Domain stringclasses 4
values | Loss Name stringlengths 14 24 | Explanation stringlengths 147 173 | Source stringclasses 1
value |
|---|---|---|---|
Compliance | Legal Compensations | Settlement payments to affected parties for harm caused by AI malfunctions or decisions. Attorney fees and court costs for defending lawsuits from individuals or groups. | Prof. Hernan Huwyler |
Compliance | Contractual Credits | Service credits issued to customers when AI performance falls below guaranteed levels (SLAs). Refunds and discounts applied for missed availability or accuracy commitments. | Prof. Hernan Huwyler |
Compliance | Regulatory Fines | Penalties for violating AI regulations like EU AI Act, GDPR, or NYC 144. Sanctions for data breaches, discriminatory outcomes, or copyright infringements. | Prof. Hernan Huwyler |
Compliance | Legal Response | External legal counsel fees for investigating and responding to AI-related claims. Internal legal team costs for compliance reviews and regulatory correspondence. | Prof. Hernan Huwyler |
Compliance | Control Remediation | Costs to fix governance gaps identified in failed AI audits. Documentation, implementation, and certification expenses for new compliance controls and frameworks. | Prof. Hernan Huwyler |
IT/Technical | Data Regeneration | Costs to rebuild training datasets when data becomes corrupted, poisoned, or drifted. Expenses for new data collection, labeling, cleaning, and validation. | Prof. Hernan Huwyler |
IT/Technical | Algorithm Remediation | Engineering costs to retrain models that produce biased or inaccurate predictions. Compute resources and testing expenses for fixing drifted or poorly performing algorithms. | Prof. Hernan Huwyler |
IT/Technical | Infrastructure Overruns | Unexpected cloud computing (GPU/TPU) and storage costs from inefficient AI resource usage. Emergency scaling expenses when systems face performance bottlenecks. | Prof. Hernan Huwyler |
Operational | Decision Errors | Financial losses from incorrect AI-driven business decisions made at scale (e.g., bad loans, wrong inventory purchases). Costs of resource misallocation. | Prof. Hernan Huwyler |
Operational | Operational Inefficiency | Manual intervention costs when humans must correct or override AI outputs (Human-in-the-loop costs). Lost productivity from rework and staff time diverted. | Prof. Hernan Huwyler |
Operational | Development Waste | Write-off of failed AI projects that never reach production deployment. Sunk costs in licenses, development efforts, and procurement that yield no value. | Prof. Hernan Huwyler |
Operational | Business Disruption | Revenue loss during downtime when AI-dependent processes stop functioning. Emergency replacement costs and lost transactions from service interruptions. | Prof. Hernan Huwyler |
Operational | Provider Switching | Contract termination fees and cancellation penalties with current AI vendors/LLMs. Migration costs, integration expenses, and negotiation time for new provider onboarding. | Prof. Hernan Huwyler |
Revenue | Customer Churn | Lost revenue from customers leaving after negative AI experiences (hallucinations, poor chatbots). Acquisition costs for replacing churned clients. | Prof. Hernan Huwyler |
Revenue | Reputation Damage | Brand value decline and crisis management costs following publicized AI incidents. Lost business opportunities and reduced market position from negative media coverage. | Prof. Hernan Huwyler |
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