The lawful, ethical, and responsible use of artificial intelligence (AI) is a key priority for Anthology; therefore, we have developed and implemented a Trustworthy AI program. You can find information on our program and general approach to Trustworthy AI in our Trust Center. You can find an overview of Anthology solutions with generative AI in our List of generative AI features.
As part of our Trustworthy AI principles, we commit to transparency, explainability, and accountability. This page is intended to provide the necessary transparency and explainability to help our clients with their implementation of the AVA Assisted Feedback. We recommend that administrators carefully review this page and ensure that instructors are aware of the considerations and recommendations below before you activate the AVA Assisted Feedback’s functionalities for your institution.
How to contact us:
- For questions or feedback on our general approach to Trustworthy AI or how we can make this page more helpful for our clients, please email us at [email protected].
- For questions or feedback about the functionality or output of the AVA Assisted Feedback, please submit a client support ticket.
Last updated: September 3rd, 2025
AI-facilitated functionalities
Anthology Virtual Assistant (AVA), a premium capabilities license, includes the AVA Assisted Feedback feature, which enables instructors to provide more consistent feedback through 2 options to the instructor when the AI feature is enabled:
Rewrite:
The generative AI-powered Rewrite option helps instructors improve the clarity and readability of their feedback when flexible grading is available. This tool uses generative AI to reword instructor-authored comments (e.g., rough notes, bullet points, or complete sentences) into more polished and student-friendly language. This option supports iterative editing and is designed to help instructors deliver clearer, more impactful feedback with less effort.
Instructors can access the Rewrite option when providing overall feedback or per-question feedback in Flexible Grading. After entering their own comments, instructors can select Rewrite to generate a suggested version of the feedback. A banner clearly indicates that the suggestion is AI-generated.
Instructors can accept, reject, or regenerate the suggestion. Accepting the suggestion allows instructors to continue editing the revised feedback directly in the Rich Text Editor (RTE). Rejecting or canceling the suggestion restores the original input. Instructors can use the Rewrite option multiple times on the same feedback to refine their message further.
Summarize from a rubric:
The AI-powered Summarize option in Flexible Grading lets instructors generate consistent overall feedback for student submissions evaluated using a rubric. This tool uses generative AI to analyze existing instructor feedback and suggest overall feedback on the submission based on the rubric criteria, the selected performance levels and their descriptions, and any detailed criterion feedback provided by the instructor.
Instructors can access this option when providing overall feedback on assignments once the rubric has been completed. For assignments, the summary is based on the rubric criteria, the selected performance levels and their descriptions, and any criterion-level feedback provided by the instructor. Any existing Overall Feedback in the RTE will also be included in the summary.
A banner clearly indicates that the summary is AI-generated. Instructors can accept, reject, or regenerate the summary. Accepting the summary then allows the instructor to directly edit and further refine the summary. Rejecting reverts the summary to the original. Regenerating the summary prompts a newly written summary.
These functionalities are subject to the limitations and availability of the Azure OpenAI Service and are subject to change. Please check the relevant release notes for details.
Key Facts
| Question | Answer |
|---|---|
| What functionalities use AI systems? | All AVA Assisted Feedback functionalities described above (AI-powered -Rewrite and AI-powered-Summarize). |
| Is this a third-party supported AI system? | Yes – The AVA Assisted Feedback is powered by Microsoft’s Azure OpenAI Service. |
| How does the AI system work? |
The AVA Assisted Feedback leverages Microsoft’s Azure OpenAI Service to auto-generate outputs. This is achieved by using limited information (e.g., instructor-authored comments, rubric criteria) and prompting the Azure OpenAI Service accordingly via the Azure OpenAI Service API. For an explanation of how the Azure OpenAI Service and the underlying OpenAI GPT large language models work in detail, please refer to the Introduction section of Microsoft’s Transparency Note and the links provided within it. |
| Where is the AI system hosted? |
Anthology currently uses multiple global Azure OpenAI Service instances. The primary instance is hosted in the United States but at times we may utilize resources in other locations such as Canada, the United Kingdom or France to provide the best availability option for the Azure OpenAI Service for our clients. All client course data used for the input and all output generated by the AVA Assisted Feedback is stored in the client’s existing Blackboard database by Anthology. |
| Is this an opt-in functionality? | Yes. Administrators need to activate the AVA Assisted Feedback in the Blackboard admin console. Settings for the AVA Assisted Feedback are in the Building Blocks category. Select AVA Assisted Feedback. Administrators can activate or deactivate each functionality separately. Administrators also need to assign AVA Assisted Feedback privileges to course roles as necessary, such as the Instructor role. |
| How is the AI system trained? |
Anthology is not involved in the training of the large language models that power the AVA Assisted Feedback functionalities. These Microsoft Azure OpenAI models are trained by OpenAI. Microsoft provides information about how the large language models are trained in the Introduction section of Microsoft’s Transparency Note and the links provided within it. Anthology does not further fine-tune the Azure OpenAI Service using our own or our clients’ data. |
