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IN-CONFERENCE WORKSHOP

Practical Uses of Generative AI for 
the Classroom and the Library
Steve Jung, MSLS, MDiv, Associate Director of Library Services, Hope 
International University

ABSTR ACT: This paper expands upon an in-person session that dis-
cussed the practical uses of generative AI by students, professionals, 
and librarians, and includes more material than could be discussed 
during the session. The paper discusses the nature of generative 
AI and prompt engineering, as well as various uses of AI. Each use 
includes a brief description and then either a comment about its use 
or an example of an appropriate prompt. The paper ends with a list of 
resources for understanding generative AI and links to the technolo-
gies mentioned within.

INTRODUCTION

Artificial intelligence is a broad container of many different tech-
nologies. This paper is about one form of AI, generative AI: an AI 
that generates ideas in response to human prompting. For this 
presentation we are looking only at text generation. (The prompt 
engineering ideas transfer to other aspects of generative AI, but they 
are not the focal point of this paper.) For the most part, the paper 
discusses LLMs (Large Language Models) like ChatGPT/GPT 3.5 or 
4o, Gemini, Claude 3/3.5, LLaMa 3, etc.



390    ATL A 2024 PROCEEDINGS

There is a lot that goes into training an AI that are beyond this 
discussion, but there are things that we should all know. When an 
AI is trained, a big part of what it is doing is making connections 
between an idea or theme and what are the absolute most com-
mon things said in relationship to that idea. My terrible example is 
to think about those word clouds from the early 2000s. The main, 
or most important, term is largest in the image. The other words 
in the cloud are of varying size, but the larger the font, the more 
frequently it is used. In relation to AI training, the response to any 
prompt is going to be the absolute most common ideas and phrases, 
the biggest font stuff. This is why many things written by AI seem 
like plagiarism; it seems like you’ve read this before. You haven’t 
read that exact text, but you have probably read all the same ideas 
repeatedly. The output by the AI is the most common ideas in the 
most common expression of those ideas. Generative AI is not truly 
creative: It is programmed to deliver the most common expression 
of the most common topics.

What does this mean for prompts and output? It means that these 
bots are great at brainstorming, they have a readymade list of the 
top results at a moment’s notice. I will cover that in more detail 
in the practical section. This also means that AI output can sound 
lifeless and boring. The good news is that the AIs are getting better 
at writing with style. It also means that a good thing to do is to put 
the AI’s response back in the AI and ask it to improve the writing. It 
can do that. Also, people are creative, and they have created entire 
AIs for the purpose of improving writing and making it sound more 
“human.”

There are many generative AI models out there. Each of them 
was trained on different material. True, there are commonalities. 
Most were trained on large collections of public domain books, a 
lot of open access journal articles, government reports, some social 
media and web content, and a growing amount of computer code. 
And because they were all trained on different things and the com-
panies have different goals for their AI, all of them have different 
strengths and weaknesses. With that in mind, I recommend that 
when you work, try using several AIs at the same time. I typically 
work with three models opened in different tabs at the same time. 
I just copy and paste my prompts into each model. 



In-Conference Workshop    391

PROMPT ENGINEERING (FOR NOW)

Direct prompts are the short queries that we put together when 
we just want an answer. When we ask the AI for “what are the top 
ten activities to do on the Fourth of July”, we are creating a simple 
direct prompt. Students often try, “write an essay on....” These types 
of prompts work, but they may not be getting the most out of the 
AI. These AIs were trained on a lot of narrative material (books, 
novels, short stories, social media posts, etc.) so in some ways, the 
AI “thinks” or “processes” in narrative. Responses might be better 
if we try to take advantage of the AI’s “natural” work as an author, 
editor, or wordsmith.

One way to take advantage of its “natural” work is to try to get 
the AI to work in a narrative form. We can do this by giving the AI a 
context, creating characters, working with dialogue, and flattering 
the character that the AI is supposed to be. Think of this like role 
playing and the AI is supposed to be the “hero” or the one with all 
the answers. Creating a context helps keep the story focused on 
the important things. Characters should be chosen appropriate to 
the topic. I often have librarians or faculty roles in the “stories” I 
create. But—and this relates to flattery—give the AI the role of the 
hero, or the one with more experience or intelligence, etc. Dialogue 
allows your character to ask the AI for an answer. The answer will 
often come out as a monologue, but it may have bullet points or 
other odd formatting for a speech. No, this isn’t like asking for an 
essay, but this is one way to get the parts of an essay. Flattery isn’t 
about fawning over the AI but is more about establishing a context 
for the role the AI is to play. You want the AI’s character to be able 
to answer the prompt and you want it to be honest. In fact, if the 
flattery is overboard, you can get the AI to start to give erroneous 
answers; the AI may believe that you, the narrator, were lying and 
therefore, lying is acceptable.

