attachment_16_genai_std_1000.pdf
PDF 697 KB Posted
- Attached to
- RFP 24-3003 ICWA Training
- Solicitation number
- 0000030954
- Issued by
- California
About this file
This document is a GenAI Disclosure and Factsheet form issued by the California Department of General Services Procurement Division. It requires bidders to disclose if they will be using or offering any generative artificial intelligence (GenAI) technology, model, or service as part of their proposed solution or service for the RFP 24-3003 contract opportunity with the California Department of Social Services.
The disclosure form requests detailed information about the GenAI system, including the model name and version, model owner, overview, purpose, intended domain, training data, model architecture, inputs and outputs, performance metrics, optimal and poor operating conditions, bias, and test data. Bidders must explain how they are ensuring the GenAI system does not adversely impact decisions related to housing, education, employment, credit, healthcare, and criminal justice. Failure to properly disclose and provide the requested details may result in disqualification and potential contract voidance.
View the file
Other files
Show all 20
On GovTribe
Work with this file
- Download the original file
- Contacts named in this file
- Similar government files
- Ask GovTribe AI about this file
Text version
STATE OF CALIFORNIA
GENAI DISCLOSURE & FACTSHEET
STD 1000 (NEW 01/2024)
DEPARTMENT OF GENERAL SERVICES
PROCUREMENT DIVISION
Generative Artificial Intelligence (GenAI) Disclosure & Factsheet
Bidder/Offer Information
Solicitation Number Bidder ID/Vendor ID (optional)
Business Name Business Telephone Number
Business Address
GenAI Disclosure & Factsheet
City State Zip Code
Will you be using or offering GenAI technology, model, or service (collectively, “system”)? Yes No (If No, skip to Signature section of this form.)
If yes, provide details regarding the GenAI system”). See GenAI Disclosure & Factsheet Definitions at the end of this form for more information.
Failure to disclose GenAI to the State and submit the detailed description may result in disqualification and may void any resulting contract.
1. GenAI Model Name, Version (including number of parameters)
2. Model Owner
3. Overview
4. Purpose
5. Intended Domain
6. Model Training Data
7. Model Information
RFP 24-3003
California Department of Social Services
Attachment 16
STD 1000 (NEW 01/2024)
STATE OF CALIFORNIA DEPARTMENT OF GENERAL SERVICES
GENAI DISCLOSURE & FACTSHEET PROCUREMENT DIVISION
8. Input and Outputs
9. Performance Metrics
10. Optimal Conditions
11. Poor Conditions
12. Bias
13. Test Data
Explain below how you are ensuring the GenAI system is not adversely affecting “decisions that materially impact access to, or approval for, housing or accommodations, education, employment, credit, health care, and criminal justice.” (AB 302, Department of Technology: High-Risk automated decision systems: inventory).
Signature
By signing this document, I certify that I have identified and disclosed, if any, all GenAI components in the proposed solution or service.
Signature Date
RFP 24-3003
California Department of Social Services
STD 1000 (NEW 01/2024)
GENAI DISCLOSURE & FACTSHEET PROCUREMENT DIVISION
GenAI Disclosure & Factsheet Definitions Please use the following definitions to complete the GenAI Disclosure and Factsheet:
1. Model Name, Version & Number of Parameters:
Definition: The unique identifier or name assigned to the specific GenAI model or service.
Purpose: Allows users to refer to and distinguish between different GenAI models.
2. Model Owner Definition: The name of the organization or entity responsible for creating or deploying the GenAI model or service.
Importance: Helps identify the source and accountability for the GenAI system.
3. Overview:
Definition: A concise summary of the GenAI model’s purpose, functionality, and key characteristics.
Role: Provides a high-level understanding for users and stakeholders.
4. Purpose:
Definition: The intended use or goal of the GenAI model (e.g., image recognition, natural language processing, text summarization).
Significance: Helps users assess whether the GenAI model aligns with their needs.
5. Intended Domain:
Definition: The context, subject matter or domain for which the GenAI model is designed to operate effectively.
Importance: Helps users determine if the GenAI model is suitable for their specific use case.
6. Training Data:
Definition: Information used to train the GenAI model (e.g., labeled images, text corpora).
Role: Influences the GenAI model’s behavior and performance.
7. Model Information:
Definition: Details about the architecture, parameters, and configuration of the GenAI model.
Relevance: Provides insights into how the GenAI model functions.
8. Inputs and Outputs:
Definition:
o Inputs: The data or features provided to the model for prediction (e.g., images, text).
o Outputs: The GenAI model’s predictions or results (e.g., class labels, probabilities).
Understanding: Crucial for integrating the GenAI model into applications.
9. Performance Metrics:
Definition: Quantitative measures (e.g., accuracy, F1-score) used to evaluate the GenAI model’s performance.
Assessment: Determines how well the GenAI model meets its intended purpose.
Continuous Monitoring Plan: Establishes a plan for continuous monitoring and evaluation of the GenAI model’s performance.
RFP 24-3003
California Department of Social Services
GENAI DISCLOSURE & FACTSHEET PROCUREMENT DIVISION
STD 1000 (NEW 01/2024)
10. Optimal Conditions:
Definition: The ideal environment or context for the GenAI model to perform optimally.
Contextual Guidance: Helps users achieve the best results.
11. Poor Conditions:
Definition: Scenarios or conditions where the GenAI model’s performance may degrade.
Risk Awareness: Alerts users to potential limitations.
12. Bias:
Definition: Any systematic error or unfairness in the GenAI model’s predictions due to biased training data or design.
Mitigation: Addressing bias is crucial for ethical and unbiased GenAI.
13. Test Data:
Definition: Independent data used to evaluate the GenAI model’s performance after training.
Validation: Ensures the GenAI model generalizes well to unseen examples.
RFP 24-3003
California Department of Social Services
File details come from the government source that posted it. Updated .