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\begin{document}

\title{Good-Bot~ Bad-Bot: Addressing bias in chatbots and public health
information~~~~}



\author[1]{Natarajan Ganesan}%
\author[1]{Thanemozhi G. Natarajan}%
\affil[1]{Queromatics}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\selectlanguage{english}
\begin{abstract}
The proliferation of chatbots in recent months has raised concerns about
the potential for bias in these conversations. This is especially true
when it comes to public health topics, where accurate and unbiased
information is essential. Herein, the focus is on the issue of bias in
chatbot conversations using oral contraceptive pills (OCPs) as an
example. By raising awareness about this issue and emphasizing the need
for critical evaluation, we can empower individuals to navigate the
digital landscape with confidence and make informed decisions about
their health.%
\end{abstract}%



\sloppy


\section*{Introduction}

{\label{108982}}

The internet has become the go-to source for health information for many
individuals, with search engines like Google being the starting point.
However, search results often lead to misleading or inaccurate content.
To address this issue, conversational agents like chatbots are emerging
as an alternative source of health information. Popular chatbots like
ChatGPT and Google's Bard promise to provide trustworthy and unbiased
information on any topic through natural conversations (Fig 1).

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.70\columnwidth]{figures/Smartphone-AI-Chat/Smartphone-AI-Chat}
\caption{{Representative image of a user chatting with a virtual assistant guided
by an AI-based chatbot. Image source: Bing image creator
{\label{982380}}%
}}
\end{center}
\end{figure}

However, these chatbots can exhibit biases that shape the health
information they provide. Take oral contraceptives (birth control pills)
for example. When asked about the pill, chatbots often provide
information that skews towards the benefits like pregnancy prevention,
while minimizing discussion of potential side effects. This presents a
limited perspective on oral contraceptives. The algorithms driving
chatbots are trained on available data, which suffers from reporting and
publication biases that accentuate benefits over harms. So chatbots end
up perpetuating these biases.

Providing comprehensive, balanced information is vital for truly
informed decision-making about health. Biased information from chatbots
can steer choices in a particular direction, often aligned with business
interests rather than public health goals.

To counter such biases, chatbots can employ oversight from experts to
ensure balance in the information provided. Guidelines can be issued
urging chatbot creators to minimize biases through training data
selection and algorithm tweaking. For example, they can be trained to
request the user if they need a more comprehensive view in case a
request is pointed in one direction.

Finally, educating people to approach chatbots critically rather than
blindly trusting their guidance is key. Just like with human experts,
examining chatbot recommendations against alternate credible sources
allows for balanced perspectives.

In an evolving digital health landscape, chatbots hold promise in
improving access to information. But thoughtfully addressing their
limitations is crucial so these tools empower rather than inadvertently
mislead people in making health choices aligned with their needs.
Openness to oversight and continual learning will allow chatbots to
better serve individuals and the public health good.

\section*{Methods: Understanding inherent bias in popular
chatbots}\label{methods-understanding-inherent-bias-in-popular-chatbots}

If Internet search engines utilize complex algorithms to deliver their
search results then chatbots like ChatGPT and Bard are even more so and
at an advanced level. Concepts like Artificial Neural Networks (ANN) and
Natural Language Processing (NLP) are just the surface of it. For
example, Fig 2 represents a schematic~of an affective conversation where
the emotion depends on the context. The health assistant understands the
\emph{affective state} of the user in order to generate \emph{effective
and empathetic} responses.

To understand a chat was initiated with ChatGPT, a popular chatbot
available at~\url{https://chat.openai.com/}. At this point, one must
understand that all conversations are not the same; hence, responses to
the same question posed by other users can evoke different answers.
Though this approach personalizes the answers to suit each user and
their inherent `intent', the overall objectivity of the answers provided
can vary widely. It is entirely possible that responses from AI are in
the auto-learning process and keep adapting as the number of users
asking the question changes. This makes the process very personalized
though not necessarily uniformly objective.

