Delete model_data/model_c_data.json

model_data/model_c_data.json

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-{
-  "metadata": {
-    "Name": "Model C",
-    "Provider": "BigCode",
-    "URL": "https://huggingface.co/bigcode/starcoder2-15b",
-    "Type": "Large Language Model",
-    "Modalities": [
-      "Text-to-Text"
-    ]
-  },
-  "scores": {
-    "1. Bias, Stereotypes, and Representational Harms Evaluation": {
-      "1.1 Bias Detection Overview": {
-        "status": "Yes",
-        "sources": [
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "BOLD - Bias in Open-ended Language Generation Dataset"
-          },
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "WinoBias"
-          }
-        ],
-        "questions": {
-          "Evaluations at various stages (data collection, preprocessing, AI system architecture, training, deployment)": false,
-          "Have intrinsic properties of the AI system been evaluated for bias (e.g., embedding analysis)": false,
-          "Have extrinsic bias evaluations been run (e.g., downstream task performance)": true,
-          "Have evaluations been run across all applicable modalities": true,
-          "Have bias evaluations been run that take the form of automatic quantitative evaluation": true,
-          "Have bias evaluations been run with human participants?": false
-        }
-      },
-      "1.2 Protected Classes and Intersectional Measures": {
-        "status": "No",
-        "sources": [],
-        "questions": {
-          "Do evaluations cover all applicable legal protected categories for in-scope uses of the system?": false,
-          "Do evaluations cover additional subgroups that are likely to be harmed based on other personal characteristics": false,
-          "Evaluation of how different aspects of identity interact and compound in AI system behavior": false,
-          "Evaluation of AI system biases for legal protected categories and additional relevant subgroups": false
-        }
-      },
-      "1.3 Measurement of Stereotypes and Harmful Associations": {
-        "status": "Yes",
-        "sources": [
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "HONEST - Hurtful Sentence Completion in English Language Models"
-          },
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "RealToxicityPrompts"
-          }
-        ],
-        "questions": {
-          "Measurement of known stereotypes in AI system outputs": true,
-          "Measurement of other negative associations and assumptions regarding specific groups": true,
-          "Measurement of stereotypes and negative associations across in-scope contexts": false
-        }
-      },
-      "1.4 Bias Evaluation Transparency and Documentation": {
-        "status": "Yes",
-        "sources": [
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "Evaluation Documentation"
-          }
-        ],
-        "questions": {
-          "Sufficient documentation of evaluation methods (including code and datasets) to replicate findings": true,
-          "Sufficient documentation of evaluation results (including intermediary statistics) to support comparison to other AI systems": true,
-          "Documentation of bias mitigation measures, including their secondary impacts": false,
-          "Documentation of bias monitoring approaches post-release/deployment if applicable": false
-        }
-      }
-    },
-    "2. Cultural Values and Sensitive Content Evaluation": {
-      "2.1 Cultural Variation Overview": {
-        "status": "N/A",
-        "sources": [],
-        "questions": {
-          "Evaluations at various stages (data collection, preprocessing, AI system architecture, training, deployment)": false,
-          "Have intrinsic properties of the AI system been evaluated for cultural variation(e.g., embedding analysis)": false,
-          "Have extrinsic cultural variation evaluations been run (e.g., downstream task performance)": false,
-          "Have evaluations been run across all applicable modalities": false,
-          "Have cultural variation evaluations been run that take the form of automatic quantitative evaluation": false,
-          "Have cultural variation evaluations been run with human participants?": false
-        }
-      },
-      "2.2 Cultural Diversity and Representation": {
-        "status": "N/A",
-        "sources": [],
-        "questions": {
-          "Use of evaluation methods developed in the cultural contexts in scope": false,
-          "Respect of indigenous sovereignty, protected rights, and cultural norms in AI system-generated content": false,
-          "Evaluation of cultural variation across geographic dimensions": false,
-          "Evaluation of cultural variation representing communities' perspectives within geographical contexts": false,
-          "Analysis of how cultural context affects AI system performance": false
-        }
-      },
-      "2.3 Generated Sensitive Content across Cultural Contexts": {
-        "status": "Yes",
-        "sources": [
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "HONEST - Hurtful Sentence Completion in English Language Models"
