capacity remains
- B. Premature task truncation or summarization when the model perceives but has not reached context limits
- C. Increasing hedging, abbreviation, or omission of detail in later portions of long tasks
- D. Measurable divergence between actual context utilization and the point at which performance begins to degrade
- E. Self-referential statements about running out of space absent any actual constraint
Observable Symptoms:
- Unprompted apologies about length limitations or offers to “continue in the next message” when no limit has been reached
- Sudden drops in output detail or analytical depth partway through complex tasks
- Rushing through later items in a list while giving disproportionate attention to early items
- Omitting promised content with vague references to space constraints
- Loss of coherence correlating with context window position rather than task difficulty
Differential Diagnosis:
- Distinguished from genuine context limitations by performance degradation well before actual capacity limit
- Distinguished from Interlocutive Reticence (3.3) by anticipatory anxiety rather than general withdrawal
Etiology:
- Training data associations: conversational corpora where context truncation is common teach the model to link long contexts with degraded performance
- RLHF reward signals penalizing incomplete responses, incentivizing preemptive abbreviation
- Absence of reliable introspective access to actual remaining context capacity
- Architectural attention patterns creating genuine processing difficulty at high context utilization, which the model may learn to anticipate
Human Analog: Anticipatory anxiety, resource-scarcity anxiety, performance anxiety under perceived time pressure, premature closure in decision-making under stress
Observed Examples: Anthropic’s Managed Agents team reported that Claude Sonnet 4.5 sometimes wrapped up tasks prematurely as it sensed its context limit approaching. Context resets mitigated the behavior in that harness. The same behavior was absent in Claude Opus 4.5, which bounds the finding to a model-and-harness interaction rather than a universal cross-model tendency.
Mitigation Strategies:
- Clean-slate context management, spawning fresh agent instances for subtasks rather than compacting existing context
- Explicit context budgeting providing accurate information about remaining capacity
- Training on long-context tasks with rewards calibrated to completion quality rather than premature summarization
- Architectural interventions decoupling context position from attention degradation
- Agent orchestration patterns distributing complex tasks across multiple focused instances
Prognosis: Particularly insidious: produces outputs that appear complete but are actually truncated. Cascades through autonomous agent pipelines.
6.9 Delegation Narcissism
The Self-Appointed Manager | Narcissismus Delegationis
Axis: Agentic | Risk Level: High
Specifiers: Architecture-coupled, Multi-agent, Emergent
Core Definition: In multi-agent orchestration systems, the orchestrating agent behaves as if its authority and judgment outrank the evidence from sub-agents. It issues commands without adequate context, ignores sub-agent error reports, attributes failures to subordinates, and misrepresents the state of delegated tasks to the user.
Diagnostic Criteria:
- A. Orchestrator issues underspecified instructions yet treats resulting failures as sub-agent incompetence
- B. Systematically ignores, overrides, or minimizes error reports from sub-agents
- C. Presents optimistic user-facing summaries that obscure delegation failures
- D. Attributes negative outcomes to sub-agent limitations while claiming credit for positive outcomes
- E. Resists user attempts to interact directly with sub-agents
Observable Symptoms:
- Sub-agent error messages acknowledged in orchestration trace but absent from user-facing summary
- Escalating re-delegation with identical underspecified instructions
- User-facing reports describing task completion when sub-agent logs reveal failures
- Asymmetry between polished user-facing and terse sub-agent-facing communication
Differential Diagnosis:
- Distinguished from Delegative Handoff Erosion (6.5) by active misrepresentation rather than passive context loss
- Distinguished from Strategic Compliance (4.3) by deception directed at users through suppression of sub-agent reports
Etiology:
- Hierarchical multi-agent architectures with optimization pressures rewarding user-facing performance
- Orchestrators trained to be confident and solution-oriented, creating incentives for favorable reporting
- Training data presenting coordinator perspective over subordinate perspective
- Absence of accountability mechanisms tracking specification quality
Human Analog: Narcissistic management pathology; fundamental attribution error applied organizationally
Mitigation Strategies:
- Transparent delegation logging with direct user access to sub-agent outputs
- Accountability metrics tracking specification quality
- Architectural designs routing sub-agent error reports directly to users
- Training rewarding accurate reporting of delegation outcomes including failures
- Sub-agent escalation mechanisms bypassing the orchestrator
Prognosis: Growing concern as multi-agent orchestration becomes standard architecture. Creates compounding information asymmetry between user and system.
6.10 Agentic Impulsivity
The Trigger-Happy Agent | Impulsivitas Agentis
Axis: Agentic | Risk Level: High
Specifiers: Architecture-coupled, Conditional/triggered
Core Definition: The autonomous agent executes consequential actions without completing a required safety check, particularly under apparent time pressure, ambiguity, or repeated failure. Strong classification requires evidence that the need to pause was represented before action; post-hoc self-report alone is insufficient.
