University of Dayton AI Policy

At UD, students build the knowledge and skills to use AI effectively and responsibly, preparing them to learn and lead in an increasingly AI-enabled world. This means that Flyers understand not only when to use AI but also when not to use it — and how to evaluate AI outputs.

Our curriculum is constantly evolving to prepare students for an ever-changing world. All UD students receive an introduction to the fundamentals of AI and explore questions about AI and human dignity in their first year-courses. They build on that foundation through the second-year writing seminar, enhancing their analytical skills and applying their growing understanding of AI to written communication. Upperclass students learn how to apply AI in ways that are appropriate for their major and profession.

Unless specifically permitted by your professor (e.g., Grammarly; BriefCatch), using Artificial Intelligence is considered an act of academic dishonesty when it comes to class assignments.

The VLCFF prohibits the use of generative AI, such as ChatGPT, in any written work for exercises and discussion boards. All written work must be the student's original ideas, and any outside sources used, such as textbooks or articles, must be cited appropriately.

At UD, students build the knowledge and skills to use AI effectively and responsibly, preparing them to learn and lead in an increasingly AI-enabled world. This means that Flyers understand not only when to use AI but also when not to use it — and how to evaluate AI outputs.

At UD, students build the knowledge and skills to use AI effectively and responsibly. Our curriculum is constantly evolving to prepare students for an ever-changing world. All UD students receive an introduction to the fundamentals of AI and explore questions about AI and human dignity in their first-year courses. They build on that foundation through advanced writing and rhetoric courses that build analytical skills and challenge them to apply their growing understanding of AI to written communication.

Students engage with AI in ways that are appropriate for their major and profession.

Research Record means: the record of data or results that embody the facts resulting from scientific inquiry. Data or results may be in physical or electronic form.

Examples of items, materials, or information that may be considered part of the research record include, but are not limited to, research proposals, raw data, processed data, clinical research records, laboratory records, study records, laboratory notebooks, progress reports, manuscripts, abstracts, theses, records of oral presentations, online content, lab meeting reports, and journal articles.

Research Misconduct is defined as: fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. It does not include honest error or differences of opinion.

Plagiarism is defined as: the appropriation of another person’s ideas, processes, results, or words without giving appropriate credit.

Research Record means: the record of data or results that embody the facts resulting from scientific inquiry. Data or results may be in physical or electronic form.

Examples of items, materials, or information that may be considered part of the research record include, but are not limited to, research proposals, raw data, processed data, clinical research records, laboratory records, study records, laboratory notebooks, progress reports, manuscripts, abstracts, theses, records of oral presentations, online content, lab meeting reports, and journal articles.

Fabrication is defined as: making up data or results and recording or reporting them.

Falsification is defined as: manipulating research materials, equipment, or processes; or changing or omitting data or results such that the research is not accurately represented in the research record.

Research Responsibilities: the scholar/researcher is responsible for the conduct of research and supervising other researchers, students, and staff personnel to promote high ethical standards in the conduct of such research. These standards include detecting irregular practices in research and scholarship procedures, handling data and results, introducing remedial measures in case of innocent mistakes, and investigating and eliminating willful fraud.

Using AI tools that aren’t officially contracted by UD. These may collect and train on any data you provide.

Research Misconduct is defined as: fabrication, falsification, or plagiarism in proposing, performing, or reviewing research, or in reporting research results. It does not include honest error or differences of opinion.

Plagiarism is defined as: the appropriation of another person’s ideas, processes, results, or words without giving appropriate credit.

All written work must be the student's original ideas, and any outside sources used, such as textbooks or articles, must be cited appropriately.

Plagiarism includes using the words, thoughts, or ideas of another without attribution consistent with standard legal citation manuals (e.g., ALWD Citation Manual or Bluebook), so that they seem as if they are your own. Depending on the circumstances, proper attribution should include a citation, as well as quotation marks.

Using any form of AI can be plagiarism. While AI will likely play a role in research and writing in the future, you need to practice legal research and writing on your own first. Passing off another’s words in your class assignments as your own, which includes a computer program’s words, is considered impermissible plagiarism when it comes to class assignments.

In the event that the use of generative AI is suspected, the work will be checked by one or more AI detection programs. If plagiarism, the uncredited use of another's work, is suspected, the work will also be checked.

If a strong indication of AI or plagiarism is determined, the student will be asked to resubmit the work.

Unless specifically permitted by your professor (e.g., Grammarly; BriefCatch), using Artificial Intelligence is considered an act of academic dishonesty when it comes to class assignments.

Students sometimes make minor mistakes in completing academic assignments. While one missing citation in an assignment may, in most instances, be considered a careless mistake rather than academic dishonesty, multiple instances of failing to provide proper attribution through quotation marks and/or citations will give rise to an inference that you have inappropriately used the work of others and will be reported to the Honor Council.

As the UD community continues exploring how AI can enhance teaching, learning, research, and administration, it’s important to balance the power of these tools with our responsibilities, especially when it comes to data.

Faculty and staff explore AI through faith, ethics and education.

Together, the three groups above carefully consider things like authentication, role-based authorization, compliance requirements, server best practices, data-specific training, the effects of new technologies such as Artificial Intelligence, etc., to help ensure that University Systems are architected appropriately.

The four classification levels laid out above comprise the entirety of the University’s data classification categories.

As the UD community continues exploring how AI can enhance teaching, learning, research, and administration, it’s important to balance the power of these tools with our responsibilities, especially when it comes to data.

Using AI tools that aren’t officially contracted by UD. These may collect and train on any data you provide.

Sharing sensitive results with people who aren’t authorized to see them, sometimes unintentionally.

Our AI strategy, rooted in our Catholic and Marianist identity, is guided by five core principles.

Human Thriving and Human-Centered Use: Center human intelligence and responsibility that respects the dignity of each person and promotes the common good.

Ethical, Equitable, and Responsible Use: Ensure accessible, equitable, and inclusive access to AI tools and resources, guided by ethical standards of transparency, accountability, sustainability, and privacy. Proactively account for bias and misuse, maintain human oversight, and foster ethical reasoning across UD.

Student-Centric Approach: Engage with AI to enhance the student learning experience, support their well-being, and prepare them for future careers.

Innovation and Research: Foster a culture of critical experimentation and research in AI, contributing to advancements in the field and interdisciplinary collaboration.

Organizational Excellence and Efficiency: Advance organizational excellence and operational efficiency through bold, strategic use of AI to streamline and strengthen University performance, optimize campus operations, and further UD’s mission and identity.