
Responsibly Designed AI
Awarded to Toddle on October 31, 2025 by Digital Promise - Product Certifications.
The edtech product’s developer team has sought to reduce bias in the product’s artificial intelligence (AI) features, from development through implementation. The developer team actively leverages a monitoring process to identify and address instances of bias within the model. Increased transparency allows users to better understand when AI is used in the product and how users may override some AI-driven decisions and recommendations. There is publicly available information about what user data is collected, how it is used, how it is stored securely, and what control a user has over their data.
Criteria
Certification Requirements
A product that earns this certification will demonstrate the following:
1. The applicant has a public, free-to-access privacy policy, or similar document, to help current and prospective users understand:
- What nonpublic personal information (NPI), including PII, data is collected, how it is stored, and for how long it is stored before being destroyed;
- How this data is or may be used (e.g. to train the AI model);
- Whether this data is shared with or sold to third parties; and
- What control the user has over this data.
2. The applicant has a public, free-to-access policy or other document describing how the product ensures data security, including a data breach or other incident response plan, as well as states which relevant data privacy laws this policy complies with (e.g. FERPA, COPPA, GDPR, etc.).
3. The applicant has documentation about how the product team has sought to acknowledge and reduce bias in the AI model from development through implementation. The applicant has provided two examples of instances where these monitoring processes identified bias and described the changes made to mitigate the bias. Additionally, users can report instances of bias through the product directly.
4. There are labels within the product to indicate when AI has been used in content generation that a user might mistake as being created or shared by a human (e.g. chat communication, images, word problems, literature, narrative feedback, etc.).
5. Educators or other individual users can override at least one AI decision or recommendation made to support learning.
Additional Information
Applicants who meet certification criteria earn an Open Badge to share that the product has been certified. The Open Badge is associated with the email address used to submit the application and is non-transferable. It is important to ensure long-term access by using a stable company address (e.g. research[at]product[dot]com), rather than an individual’s, to create an account and submit this application.
This certification expires after two years from the date of earning. Products must reapply to retain certified status to ensure the requirements are upheld over time.
To apply, a product must be part of ISTE’s Learning Technology Directory (LTD) and have a Universal Learning Technology Identifier (ULTID), which are also prerequisites for inclusion in the EdTech Index. There is no cost to companies to register. Learn more about the LTD, and how to register, here. The product certification review processes for any applicants that submit without having a ULTID will be paused until registration in the LTD is complete and the ULTID is shared with the Digital Promise team.
Please note that an application may be submitted on behalf of only one product. For the purpose of this certification, a ULTID denotes a single product. Multiple ULTIDs denote multiple products, and therefore multiple applications would be required.
A successful application will show a clear through line across all of the artifacts submitted.
What does Digital Promise consider “AI”?
AI is used in many capacities in edtech, from generative AI to speech recognition to computer vision. Please see the Alan Turing Institute’s definition of AI: “The design and study of machines that can perform tasks that would previously have required human (or other biological) brainpower to accomplish. AI is a broad field that incorporates many different aspects of intelligence, such as reasoning, making decisions, learning from mistakes, communicating, solving problems, and moving around the physical world. AI was founded as an academic discipline in the mid-1950s, and is now found in myriad everyday applications, including virtual assistants, search engines, navigation apps and online banking.”
What should I include in this application if there are multiple different AI models within the product?
This application is designed with the knowledge that edtech developers may use a variety of types or combinations of AI models to support learning. The certification requirements are written such that applicants can consider the variety of types of AI models in their product in their responses.
How is “bias” defined in this application?
For the purpose of this certification, bias refers to algorithmic bias, wherein the data that is used in training algorithms are unrepresentative of those from historically excluded communities, including communities of color and people with disabilities, leading to the generation of inequitable outputs. Users may also perceive that an AI-powered product is biased against them, which may negatively impact their experiences and outcomes with the product. For further reading, explore the Digital Promise reports in the Resources section.
Please reach out to productcertifications@digitalpromise.org with any further questions.
Assessment
Overview
Question 1
The following responses will not be assessed for content; however, full responses are required to pass Part 1.
What is the name of the product and its website? What is the product’s ULTID?
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Note: To apply, a product must be part of ISTE’s Learning Technology Directory (LTD) and have a universal learning technology identifier (ULTID). Learn more about the LTD, and how to register,
here . There is no cost to companies to register. The product certification review processes for any applicants that submit without having a ULTID will be paused until registration in the LTD is complete and the ULTID is shared with the Digital Promise team.
Overview
Question 2
If this product is awarded the certification, do we have the product team’s permission to share its award status with partners that host product catalogs, such as ISTE’s EdTech Index and LearnPlatform? Please respond with a yes or no.
Overview
Question 3
What general company email address can we use to communicate about certification status after a decision has been made? Note: If earned, the Open Badge is associated with the email address used to submit the application and is non-transferable. It is important to ensure long-term access by using a stable company address (e.g. research[at]product[dot]com), rather than an individual’s, to create an account and submit this application.
Who was involved in completing this application? Please include names, roles, and email addresses.
Overview
Question 4
Tell us about your product: What learning or challenge does the product intend to address? How many users does the product serve? Who is the intended audience for the product (e.g., learners or educators, grade or learner levels)? Which subject area(s) does the product cover?
Overview
Question 5
Tell us about the AI in the product. Describe all type(s) of AI models used. How is AI being used, and how is this intended to support teaching and/or learning? If generative AI is used, describe all ways that content is generated within the product, including what human oversight there may be of this content.