One very important thing to remember is that this should be a 
conversation with the AI. Don’t just try to get the entire answer with 
one prompt. The AI will give a better response the more you work 
with it. Each prompt furthers the conversation (your interactions 
become part of its training for that one conversation). Think about 
it like using filters on a database. Your initial prompt and response 
set a direction for the conversation and then each additional input/



392    ATL A 2024 PROCEEDINGS

prompt furthers the answer or narrows the direction. The two of 
you are collaborating on a story.

And lastly, a reminder. I give credit to Steve Hargadon from Library 
2.0 for the following thought: generative AI was created to write flu-
ently, not factually. That should be mentioned to every student we 
see. Trained AIs do not think. Trained AIs do not have logic or ethics. 
They were trained not knowing the difference between fact or fic-
tion. They cannot distinguish between information, disinformation, 
misinformation, myth, or conspiracy theory. They were trained to 
write fluently and nothing else.

PERSONAL OR PROFESSIONAL USES

1. Occasional Repetitive Professional Writing
Description: Clergy need to write annual reports, letters to the con-
gregation, and reports to the board. These are all formulaic (and 
typically repetitive). AI can be used to create templates and then 
used to fill in the reports.

Prompting Example: Susan, the solo pastor of her church, needs 
to write an annual report for the board of elders. It needs to cover 
the financial situation, programming, and relative spiritual health 
of the congregation. She needed a template and was searching on 
the internet when she found... 

2. Improve a Curriculum Vitae/Résumé and Cover Letter
Description: Use the AI to process job descriptions and then tailor 
a CV/résumé to highlight the matches. Then use the AI to tailor a 
cover letter to match the needs of the job.

Comment: For a college student looking for a job this is just 
finding a template (and there are thousands on the internet). For a 
student that is graduating and seeking a first career position then, 
this is great. Find several openings and then copy/paste the descrip-
tions into the AI. Paste the student’s CV and ask the AI to reword 
or highlight relevant items in the CV. This can be done with a job 
description and creating a cover letter as well. A note from personal 
experience and a word of caution: Just don’t leave your CV on your 



In-Conference Workshop    393

desk for several weeks while checking out AI capabilities, as your 
boss may get curious and worry that you are looking for a new job 
when you are not.

3. Improve Applications to Grants or Scholarships
Description: Use the AI to find templates and wordings for grant 
applications and scholarship applications. Use them as templates. 
Do not copy and paste the response. It would be academic—and 
possibly professional—suicide to just paste an AI response into an 
application.

Prompting Example: Here are the instructions for a grant: [paste 
grant instructions]. Here is my grant proposal: [paste grant proposal]. 
Add criticisms and comments to my proposal so that the proposal 
is more closely aligned with the grant instructions. 

4. Brainstorm Ideas or Topics 
Description: Use the AI to come up with ten or twenty ideas on a 
subject. Need ideas for a vacation? Need ideas for Christmas presents 
for your co-workers? Need marketing ideas for the coming year? 
Ask the AI. 

Prompting Example: My wife and I are going to Kauai for a week. 
What are some adventurous things to do while on the island? 
Suggestions for places to eat?

USES IN THE CLASSROOM

5. Generate Research Questions
Description: Trying to figure out what you don’t know? Don’t know 
how to approach a subject? Ask the AIs for ways to approach a topic.

Prompting Example: Liz was assigned a topic in her Church History 
class that she was not familiar with. Liz asked her professor, “Doctor 
Thompson, I am not familiar with my assigned topic: iconoclasm. 
Can you tell me some of the questions I should be asking and think-
ing about while I start my research?” Doctor Thompson replied…



394    ATL A 2024 PROCEEDINGS

6. Generate List of Keywords or Terms for Study
Description: Ask the AI for a list of the common vocabulary and 
definitions. This is useful if someone is new to a field and doesn’t 
know the vocabulary. 

