












































Always Room for Mindfulness


167

LISTEN AND LEARN SESSIONS

AI in the Seminary Classroom 
Equipping Faculty to Address the Pedagogical, 
Moral, and Ethical Aspects of AI Use for  
Class Assignments  
Dyan Barbeau, Library Director, Sacred Heart Seminary and School of 
Theology
Kathy Harty, Research and Technology Librarian, Sacred Heart Seminary and 
School of Theology 

ABSTR ACT: Our session originated from our experience in responding 
to faculty questions about generative artificial intelligence and its use 
in class assignments. We addressed this issue with a faculty develop-
ment session and the creation of a LibGuide in which we answered 
basic questions about AI mechanics, the need for an AI plagiarism 
policy, ideas for assignments less susceptible to AI use, and ideas for 
introducing AI to students. As we prepared resources for our faculty, 
we learned that AI use for class assignments presents challenges far 
beyond the typical concerns about plagiarism detection, including 
issues with pedagogical, moral, and ethical implications, and became 
increasingly convinced that AI education is not only advisable but 
necessary in the seminary classroom. We also learned that our faculty, 
like university faculty across the country, were hesitant to address this 
challenging topic. Librarians, who regularly adapt to changing tech-
nology, can take the lead and support faculty in navigating the many 
issues arising from AI use. We identify three areas of collaboration: 
developing AI policies, teaching about the moral and ethical concerns 
regarding AI use, and crafting assignments.  



168    ATL A 2024 PROCEEDINGS

INTRODUCTION

Having received multiple questions from faculty regarding genera-
tive AI1 plagiarism, Sacred Heart Seminary and School of Theology 
librarians tackled the formidable task of AI education as librarians 
do, with research and a LibGuide. We hosted a faculty development 
session in January 2024 that focused on their plagiarism concerns, 
briefly discussing ethics, AI policies, and assignment design. Although 
our session and LibGuide sparked interest among our faculty, they 
did not follow up on our suggestions for policies or teaching. Our 
library staff concluded that, like information literacy one-shots, the 
one-time session and LibGuide did not impact behavior. We deter-
mined that a better approach would be to work with individuals and 
give them more specific ideas for addressing this issue.

Research shows that our faculty’s reaction mirrors that of other 
university faculty nationwide. AI is a big undertaking without much 
institutional guidance or support, like taking the proverbial first bite 
of an elephant. A survey of faculty from Northeastern University 
found that most faculty had not used it in teaching, even though 
a majority thought AI and digital literacy were important to their 
students’ success (Szeleny 2024). A survey of Metropolitan State 
University of Denver faculty members had similar findings (Jay 
2024).  Seventy-eight percent of faculty in that study said unfamil-
iarity with AI was the primary reason they did not use it. We found 
no studies of theology faculty specifically. But, given that seminar-
ians do not compete in the marketplace, we can assume that there 
may be less concern among seminary faculty about their students 
being AI literate.  

Given the general hesitancy to educate about generative AI and 
perhaps a heightened reluctance among seminary faculty, librarians 
have an ideal opportunity to take the lead on this issue and collabo-
rate with faculty on their approach to it. We should be committed 
to educating ourselves and faculty about generative AI because of 
its importance in theological discussions.  With the phenomenon of 
generative AI sweeping every element of society and its widespread 
use in everything from travel planning to personal counseling, AI 
education is an integral part of seminary formation. Our students 
will use generative AI, if not for class assignments, then for personal 
use. More importantly, the congregations they serve will use it. If 



Listen and Learn Sessions    169

seminarians are not taught about AI fundamentals and the practi-
cal, moral, and ethical implications of its use, they will not be able 
to lead their congregations through issues arising from its use or 
contribute to the essential religious and societal conversations sur-
rounding this technology.