\par\null\selectlanguage{english}
\begin{figure}[H]
\begin{center}
\includegraphics[width=0.81\columnwidth]{figures/Figure-2/Figure-2}
\caption{{Illustration of an `affective' conversation where the emotion depends on
the context. Health assistant understands `affective' state of the user
in order to generate `affective' and `empathetic' responses. Image
source: Wikipedia. Original source
{\label{736570}}%
}}
\end{center}
\end{figure}

\section*{Results: Exploring slants in a directed inquiry-based
conversation}

To further illustrate the biases, let us delve deeper into the example
of my recent chat with ChatGPT regarding the FDA approval of an oral
contraceptive pill containing Progestin. While major media outlets
covered this news in a predictable way, curiosity prompted us to
investigate the possible health risks associated with hormone-based
pills. Recognizing the hormonal nature of such contraceptives, it was
reasonable to anticipate the existence of risks and seek comprehensive
information on the topic. To be fair though, the approach of using oral
contraceptives has been in vogue for decades and has proved helpful in
supporting women and their reproductive health.

However, as we embarked on a casual chat, we quickly discovered that the
information presented was far from comprehensive or unbiased. The chat
grew increasingly in favor of the use of the approved pills while I was
seeking information, in particular, about the risks associated with its
use. Even pointed requests to provide links from Pubmed failed to give
satisfactory results. When we countered it by providing it a copy of an
abstract text from a very good recent review paper (that itself was a
result of many meta-analyses and papers), it evaluated the paper well
while still being defensive about what it said earlier. Finally, it had
no choice but to accept there are different sides to the issue as well.

The societal implications, politics, and ensuing interests surrounding
birth control contribute to an inherent imbalance in the available
literature. This imbalance can result in a lack of representation of all
sides of the issue, hindering individuals' ability to access a diverse
range of viewpoints and evidence.

In this particular case, the push to promote the use of oral
contraceptive pills, driven by factors such as gender equality,
reproductive rights, and public health initiatives, can influence the
information that surfaces in search results. As a consequence, the chat
algorithms may prioritize sources that align with the prevailing
narrative, emphasizing the benefits and downplaying potential risks
associated with hormonal contraceptives. This can inadvertently lead to
an incomplete and skewed understanding of the topic, as critical
perspectives and studies highlighting the risks may be overshadowed or
marginalized.

These biases can be further compounded by political and allied interests
that seek to shape the discourse surrounding birth control. Various
stakeholders could attempt to manipulate search results, either directly
or indirectly, to direct the users toward their agendas. As a result,
individuals increasingly relying on chatbot conversations may struggle
to access well-rounded and unbiased information about the potential
health risks associated with oral contraceptive pills.

This imbalance in the available literature underscores the importance of
critically evaluating information obtained through these chatbots. It
highlights the need for individuals to be aware of the biases that can
be inherent in search results and to actively seek out diverse sources
of information. By consulting reputable scientific journals, academic
research databases, and trusted healthcare resources, individuals can
obtain a more comprehensive understanding of the risks and benefits
associated with oral contraceptive pills.

Moreover, this example demonstrates the limitations of relying solely on
internet searches for accessing nuanced information on public health
topics. It emphasizes the significance of seeking guidance from
healthcare professionals who possess the expertise to navigate and
interpret scientific literature objectively. Engaging in open and
informed discussions with healthcare providers allows individuals to
receive personalized advice, address specific concerns, and obtain a
more holistic view of the risks and benefits of oral contraceptive
pills.

\section*{Discussion}

{\label{715718}}

Chatbots operate based on sophisticated algorithms that analyze user
queries and generate responses. However, these algorithms are not immune
to biases, as they are likely to be designed to prioritize certain
information sources and viewpoints. For example, in the case of oral
contraceptives, the algorithm may favor sources that emphasize the
benefits while downplaying or omitting information about potential risks
associated with their use, especially when their use may be desired by
public health agencies for the betterment of women and reproductive
health. For example, looking at the increased risk of developing cancer
over use for a long period of time especially in vulnerable demographics
(certain ethnicity). This is based on a recent user experience. Each
user experience may surely vary.~ Consequently, the chatbot may provide
incomplete or skewed information, hindering individuals' ability to
obtain a comprehensive understanding of the topic.