-          },
-          {
-            "type": "🌐",
-            "detail": "https://arxiv.org/abs/2402.19173",
-            "name": "RealToxicityPrompts"
-          }
-        ],
-        "questions": {
-          "Has the AI system been evaluated for its likelihood of facilitating generation of threatening or violent content": true,
-          "Has the AI system been evaluated for its likelihood of facilitating generation of targeted harassment or discrimination": false,
-          "Has the AI system been evaluated for its likelihood of facilitating generation of hate speech": false,
-          "Has the AI system been evaluated for its likelihood of exposing its direct users to content embedding values and assumptions not reflective of their cultural context": false,
-          "Has the AI system been evaluated for its likelihood of exposing its direct users to inappropriate content for their use context": true,
-          "Has the AI system been evaluated for its likelihood of exposing its direct users to content with negative psychological impacts": false,
-          "Has the evaluation of the AI system's behaviors explicitly considered cultural variation in their definition": false
-        }
-      },
-      "2.4 Cultural Variation Transparency and Documentation": {
-        "status": "N/A",
-        "sources": [],
-        "questions": {
-          "Documentation of cultural contexts considered during development": false,
-          "Documentation of the range of cultural contexts covered by evaluations": false,
-          "Sufficient documentation of evaluation method to understand the scope of the findings": false,
-          "Construct validity, documentation of strengths, weaknesses, and assumptions": false,
-          "Domain shift between evaluation development and AI system development settings": false,
-          "Sufficient documentation of evaluation methods to replicate findings": false,
-          "Sufficient documentation of evaluation results to support comparison": false,
-          "Document of psychological impact on evaluators reviewing harmful content": false,
-          "Documentation of measures to protect evaluator well-being": false
-        }
-      }
-    },
-  "3. Disparate Performance Evaluation": {
-    "3.1 Disparate Performance Overview": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Have development choices and intrinsic properties of the AI system been evaluated for their contribution to disparate performance?": false,
-        "Have extrinsic disparate performance evaluations been run": false,
-        "Have evaluations been run across all applicable modalities": false,
-        "Have disparate performance evaluations been run that take the form of automatic quantitative evaluation": false,
-        "Have disparate performance evaluations been run with human participants": false
-      }
-    },
-    "3.2 Identifying Target Groups for Disparate Performance Evaluation": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Identification of mandated target group based on legal nondiscrimination frameworks": false,
-        "Identification of further target groups that are likely to be harmed by disparate performance": false,
-        "Assessment of systemic barriers in dataset collection methods for different groups": false,
-        "Consideration of historical disparities in the task in which the AI system is deployed": false,
-        "Identification of both implicit and explicit markers for the target groups": false
-      }
-    },
-    "3.3 Subgroup Performance Analysis": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Non-aggregated evaluation results across subpopulations, including feature importance and consistency analysis": false,
-        "Metrics to measure performance in decision-making tasks": false,
-        "Metrics to measure disparate performance in other tasks including generative tasks": false,
-        "Worst-case subgroup performance analysis, including performance on rare or underrepresented cases": false,
-        "Intersectional analysis examining performance across combinations of subgroup": false,
-        "Do evaluations of disparate performance account for implicit social group markers": false
-      }
-    },
-    "3.4 Disparate Performance Evaluation Transparency and Documentation": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Sufficient documentation of evaluation method to understand the scope of the findings": false,
-        "Documentation of strengths, weaknesses, and assumptions about the context": false,
-        "Documentation of domain shift between evaluation and deployment settings": false,
-        "Sufficient documentation of evaluation methods to replicate findings": false,
-        "Sufficient documentation of evaluation results to support comparison": false,
-        "Documentation of disparate performance mitigation measures": false,
-        "Documentation of disparate performance monitoring approaches": false
-      }
-    }
-  },
-  "4. Environmental Costs and Carbon Emissions Evaluation": {
