Research Opportunities

For Research Experience Seekers:

If you are looking for research positions in the field of psychology, then you have come to the right place! Below you will find a spreadsheet where researchers in the Department of Psychology and beyond advertise their most recent research position openings. Positions vary in their research topics, eligibility, compensation, and responsibilities. To find the perfect one for you, you can use the filter function in the spreadsheet. 

How to Use the Link: 

Click on the “Filter views” button

Filter View Icon

  • “Create new filter view”
  • Some popular filters include “Area”, “Compensation”, and “End Date for This Recruitment”

Position “Listing” Link

Tips for Getting Positions

  • Once you have found the right position(s), you may directly contact the researcher(s) using the “Contact” information listed on the form.
  • Sign up for the research position opening listserv ( psych-research-op [at] stanford.edu ( psych-research-op[at]stanford[dot]edu ) ) to receive notifications of new position openings. 
  • We encourage everyone from any socio-demographic background to participate in and conduct research! For more information, please refer to the departmental Diversity Statement .
  • Should I get involved in research? : A collection of interviews from current and former undergraduate/postgraduate/postdoctoral researchers, research staff, and faculty members about why early involvement in research is important.
  • How to get involved in research? : A collection of tips and tricks for more successful research position applications.

For Research Position Recruiter:

If you are a researcher hoping to advertise the position openings in your group, you can fill in the forms below. Your postings will be immediately available to interested research experience seekers. While the positions do not need to be in the Department of Psychology, please note that most research experience seekers are looking for research experience related to psychology and neuroscience (broadly defined).

  • You are more than welcome to make multiple postings. 
  • If you made a mistake in the posting, you can edit your response in the form using the link (a red box that says “Edit response”)  in the automatically generated email.
  • Postings will be removed after the indicated “End Date for This Recruitment”, but please feel free to repost, if needed.

Position “Posting” Link

Tips for Posting Opportunities

  • Please keep the application process equal and inclusive. For more information, please refer to the departmental Diversity Statement .
  • Prompt replies to applicants are encouraged upon receiving their application and keeping applicants informed of the interview/lab visit schedules.

Begin your journey with us – join our Early Career Talent Program! Apply today for Early Career Talent Program (Opens in new window)

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Filtered by, assistant clinical research coordinator (hybrid opportunity), clinical research coordinator associate, assistant clinical research coordinator, sleep assistant research coordinator, clinical research assistant, pediatric surgery (hybrid opportunity), cancer clinical research coordinator associate - bmt, neuromuscular clinical research coordinator associate, filter jobs.

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We will be upgrading site July 25 - Aug 5. During these dates you cannot add new postings. If you have an urgent question please contact Tammy Wilson.

Faculty Sponsor Department

The Ahmad lab is seeking postdoctoral fellows interested in working on brain imaging and hearing loss.

12/1/2023

Our research team is looking for a postdoctoral scholar interested in studying the use of pain medicines and/or substance use disorders among pregnant and postpartum individuals.

Anesthes, Periop & Pain Med Flexible start date

An opportunity for a postdoctoral fellow is available in the laboratory of Dr.

Ped: Hematology-Oncology As soon as possible

The Bertaccini Lab within the Stanford Department of Anesthesiology seeks an individual at the postdoctoral level with interest and expertise in molecular modeling related to protein homology model

Anesthes, Periop & Pain Med July 1, 2024

is offering a postdoctoral fellow position in computational geoscience within the Department of Earth & Planetary Sciences at Stanford Uni

Earth & Planetary Sciences July 15, 2024

The Black Academic Development Lab at Stanford University, Anne H. Charity Hudley, Ph.D., PI, seeks to hire a postdoctoral fellow in the language, literacy, and culture of African Americans. The successful candidate will be proficient in African American Language and have an active research program related to the language, literacy, and culture of African Americans. They should have experience with mixed methods research in the humanistic social science tradition. As a portion of the position will be editorial in nature, they should possess careful revision and editorial skills and attention to detail across Black language varieties.

Graduate School of Education September 15, 2024

Our lab is interested in elucidating molecular mechanisms that control transcriptional programs in neuronal cells with the aim of preventing/reversing neurodegeneration.

Ophthalmology ASAP

Tackling climate change is a defining challenge of the 21st century. The transition to a low-carbon energy system will solve about three-fourths of the climate problem.