Overview
Question 6
How do interested purchasers learn about the pricing structure for the product? Is there a recommended dosage of use for the product to achieve intended outcomes and how do you communicate this to your users?
Work Example
The following responses will be assessed to inform the certification results.
Certification Requirement 1:
The applicant has a public, free-to-access privacy policy, or similar document, to help current and prospective users understand:
- What nonpublic personal information (NPI), including PII, data is collected, how it is stored, and for how long it is stored before being destroyed;
- How this data is or may be used (e.g. to train the AI model);
- Whether this data is shared with or sold to third parties; and
- What control the user has over this data.
Submit a file with both a link to a public-facing privacy policy or similar document, as well as documentation that indicates where the above information is found within the policy. The policy must be on the product’s website and designed for diverse audiences to review.
(Note: Data sharing agreements with particular clients may supersede the shared policy document.)
Work Example
Certification Requirement 2:
The applicant has a public, free-to-access policy or other document describing how the product ensures data security, including a data breach or other incident response plan, as well as states which relevant data privacy laws this policy complies with (e.g. FERPA, COPPA, GDPR, etc.).
Submit a file with both a link to a public-facing data security policy or similar document, as well as documentation that indicates where the above information is found within the policy. The policy must be on the product’s website and designed for diverse audiences to review. This may be the same policy page submitted for Certification Requirement 1 if applicable.
Work Example
Certification Requirement 3:
The applicant has documentation about how the product team has sought to acknowledge and reduce bias in the AI model from development through implementation. The applicant has provided two examples of instances where these monitoring processes identified bias and described the changes made to mitigate the bias. Additionally, users can report instances of bias through the product directly.
Submit the Certification Requirement 3 template, found in the Resources section.
- In Part A, describe up to two different AI models used in the product. For each model, use the template to submit a narrative describing the kind of model used in the product and its intended benefit to instruction or learning. You may reuse language from the application’s Part 1 Overview question if applicable. Then, describe how the developer team proactively sought to avoid bias in the model or in the implementation of the model in the product, and how the team continually monitors for bias.
- In Part B, describe two instances where bias monitoring processes identified bias, or potential for bias, in the AI model or in the implementation of the model in the product. Then, describe how the team responded and the change made to address this finding. Then, demonstrate how users can report, as feedback, their experience of bias or perceived bias while using the product (e.g. through a ticketing system).
Please reference “Additional Information” for a working definition of bias.
Work Example
Certification Requirement 4:
There are labels within the product to indicate when AI has been used in content generation that a user might mistake as being created or shared by a human (e.g. chat communication, images, word problems, literature, narrative feedback, etc.).
Submit a file with documentation (e.g. screenshots or videos) and a short description of each item included to demonstrate labels on different categories of content that AI has been used in generating content that a user might mistake as created or shared by a human (for example, if AI generates images in one part of the product, and provides narrative feedback in another, submit evidence for how each of these are labeled).
The purpose of this requirement is for a user to understand when AI has had a role in developing content, and your response must demonstrate how your product does this. If AI-generated content has been edited or reviewed by a human, labels are still required (but may also reflect the role a human has played). The label must be visible to the user (student and/or educator) on that content.
If the product does not contain any generative AI as described in this requirement, submit a file or link describing why this is the case, and showing where users can access information about how the product leverages AI, why the product uses AI, and what inputs inform the AI outputs. This can be a public-facing blog post, report, etc. and must be on the product’s website.
Work Example
Certification Requirement 5:
Educators or other individual users can override at least one AI decision or recommendation made to support learning.
Submit a file with evidence (e.g. screenshots, videos, etc.) and a description of how users can override at least one type of AI decision or recommendation made to support learning.
If the AI in the product does not make decisions or recommendations for the user, submit a file or link describing why this is the case, and showing where users can access information about how the product leverages AI, why the product uses AI, and what inputs inform the AI outputs. This can be a public-facing blog post, report, etc., must be on the product’s website, and may be the same public-facing documentation from the previous certification requirement if applicable.
Reflection
Reflect on the process of applying to this product certification.
- Are there additional ways your team designs AI responsibly that were not highlighted in this application?
- How did the process of applying for this certification influence conversations about the need to develop AI capabilities responsibly? To what extent did the application initiate conversations for future or ongoing research on the product’s responsible design of AI?
- Did your team make changes to the product, website, or organizational processes as a result of the requirements of this certification?
Achievement Type
- Certification
Supporting Information
Supporting Research and Rationale
- AI Literacy: A Framework to Understand, Evaluate, and Use Emerging Technology (Digital Promise)
- AI-Powered Innovations in Mathematics Teaching & Learning: Initial Findings (Digital Promise)
- Glossary of Artificial Intelligence Terms for Educators (CIRCLS)
- Policy Statement of the Federal Trade Commission on Education Technology and COPPA (Federal Trade Commission)
- Create a Universal Learning Technology Identifier (ULTID) (ISTE)
Resources
Template
Check out the FAQ page to learn more about the certification, the 4-week review process, and the application.
Submitting the Application
The responses for Parts 1 and 3 will be used only (1) to provide context for assessors while evaluating Part 2 of the submission, and (2) to enable Digital Promise to track aggregated data about the types of products that apply to and earn product certifications, such as content area, learner level, and product reach. These responses will not be included in the assessment of your application. The responses for Part 2 will be assessed to inform the certification results.
Applicants are encouraged to download the documents in the Resources section before beginning their application.
View the printable version of this application here.