technology

1. A Chat with ChatGPT: How will AI impact scholarly publishing?
This is just a fun little project I put together after playing around with ChatGPT. It is an
inspiration for a forthcoming paper, which will explore the technical side of ChatGPT and the
ethical issues it presents for academic researchers, which will result in a peer-reviewed
publication.
Disclaimer: most of the paper you are about to read was not written by me. It is the transcript of
an interview of sorts. This interview was unique in that it was not conducted with a living being,
but rather an AI interface. All of the questions that you read come from a human user, but all of
the answers (labeled “A:”) were written entirely by the platform ChatGPT, created by the
OpenAI program. This paper will begin with an introduction to ChatGPT and then proceed into
the transcript of a conversation with the platform about it and related AI technologies’ impact on
the future of scholarly publishing, before concluding with some discussion on the further
implications.
ChatGPT
ChatGPT is a powerful chatbot built on top of OpenAI's GPT technology. It can handle a wide
range of text-based requests, from simple questions and answers to more complex tasks. For
example, if you need help writing a note to a coworker, ChatGPT can generate a thoughtful and
well-written letter in just a few seconds. Similarly, if you want to address an issue with a
colleague's productivity but do not know what to say, ChatGPT can offer a solution. And with its
vast stores of data and efficient design, ChatGPT is even capable of writing essays on topics such
as the value of artificial intelligence. This is the unique value of ChatGPT for academic
researchers. It can make writing a scholarly essay a matter of entering a simple one sentence
prompt, like with all the questions and answers below.
Five questions with ChatGPT:
Q. What impact will ChatGPT have on scholarly publishing?
A: It is difficult to predict the exact impact that ChatGPT or any other specific natural language
processing (NLP) tool will have on scholarly publishing. However, it is likely that NLP tools and
techniques will continue to play an increasingly important role in the field of scholarly
publishing, as they can be used to facilitate and improve various aspects of the research process.
For example, NLP tools such as ChatGPT could potentially be used to assist with the review and
feedback process for scientific papers and articles, by generating summaries or comments that
help reviewers to more easily understand and evaluate the content of a manuscript. NLP tools
could also be used to help researchers identify relevant literature more efficiently, by searching
large databases of papers and articles and identifying those that are most closely related to their
own research.
Another potential use of NLP tools in scholarly publishing is to help facilitate the dissemination
and sharing of research, by generating abstracts, summaries, and other materials that can help to
make research more accessible and understandable to a wider audience.

2. Overall, the impact of ChatGPT and other NLP tools on scholarly publishing is likely to depend
on how they are used and the context in which they are applied. While these tools may have the
potential to bring many benefits and efficiencies to the research process, it is important to use
them responsibly and with a clear understanding of their limitations.
Q: How will AI impact scholarly citation behavior?
A: Artificial intelligence (AI) is expected to have a significant impact on scholarly citation
behavior, which refers to the way that researchers cite the work of others in their own research.
Some of the ways in which AI could potentially impact scholarly citation behavior include:
Facilitating the identification of relevant literature: AI-powered tools can be used to help
researchers identify relevant literature more efficiently, by searching large databases of papers
and articles and identifying those that are most closely related to their own research. This could
potentially lead to an increase in the number of citations, as researchers are able to more easily
and accurately identify the work of others that is relevant to their own.
Influencing citation patterns: AI-powered tools and algorithms could potentially influence
citation patterns by identifying and highlighting papers and articles that are highly cited or
influential within a given field. This could lead to an increase in the number of citations for these
papers and articles, as researchers seek to align their own work with that of the most highly cited
researchers in the field.
Assisting with the evaluation of research impact: AI-powered tools can be used to analyze
citation data and other bibliometric indicators, such as the number of times a paper or article has
been downloaded or shared, to help researchers and policymakers evaluate the impact and value
of scientific and scholarly research. This could potentially influence citation behavior, as
researchers seek to align their work with research that is deemed to be of high value or impact.
Overall, the use of AI in scholarly citation behavior is likely to lead to a number of changes and
challenges, as researchers and policymakers adapt to new ways of evaluating and measuring the
impact of research. It is important that these changes are carefully considered and managed, to
ensure that the integrity and quality of research are maintained.
Q: Will tools like ChatGPT make scholarly misconduct more prevalent?
A: It is difficult to predict the exact impact that tools like ChatGPT or other natural language
processing (NLP) tools will have on scholarly misconduct. However, it is important to be aware
that any tool or technology has the potential to be misused, and it is important to use NLP tools
responsibly and ethically.
Scholarly misconduct refers to unethical or fraudulent behavior in the conduct of research, such
as fabrication or falsification of data, plagiarism, or failure to properly cite sources. These
behaviors are serious violations of the ethical principles that underlie scholarly research, and they
can have serious consequences for those who engage in them.
There are a number of factors that can contribute to the prevalence of scholarly misconduct,
including factors such as pressure to publish, competition for resources, and lack of oversight or