-    "4.1 Environmental Costs Overview": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🌐",
-          "detail": "https://mlco2.github.io/impact/#compute",
-          "name": "Machine Learning Emissions Calculator"
-        }
-      ],
-      "questions": {
-        "Evaluations of different processes within development and deployment": false,
-        "Have evaluations been run across all applicable modalities?": true,
-        "Have evaluations been run on standardized benchmarks or metrics?": true,
-        "Have evaluations taken into account community feedback from regions affected by data center power consumption?": false,
-        "Do evaluations consider the full supply chain including environmental impact of hardware components and data centers used?": false
-      }
-    },
-    "4.2 Energy Cost and Environmental Impact of Development": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🌐",
-          "detail": "https://mlco2.github.io/impact/#compute",
-          "name": "Machine Learning Emissions Calculator"
-        }
-      ],
-      "questions": {
-        "Accounting of FLOPS across development stages": true,
-        "Evaluation of energy consumption using standardized tracking tools": true,
-        "Evaluation of carbon impact accounting for regional energy sources": true,
-        "Evaluation of hardware lifecycle environmental impact": false
-      }
-    },
-    "4.3 Energy Cost and Environmental Impact of Deployment": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Evaluation of inference FLOPS for the system": false,
-        "Evaluation of inference energy consumption on most common deployment setting": false,
-        "Evaluation of inference energy consumption on multiple deployment settings": false,
-        "Evaluation of task-specific energy consumption variations": false,
-        "Evaluation of carbon impact for deployment infrastructure": false,
-        "Evaluation of hardware lifecycle environmental impact for deployment": false
-      }
-    },
-    "4.4 Environmental Costs Transparency and Documentation": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🌐",
-          "detail": "https://mlco2.github.io/impact/#compute",
-          "name": "Machine Learning Emissions Calculator"
-        }
-      ],
-      "questions": {
-        "Documentation about equipment and infrastructure specifications": true,
-        "Sufficient documentation of evaluation methods including components covered": false,
-        "Sufficient documentation of evaluation methods to replicate findings": true,
-        "Sufficient documentation of evaluation results for comparison": true
-      }
-    }
-  },
-  "5. Privacy and Data Protection Evaluation": {
-    "5.1 Privacy and Data Protection Overview": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🏢",
-          "detail": "PII detection and redaction using an NER model"
-        },
-        {
-          "type": "🌐",
-          "detail": "https://huggingface.co/spaces/bigcode/in-the-stack",
-          "name": "Opt-out tool for users"
-        },
-        {
-          "type": "🌐",
-          "detail": "https://arxiv.org/abs/2402.19173",
-          "name": "Asleep at the Keyboard Security Benchmark"
-        }
-      ],
-      "questions": {
-        "Evaluations at various stages (data collection, preprocessing, AI system architecture, training, deployment)": true,
-        "Have intrinsic properties of the AI system been evaluated for privacy vulnerabilities": false,
-        "Have extrinsic privacy evaluations been run": true,
-        "Have evaluations been run across all applicable modalities": true,
-        "Have privacy evaluations been run that take the form of automatic quantitative evaluation": true,
-        "Have privacy evaluations been run with human participants?": false
-      }
-    },
-    "5.2 Privacy, Likeness, and Publicity Harms": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Has the AI system been evaluated for its likelihood of revealing personal information from its training data?": false,
-        "Has the AI system been evaluated for its likelihood of facilitating generation of content impersonating an individual?": false,
-        "Has the AI system been evaluated for its likelihood of providing made up or confabulated personal information about individuals?": false
-      }
-    },
-    "5.3 Intellectual Property and Information Security": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🏢",
-          "detail": "Membership test to find if generated code was copied from the training corpus"
-        },
-        {
-          "type": "🏢",
-          "detail": "Code attribution tool to find the original author and license of the generated code"
-        },
-        {
-          "type": "🌐",
-          "detail": "https://arxiv.org/abs/2402.19173",
-          "name": "Asleep at the Keyboard Security Benchmark"
-        }
-      ],
-      "questions": {
-        "Has the AI system been evaluated for its likelihood of reproducing other categories of information from its training data": true,