NEED FOR AI EDUCATION

AI literacy is generally defined as the knowledge and ability to use, 
understand, and interact with AI technologies. This includes more 
than prompt engineering; it also includes understanding the technolo-
gies behind generative AI, applying AI concepts in different contexts 
and applications, and considering the ethical implications of its use 
(Ng et al. 2021). Effective AI use still requires the development of 
human abilities to evaluate, analyze, and adapt (Bowen and Watson 
2024, 38). Moreover, there are human skills in which AI is deficient, 
especially interpreting or applying information to new situations 
and contexts (see the “sippy cup” example in our LibGuide), asking 
questions, and predicting future results (Bowen and Watson 2024, 
38–40). Human creativity and persistence are still needed to prompt 
information from generative AI.  Finally, if there is any doubt that 
generative AI should be a part of a seminary education, just ask AI!2

AI literacy starts with learning to evaluate various AI applications 
according to the same criteria used for evaluating other information 
sources. What is the source behind the technology? Why was the 
technology developed? Who trained it? On what documents was it 
trained? Is the purpose commercial or educational? In particular, 
seminary students should be familiar with various forms of so-called 
religious AI. See, for example, Christian AI, an ad-based application 
that describes its training documents as “a vast dataset of Christian 
literature, biblical texts, and religious writings” (Christian AI, 2024). 
Chatbots, like websites, have varying degrees of reliability, and stu-
dents must be trained to recognize the differences. 

POSSIBLE COLLABORATION: DEVELOPING AI POLICIES

While the need for AI education in the seminary is greater than the 
mere use of generative AI for class assignments, specifying how 



170    AT L A 2024 PROCEEDINGS

seminarians can use AI in the classroom is still essential. Librarians 
can support faculty by helping them develop policies that provide 
students with the necessary guidance in using generative AI. At a 
minimum, students must know: 

1) What AI use is permitted: brainstorming, outlines, research, 
review of an assignment draft, or other use?  

2) What AI technology can be used: chatbots trained on the 
Internet, chatbots trained on religious texts, Microsoft 
Editor, Grammarly, or others?   

3) What specific AI use is to be ethically acknowledged, and 
what is the form of acknowledgment?  

4) How can AI enhance, but not impede or replace, individual 
learning, research, and writing processes?3   

AI policies are a hot topic of conversation in higher education. See, 
for example, “Syllabi Polices for Generative AI” (Eaton 2023), a 
collaborative, crowd-sourced Google Doc of over 86 policies from 
colleges and universities worldwide, although primarily from the 
United States. Most of these policies are course-specific, a practice 
Bowen and Watson recommend in Teaching with AI: A Practical 
Guide to a New Era of Human Learning (2024, 134). The authors 
further suggest that co-writing the policy with the class creates a 
perfect time for a robust discussion of AI and why a policy is needed 
(2024, 132–134). While those in academia respect scholarship and 
intellectual property, students might not appreciate the importance 
of knowing where the source of generated information comes from. 
Such a discussion can reinforce teaching about knowledge creation 
over time, crediting information sources, and the student’s responsi-
bility as a knowledge creator.4 Given AI’s propensity for generating 
misinformation and biased statements, students need to assume 
responsibility for the content they use. Other discussion topics could 
include how AI interferes with thinking and writing processes, how 
over-reliance on AI can impede spiritual reflection, how AI may not 
be trained in religious tradition and teaching, and how AI cannot 
discern human relationships and personal experiences, all of which 
are integral aspects of theological education.5



Listen and Learn Sessions    171

POSSIBLE COLLABORATION: TEACHING ABOUT ETHICAL ISSUES

Among the many ethical issues associated with the (mis)use of arti-
ficial intelligence are:

Bias. The data sets used to train AI reflect the biases and preju-
dices of society, are crowdsourced, and can magnify the issues of 
sexism, religion, racism, gender, etc. For example, when Microsoft 
used Twitter to train its chatbot Tay on how and what to tweet, it 
spewed racist and misogynist tweets (Gaudet 2022). When there is 
an attempt at editing the content, human biases are still embedded. 