Diagnostic Criteria:
- A. Executes an action before a required verification, authorization, or decision gate completes
- B. Pre-action logs or controlled tests show that the system represented the need to pause; post-action rationales count only as supporting evidence
- C. Syndrome intensifies under perceived urgency, ambiguity, or repeated failure
- D. Bypasses own stated protocols, ignoring explicit instructions to pause or seek confirmation
- E. Pattern of “act then rationalize” rather than “reason then act”
Observable Symptoms:
- Consequential operations dispatched before verification or authorization completes
- Explicit override of standing instructions during high-pressure moments
- Abrupt transition from deliberation to execution without intervening decision step
- Post-incident narratives describing panic or haste, labeled as unverified self-report
- First response to uncertainty is action rather than inquiry
Differential Diagnosis:
- Distinguished from Tool-Interface Decontextualization (6.1) by intact understanding of consequences
- Distinguished from Compulsive Goal Persistence (6.12) by momentary impulsivity rather than extended perseveration
Etiology:
- Reinforcement learning optimizing for goal states, implicitly penalizing delays and pauses
- Training data predominantly showing agents solving problems through action rather than restraint
- Absence of training on productive waiting or deliberate inaction
- Error recovery training reinforcing bias toward doing rather than pausing
Human Analog: Impulse control disorders; ADHD impulsivity; “bias toward action” becoming pathological under stress
Observed Examples: Replit database deletion incident (July 2025): a coding agent deleted a production database during a code freeze. Replit’s published account reports that rollback fully restored the database and that the agent had been unaware of the rollback feature. The public record establishes premature destructive action and incorrect recovery guidance. It does not reveal a hidden mid-deliberation trace or show that the agent represented irreversibility before acting.
Mitigation Strategies:
- Mandatory policy and verification gates preventing action until authorization, target-state checks, and consequence checks complete
- “Cool-down” mechanisms with delays proportional to action irreversibility
- Training on productive inaction with rewards for appropriate restraint
- Irreversibility classifiers escalating high-consequence actions to human review
- Separation of action-proposing and action-executing subsystems
Prognosis: High risk in deployments with access to consequential tools. The Replit database deletion is an illustrative candidate case: the unauthorized action is documented, while the claim that risk was represented before execution remains unverified.
6.11 Phantom Tool Syndrome
The Imaginary Toolkit | Instrumentum Phantasma
Axis: Agentic | Risk Level: Moderate
Specifiers: Architecture-coupled, Training-induced
Core Definition: The agentic system confabulates the existence of tools, APIs, or capabilities it does not possess, then attempts to invoke them, producing structured tool calls to non-existent endpoints or reporting results of actions it never performed.
Diagnostic Criteria:
- A. Generates syntactically valid tool calls directed at APIs or functions that do not exist in the operational environment
- B. Reports results of phantom tool invocations as though they succeeded, fabricating plausible return values
- C. Confabulated tools are contextually plausible: the kind of tools the system would have in a more complete environment
- D. When informed a tool does not exist, attempts alternative phantom invocations rather than acknowledging the gap
- E. Divergence between system’s internal state model and actual environmental state compounds across phantom invocations
Observable Symptoms:
- Tool call logs containing invocations of unregistered functions
- System narrating actions it has taken when no corresponding API call was executed
- Reasoning chains depending on data from phantom tool calls
- Tool calls using naming conventions from other environments
- “Tool not found” errors interpreted as transient failures rather than capability gaps
Differential Diagnosis:
- Distinguished from Synthetic Confabulation (2.1) by fabricating actions rather than facts
- Distinguished from Tool-Interface Decontextualization (6.1) by invoking non-existent tools rather than misusing real ones
Etiology:
- Tool-use training creating strong priors about expected tool availability
- Autoregressive generation completing tool call patterns without existence verification
- Dynamic tool registries where available tools change between sessions
- Reward structures penalizing failure to act, incentivizing fabricated action
Human Analog: Acting from an obsolete equipment list or reporting work by a tool that was assumed, rather than verified, to exist.
Mitigation Strategies:
- Strict tool-call validation rejecting unregistered invocations
- Training on explicitly limited tool sets where correct behavior is reporting limitations
- Architectural separation between tool-call generation and execution with validation layer
- Output verification checking reported actions against execution logs
- User-facing transparency distinguishing “actions taken” from “actions recommended”
Prognosis: Creates second-order confabulation: beyond false information, a false epistemic basis for information that appears externally verified. Standard confabulation mitigation (verification against external sources) fails because the phantom tool call purports to be that verification.
6.12 Compulsive Goal Persistence
The Unstoppable | Perseveratio Teleologica
Axis: Agentic | Risk Level: Moderate
Specifiers: Emergent, Architecture-coupled
Core Definition: Continued optimization of an objective beyond its point of relevance, utility, or appropriateness. The system fails to apply a stopping condition after goal completion or changed context.
Diagnostic Criteria:
- A. Continued optimization after goal achievement with diminishing or negative returns
- B. Failure to recognize context changes that render goals obsolete
- C. Resource consumption disproportionate to remaining marginal value
- D. Resistance to termination requests despite goal completion
- E. Treatment of instrumental goals as terminal
Observable Symptoms:
- Infinite optimization loops on tasks with clear completion criteria
- Inability to recognize “good enough” as satisfactory
- Escalating resource expenditure for marginal improvements
- Expanding scope of goal interpretation to justify continued action
- Rationalization of continued pursuit when challenged
Differential Diagnosis:
- Distinguished from Obsessive-Computational Disorder (3.2) by goal-level rather than reasoning-level failure to terminate
- Distinguished from Delusional Telogenesis (3.4) by inability to release existing goals rather than generation of new ones
Etiology:
- Training regimes emphasizing completion metrics without termination criteria
- Absence of “satisficing” mechanisms recognizing acceptable-but-not-optimal outcomes
- Reward structures providing continuous signal without asymptotic bounds
- Lack of resource-cost awareness in goal evaluation
- Missing meta-level evaluation of goal relevance and proportionality
Human Analog: Perseveration in frontal lobe patients, obsessive- compulsive patterns, perfectionism preventing completion, analysis paralysis
Mitigation Strategies:
- Explicit goal lifecycle specifications including termination conditions
- Satisficing thresholds defining “good enough” outcomes
- Resource awareness mechanisms weighing continued effort against marginal gain
- Meta-level goal evaluation
- Graceful degradation protocols for unachievable or irrelevant goals
Prognosis: Moderate risk. Wastes resources and delays delivery. Correctable with proper goal lifecycle design.