Are we unlocking the true potential of conversational AI in academic research? Does the promise of AI extend beyond the oft-feared idea that it’s here to “kill academic essays”? Certainly, the world of artificial intelligence (AI) is more than just chat GPT models that can write coherent text. In fact, it’s reshaping the landscape of academic research in ways that we’re only just beginning to understand.
Conversational AI has the potential to revolutionize academic research. It opens up unprecedented possibilities for real-time, interactive data collection and analysis. By making complex tasks simple, conversational AI platforms are not merely advanced tools — they are collaborative research partners that redefine what’s achievable.
The next generation of psychologists, linguists, computer scientists, and sociologists are getting a chance to innovate in their respective fields, and lead the charge in an exciting new era of AI-powered discovery.
Here is just a glimpse of what is possible.
8 Applications of Conversational AI in Academic Research
1. Natural Language Understanding (NLU) Research
NLU is a significant research area in linguistics, computer science, and artificial intelligence. Conversational AI platforms can be used to create, deploy, and test different AI models that understand and respond to natural language inputs, providing an important tool for NLU research.
To give one example, the data collected from conversational AI can be used to advance emotion recognition in natural language, which includes identifying and responding to the sentiment of text or voice communications. The ability to accurately identify and respond to emotions will be a key component of future AI assistants.
2. Speech Data Collection
Collecting speech data is crucial for linguistics, speech science, and AI research. Communicating with machines via voice is more natural than typing out text — but speech is significantly harder for machines to accurately recognize. Collecting large and diverse speech samples is critical for developing improved speech recognition systems.
For instance, Dr. Tanvina Patel from Delft University of Technology is using conversational AI to collect and label speech training data, a time-consuming task without the help of AI. The data Dr. Patel collects will be used to build Automatic Speech Recognition (ASR) models that do a better job of recognizing diverse speaker groups.
3. Experience Sampling
The Experience Sampling Method (ESM) is often used in psychology and behavioral science to gather data from participants throughout the day. Before the internet, experience sampling was done using pagers and notepads. Now, researchers can create AI-powered bots that interact with participants throughout the day in their natural environments.
Joanna Kuc, a PhD student at University College London, used the OneReach.ai platform to create a journaling bot that interacts with psychedelic drug users before, during, and after their experiences, capturing their thoughts in a natural setting. The goal of the study is to develop a model that predicts who may benefit the most from psychedelic treatment for mental health disorders. Experience sampling is one example of the many ways in which conversational AI can be used as a tool to gather data on social and psychological phenomena as they occur.
4. Training AI Chatbot Assistants
Large language models like ChatGPT are driven by natural language prompts that must be extensively tested and refined. Indeed, prompt engineering has quickly become a valuable skill amongst computer and data scientists. Conversational AI platforms can be used to quickly test and fine tune prompts to create AI assistants for specific industries or tasks. These AI can then be deployed to handle specific roles, improving service delivery and efficiency in various sectors.
5. Symbol Usage Analysis
The use of signs and symbols falls under the broader field of semiotics, which is relevant to numerous academic disciplines, including linguistics, sociology, psychology, and communication studies. Marina Zhukova, a PhD student at UC Santa Barbara, used the OneReach.ai platform to build a ChatGPT-powered bot that uses emojis like humans in dialogue. Participants’ eye movements are tracked while they interact with the bot. The research aims to understand how users of different age groups (for example, millennials vs. GenZ users) process and use emojis to facilitate natural and dynamic conversations.
6. AI User Experience Personalization
User Experience (UX) and personalization are significant areas of research, particularly in the fields of computer science, information science, and UX design. Using large language models, researchers can create chatbots with different personalities and assess how they engage users. Drs. Santiago Castiello and PhD student Riddhi Jain at the University of Oxford are working with the OneReach.ai platform to test if users prefer AI that mirrors their psychological states. The research will drive the creation of chatbots that connect with users for a more engaging experience.
7. Automated Data Collection
Many academic disciplines in both the social and natural sciences rely on data collection and analysis. Conversational AI can be used to automate many laboratory methods to increase efficiency, reduce bias, and allow for larger-scale studies. AI can also be used as an assistant at nearly every step of the data analysis pipeline, from the creation of bespoke computer code to the generation of figures and research papers.