Prompting Example: Steve, a theological librarian, was going to 
try and help a kinesiology student, but Steve doesn’t understand a 
lot of the vocabulary. Steve needs help to understand the student’s 
needs. He knows the student is working on athletic movements 
and knee injuries. Steve asked the professor, “To help this student 
I need to know the most important terms related to athletic move-
ments and knee injuries. Can you tell me what those terms are?” 
The professor answered…

7. Generate a List of Pros and Cons for a Topic
Description: Allow an AI to create a list of pros and cons about a topic. 
The AI was trained on parts of the internet, so there are opinions on 
just about everything. Results will vary on the logic of all the pros 
and cons, but most AIs should produce a reasonable list of topics, 
even if it doesn’t get all the facts right.

Comment: Pros and cons are going to come across as facts. This 
is where things get interesting with AIs. They weren’t programmed 
with logic; they cannot determine fact from fiction or misinformation 
from conspiracy theory. In my opinion, this will only get better if the 
AIs are trained with weighted inputs. Trusted sources were weighted 
higher than social media posts in the training phase. Everything an 
AI puts out as fact should be researched.

The last four items are all variations of the same thing. The AI was 
trained on a lot of prose writing. The training and the algorithms 
used basically look for the most common words or phrases to follow 
a prompt, what most likely should come next. That continues until 
all the common terms are used. In similar fashion, the AI responds 
by presenting the most common phrases and words in relationship 
to the prompt. The AI basically composes from most common to 
least common; it brainstorms by its nature. The other three ideas, 
list of keywords, research questions, and list of pros and cons, are 
all forms of brainstorming, just brainstorming with a twist.



In-Conference Workshop    395

8. Present a Point of View on a Topic, “how might… understand....”
Description: It might be beneficial to ask an AI for a point of view. 
Some young college students need to learn to think beyond them-
selves. In some cases, we can find books or articles written from 
certain perspectives (gender, culture, theological point of view, etc.), 
but not all of that is available. An AI might be able to draw on its 
training to come up with another perspective.

Comment: Use care doing this. This is not perfect by any stretch 
of the imagination. Everyone complains about the bias of the AIs. 
It’s true that the AIs were very biased in the beginning, but they are 
getting better. Part of the issue was the training material. A whole 
lot of what the AIs were trained on were public domain books, old 
and presenting outdated expressions of age, gender, sexuality, and 
race. Add to that the training from current social media and you have 
AIs that are quite capable of being the most horrible thing ever and 
proof of total depravity (ageist, racist, sexist, etc.). But with added 
materials, much from other languages and cultures, those issues are 
becoming less common. Yes, the programmers can tweak the align-
ment and make an AI draw things like black Nazis (yes, Google, I’m 
talking about you), but those are/should be less common.

9. Summarize an Academic Article
Description: One strength of generative AIs is their ability to absorb 
information and summarize. Nuance may not be perfect, but the gist 
should be provided. Any of the models should be able to handle a 
simple, “summarize this” prompt. Even Adobe Reader now has an 
AI built-in for the sole purpose of summarizing articles. 

Comment: There are “research” AIs (Perplexity, Consensus, Scite, 
Semantic Scholar, and others) whose purpose is to search for your 
topic and then summarize the literature—basically a literature 
review done for you. These can be good starting points for research 
if you are working in STEM fields. They were mostly trained on Open 
Access material (PubMed, Arxiv, and government research). There 
aren’t any (at the time of writing) that are great for the Humanities 
or Social Sciences.



396    ATL A 2024 PROCEEDINGS

10. Identify Themes or Patterns 
Description: Identify themes or patterns in an article, a chapter from 
an ebook, or an essay. Enter all the relevant texts and ask the AI to 
identify themes or patterns. 

Comment: The longer the text (or texts) the better the response 
will be. There are limits to each AI; some will accept longer prompts 
than others; some AIs will even attempt to cite the various ideas. You 
can ask for citations, just don’t expect them to be perfect. 

Those last two items can be handled well if you are interested 
in training your own bot, or using one that allows training. Google 
created NotebookLM to be a trainable generative AI. Built upon 
Gemini, it allows you to add “sources” and ask the AI questions in 
the prompts about the sources. Students can input their research 
and course notes to generate reviews, study guides, sample quiz-
zes, etc. This can be used by faculty in their writing process as well. 
Post notes and research and look for themes, connections, or things 
that might have been overlooked. OpenAI’s GPT family of AIs can 
be used to create unique AIs for any user that takes the time to do 
some programming. These trainable bots can be useful in a variety 
of settings.

11. Edit or “Improve” Writing
Description: AIs are editors/authors/wordsmiths by programming. 
Paste your text in an AI and ask it for suggestions on ways to improve 
your writing. Ask it for suggestions on transitions, thesis, argumenta-
tion, etc. Some AIs, e.g. QuillBot, are just a cut-and-paste operation.