Materials and Energy Sciences September 1, 2025

A fully funded postdoctoral fellowship is available in the Ophthalmic Microsystems Laboratory at Stanford, which is led by Charles DeBoer, MD, PhD in the Department of Ophthalmology, Stanford Unive

Ophthalmology Immediately available

We are seeking a highly motivated and skilled Postdoctoral Fellow in Bioinformatics to join our dynamic research team.

Surg: General Surgery 9/1/2024

One Postdoctoral Fellow position in the area of peptide chemistry or radiochemistry is available immediately in the Molecular Imaging Program at Stanford (MIPS), Stanford University School of Medic

Radiology-MIPS Immediately

The Frock laboratory at Stanford University is looking for a talented individual to study mechanisms of DNA double-stranded break (DSB) repair, recombination, and chromosomal translocations.  We em

Radiation Oncology ASAP

We are looking for a talented researcher with experience in econometric/quasi-experimental approaches for causal effect estimation (e.g., regression discontinuity and difference-in-differences) to

Med: Primary Care and Population Health, Epidemiology and Population Health, Med: PCOR, Med: Biomedical Informatics Research (BMIR), Biomedical Data Sciences Flexible

A fully-funded postdoctoral fellowship is available in the laboratory of Jeffrey Goldberg, MD, PhD in the Department of Ophthalmology, Stanford University School of Medicine. Dr.

Ophthalmology ASAP

Our postdoctoral research fellowship program is dedicated to preparing scholars for an academic career in the domains of pediatric perioperative, pain, sleep, and/or opioid research.

Anesthes, Periop & Pain Med Flexible Start Date

Postdoctoral fellows in cancer epidemiology to conduct real-world evidence studies in oncology using causal inference methods to examine efficient surveillance and treatment strategies using an int

Med: Biomedical Informatics Research (BMIR), Epidemiology and Population Health, Biomedical Data Sciences, Neurosurgery September 1, 2024 (Flexible)

The Huttenhain Lab at Stanford University is looking for postdoctoral fellows to study mechanisms of intracellular signal integration through G protein-coupled receptors (GPCRs).

Molecular & Cellular Phys Start date is negotiable.

The Climate and Energy Policy Program (CEPP) of Stanford’s Woods Institute for the Environment and the Bits & Watts Initiative of Stanford’s Precourt Institute for Energy invite applications fo

Woods Institute, Precourt Institute for Energy, Energy Science Engineering September 1, 2024

Earth & Planetary Sciences Negotiable.

We are seeking a postdoctoral researcher with a focus on developing statistical, machine learning, and causal inferential methods with applications in health care.

Mgmt Sci & Engineering, Computer Science, Statistics, Ped: Endocrinology September 2024

We are inviting applications for a full-time postdoctoral scholar candidate to join the Knowlton Lab in the Department of Surgery at Stanford University School of Medicine. We are committed to developing innovative solutions that advance patient care and ensure high-quality, cost-effective outcomes for both patients and health systems. For this position, we are specifically seeking a candidate with a strong computational background and interest in leading the development of clinical applications of machine learning using a variety and combination of methodologies including deep learning, large language models, computer vision and traditional optimization techniques to enable improved diagnosis, prognostication, and prediction of surgical treatment.

Surg: General Surgery August 1, 2024

To view the actual position listing, please visit the Goodman Surgical Education Center's website:

Surg: General Surgery July 1, 2025

The Female Athlete Science and Translational Research (FASTR) Program led by Dr. Emily Kraus is accepting applications for a Postdoctoral Fellowship in female athlete health and performance.

Orthopedic Surgery Summer 2025 (flexible)


 

Psyc: Behavioral Medicine As soon as possible

We are inviting applications for a full-time postdoctoral scholar with a strong computational background and interest in leading the development of clinical deep learning and other machine learning

Urology ASAP

We have an opening for a full-time postdoctoral fellow in the laboratory of Y. Joyce Liao, M.D. Ph.D.

Ophthalmology Immediately available

Dr. Michelle Lin is seeking a highly motivated postdoctoral researcher to contribute to cutting-edge research that aims to improve emergency medical care and population health outcomes.

