Skip to content
MarketScale
‹ Back to IndustriesSciences

Can Professors Use ChatGPT for Academic Research?

We have yet to reach the limit of what generative AI can consistently create. In fact, hobbyists and professionals are just getting started with leveraging ChatGPT for a variety of long-form text use cases. In just a few seconds, the tool can spit out five-paragraph essays on the metaphors of Romeo and Juliet. What about…

This story was produced through MarketScale. See how Sciences teams put it to work with Executive Thought Leadership.

By Education Technology · Academic ResearchAutomationChatgptGenerative Ai
Share

Key takeaways

01

We have yet to reach the limit of what generative AI can consistently create.

02

In fact, hobbyists and professionals are just getting started with leveraging ChatGPT for a variety of long-form text use cases.

03

In just a few seconds, the tool can spit out five-paragraph essays on the metaphors of Romeo and Juliet.

We have yet to reach the limit of what generative AI can consistently create. In fact, hobbyists and professionals are just getting started with leveraging ChatGPT for a variety of long-form text use cases. In just a few seconds, the tool can spit out five-paragraph essays on the metaphors of Romeo and Juliet. What about a scientific essay? What about supporting the presentation of scientific theories? Could professors use ChatGPT for academic research?

Generative AI and ChatGPT automation allow for near-instant searches of massive datasets and the ability to spot inconsistencies that us users might have missed. While this can be a massive boon for scientists and researchers, issues arise with generative AI’s propensity for confidently presenting false information. For example, when asked to write that five-paragraph essay on Romeo and Juliet, if asked to show its sources, ChatGPT will simply make them up.

Despite these issues, René Morkos, the founder and CEO at generative AI company ALICE Technologies and Adjunct Professor of Construction Management at Stanford is confident that Generative AI and ChatGPT automation’s effects will ripple up and down the science vertical and larger academic field. He and other Stanford academics have already been deep in discussion around how to use ChatGPT for academic research. Here’s his take on how ChatGPT could support his own research.

René’s Thoughts:

“ChatGPT is going to change your life, but not the way you think. My name is René Morkos, and I’m an adjunct professor of construction management at Stanford University. I’m also the founder and CEO of ALICE Technologies, a generative AI company for construction that can generate millions of different ways to build a given construction project, reducing construction durations by 17%, and labor costs by 13%.

So, what does ChatGPT and other generative AI mean for the science vertical? We’ve been having that discussion amongst Stanford researchers for some time, and whether or not ChatGPT will fundamentally change how research is done. For example, not only are we asking if it can create papers but can it grade them?

When I’m doing research, I split my time into three categories: creating, arranging, and polishing. Which I work on is usually dictated by how much sleep I’ve gotten. Creating is making the actual pieces that compose the original body of intellectual work. This is a theoretical contribution, the hard part that you need to be fully present and creative for. Arranging is moving those pieces around to create a narrative. And polishing is ironing out the grammar, the formatting, or even writing a short introduction using other sources, stuff that’s relatively easy. ChatGPT is really good at receiving a query and outputting words in the order which it thinks is correct, but it uses large existing data sets to do so, and therefore is limited by what those data sets contain.

It can easily create inaccurate content. It does not have the ability to create new original contributions. It’ll be used for arranging and polishing in the research fields, even creating standard introductions, but it cannot create an original theory yet.”

About the author

ET
Education Technology

Sciences: are you visible to AI?

Before they reach out, Sciences buyers ask AI engines which vendors to trust. See how AI describes your company today, and where competitors show up instead.

Free workspace

You just read one expert. Imagine publishing your whole team.

This article was produced through MarketScale. Create a free workspace and turn your own team's expertise into articles, video, and social posts. No credit card, no demo required.

NPS +73 · 1,000+ creators · 38+ countries

What you get, free

Your own MarketScale Studio workspace
One video edit a month, on us
AI writing, editing, and publishing tools
In-platform coaching to learn the system

More Sciences Insights

Biopharma's $300 Billion Problem Is Driving the Biggest M&A Cycle in a Decade

Biopharma's $300 Billion Problem Is Driving the Biggest M&A Cycle in a Decade

The pharmaceutical industry is facing a significant challenge as over $300 billion in branded pharmaceutical revenue is set to lose patent protection by 2030. This revenue gap is driving the largest merger and acquisition cycle seen in a decade, with companies seeking external growth through acquisitions. This shift is impacting the entire life sciences supply chain, prompting strategic changes across the industry.

  • 01Over $300 billion in pharmaceutical revenue is at risk due to patent expirations by 2030.
  • 02Big Pharma is engaging in an aggressive cycle of mergers and acquisitions.
  • 03The acquisitions are reshaping the life sciences supply chain.

Jun 29, 2026

Quotient Sciences launches Phase I study of what it calls the first AI-formulated drug in the clinic

Quotient Sciences launches Phase I study of what it calls the first AI-formulated drug in the clinic

Quotient Sciences has initiated a Phase I clinical study at its UK facility for an oral solid dose formulation designed using artificial intelligence — what the company believes is the first AI-formulated drug to reach human clinical evaluation. The study, cleared by the UK's Medicines and Healthcare products Regulatory Agency, will assess safety and pharmacokinetics in healthy volunteers. The program, which used Intrepid Labs' machine learning algorithm, signals a broader shift in how contract drug development organizations are integrating AI across formulation and clinical workflows.

  • 01Quotient Sciences initiated a Phase I study of an AI-designed oral solid dose formulation at its UK facility following MHRA approval — the first such case the company believes has been reported.
  • 02The formulation was developed using Intrepid Labs' advanced machine learning algorithm in combination with Quotient Sciences' Translational Pharmaceutics platform.
  • 03The milestone is part of a broader CRDMO strategy to embed AI-enabled approaches across formulation development and clinical workflows, with implications for the wider contract pharma sector.

Jun 17, 2026

Quotient Sciences launches Phase I trial of what it calls the first AI-formulated drug to reach the clinic

Quotient Sciences launches Phase I trial of what it calls the first AI-formulated drug to reach the clinic

Quotient Sciences has initiated a Phase I clinical study of an oral solid dose formulation designed using AI, cleared by the UK's MHRA and conducted at the company's UK facility. The trial—built on machine learning algorithms from partner Intrepid Labs and Quotient's Translational Pharmaceutics platform—aims to validate AI as a direct contributor to formulation design rather than just an upstream analytical tool. Benchling characterizes the broader moment as biotech entering a "builder phase," in which leading organizations embed AI capability at the bench level rather than running isolated pilots.

  • 01Quotient Sciences has dosed healthy volunteers in a Phase I study it describes as the first clinical evaluation of an AI-designed oral formulation, following approval from the UK's MHRA.
  • 02The formulation was developed using advanced machine learning algorithms from Intrepid Labs, integrated with Quotient Sciences' Translational Pharmaceutics platform.
  • 03Benchling identifies a sector-wide shift toward embedding AI capability directly at the bench, moving beyond isolated pilots to structural adoption across biotech R&D.

Jun 17, 2026

Explore More Sciences Insights

Read more expert perspectives from across Sciences.

Browse Sciences Hub

About the Expert

ET
Education Technology

For B2B teams

Your experts could be publishing here

Stories like this one run on content MarketScale captures from real practitioners. See how your team's expertise becomes coverage in Sciences and beyond.

Book a 15-minute demo

Or call us. No forms required. We pick up. 214-945-2512