Policing plagiarism of ideas in generative AI-assisted research writing
Commentary: Onus is on researchers to use GenAI responsibly and ensure integrity, proper attribution
- Plagiarism of ideas harms the research environment by eroding trust among scientists
- Beyond researchers, plagiarism is an ethical concern for students, professionals in law, business and medicine
- ‘Checking AI output is still the simple and only way to ensure content is correct and reliable’
CHICAGO — As more people — including researchers — use generative artificial intelligence (GenAI) in their writing, it’s becoming increasingly important to define what plagiarism looks like and how to police it.
A new commentary written by researchers at Northwestern University and the National Institutes of Health (NIH) that will publish May 18 in Nature Machine Intelligence weighs various options on how to define plagiarism in research manuscript writing in the ever-evolving world of GenAI.
The commentary argues plagiarism in manuscript writing harms the research environment by eroding trust among scientists, misrepresenting the origin and authenticity of scholarly work, and discouraging innovation and original inquiry.
Currently, most plagiarism policies address two types of plagiarism: plagiarism of original works, such as text or verbatim plagiarism, and plagiarism of ideas. Since GenAI tools can easily rephrase text, verbatim plagiarism is becoming less of an issue. But plagiarism of ideas, which is essentially a form of intellectual theft, is still an important concern because a GenAI tool may plagiarize underlying ideas without giving appropriate credit.
“It is fine and in fact helpful to use GenAI to increase the readability of writing and bounce ideas back and forth, but we know these tools frequently make mistakes of fact and accuracy and have enormous social and environmental impacts,” said corresponding author Mohammad Hosseini, assistant professor of preventive medicine in the division of biostatistics and informatics at Northwestern University Feinberg School of Medicine. “Checking AI output is still the simple and only way to ensure content is correct and reliable.”
Because plagiarism of ideas is difficult to detect and enforce, the commentary recommends that definitions of research misconduct — which includes plagiarism as well as data fabrication and falsification — be revised to include that misconduct may be committed by a person when using GenAI tools.
“If a person using GenAI tools does not do their own background research and carefully review the GenAI’s output, they may not be aware that the tool has plagiarized,” Hosseini said. “By revising the definition, we’re hoping to make it clear that those who use GenAI tools are responsible for avoiding plagiarism, which will ultimately promote more responsible use of GenAI tools.”
Enforcement of plagiarism goes beyond researchers
When universities or funders conclude that a researcher has committed research misconduct, they may impose sanctions with serious adverse career consequences, including retractions, loss of current funding or debarment from future grants, termination of employment or revocation of academic degrees. But the study authors said this discussion goes beyond writing in the research world.
“Non-researchers should also use GenAI in responsible ways,” Hosseini said. “Plagiarism is an ethical and legal concern not just for researchers but also for students and those working in various professions, such as law, business and medicine.”
The commentary is titled, “Plagiarism of ideas in the age of generative artificial intelligence.” David Resnick, a senior bioethicist at the NIH, is a co-author.
Journal
Nature Machine Intelligence
Article Title
Plagiarism of ideas in the age of generative artificial intelligence
Article Publication Date
18-May-2026
Therapy at your fingertips: new Reichman University study led by Prof. Anat Shoshani of the Baruch Ivcher School of Psychology finds AI could transform mental health care
image:
Prof. Anat Shoshani of the Baruch Ivcher School of Psychology, Reichman University
view moreCredit: Gilad Kavalerchik
A new study from Reichman University, published in the prestigious journal JAMA Network Open, has found that an AI-based conversational support platform can significantly reduce symptoms of anxiety and depression, form a meaningful therapeutic alliance with users, and provide round-the-clock emotional support.
Led by Prof. Anat Shoshani of the Baruch Ivcher School of Psychology at Reichman University, and conducted in collaboration with the Kai.ai platform, the study explored whether AI systems could offer an innovative response to the global mental health crisis. Approximately 1,000 Israeli students experiencing emotional distress, anxiety, and depression participated in the study. They were assigned to one of three groups: traditional in-person group therapy with psychologists, a waitlist control group, or a group given access to “Kai,” an AI-powered emotional support platform operating within a popular messaging app and available to users at any time.
The study was conducted during a period of prolonged security tensions in Israel, which heightened the need for accessible and immediate mental health support. The “Kai” system is grounded in established scientific protocols, including CBT, ACT, DBT, mindfulness, and positive psychology. It is capable of sustaining ongoing conversations, recalling past interactions, identifying signs of distress, and offering real-time tools for emotional regulation, breathing exercises, and reflective writing.
The findings showed that users of the conversational AI platform experienced a significant reduction in symptoms of anxiety and depression compared to the waitlist group. In reducing anxiety, the system even outperformed human-led group therapy. Notably, approximately 58% of participants who initially presented with clinical levels of anxiety moved into the healthy range following the intervention. Among participants experiencing depression, nearly half reported substantial improvement.
One of the study’s most striking findings was the formation of a “therapeutic alliance” — a sense of trust, understanding, and emotional connection between users and the AI platform. Participants rated the system as empathetic, professional, and supportive at levels comparable to human therapists. Many also reported that they found it easier to open up to a digital system, free from concerns about judgment or embarrassment.
Prof. Anat Shoshani of Reichman University’s Baruch Ivcher School of Psychology explains: “Anxiety is highly situational. Clinical therapy is invaluable, but it is episodic. AI sits in the user’s pocket — on the bus, in the library, and during sleepless nights — providing continuous support precisely when it is needed. The goal is not to create machines that sound more human, but to build systems that help make our society more human. The therapy of the future will be a continuum of support, available where life actually happens.”
While many mental health apps experience high dropout rates, the study found that 61% of users continued to engage with the platform throughout the 12-week study, using it on average three days per week. According to the researchers, the sense of continuity, personalized availability, and the system’s ability to “remember” users and their personal context fostered a deeper connection that sustained engagement over time.
Notwithstanding these promising findings, the researchers stress that AI is not a substitute for human psychological treatment, particularly in complex conditions such as post-traumatic stress disorder (PTSD). The Kai.ai platform operates within a hybrid model that includes a human support team available 24/7. When the system detects signs of acute distress or risk, it triggers an alert to enable immediate human intervention.
The full study was published on April 14, 2026, in JAMA Network Open, under the title “Efficacy of a Conversational AI Agent for Psychiatric Symptoms and Digital Therapeutic Alliance: A Randomized Clinical Trial.”
Journal
JAMA Network Open
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