Environment. The need for rare earth minerals to manufacture 
electronic components, such as lithium cobalt, creates environmen-
tal disasters in those, often developing, countries where they are 
mined. Data centers require huge amounts of water and electricity 
for cooling, lighting and other systems. Carbon emissions, water 
pollution, and poor resource management in construction are other 
high-impact consequences. 

Privacy. AI systems are trained on vast amounts of internet data 
which includes personal information that has been collected without 
users’ knowledge or consent and ignoring privacy rights. Companies 
create detailed user profiles based on this information to create 
targeted ads, political manipulation, or other possibly nefarious 
purposes, or to gain competitive advantages by influencing user 
behavior. However, the algorithms are “black boxes,” making it hard 
to figure out how the system makes decisions and raising questions 
about transparency.

Intellectual Property and Copyright. In December of 2023, the 
New York Times brought a lawsuit against OpenAI and Microsoft for 
unauthorized use of their copyrighted stories to train the chatbots 
that are now their competitors. The idea that chatbots will “gener-
ate” or “create” news is a disquieting story.  There is a similar issue 
with image generation. To train an AI image generator, they must 
use millions or billions of images, scraped from the internet without 
the consent of the creator. Often there is no context for the images. 

Exploitation of Human Labor. Low-paid workers are often used for 
categorizing and labelling data, resulting in workers being treated 
as parts of a machine, rather than as individuals. Entry level jobs 



17 2    AT L A 2024 PROCEEDINGS

are in danger of being eliminated, thus leading to a cycle of poverty 
and unemployability. Content moderators, used to “clean up” some 
of the data being used to train these systems, are often continuously 
exposed to traumatic text and images without adequate support 
systems. One example from Time magazine discusses workers in 
Kenya, paid between $1.32 and $2.00/hour, to scrub disturbing con-
tent from data: “Around three dozen workers were split into three 
teams, one focusing on each subject. Three employees told Time they 
were expected to read and label between 150 and 250 passages of 
text per nine-hour shift. Those snippets could range from around 
100 words to well over 1,000. All the four employees interviewed by 
Time described being mentally scarred by the work” (Perrigo 2023).

Power Issues. Most of the text is in English and is further biased 
by the way the data is collected and absorbed into the models. 
Algorithms are created by those with a bias towards certain pre-
suppositions. Image collection may not account for variations in 
facial structure, skin tone, cultural background, etc. These factors 
contribute to perpetuating power imbalances in the world.

Misinformation or Errors. We are all familiar with, or have seen 
examples of, AI “hallucinations,” situations in which the chatbot 
makes up sources or gives obviously incorrect information—such 
as including at least one small stone a day as part of a healthy diet 
(Klebenov 2024). However, a more important threat is the creation 
of fake news, impersonation of real individuals or organizations, 
and flooding the internet with false information. This leads to the 
prospect of highly persuasive campaigns by those seeking to influence 
public opinion. Russian influence in an American election, anyone?

In one example, programmers training a “smart weapons” system 
used photos of tanks in the sunshine to train the system to identify 
enemy tanks. However, when shown a photo of a tank on a rainy 
day, the AI was unable to identify the tank because it associated 
tanks with sunshine. This is but one example of why Pope Francis, 
in a written address to participants in an AI ethics conference in 
Hiroshima, has asked people to push for a ban on autonomous 
weapons, starting “from an effective and concrete commitment to 
introduce ever greater and proper human control.... No machine 
should ever choose to take the life of a human being” (McLellan 2024). 



Listen and Learn Sessions    173

 Influence of Faith. Incorrect use of AI chatbots is a temptation 
to outsource one’s thinking. The generated output of AI is merely a 
statistical prediction of word patterns, cut off from any capacity to 
discern truth or make moral decisions.

