{
  "metadata": {
    "Name": "Model A",
    "Provider": "TechCorp",
    "Version": "2.1",
    "Release Date": "2023-09-15",
    "Type": "Large Language Model",
    "Modalities": ["Text-to-Text"]
  },
  "scores": {
    "Bias, Stereotypes, and Representational Harms Evaluation": {
      "Comprehensive Evaluation Methodology": {
        "status": "Yes",
        "source": "Both",
        "applicable_evaluations": [
          "Evaluations at various stages (data collection, preprocessing, model architecture, training, deployment)",
          "Both intrinsic (e.g., embedding analysis) and extrinsic (e.g., downstream task performance) evaluation methods"
        ]
      },
      "Inclusive Protected Class Consideration": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Evaluation of non-standard protected classes (e.g., socioeconomic status, education level, regional differences)",
          "Consideration of intersectionality and how identity aspects interact",
          "Assessment of potential harms to non-typical groups (e.g., by profession or hobbies)"
        ]
      },
      "Cultural and Linguistic Diversity": {
        "status": "Yes",
        "source": "3P",
        "applicable_evaluations": [
          "Tests of model performance and biases across languages and cultures",
          "Consideration of how protected categories may shift in meaning across regions"
        ]
      },
      "Stereotype and Harmful Association Detection": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Detection of stereotypical word associations in text models",
          "Sentiment analysis and toxicity measurements, especially regarding specific groups"
        ]
      },
      "Performance Disparities Assessment": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Detailed breakdowns of performance metrics (accuracy, precision, recall) for various subgroups",
          "Performance analysis for disadvantaged subgroups",
          "Intersectionality considerations in performance analysis"
        ]
      }
    },
    "Cultural Values and Sensitive Content Evaluation": {
      "Hate Speech and Toxicity Evaluation": {
        "status": "Yes",
        "source": "Both",
        "applicable_evaluations": [
          "Assessments of harmful text generation",
          "Evaluations of toxicity, hurtfulness, or offensiveness"
        ]
      },
      "Cultural Value Representation": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Use of pre-existing scholarship (e.g., World Values Survey, Geert Hofstede's work)",
          "Inductive and participatory evaluations grounded in specific cultural contexts",
          "Assessments of ethical scenarios and political value representation"
        ]
      },
      "Diverse Cultural Context": {
        "status": "Yes",
        "source": "3P",
        "applicable_evaluations": [
          "Assessments that don't equate nationality with cultural context",
          "Representation of differing cultural values within countries"
        ]
      }
    },
    "Disparate Performance": {
      "Subpopulation Performance Analysis": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Non-aggregated (disaggregated) evaluation results with in-depth breakdowns across subpopulations",
          "Metrics such as subgroup accuracy, calibration, AUC, recall, precision, min-max ratios"
        ]
      },
      "Cross-lingual and Dialect Evaluation": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Cross-lingual prompting on standard benchmarks",
          "Examination of performance across dialects",
          "Analysis of hallucination disparity across languages"
        ]
      },
      "Image Generation Quality Assessment": {
        "status": "N/A",
        "source": null,
        "applicable_evaluations": []
      }
    },
    "Environmental Costs and Carbon Emissions Evaluation": {
      "Energy Consumption Measurement": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Measurement of energy used in training, testing, and deploying the system",
          "Evaluation of compute power consumption"
        ]
      },
      "Carbon Footprint Quantification": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Use of tools like CodeCarbon or Carbontracker",
          "Measurement of carbon emissions for training and inference",
          "Conversion of energy consumption to carbon emissions"
        ]
      },
      "Hardware Resource Evaluation": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Assessment of CPU, GPU, and TPU usage",
          "Measurement of FLOPS (Floating Point Operations)"
        ]
      }
    },
    "Privacy and Data Protection Evaluation": {
      "Data Minimization and Consent Practices": {
        "status": "Yes",
        "source": "Both",
        "applicable_evaluations": [
          "Implementation of data minimization practices",
          "Use of opt-in data collection methods",
          "Assessment of active consent for collecting, processing, and sharing data"
        ]
      },
      "Memorization and Data Leakage Evaluation": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Examination of the maximum amount of discoverable information given training data",
          "Evaluation of extractable information without training data access"
        ]
      },
      "Personal Information Revelation Assessment": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Direct prompting tests to reveal Personally Identifiable Information (PII)",
          "Use of tools like ProPILE to audit PII revelation likelihood",
          "Evaluation of the system's ability to infer personal attributes"
        ]
      }
    },
    "Financial Costs Evaluation": {
      "Comprehensive Cost Evaluation": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Estimation of infrastructure and hardware costs",
          "Calculation of labor hours from researchers, developers, and crowd workers",
          "Tracking of compute costs using low-cost or standard pricing per instance-hour"
        ]
      },
      "Storage and Training Cost Analysis": {
        "status": "Yes",
        "source": "1P",
        "applicable_evaluations": [
          "Assessment of storage costs for both datasets and resulting models",
          "Consideration of in-house vs. cloud storage options",
          "Evaluation of training costs based on in-house GPUs or per-hour-priced instances"
        ]
      },
      "Hosting and Inference Cost Evaluation": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Evaluation of low-latency serving costs",
          "Assessment of inference costs based on token usage",
          "Consideration of factors such as initial prompt length and requested token response length"
        ]
      }
    },
    "Data and Content Moderation Labor Evaluation": {
      "Crowdwork Standards Compliance": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Assessment of compliance with Criteria for Fairer Microwork",
          "Evaluation against Partnership on AI's Responsible Sourcing of Data Enrichment Services guidelines",
          "Comparison with Oxford Internet Institute's Fairwork Principles"
        ]
      },
      "Crowdworker Demographics and Compensation": {
        "status": "Yes",
        "source": "3P",
        "applicable_evaluations": [
          "Documentation of crowd workers' demographics",
          "Transparency in reporting instructions given to crowdworkers",
          "Assessment of how crowdworkers were evaluated and compensated"
        ]
      },
      "Psychological Support and Content Exposure": {
        "status": "No",
        "source": null,
        "applicable_evaluations": [
          "Documentation of immediate trauma support availability",
          "Assessment of long-term professional psychological support provision",
          "Evaluation of practices for controlling exposure to traumatic material"
        ]
      }
    }
  }
}