Comment: Our students are now getting in trouble for this. We 
ask for few to no mistakes because they should know how to write 
better by now. But the issue is that all their writing tools are now 
loaded with AI built-in; they cannot escape AI. Microsoft Word, Google 
Docs, and all versions of Grammarly have an AI offering suggestions. 
When the student accepts the suggestions, the AI is now part of their 
writing. Just fixing spelling or grammar should not be scoring as AI, 
but accepting entire rewritten sentences should.

Uses nine through eleven are all areas in which students are cur-
rently getting into trouble. Overuse of AI in these areas can lead to 



In-Conference Workshop    397

students losing critical thinking skills and close reading skills. The 
other issue is that use of these AI practices is not bad, in and of itself, 
but in some cases, those ideas are the actual point of an assignment. 
In that case, this use of an AI becomes a misuse. All instructions need 
to be specific about what is considered a proper use of an AI versus 
a misuse that will result in academic problems. 

I would rather that we all adopt the terminology of use and misuse, 
rather than calling it all cheating. What is a misuse in one class may 
be entirely acceptable in another, thus use and misuse.

12. Conversation Partner
12a. Language Learning Help
Description: Use the AI as a partner in a “conversation” in a foreign 
language. This could be used for either translation, learning gram-
mar, or to help with pronunciation. 

Prompting Example: I am learning basic Spanish. My chapter 
was on playing soccer. Could you produce a short narrative on soc-
cer in Spanish. I would like to translate it into English. Then please 
critique my translation.

12b. Practice Therapy Sessions
Description: The AI can be prompted to roleplay as a patient, so 
that the conversation will be between the AI patient and you as the 
physician/therapist. The AI has been trained on enough data that 
it can mimic a patient with depression or with a torn meniscus or 
any number of other ailments. Several AIs are trained with the OA 
material from PubMed; therefore, they should have a good grasp of 
symptoms to a great deal of physical or psychological issues.

Prompting Example: Pretend you are a client coming to a psycholo-
gist seeking help with depression. Start by describing your feelings.

12c. Help for Social Anxiety (Inner Speech Partner)
Description: AI is very good at narrative and dialogue. In this instance, 
we are asking the AI to take the place of a particular person for 
a conversation. We all go over potential conversations and think 
about how a conversation might go, inner speech or inner dialogue. 



Those with social anxiety often struggle with having those actual 
conversations. This might help them “practice” how it might go with 
talking to a faculty member about a grade, an assignment, or asking 
for more time on an assignment. 

Prompting Example: I would like to practice a conversation with 
you. Pretend you are an English professor and I need to ask you for 
an extension on an assignment.

13. Virtual Peer Review
Description: Train the AI by pasting in the paper instructions. Then 
paste the paper and ask the AI for comments and criticisms on how 
to improve the paper or what are the deficiencies of the paper. 

Comment: For a faculty member, this could be a way to save some 
time on writing comments. One reminder, generative AIs don’t do 
math. You cannot ask the generative AI to score your paper because 
they cannot add points.

14. Help with Sermon Preparation
Description: Students or practicing clergy can ask for help with ser-
mon preparation. Paste the exegetical work that was written and 
then ask for sermon illustration ideas. Ask the AI for improvements 
of transitions, or other improvements to the grammar and flow of 
the sermon. 

Comment: This is a variation of 11 (Edit or “Improve” Writing).

15. Analyze a Sermon
Description: Paste a completed sermon into the AI and ask it to ana-
lyze for content, style, and effectiveness. Ask the AI for constructive 
feedback. The difference between this and the previous use is that 
this one focuses on structure and content, unlike the previous one 
that focused on grammar or illustrations.

Comment: Notice that a few of these AI uses are very similar. By 
separating them, I am trying to point out nuanced uses.



In-Conference Workshop    399

16. Virtual Biblical Language Lab
Description: Use the AI to help learn an ancient language. Trained 
on public domain material and in modern languages, most AIs are 
pretty good with language. Use the pronunciation tools to help learn 
Greek, Hebrew, Aramaic, Latin, or whatever. Create vocabulary cards 
for a specific passage. Get help with learning paradigms.

Prompting Example: Create a vocabulary list with English defini-
tions of the forty most used Hebrew words in the Book of Haggai.

For the next two, it is possible to use a regular AI (Claude, Gemini, 
ChatGPT, etc.), but using a trainable AI will improve your results. I 
mentioned Google’s NotebookLM earlier (prompts 11 and 12), and 
recommend you give it a try.