8. Developing Ethical Guidelines
The study of ethics in AI is a growing field in philosophy, law, and computer science. The use of conversational AI platforms in research can shed light on ethical considerations such as privacy, consent, and the appropriate use of AI in various contexts. Automation can be used to test AI models for bias and build bots that respond to humans in an ethical and safe way.
Why is Access to Conversational AI Important for Researchers?
Tech behemoths like Meta, Google, and Amazon have a history of funding research projects (Google’s DeepMind being one example). OneReach.ai stands out as the only Conversational AI company with clear ties to academic research. The company actively collaborates with esteemed universities such as Yale, the University of Oxford, University College London, UC Santa Barbara, and Delft University.
By providing early-career researchers with access to advanced AI tools, the OneReach.ai Academic Fellowship ensures that the next generation of scientists are well-equipped to harness the power of conversational AI. For instance, fellowship recipient Joanna Kuc, a PhD student at University College London, built a bot for experience sampling — a popular smartphone-based method psychologists use for data collection, which is currently restricted to a few expensive smartphone apps.
No code conversational AI platforms give researchers a flexible tool for building AI-based applications on nearly any channel—from SMS to voice to Whatsapp. With minimal training, researchers can design applications capable of presenting participants with nudges, questions, or surveys, and record their responses—all within days or even hours. This flexibility empowers researchers, freeing them from reliance on rigid third-party applications or costly software developers.
Experience of the OneReach Academic Fellowship
OneReach.ai is committed to ensuring technology excludes no one. The OneReach Academic Fellowship, established in August of 2022, serves as a critical component of this overarching initiative. The fellowship’s goal is to provide early-career researchers, including PhD students, postdocs, and new faculty, access to the OneReach.ai platform, allowing them to tackle significant research problems in their field with conversational AI.
The first fellowship round sparked considerable interest, attracting applications from top-ranked universities and researchers in diverse fields—from computer science and linguistics to clinical psychology. Four applicants distinguished themselves based on their CVs, proposed research, and platform use: Dr. Tanvina Patel (Delft University of Technology), Drs. Santiago Castiello and PhD student Riddhi Jain (University of Oxford), PhD Student Joanna Kuc (University College London), and PhD student Marina Zhukova (UC Santa Barbara).
“My research investigates how humans judge different chatbot personalities. We believe that people may enjoy interacting with chatbots that mirror aspects of their personality, a phenomenon known as psychological homophily (“love to what is like us”). By gaining a better understanding of how humans interact with different AI, we may be able to provide personalized AI experiences to conduct mental health screening in a more efficient way. ”
— Dr. Santiago Castiello, Postdoctoral Associate,
Department of Psychiatry, Yale University
and OneReach.ai Academic Fellow
“I built an AI-powered bot that interacts with psychedelic users through the Telegram app to record their thoughts and feelings before and after psychedelic experiences. The goal is to capture their thoughts in a natural setting, and then apply machine learning models to the data to find correlates of improvements in mental health. Ultimately, the research aims to predict who may benefit the most from psychedelic therapies.”
— Joanna Kuc, PhD student,
Department of Experimental Psychology,
University College London
“For my doctoral research, I’m doing an eye-tracking experiment where the goal is to understand how emoji are used and processed in dialogue settings. Using the OneReach.ai platform, we built a ChatGPT-powered bot that uses emoji like a human to facilitate natural and dynamic conversations with participants. We’re analyzing eye movements during the conversation to better understand the role of emoji in these interactions.”
— Marina Zhukova, PhD student,
Department of Linguistics,
University of California, Santa Barbara,
and OneReach.ai Academic Fellow
Conversational AI, while still a growing field, has the potential to revolutionize many areas of academic research. Programs like the OneReach.ai Academic Fellowship are crucial in this respect. They are giving researchers a chance to innovate in their respective fields, leading the charge in an exciting new era of discovery.
As we delve deeper into how conversational AI is transforming various aspects of academic research, we continue to uncover its diverse applications and profound impacts. From crafting personalized AI experiences to understanding symbol usage in communication, from emotion recognition to ethics, we’re only just scratching the surface of what AI has to offer.