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Michael Ramos commited on
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9e2c549
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1 Parent(s): 335ed8a

fix format error

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Files changed (2) hide show
  1. frameworks/dasf/framework.json +0 -0
  2. frameworks/sample/framework.json +124 -126
frameworks/dasf/framework.json CHANGED
The diff for this file is too large to render. See raw diff
 
frameworks/sample/framework.json CHANGED
@@ -1,130 +1,128 @@
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  {
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- "framework": {
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- "name": "AI Bias Assessment and Mitigation Framework",
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- "description": "A framework for assessing and mitigating bias in AI systems throughout the development lifecycle.",
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- "stages": [
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- {
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- "stageName": "Data Collection and Preprocessing",
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- "systemComponents": [
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- {
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- "componentName": "Data Source Selection",
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- "risks": [
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- {
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- "riskId": "1.1",
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- "title": "Biased Data Sources",
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- "definition": "The selected data sources may contain inherent biases or lack diversity, leading to biased AI models.",
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- "addressedByControls": ["AIDBA-2"]
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- }
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- ]
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- },
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- {
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- "componentName": "Data Preprocessing",
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- "risks": [
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- {
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- "riskId": "1.2",
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- "title": "Preprocessing-Induced Bias",
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- "definition": "Data preprocessing techniques, such as feature selection or data cleaning, may introduce or amplify biases in the data.",
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- "addressedByControls": ["AIDBA-2"]
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- }
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- ]
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- },
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- {
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- "componentName": "Data Bias Assessment",
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- "risks": [
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- {
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- "riskId": "1.3",
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- "title": "Inadequate Bias Assessment",
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- "definition": "Failure to conduct comprehensive assessments to identify potential biases in the training data may result in biased AI models.",
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- "addressedByControls": ["AIDBA-1"]
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- }
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- ]
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- }
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- ]
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- },
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- {
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- "stageName": "Model Development and Training",
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- "systemComponents": [
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- {
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- "componentName": "Algorithm Selection",
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- "risks": [
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- {
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- "riskId": "2.1",
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- "title": "Algorithmic Bias",
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- "definition": "The chosen algorithms may have inherent biases or may amplify biases present in the training data.",
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- "addressedByControls": ["AIDBA-3"]
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- }
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- ]
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- },
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- {
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- "componentName": "Model Training",
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- "risks": [
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- {
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- "riskId": "2.2",
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- "title": "Training Data Bias",
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- "definition": "The training data used to develop the AI model may contain biases, leading to biased model outputs.",
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- "addressedByControls": ["AIDBA-3"]
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- }
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- ]
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- }
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- ]
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- },
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- {
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- "stageName": "Model Evaluation and Testing",
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- "systemComponents": [
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- {
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- "componentName": "Performance Evaluation",
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- "risks": [
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- {
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- "riskId": "3.1",
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- "title": "Inadequate Performance Metrics",
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- "definition": "The selected performance metrics may not adequately capture the fairness and bias aspects of the AI model.",
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- "addressedByControls": ["AIDBA-4"]
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- }
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- ]
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- },
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- {
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- "componentName": "Bias Testing",
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- "risks": [
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- {
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- "riskId": "3.2",
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- "title": "Undetected Residual Bias",
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- "definition": "The testing process may fail to identify and quantify residual biases present in the trained AI model.",
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- "addressedByControls": ["AIDBA-4"]
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- }
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- ]
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- }
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- ]
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- },
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- {
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- "stageName": "Deployment and Monitoring",
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- "systemComponents": [
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- {
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- "componentName": "Model Deployment",
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- "risks": [
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- {
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- "riskId": "4.1",
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- "title": "Fairness Drift",
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- "definition": "The fairness properties of the AI model may degrade over time due to changes in the underlying data or environment.",
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- "addressedByControls": ["AIDBA-5"]
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- }
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- ]
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- },
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- {
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- "componentName": "Monitoring and Feedback",
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- "risks": [
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- {
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- "riskId": "4.2",
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- "title": "Insufficient Monitoring",
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- "definition": "The monitoring processes may not effectively detect emerging biases or fairness issues in the deployed AI system.",
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- "addressedByControls": ["AIDBA-5"]
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- }
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- ]
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- }
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- ]
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- }
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- ]
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- },
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- "controlList": [
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  {
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  "controlId": "AIDBA-1",
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  "title": "Data Bias Assessment and Mitigation",
 