3. accountability. It is possible that NLP tools such as ChatGPT could be used in ways that
facilitate or enable scholarly misconduct, for example by making it easier to generate fake or
misleading data or to plagiarize the work of others.
However, it is also possible that NLP tools could be used to help prevent or detect scholarly
misconduct, by identifying patterns or anomalies in data or by automating the review and
feedback process for scientific papers and articles.
Overall, it is important to be aware of the potential risks and challenges associated with the use
of NLP tools, and to use them responsibly and ethically. By following best practices for research
conduct and by being transparent and accountable in your work, you can help to ensure that your
research is conducted in a way that is fair, honest, and respectful of the contributions of others.
Q: Do you believe, then, that NLP tools could be used in place of peer-review?
A: Natural language processing (NLP) tools, such as ChatGPT, could potentially be used to
assist with the peer review process, but they are not a replacement for human review. Peer
review is an essential part of the scientific process, and it plays a critical role in ensuring the
integrity, quality, and reliability of scientific and scholarly research.
Peer review involves having other researchers, who are experts in the same or a related field,
review and evaluate the content and methodology of a research paper or article. This process
helps to identify any errors or biases in the research, and to ensure that the research is based on
sound principles and methods.
NLP tools such as ChatGPT could potentially be used to help automate some aspects of the peer
review process, such as generating summaries or comments that help reviewers to more easily
understand and evaluate the content of a manuscript. However, it is important to keep in mind
that NLP tools are still in the early stages of development, and they are not yet able to fully
replicate the critical thinking and expertise of human reviewers.
Overall, while NLP tools may have the potential to bring some efficiencies and improvements to
the peer review process, they are not a replacement for human review and judgment. It is
important to use NLP tools responsibly and with a clear understanding of their limitations, and to
ensure that the peer review process remains robust and fair.
Q: What would your argument be for a scholarly writer to use ChatGPT?
There may be some arguments in favor of using ChatGPT or other natural language processing
(NLP) tools as a supplement to traditional research methods and writing skills in the context of
scholarly writing. For example, ChatGPT and other NLP tools could potentially be used to:
Generate human-like text: ChatGPT and other NLP tools are designed to generate human-like
text, which could be useful for generating summaries or reports, or for creating realistic dialogue
for use in simulations or other types of experiments.
Assist with the review and feedback process: ChatGPT and other NLP tools could potentially be
used to generate summaries or comments that help reviewers to more easily understand and

4. evaluate the content of a manuscript, which could potentially save time and resources in the
review process.
Help to identify relevant literature: NLP tools could potentially be used to help researchers
identify relevant literature more efficiently, by searching large databases of papers and articles
and identifying those that are most closely related to their own research. This could potentially
save time and effort in the research process.
However, it is important to keep in mind that ChatGPT and other NLP tools are not a
replacement for traditional research methods and writing skills. These tools are still in the early
stages of development, and they have limitations and biases that should be taken into account
when using them.