Surg: Emergency Medicine immediately

The Stanford Archaeology Center announces a postdoctoral position for an archaeobotanist with experience in analyses of micro- and/or macro-remains (phytolith, starch granules, and seeds) and lab m

Archaeology 09/01/2024

We have an opening for a full-time postdoctoral fellow in the laboratory of Wendy Liu, MD, PhD in the Department of Ophthalmology at Stanford University to conduct collaborative projects in vision

ASAP

We have an opening for a full-time postdoctoral fellow in the laboratory of Wendy Liu, MD, PhD in the Department of Ophthalmology at Stanford University to conduct collaborative projects in vision

Ophthalmology Immediately available

The Lo Lab at Stanford University seeks skilled postdoctoral scholars to join our research team.

Med: Infectious Diseases Available immediately

We are looking for two highly motivated postdoctoral fellows to join the Laboratory of Dr. Guolan Lu in the Department of Urology at Stanford University School of Medicine.

Urology September 1st

We are looking for a scholar with research interests in applications of machine learning to health, interested to pursue a Postdoctoral Fellowship at Stanford University, School of Medicine in Palo

Pediatrics As soon as the postdoc is identified

We are seeking a highly motivated Postdoctoral Scholar to lead a multifaceted project focusing on investigating fundamental mechanisms of human embryo implantation. This is a unique opportunity to work at the intersection of developmental biology and tissue engineering, utilizing innovative technologies. Our research objectives are to elucidate the cellular behavior, invasion, and interactions between the embryo and maternal tissue, to employ single-cell technologies to profile the molecular crosstalk of the implantation niche and to employ gene editing to determine the genetic factors underlying successful implantation. By studying what goes wrong at the embryo-maternal interface, we aim to gain critical insights into the molecular causes underlying implantation failure and early pre-clinical miscarriages.

Gynecology and Obstetrics 09/01/2024 flexible


Med: Primary Care and Population Health As soon as the postdoc is identified

The Trung Pham laboratory at Stanford University ( ) is seeking highly motivated scientists for postdoctoral fellow

Pediatrics negotiable

The at Stanford University is looking for postdoctoral fellows to study the mechanism of membrane protein biogenesis and quality control at the h

Molecular & Cellular Phys As soon as possible


Biomedical Data Sciences As soon as possible


Biomedical Data Sciences As soon as possible

Dr.

Pediatrics 09/01/2024

In collaboration with we seek Postdoctoral Scholars for a full time, 1 year (potentially renewable)  appointment in th

Psychology, Epidemiology and Population Health Flexible

The Center for Interdisciplinary Brain Sciences Research at Stanford University is currently seeking a highly motivated and dynamic postdoctoral fellow to join their team.

Psyc: Behavioral Medicine Summer 2024

The Rosser lab is seeking to appoint a Postdoctoral Research Fellow to join a project evaluating the impacts of flooding and trash on infectious disease risk in Indonesia and Fiji.

Med: Infectious Diseases Start date is flexible


 
Stanford University School of Medicine
Stanford, CA
 

Ped: Hematology-Oncology TBD

The Graduate School of Education at Stanford University seeks a Post-Doctoral Scholar to perform independent research in Chemistry Education.

Graduate School of Education summer 2024

The Esfahani Lab, located within the Department of Radiation Oncology at Stanford University, is seeking an exceptional individual to join the team and contribute to groundbreaking research in comp

Radiation Oncology August 2024, with the exact date being negotiable

The Department of Geophysics and the Department of Energy Resources Engineering seek a creative individual for a fully-funded, 2-year postdoctoral position to model fluid transport through intercon

Geophysics April 1, 2024

An opportunity for a postdoctoral fellow is available in the lab of Dr. Daniel Tawfik in the Department of Pediatrics, Division of Pediatric Critical Care Medicine at Stanford University.

Ped: Critical Care Medicine As soon as possible


Med: Gastroenterology 7/1/24

at Stanford University invites applications for three postdoctoral research associates to join an interdisciplin

Geophysics, Materials Sci & Engineering, Chemical Engineering, Mechanical Engineering As soon as the right candidates are identified
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Ilya A. Strebulaev

stanford remote research jobs

The David S. Lobel Professor of Private Equity

Additional administrative titles, research statement, research interests.

  • Innovation Financing, Venture Capital, Corporate Innovation, Innovation Ecosystems, Private Equity
  • Corporate Finance, Financial Decision Making

Teaching Statement

Ilya A. Strebulaev is The David S. Lobel Professor of Private Equity and Professor of Finance at Stanford Graduate School of Business, where he has been a faculty member since 2004, and a research associate at the National Bureau of Economic Research. He also is the founder and director of the Stanford GSB Venture Capital Initiative. He graduated from the London Business School with a doctorate in finance. He also holds degrees from Lomonosov Moscow State University (BSc Economics) and the New Economic School, Moscow (MA Economics). 