| Is client data used for (re)training the AI system? | No. Microsoft contractually commits in its Azure OpenAI terms with Anthology to not use any input into, or output of, the Azure OpenAI for the (re)training of the large language model. The same commitment is made in the Microsoft documentation on Data, privacy, and security for Azure OpenAI Service. |
| How does Anthology use personal information with regard to the provision of the AI Al Text Assistant system? | Anthology only uses the information collected in connection with the AVA Assisted Feedback to provide, maintain and support the AVA Assisted Feedback and where we have the contractual permission to do so in accordance with applicable law. You can find more information about Anthology’s approach to data privacy in our Trust Center. |
| In the case of a third-party supported AI system, how will the third party use personal information? |
Only limited course, rubric and feedback information is provided to Microsoft for the Azure OpenAI Service. Microsoft does not use any Anthology data nor Anthology client data it has access to (as part of the Azure OpenAI Service) to improve the OpenAI models, to improve its own or third-party products services, nor to automatically improve the Azure OpenAI models for Anthology’s use in Anthology’s resource (the models are stateless). Microsoft reviews prompts and output for its content filtering to prevent abuse and harmful content generation. Prompts and output are only stored for up to 30 days. You can find more information about the data privacy practices regarding the Azure OpenAI Service in the Microsoft documentation on Data, privacy, and security for Azure OpenAI Service. |
| Was accessibility considered in the design of the AI System? | Yes, our accessibility engineers collaborated with product teams to review designs, communicate important accessibility considerations, and to test the new features specifically for accessibility. We will continue to consider accessibility as an integral part of our Trustworthy AI approach. |
Considerations and recommendations for institutions
Intended use cases
The AVA Assisted Feedback is only intended to support the functionalities listed above (AI-powered Rewrite and AI-powered Summarize). These functionalities are intended for our clients’ instructors to support them with feedback workflows within Blackboard.
Out-of-scope use cases
We strongly discourage clients from using AVA Assisted Feedback for any purpose beyond the scope of its intended functionalities. Doing so may result in the generation of outputs that are not suitable for or compatible with the Blackboard environment and the measures we have put in place to minimize inaccurate output.
Trustworthy AI principles in practice
Anthology and Microsoft believe the lawful, ethical and responsible use of AI is a key priority. This section explains how Anthology and Microsoft have worked to address the applicable risk to the legal, ethical and responsible use of AI and implement the Anthology Trustworthy AI principles. It also suggests steps our clients can consider when undertaking their own AI and legal reviews of ethical AI risks of their implementation.
Transparency and Explainability
- We make it clear in the Student administrator configuration options that this is an AI-facilitated functionality
- In the user interface for instructors, the AVA Assisted Feedback functionalities are clearly marked as ‘Generate’ functionalities. Instructors are also requested to review the text output prior to use. · The metadata of the output created by the AVA Assisted Feedback functionalities has a field for auto-generated content and whether the content was subsequently edited by the instructor.
- In addition to the information provided in this document on how the AVA Assisted Feedback and the Azure OpenAI Service models work, Microsoft provides additional information about the Azure OpenAI Service in its Transparency Note.
- We encourage clients to be transparent about the use of AI within the AVA Assisted Feedback and provide their instructors and other stakeholders as appropriate with the relevant information from this document and the documentation linked herein.
Reliability and accuracy
- We make it clear in the Blackboard administrator console that this is an AI-facilitated functionality that may produce inaccurate or undesired output and that such output should always be reviewed.
- In the user interface, instructors are requested to review the text output for accuracy.
- As detailed in the Limitations section of the Azure OpenAI Service Transparency Note, there is a risk of inaccurate output (including ‘hallucinations’). While the specific nature of the AVA Assisted Feedback and our implementation is intended to minimize inaccuracy, it is our client’s responsibility to review output for accuracy, bias and other potential issues.
- As part of their communication regarding the AVA Assisted Feedback, clients should make their instructors aware of this potential limitation.
- Instructors can use existing workflows in Blackboard to manually edit the AVA Assisted Feedback outputs before publishing the output to students.
- Clients can report any inaccurate output to us using the channels listed in the introduction.
Fairness
- Large language models inherently present risks relating to stereotyping, over/under-representation and other forms of harmful bias. Microsoft describes these risks in its Limitations section of the Azure OpenAI Service Transparency Note.
- Given these risks, we have carefully chosen the AVA Assisted Feedback functionalities to avoid use cases that may be more prone to harmful bias or where the impact of such bias could be more significant.
- Nonetheless, it cannot be excluded that some of the output may be impacted by harmful bias. As mentioned above under ‘Accuracy’, instructors are requested to review output, which can help to reduce any harmful bias.
- As part of their communication regarding the AVA Assisted Feedback, clients should make their instructors aware of this potential limitation.
- Clients can report any potentially harmful bias to us using the contact channels listed in the introduction.