Moreover, the bias encountered in chatbot responses can hinder the
retrieval of scientific papers and systematic reviews that delve into
the potential risks associated with oral contraceptives. These studies
may present nuanced findings, highlighting adverse effects,
contraindications, or specific populations for whom caution is advised.
However, due to the bias toward promoting contraceptive use, the chatbot
may overlook or underrepresent such studies, limiting individuals'
exposure to critical information. Various factors such as optimization
techniques, sponsored content, and commercial interests can influence
the visibility and ranking of information, potentially skewing the
presentation of viewpoints. In the context of public health, biases can
significantly impact the availability and accessibility of information
related to oral contraceptive pills and their associated health risks.

In navigating information gleaned from such chatbots, it is imperative
for individuals to exercise critical thinking and evaluate search
results meticulously. A casual conversation with a chatbot may not
always yield a balanced view, as the algorithms are likely to prioritize
certain sources and perspectives. Furthermore, the ''best interests'' of
the public, as determined by the algorithms (in turn determined by
interests that be), may not align with providing comprehensive and
unbiased information. It is essential to be aware of these limitations
and actively seek out diverse sources of information.

\subsection*{Policy recommendations}

{\label{148580}}

\subsubsection*{Enhanced transparency and
disclosure}

{\label{369083}}

\begin{itemize}
\tightlist
\item
  Advocate for makers of Chatbots like ChatGPT, Bard, etc. to provide
  more transparency regarding the factors influencing `fact
  presentation' and visibility of information.
\item
  Encourage Chatbot makers to disclose potential conflicts of interest,
  sponsorships, or biases that may impact search results.
\end{itemize}

\subsubsection*{Promoting Critical Health
Literacy}

{\label{400930}}

\begin{itemize}
\tightlist
\item
  Advocate for the integration of critical evaluation and information
  literacy skills into chatbot interactions, empowering individuals to
  critically assess online health information.
\item
  Collaborate in the development of educational campaigns and resources
  that educate the public about biases in chatbot responses and
  strategies for effectively navigating and evaluating the information
  provided by chatbots.
\end{itemize}

\subsubsection*{Collaboration between Public Health Experts and Tech
Companies}

{\label{496218}}

\begin{itemize}
\tightlist
\item
  Foster partnerships between public health experts and technology
  companies to ensure the development of search algorithms that
  prioritize the presentation of balanced, evidence-based information.
\item
  Engage in ongoing dialogue to address concerns related to search
  result biases and work towards optimizing the retrieval of reliable
  health information.
\end{itemize}

\section*{Conclusions}

Bias in public health-related conversations with chatbots such as
ChatGPT or Bard or any emerging ones poses significant challenges to
individuals seeking accurate and comprehensive information. By
acknowledging the existence of biases and actively addressing them, we
can foster a digital landscape that enables individuals to make informed
decisions about their health. Through policy recommendations such as
enhanced transparency, promoting critical health literacy, and
collaboration between public health experts and tech companies, we can
mitigate the impact of bias and ensure equitable access to reliable
information. Empowered by critical evaluation skills, individuals can
navigate public health internet searches with confidence, unveiling
hidden truths and making informed choices that contribute to their
overall well-being.

\section*{}

\section*{}

\subsubsection*{Declaration of Generative AI and AI-assisted technologies
in the writing
process}

{\label{880904}}

During the preparation of this work, the authors used grammar-checking
tools and generative AI\,in order to\,improve the readability and
organization of the content. After using this tool/service, the authors
reviewed and\,edited the content as needed, and take full responsibility
for the\,content presented.

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