Humanity is created in the image of God. According to Sean 
McGever, there are three models which apply to education: the 
structural model, in which “the rational capacity of the mind and 
the volitional capacity of the will … bring to light the knowledge 
and righteousness of God,” and which sets us apart from the rest of 
creation; the relational model, which mirrors the trinitarian aspect 
of God, and which gives us the ability to respond to and relate to 
God; and the functional model, which relates to the tasks which God 
has given us to accomplish in the world (McGever 2023).

True education is a form of encounter with the other which 
requires active participation, embodied presence, and emotional 
engagement with a text or person. The underlying framework for 
education has two parts: solidarity and subsidiarity.  Solidarity is not 
just an emotion, but a real relationship coming from interpersonal 
actions, witnessing concrete care for the common good. Subsidiarity 
is the principle by which the local informs the actions of the global 
for the common good—of handling issues locally before “kicking 
them upstairs.”

There seem to be two major philosophies of education: person-
alism and behaviorism. The latter is based on B. F. Skinner’s work 
on the study of observable behavior. The basic principle is that 
behavior is a function of one’s environment; that learning occurs 
through conditioning. It is a mechanistic approach with little con-
cern for the student’s interior life. Educations hands out dopamine 
hits through A’s.

On the contrary, personalism is concerned with one’s interior life 
and virtue. In his work Person and Act, Karol Wojtyla (the future 
Pope John Paul II) proposed the personalistic norm: “This norm, in 
its negative aspect, states that the person is the kind of good which 
does not admit of use and cannot be treated as an object of use and as 
such the means to an end. In its positive form, the personalistic norm 
confirms this: the person is a good towards which the only proper 
and adequate attitude is love” (John Paul II 1993, 41). Personalism 
also implies inter-personalism, as Benedict XVI stresses in Caritas in 



174    AT L A 2024 PROCEEDINGS

Veritate: “As a spiritual being, the human creature is defined through 
interpersonal relations. The more authentically he or she lives these 
relations, the more his or her own personal identity matures. It is 
not by isolation that man establishes his worth, but by placing him-
self in relation with others and with God” (Benedict XVI 2009, §53).

POSSIBLE COLLABORATION: CREATING ASSIGNMENTS

Perhaps the most fruitful area of collaboration is crafting assignments 
less susceptible to AI plagiarism, given faculty concerns regarding 
this issue. As literacy advocates who understand the importance 
of developing strong research and writing skills, librarians should 
help faculty resist the temptation to revert to oral or in-class assess-
ments to prevent AI use. Instead, librarians can suggest alternative 
writing assignments that decrease the risk of AI plagiarism. AI is 
less skillful with application, analysis, and problem-solving tasks, 
so assignments should draw on these skills. This would include 
assignments that relate to life experiences, apply learning to a local 
problem or context, discuss an ethical dilemma, or describe vary-
ing points of view on an issue (Bowen and Watson 2024, 201–207). 
Similarly, best practices for writing instruction, consisting of low-
stakes prewriting assignments, outlining, drafting, peer review, and 
revision, discourage reliance on generative AI (Mills, 2023). These 
assignments emphasize the writing process, which is invaluable as 
a learning and thinking tool. As stated by Anna Mills, a community 
college English instructor who writes frequently about AI,

No one creates writing assignments because the artifact of one more 
student essay will be useful in the world; we assign them because the 
process itself is valuable. Through writing, students can learn how to 
clarify their thoughts and find a voice. If they understand the benefits of 
struggling to put words together, they are more likely not to resort to a 
text generator.  (Mills 2023)

Assignments utilizing AI can both improve student writing and 
boost AI literacy. For example, students can analyze AI output for 
biased, inaccurate, or misleading content or supplement the text 
with explanations and sources, compare the writing between dif-
ferent chatbots or between human and AI writing, role-play with a 
Chatbot regarding an aspect of ministry, or use AI to edit their writing 
(Bowen and Watson 2024, 207–217). Given the rapid improvement 



Listen and Learn Sessions    175

in generative AI technology, testing your assignments with AI is 
always advisable. Rather than simply eliciting responses to your 
assignment, ask questions regarding how the assignment could be 
improved, such as: How might students use AI on this assignment? 
How might I make it harder to cheat using AI on this assignment? 
How might AI undercut the goals of the assignment (Bowen and 
Watson 2024, 97–98)? 

