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Artificial Intelligence (AI) Statement

Artificial Intelligence (AI) Statement

Artificial Intelligence (AI) Statement

Plan Forward recognizes the importance of responsible AI and is steadfastly committed to implementing ethical AI practices that prioritize transparency, fairness, and accountability.

Purpose of the Plan Forward platform:


Plan Forward's AI-powered platform using large language Models (LLMs) acts as a co-pilot for school and district administrators by organizing, analyzing, and delivering actionable insights from collected data to drive evaluation of initiatives and goal attainment. The tool directly aids in the implementation of comprehensive progress monitoring and evaluation strategies while also providing valuable insights into the successes and challenges associated with targeted programs. Plan Forward fosters improved goal attainment and continuous improvement. 

Supported by well-regarded research frameworks, including Mosseri's (2010) data-informed decision-making approach, the Continuous Improvement Cycle of Plan-Do-Study-Act by Shakman et al. (2020), Locke & Latham's (1990) goal-setting theory, and Bandura's (1977) self-efficacy theory, Plan Forward's methodology ensures that every step is grounded in rigorous, evidence-based strategies focused on continuous monitoring and feedback for mastery.


Data Collection:


Plan Forward stores data securely through a multi-faceted approach that incorporates industry-standard encryption, rigorous access controls, and continuous monitoring. Data encryption, both in transit and at rest, ensures that sensitive information remains protected from unauthorized access. Plan Forward requires advanced access controls, such as multi-factor authentication (MFA) and role-based access permissions, enabling only authorized personnel to interact with the data, thereby minimizing the risk of internal breaches. Through these comprehensive measures, the integrity and confidentiality of the data in LLM-powered software are robustly safeguarded. 


The qualitative and quantitative information provided to Plan Forward in an anonymized form without and excluding any Personally Identifiable Information (PII) as it is outlined and defined by the Family Educational Rights and Privacy Act of 1974 (“FERPA”).    

For more information, please review the Plan Forward Privacy Statement.


Compliance & Legal Considerations:

Plan Forward's advanced LLM is trained to qualitatively analyze textual data, including open-ended survey responses and transcripts. This AI system excels in extracting and organizing text into prominent themes based on frequency and relevance. 


Leveraging a closed knowledge base, Plan Forward provides well-founded recommendations and actionable steps, grounded in best practices and supported by empirical research from reputable sources such as the What Works Clearinghouse. Source lists and articles referenced will be listed in each report. These capabilities ensure that school districts have access to tailored, evidence-based strategies for addressing their unique priorities and challenges.


Plan Forward recognizes the importance of responsible AI and is steadfastly committed to implementing ethical AI practices that prioritize transparency, fairness, and accountability.

Purpose of the Plan Forward platform:


Plan Forward's AI-powered platform using large language Models (LLMs) acts as a co-pilot for school and district administrators by organizing, analyzing, and delivering actionable insights from collected data to drive evaluation of initiatives and goal attainment. The tool directly aids in the implementation of comprehensive progress monitoring and evaluation strategies while also providing valuable insights into the successes and challenges associated with targeted programs. Plan Forward fosters improved goal attainment and continuous improvement. 

Supported by well-regarded research frameworks, including Mosseri's (2010) data-informed decision-making approach, the Continuous Improvement Cycle of Plan-Do-Study-Act by Shakman et al. (2020), Locke & Latham's (1990) goal-setting theory, and Bandura's (1977) self-efficacy theory, Plan Forward's methodology ensures that every step is grounded in rigorous, evidence-based strategies focused on continuous monitoring and feedback for mastery.


Data Collection:


Plan Forward stores data securely through a multi-faceted approach that incorporates industry-standard encryption, rigorous access controls, and continuous monitoring. Data encryption, both in transit and at rest, ensures that sensitive information remains protected from unauthorized access. Plan Forward requires advanced access controls, such as multi-factor authentication (MFA) and role-based access permissions, enabling only authorized personnel to interact with the data, thereby minimizing the risk of internal breaches. Through these comprehensive measures, the integrity and confidentiality of the data in LLM-powered software are robustly safeguarded. 


The qualitative and quantitative information provided to Plan Forward in an anonymized form without and excluding any Personally Identifiable Information (PII) as it is outlined and defined by the Family Educational Rights and Privacy Act of 1974 (“FERPA”).    

For more information, please review the Plan Forward Privacy Statement.


Compliance & Legal Considerations:

Plan Forward's advanced LLM is trained to qualitatively analyze textual data, including open-ended survey responses and transcripts. This AI system excels in extracting and organizing text into prominent themes based on frequency and relevance. 


Leveraging a closed knowledge base, Plan Forward provides well-founded recommendations and actionable steps, grounded in best practices and supported by empirical research from reputable sources such as the What Works Clearinghouse. Source lists and articles referenced will be listed in each report. These capabilities ensure that school districts have access to tailored, evidence-based strategies for addressing their unique priorities and challenges.


Training Data & Model Updates

User Authentication & Access Control

Implementation

Aligning with State and District Policies

Training Data & Model Updates

User Authentication & Access Control

Implementation

Aligning with State and District Policies

Training Data & Model Updates

User Authentication & Access Control

Implementation

Aligning with State and District Policies

Contact Information


If you have any questions about this AI Statement or our privacy practices, please contact us at info@k12planforward.com


By using our Services, you agree to the terms of this Privacy Statement.


*Last updated: June 2024

Contact Information


If you have any questions about this AI Statement or our privacy practices, please contact us at info@k12planforward.com


By using our Services, you agree to the terms of this Privacy Statement.


*Last updated: June 2024

© Plan Forward | All rights reserved

Washington D.C.

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© Plan Forward | All rights reserved

Washington D.C.

Connect with us

© Plan Forward | All rights reserved

Washington D.C.

Connect with us

© Plan Forward | All rights reserved

Washington D.C.

Connect with us