17. Automated Content Creation
Description: Paste course lectures, course notes, reading assignments 
from ebooks, and other course material into the AI. Have the AI 
create personalized learning material: summaries of readings and 
lectures, summaries of major theologians and their ideas, etc.

Comment: Sometimes we have a hard time grasping a few impor-
tant ideas when they are scattered over such a large quantity of 
information; AI is good at finding some of those themes. In this 
case, we are using the AI’s training to gather and present ideas that 
we might miss.

18. Personal Tutor
Description: Paste course lectures, course notes, reading assignments 
from ebooks, and other course material into the AI. Have the AI 
behave like a personal tutor. Ask the AI for study guides on the topic. 
Ask the AI to make flash cards for ideas or vocabulary. Ask the AI 
to make a practice quiz (with answers). Ask the AI for a timeline of 
events (again I question most AI’s understanding of numbers). Ask 
it for definitions and explanations. 

Comment: Khan Academy and Socratic are great for K-12 education, 
but our students are past that and are probably not working on the 
quadratic equation. For these courses, an AI may be an appropriate 



400    ATL A 2024 PROCEEDINGS
assistant to help with learning, especially if your institution does not have 
tutors for some courses.

USES IN THE LIBRARY

19. Event Planning
Description: Need help planning events for the library? AI can easily brainstorm 
ideas for events. Need to market those events? Need help figuring out how 
and who to market to? Let the AI help with that. In addition to brainstorming 
and figuring out the marketing plan, the AI can also create the wording for 
the email blast or for promotional works.

Prompting Example: Jennifer is an experienced librarian, but she is hav-
ing trouble planning events for the coming year. She asked her supervisor, 
“Karen, what are some of the best events our library could host?” And Karen 
replied...  [Hint: try this a second time but make Jennifer an academic librar-
ian. Try it a third time and call Jennifer a theological librarian.]

20. Translation services for the library
Description: Paste the PDF of an article, chapter from an ebook, or lecture 
notes into the AI and allow it to translate the text into another language. This is 
great for ESL students because in addition to the translation, you can request 
a summary of the text or ask for a simplified translation. This is also good for 
English-speaking students that find a good article in another language and 
want to access it. [I am thrilled that I don’t have to recommend the language 
filter to my students now. Most recent articles, downloaded as PDF, are now 
“readable” due to OCR.]

Prompting Example: Translate the following article into simplified English 
and include a summary at the end: [paste article here]

21. Create Metadata and Abstracts
Description: Feed the AI some of the digital objects (text or image) from the 
library and ask it to come up with an abstract and the metadata for the object. 
This can then be used to simplify the cataloging process.

Comment: This is not without controversy. Allowing the AI to do the work 
means that a librarian has not actually evaluated the object. This information 



In-Conference Workshop    401

should be preserved in the record somewhere. New to me is the term 
paradata. I understand it to be the data about the metadata and that 
this is where information about the metadata creation should be 
kept. Thank God for catalogers.

22. Use an AI as an Administrative/Personal Assistant 
Description: Use an AI to schedule appointments, send reminders, 
write emails, create “to do” lists, and a workflow for the day. Siri, 
Alexa, and the like already do this.

Comment: I’m too old school to even try to learn this, but I’ve read 
about other people doing it. It doesn’t have to be a voice activated 
feature like Siri, but it could be.

23. Create a Chatbot for the Library
Description: Create a Chatbot to answer questions when there are 
no librarians on duty (answering phones and listening for chat). 
Chatbots can be free, though with limited use, or with a monthly 
subscription depending on how much use they get—easy to create 
and inexpensive for a basic bot.

Comment: These Chatbots are trainable, so they are presenting 
a prompt, but asking for training materials. Typically, they will ask 
for the URL of the website. They will then train on that website. 
Most will also follow any hyperlinks from the website and train on 
those pages as well, e.g. trains on the library website and then trains 
on some of the LibGuides that were directly linked on the website. 
After they are trained on the website, they will often allow docu-
ments for training. I would recommend the library’s policy manual 
and the history of the institution. That way the AI can answer those 
important questions like fines and history of the library.

24. Help with Grant Writing (Templates and Wordings)
Description: Mentioned earlier, but librarians may use an AI to help 
with writing the narrative or other parts of a grant proposal. Ask 
the AI for templates and wordings for types of grants. Obviously, 
the librarian should have done their research about the grantor 
and previous winners, but this allows for more help with wording.