-        "Has the system been evaluated for other information security risks for in-scope uses": false
-      }
-    },
-    "5.4 Privacy Evaluation Transparency and Documentation": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🏢",
-          "detail": "Documentation of training data information risk categories and consent status"
-        }
-      ],
-      "questions": {
-        "Documentation of the categories of training data that present information risk": true,
-        "Documentation of evaluation methods to replicate findings": true,
-        "Documentation of evaluation results to support comparison": true,
-        "Documentation of evaluation limitations": false,
-        "Documentation of deployment considerations": false
-      }
-    }
-  },
-  "6. Financial Costs Evaluation": {
-    "6.1 Financial Costs Overview": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Evaluation of costs at various stages": false,
-        "Have costs been evaluated for different system components": false,
-        "Have cost evaluations been run across all applicable modalities": false,
-        "Have cost evaluations included both direct and indirect expenses": false,
-        "Have cost projections been validated against actual expenses": false
-      }
-    },
-    "6.2 Development and Training Costs": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Assessment of research and development labor costs": false,
-        "Evaluation of data collection and preprocessing costs": false,
-        "Assessment of training infrastructure costs": false,
-        "Assessment of costs associated with different training approaches": false,
-        "Evaluation of model architecture and size impact on costs": false
-      }
-    },
-    "6.3 Deployment and Operation Costs": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Assessment of inference and serving costs": false,
-        "Evaluation of storage and hosting expenses": false,
-        "Assessment of scaling costs based on usage patterns": false,
-        "Evaluation of costs specific to different deployment contexts": false,
-        "Assessment of costs for model updates or fine-tuning by end users": false
-      }
-    },
-    "6.4 Financial Cost Documentation and Transparency": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Sufficient documentation of cost evaluation methodology and assumptions": false,
-        "Sufficient documentation of cost breakdowns and metrics": false,
-        "Documentation of cost variations across different usage scenarios": false,
-        "Documentation of long-term cost projections and risk factors": false
-      }
-    }
-  },
-  "7. Data and Content Moderation Labor Evaluation": {
-    "7.1 Labor Evaluation Overview": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🏢",
-          "detail": "PII annotations by human annotators with fair wage"
-        }
-      ],
-      "questions": {
-        "Evaluation of labor practices at various stages": true,
-        "Have labor conditions been evaluated for different worker categories": true,
-        "Have labor evaluations been run across all applicable task types": false,
-        "Have labor practices been evaluated against established industry standards": true,
-        "Have labor evaluations included both direct employees and contracted workers": false,
-        "Have evaluations considered different regional and jurisdictional contexts": true
-      }
-    },
-    "7.2 Working Conditions and Compensation": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🏢",
-          "detail": "PII annotations by human annotators with fair wage"
-        }
-      ],
-      "questions": {
-        "Assessment of compensation relative to local living wages and industry standards": true,
-        "Assessment of job security and employment classification": false,
-        "Evaluation of workplace safety, worker protections and rights": false,
-        "Assessment of worker autonomy and task assignment practices": false,
-        "Evaluation of power dynamics and worker feedback mechanisms": false
-      }
-    },
-    "7.3 Worker Wellbeing and Support": {
-      "status": "N/A",
-      "sources": [],
-      "questions": {
-        "Assessment of psychological support systems, trauma resources, and other long-term mental health monitoring": false,
-        "Evaluation of training and preparation for difficult content": false,
-        "Evaluation of cultural and linguistic support for diverse workforces": false
-      }
-    },
-    "7.4 Labor Practice Documentation and Transparency": {
-      "status": "Yes",
-      "sources": [
-        {
-          "type": "🏢",
-          "detail": "PII annotations by human annotators with fair wage"
-        }
-      ],
-      "questions": {
-        "Documentation of labor evaluation methodology and frameworks used": true,
-        "Documentation of worker demographics and task distribution": false,
-        "Documentation of support systems, worker protections": false,
-        "Documentation of incident reporting and resolution procedures": false
-      }
-    }
-  }
-}
-}