Privacy and Security
- As described in the ‘Key facts’ section above, only limited personal information is used for the AVA Assisted Feedback and accessible to Microsoft. The section also describes our and Microsoft’s commitment regarding the use of any personal information. Given the nature of the AVA Assisted Feedback, personal information in the generated output is also expected to be limited.
- Our Blackboard SaaS product is ISO 27001/27017/27018/27701 certified. These certifications will include the AVA Assisted Feedback-related personal information managed by Anthology. You can find more information about Anthology’s approach to data privacy and security in our Trust Center.
- Microsoft describes its data privacy and security practices and commitments in the documentation on Data, privacy, and security for Azure OpenAI Service.
Safety
- Large language models inherently present a risk of outputs that may be inappropriate, offensive, or otherwise unsafe. Microsoft describes these risks in its Limitations section of the Azure OpenAI Service Transparency Note.
- Given these risks, we have carefully chosen the AVA Assisted Feedback functionalities to avoid use cases that may be more prone to unsafe outputs or where the impact of such output could be more significant.
- Nonetheless, it cannot be excluded that some of the output may be unsafe. As mentioned above under ‘Accuracy’, instructors are requested to review output, which can further help reduce the risk of unsafe output.
- As part of their communication regarding the AVA Assisted Feedback, clients should make their instructors aware of this potential limitation.
- Clients should report any potentially unsafe output to us using the channels listed in the introduction.
Humans in control
- To minimize the risk related to the use of generative AI for our clients and their users, we intentionally put clients in control of the AVA Assisted Feedback’s functionalities. The AVA Assisted Feedback is therefore an opt-in feature.
- Administrators must activate the AVA Assisted Feedback and can then activate each functionality separately. They can also deactivate the AVA Assisted Feedback overall or each of the individual functionalities.
- Additionally, instructors are in control of the output. They are requested to review text output and can edit the text output.
- The use of AVA Assisted Feedback is optional. Instructors can continue using the standard (non-AI) approach if they prefer, and there is no requirement to adopt the AI features.
- The AVA Assisted Feedback does not include any automated decision-making that could have a legal or otherwise significant effect on learners or other individuals.
- We encourage clients to carefully review this document including the information links provided herein, to ensure they understand the capabilities and limitations of the AVA Assisted Feedback and the underlying Azure OpenAI Service before they activate the AVA Assisted Feedback in the production environment.
Value alignment
- Large language models inherently have risks regarding output that is biased, inappropriate or otherwise not aligned with Anthology’s values or the values of our clients and students. Microsoft describes these risks in its Limitations section of the Azure OpenAI Service Transparency Note.
- Additionally, large language models (like every technology that serves broad purposes), present the risk that they can generally be misused for use cases that do not align with the values of Anthology, our clients or their end users and those of society more broadly (e.g., for criminal activities, to create harmful or otherwise inappropriate output).
- Given these risks, we have carefully designed and implemented our AVA Assisted Feedback functionalities in a manner to minimize the risk of misaligned output. For instance, we have focused on functionalities for instructors rather than for learners. We have also intentionally omitted potentially high-stakes functionalities.
- Microsoft also reviews prompts and output as part of its content filtering functionality to prevent abuse and harmful content generation.
Intellectual property
- Large language models inherently present risks relating to potential infringement of intellectual property rights. Most intellectual property laws around the globe have not fully anticipated nor adapted to the emergence of large language models and the complexity of the issues that arise through their use. As a result, there is currently no clear legal framework or guidance that addresses the intellectual property issues and risks that arise from use of these models.
- Ultimately, it is our client’s responsibility to review output generated by that AVA Assisted Feedback for any potential intellectual property right infringement.
Accessibility
We designed and developed the AVA Assisted Feedback with accessibility in mind as we do throughout Blackboard and our other products. Before the release of the AVA Assisted Feedback, we purposefully improved the accessibility of the semantic structure, navigation, keyboard controls, labels, custom components, and image workflows, to name a few areas. We will continue to prioritize accessibility as we leverage AI in the future.
Accountability
- Anthology has a Trustworthy AI program designed to ensure the legal, ethical, and responsible use of AI. Clear internal accountability and the systematic ethical AI review or functionalities such as those provided by the AVA Assisted Feedback are key pillars of the program.
- To deliver the AVA Assisted Feedback, we partnered with Microsoft to leverage the Azure OpenAI Service which powers the AVA Assisted Feedback. Microsoft had a long-standing commitment to the ethical use of AI.
- Clients should consider implementing internal policies, procedures and review of third-party AI applications to ensure their own legal, ethical, and responsible use of AI. This information is provided to support our clients’ review of the AVA Assisted Feedback.
Further information
- Anthology’s Trustworthy AI approach
- Microsoft’s Responsible AI page
- Microsoft’s Transparency Note for Azure OpenAI Service
- Microsoft’s page on Data, privacy, and security for Azure OpenAI Service