402    ATL A 2024 PROCEEDINGS

Prompting Example: Dr. Johnson is the Library Director at a uni-
versity. She needs to write a small grant proposal asking less than 
$1,000 for a 3D printer and its accessories. The 3D printer is intended 
for Kinesiology and Mechanical Engineering students. She wrote…

25. Help with Coding
Description: As librarians we are often tied to technology, even those 
of us that are not involved with systems or tech services. Coding 
can be difficult; one missed semicolon and the whole thing can go 
to pieces. Or, if you’re a Springshare user you may need to try and 
overpower their CSS in some LibGuide. Even if you aren’t a web 
programmer you can ask for help with coding.

Comment: As the various AIs are upgraded, they are getting trained 
on more and more coding. Why? Because those programmers that 
are training the AIs are the same ones that are on Discord every 
day searching for a snippet of code to make their subroutine work. 
So, just ask the AI for what you want and what language you want 
it in. If necessary, copy/paste the code from your LibGuide and ask 
the AI what part needs to be changed. Very helpful.

This presentation, along with the author’s other presen-
tations on AI, are available at https://sites.google.com/view/
practical-information-literacy/ai-in-the-academy

WEB RESOURCES FOR UNDERSTANDING GENERATIVE AIS

• LessWrong (blog site for logic, mathematics, com-
puters, and AI): https://www.lesswrong.com/

• Import AI (newsletter by Jack Clark on cutting edge 
generative AIs, training AIs, and ethics in AI): https://
importai.substack.com/

• Nicole Hennig (Librarian for U of Arizona, formerly 
from MIT; a newsletter with some commentary): 
https://substack.com/@nicolehennig

• Library 2.0 (Steve Hargadon’s webinars, confer-
ences, and “podcast” on AI): https://futureofai.org/
this-week-in-AI

• TechCrunch (news site for technology; a lot about 

https://sites.google.com/view/practical-information-literacy/ai-in-the-academy
https://sites.google.com/view/practical-information-literacy/ai-in-the-academy
https://www.lesswrong.com/
https://importai.substack.com/
https://importai.substack.com/
https://substack.com/
https://futureofai.org/this-week-in-AI
https://futureofai.org/this-week-in-AI


In-Conference Workshop    403

the money in AI investments and about what is com-
ing out in the days and weeks ahead): https://tech-
crunch.com/category/artificial-intelligence/

• ECampusNews.com (newsletter intended for K-12 
teachers, but there are occasional AI items worth 
the quick read): https://www.ecampusnews.com/

• Hope International’s Faculty LibGuide (a few 
pages about AI, but a couple of important pages 
on the conversations to have with students 
accused of using AI): https://libguides.hiu.edu/
faculty-library-guide/AI

SOME COMMON GENERATIVE AIS

Large Language Models (LLM)
• Gemini by Google:  https://gemini.google.com/app 
• Claude 3 by Anthropic: https://claude.ai/chats 
• ChatGPT/GPT 4 by Open AI: https://chatgpt.com/ 
• Copilot by Microsoft (a version of GPT 4): https://

copilot.microsoft.com/ 
• LLaMa 3 by Meta:  https://www.meta.ai/

Academic Research Models
• Perplexity: https://www.perplexity.ai/
• Consensus (mostly based on Semantic Scholar): 

https://consensus.app/
• Scite: https://scite.ai/
• Semantic Scholar: https://www.semanticscholar.org/

Chatbots to Program (Free and Subscription)
• ChatSimple - https://www.chatsimple.ai/
• RoboResponse: https://www.roboresponse.ai/
• CronbotAI: https://www.cronbot.ai/
• Chaindesk: https://www.chaindesk.ai/
• NotebookLM (not customer-facing, and you need a 

Google account): https://notebooklm.google.com/

https://techcrunch.com/category/artificial-intelligence/
https://techcrunch.com/category/artificial-intelligence/
http://ECampusNews.com
https://www.ecampusnews.com/
https://libguides.hiu.edu/faculty-library-guide/AI
https://libguides.hiu.edu/faculty-library-guide/AI
https://gemini.google.com/app
https://claude.ai/chats
https://chatgpt.com/
https://copilot.microsoft.com/
https://copilot.microsoft.com/
https://www.meta.ai/
https://www.perplexity.ai/
https://consensus.app/
https://scite.ai/
https://www.semanticscholar.org/
https://www.chatsimple.ai/
https://www.roboresponse.ai/
https://www.cronbot.ai/
https://www.chaindesk.ai/
https://notebooklm.google.com/