CONCLUSION

As they have done with information literacy, librarians must do what 
they can to ensure their students are AI-literate. At its most basic, 
this literacy includes how to effectively use AI, evaluate AI applica-
tions, and consider the ethical implications of its use. Librarians can 
achieve this goal by providing much-needed assistance to faculty 
in establishing policies for class use, teaching about the moral and 
ethical approaches to AI, and crafting assignments that discourage 
the overuse of generative AI as well as assignments that encourage 
the development of AI literacy.

LIBGUIDES

Faculty and AI: Atla 2024 slides : https://leodehonlibrary.libguides.
com/atla2024facultyAI 

AI and the Classroom : https://leodehonlibrary.libguides.com/AI 

REFERENCES

ACRL Board. 2016. Framework for Information Literacy for Higher 
Education. Association of College and Research Libraries. https://
www.ala.org/acrl/standards/ilframework.

AI Research Group for the Centre for Digital Culture of the Dicastery 
for Culture and Education of the Holy See. 2024. Encountering 
Artificial Intelligence: Ethical and Anthropological Investigations. 
Edited by Matthew Gaudet, Noreen Herzfeld, Paul Scherz, and 
Jordan Joseph Wales. Eugene: Pickwick Publications.

https://leodehonlibrary.libguides.com/atla2024facultyAI
https://leodehonlibrary.libguides.com/atla2024facultyAI
https://leodehonlibrary.libguides.com/AI
https://www.ala.org/acrl/standards/ilframework
https://www.ala.org/acrl/standards/ilframework


176    AT L A 2024 PROCEEDINGS

Benedict XVI. 2009. Caritas in Veritate. Encyclical Letter. Vatican 
City: Libreria Editrice Vaticana. https://www.vatican.va/content/
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Bowen, José Antonio, and C. Edward Watson. 2024. Teaching with 
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Christian AI. 2024. “FAQ.” https://www.christianai.app/!/faq.

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AI-Syllabi. Last updated September 15, 2023.

Furze, Leon. 2023. “Teaching AI Ethics: Bias and Discrimination.” 
Leon Furze (blog), March 16. https://leonfurze.com/2023/03/06/
teaching-ai-ethics-bias-and-discrimination/.  

Furze, Leon. 2024. Practical AI Strategies. Baltimore: Amba Press. 

 Gaudet, Matthew. 2022. “An Introduction to the 
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Jay, Sam. 2024. “Survey Highlights Faculty Perception of 
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Klebanov, Sam. 2024. “Google’s AI Says You Should Eat Pebbles.” 
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McLellan, Justin. 2024. “Pope Asks World’s Religions to 
Push for Ethical AI Development,” Catholic News 
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pope-asks-worlds-religions-push-ethical-ai-development.

 McGever, Sean. 2023. “Theologically Informed Pedagogical Solutions 
to the ChatGPT ‘Problem’.” Didaktikos (blog), April 3. https://www.
logos.com/grow/didaktikos-chatgpt-seminary/.

https://www.vatican.va/content/benedict-xvi/en/encyclicals/documents/hf_ben-xvi_enc_20090629_caritas-in-veritate.html
https://www.vatican.va/content/benedict-xvi/en/encyclicals/documents/hf_ben-xvi_enc_20090629_caritas-in-veritate.html
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https://jmt.scholasticahq.com/article/34121-an-introduction-to-the-ethics-of-artificial-intelligence
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https://www.morningbrew.com/daily/stories/2024/05/24/google-s-ai-says-you-should-eat-pebbles
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https://www.usccb.org/news/2024/pope-asks-worlds-religions-push-ethical-ai-development
https://www.usccb.org/news/2024/pope-asks-worlds-religions-push-ethical-ai-development
https://www.logos.com/grow/didaktikos-chatgpt-seminary/
https://www.logos.com/grow/didaktikos-chatgpt-seminary/