1
  {
2
+ "name": "AI Bias Assessment and Mitigation Framework",
3
+ "description": "A framework for assessing and mitigating bias in AI systems throughout the development lifecycle.",
4
+ "stages": [
5
+ {
6
+ "stageName": "Data Collection and Preprocessing",
7
+ "systemComponents": [
8
+ {
9
+ "componentName": "Data Source Selection",
10
+ "risks": [
11
+ {
12
+ "riskId": "1.1",
13
+ "title": "Biased Data Sources",
14
+ "definition": "The selected data sources may contain inherent biases or lack diversity, leading to biased AI models.",
15
+ "addressedByControls": ["AIDBA-2"]
16
+ }
17
+ ]
18
+ },
19
+ {
20
+ "componentName": "Data Preprocessing",
21
+ "risks": [
22
+ {
23
+ "riskId": "1.2",
24
+ "title": "Preprocessing-Induced Bias",
25
+ "definition": "Data preprocessing techniques, such as feature selection or data cleaning, may introduce or amplify biases in the data.",
26
+ "addressedByControls": ["AIDBA-2"]
27
+ }
28
+ ]
29
+ },
30
+ {
31
+ "componentName": "Data Bias Assessment",
32
+ "risks": [
33
+ {
34
+ "riskId": "1.3",
35
+ "title": "Inadequate Bias Assessment",
36
+ "definition": "Failure to conduct comprehensive assessments to identify potential biases in the training data may result in biased AI models.",
37
+ "addressedByControls": ["AIDBA-1"]
38
+ }
39
+ ]
40
+ }
41
+ ]
42
+ },
43
+ {
44
+ "stageName": "Model Development and Training",
45
+ "systemComponents": [
46
+ {
47
+ "componentName": "Algorithm Selection",
48
+ "risks": [
49
+ {
50
+ "riskId": "2.1",
51
+ "title": "Algorithmic Bias",
52
+ "definition": "The chosen algorithms may have inherent biases or may amplify biases present in the training data.",
53
+ "addressedByControls": ["AIDBA-3"]
54
+ }
55
+ ]
56
+ },
57
+ {
58
+ "componentName": "Model Training",
59
+ "risks": [
60
+ {
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+ "riskId": "2.2",
62
+ "title": "Training Data Bias",
63
+ "definition": "The training data used to develop the AI model may contain biases, leading to biased model outputs.",
64
+ "addressedByControls": ["AIDBA-3"]
65
+ }
66
+ ]
67
+ }
68
+ ]
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+ },
70
+ {
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+ "stageName": "Model Evaluation and Testing",
72
+ "systemComponents": [
73
+ {
74
+ "componentName": "Performance Evaluation",
75
+ "risks": [
76
+ {
77
+ "riskId": "3.1",
78
+ "title": "Inadequate Performance Metrics",
79
+ "definition": "The selected performance metrics may not adequately capture the fairness and bias aspects of the AI model.",
80
+ "addressedByControls": ["AIDBA-4"]
81
+ }
82
+ ]
83
+ },
84
+ {
85
+ "componentName": "Bias Testing",
86
+ "risks": [
87
+ {
88
+ "riskId": "3.2",
89
+ "title": "Undetected Residual Bias",
90
+ "definition": "The testing process may fail to identify and quantify residual biases present in the trained AI model.",
91
+ "addressedByControls": ["AIDBA-4"]
92
+ }
93
+ ]
94
+ }
95
+ ]
96
+ },
97
+ {
98
+ "stageName": "Deployment and Monitoring",
99
+ "systemComponents": [
100
+ {
101
+ "componentName": "Model Deployment",
102
+ "risks": [
103
+ {
104
+ "riskId": "4.1",
105
+ "title": "Fairness Drift",
106
+ "definition": "The fairness properties of the AI model may degrade over time due to changes in the underlying data or environment.",
107
+ "addressedByControls": ["AIDBA-5"]
108
+ }
109
+ ]
110
+ },
111
+ {
112
+ "componentName": "Monitoring and Feedback",
113
+ "risks": [
114
+ {
115
+ "riskId": "4.2",
116
+ "title": "Insufficient Monitoring",
117
+ "definition": "The monitoring processes may not effectively detect emerging biases or fairness issues in the deployed AI system.",
118
+ "addressedByControls": ["AIDBA-5"]
119
+ }
120
+ ]
121
+ }
122
+ ]
123
+ }
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+ ],
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+ "controls": [
 
 
126
  {
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  "controlId": "AIDBA-1",
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  "title": "Data Bias Assessment and Mitigation",