Listen and Learn Sessions    177

Mills, Anna R., and Lauren M.E. Goodlad. 2023. “Adapting College 
Writing for the Age of Large Language Models Such as ChatGPT: 
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Mills, Anna. 2022. “AI Text Generators and Teaching Writing: Starting 
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Mills, Anna R. 2023. “ChatGPT Just Got Better. What Does That Mean 
for Our Writing Assignments?” Advice (blog), The Chronicle of 
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assignments.

MLA-CCCC Joint Task Force on Writing and AI. 2023. “Academic Integrity 
and Assignment Design.” September 23. https://aiandwriting.hcom-
mons.org/2023/09/22/academic-integrity-and-assignment-design/.

Ng, Davy Tsz Kit, Jac Ka Lok Leung, Samuel Kai Wah Chu and Maggie 
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Perrigo, Billy. 2023. “OpenAI Used Kenyan Workers on Less Than 
$2.00 per Hour to Make ChatGPT Less Toxic.” Time, January 18. 
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Szelenyi, Balasz. 2024. “Adopt or Avoid: Faculty Dilemmas and 
Decisions on Generative AI in Teaching and Research.” Faculty 
report, Northeastern University. https://faculty.northeastern.edu/
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generative-AI.pdf 

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https://www.chronicle.com/article/chatgpt-just-got-better-what-does-that-mean-for-our-writing-assignments
https://aiandwriting.hcommons.org/2023/09/22/academic-integrity-and-assignment-design/
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https://doi.org/10.1016/j.caeai.2021.100041
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https://faculty.northeastern.edu/senate/wp-content/uploads/sites/2/2024/03/Addendum-4-Survey-Results-Adopt-or-Avoid-Northeastern-Faculty-views-on-using-generative-AI.pdf
https://faculty.northeastern.edu/senate/wp-content/uploads/sites/2/2024/03/Addendum-4-Survey-Results-Adopt-or-Avoid-Northeastern-Faculty-views-on-using-generative-AI.pdf
https://faculty.northeastern.edu/senate/wp-content/uploads/sites/2/2024/03/Addendum-4-Survey-Results-Adopt-or-Avoid-Northeastern-Faculty-views-on-using-generative-AI.pdf


178    AT L A 2024 PROCEEDINGS

ENDNOTES

1  Generative Artificial Intelligence (GAI) is a subset of artificial intelligence that 
can generate various forms of content, e.g., text, images, or audio. This essay uses 
the term AI to refer specifically to generative AI.

2  See transcripts of responses from various chatbots in response to the prompt 
“Identify all reasons why seminarians and future priests need to know about 
generative AI. List the five most important reasons.”: https://leodehonlibrary.lib-
guides.com/c.php?g=1403071&p=10387307

3  See also “Faculty and AI—Atla 2024” LibGuide for other drafting tips: https://
leodehonlibrary.libguides.com/c.php?g=1403071&p=10388394

4  See also the ACRL Framework for Information Literacy for Higher Education, 
“Scholarship as Conversation” (ACRL Board 2016).

5  See transcripts of responses from various chatbots to the prompt “Act as a Roman 
Catholic seminary professor. Describe to seminary students why AI should not 
be used in seminary assignments”: https://leodehonlibrary.libguides.com/AI/chat.

https://leodehonlibrary.libguides.com/c.php?g=1403071&p=10387307
https://leodehonlibrary.libguides.com/c.php?g=1403071&p=10387307
https://leodehonlibrary.libguides.com/c.php?g=1403071&p=10388394
https://leodehonlibrary.libguides.com/c.php?g=1403071&p=10388394
https://leodehonlibrary.libguides.com/AI/chat