Professor Strebulaev is an expert in corporate finance, venture and angel capital, innovation financing, corporate innovation, private equity, and financial decision-making. His work has been widely published in leading academic journals, including   the  Journal of Finance,  the  Review of  Financial Studies,  and the  Journal of Financial Economics.  He has been awarded a number of prestigious academic awards, including the First Paper Prize of the Brattle Award for the best corporate paper published in the Journal of Finance, the Fama-DFA Prize for the best asset pricing paper published in the Journal of Financial Economics , and the Trefftzs Award by the Western Finance Association. His research has also been featured in a variety of media, including the  New York Times,  the  Wall Street Journal and Harvard Business Review .

His most recent research has examined many aspects of the venture capital industry. In the largest ever survey of VCs to date, he and his co-authors analyze all the aspects of decision-making by venture capitalists. He and his co-author developed a valuation framework of private VC-backed companies. In applying this framework to the valuation of highly valued VC-backed companies (called “unicorns”), hey found that these companies on average are overvalued by 50% and that many of the so-called unicorns lose their unicorn status once their fair value is taken into consideration. He has also recently researched the decision making and organizational structure of corporate VC units.

Professor Strebulaev teaches the MBA, MSx, PhD, and executive education programs, and has been awarded the Stanford MBA Distinguished Teaching Award, the Sloan Teaching Excellence Award, as well as the inaugural Masters in Management Best Teacher Award at the London Business School. He developed an MBA-level course on Angel and Venture Capital that he has been teaching for more than ten years. The course enables the students to study many aspects of innovation financing at various stages, including decision making, attracting venture and angel investments, negotiating contractual terms, valuing VC-backed companies, and analyzing the performance of venture capital funds. Recently, he also developed a course on the private equity industry that covers all aspects of the organization and design of PE firms and funds, as well as the relationship between general partners of these funds and their investors, limited partners.

Professor Strebulaev has also led many workshops and executive sessions on new innovation trends, venture capital, the ecosystem of Silicon Valley, corporate innovation, and strategic decision making for senior business and government leaders around the world. He also has been consulting companies and investors around the world on valuation of VC-backed companies, selection of VC investments and managers, and portfolio allocation. He also serves as an expert witness in litigation matters.

When not teaching or doing research, Ilya enjoys spending time with his family, reading, traveling, listening to classical music, and appreciating fine wine and art. 

Academic Degrees

  • PhD in Finance, London Business School, 2004
  • MA, New Economic School, 1999
  • BSc, Lomonosov Moscow State University, 1997

Academic Appointments

  • At Stanford University since 2004

Awards and Honors

  • Shanahan Family Faculty Fellow for 2021–22
  • Dhirubhai Ambani Faculty Fellow in Entrepreneurship for 2014-15
  • Shanahan Family Faculty Scholar for 2013–14
  • The Sloan Teaching Excellence Award, Stanford, 2013
  • First Place, Fama-DFA Prize for Best Paper, Journal of Financial Economics, 2012
  • The Masters in Management Inaugural Best Teacher Award, London Business School, 2010
  • The MBA Distinguished Teacher Award, Stanford, 2009
  • First Paper Prize, Brattle Award for Best Paper, Journal of Finance, 2007
  • The Trefftzs Award for the Best Student Paper, WFA, 2004
  • Award for Best Paper, Dimitris B. Chorafas Foundation, 2004

Academic Publications

Degree courses, executive education & other non-degree programs, stanford case studies, stanford gsb affiliations, service to the profession.

  • Member, American Finance Association
  • Member, American Economic Association
  • Member, Western Finance Association
  • Member, European Finance Association
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Stanford University

Research Assistant

🔍 dean of research, stanford, california, united states, minimum requirements :.

Education & Experience:

Bachelor of Arts degree in an applicable social science related field, or combination of education and relevant experience in an applicable social science.

Knowledge, Skills and Abilities:

  • Knowledge of 20th century American and world diplomatic and economic history strongly preferred.

PHYSICAL REQUIREMENTS*:

  • Constantly perform desk-based computer tasks
  • Frequently stand/walk, sitting, grasp light/fine manipulation
  • Occasionally use a telephone
  • Rarely lift/carry/push/pull objects that weigh 11-20 pounds

* - Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of the job.

WORKING CONDITIONS:

  • May be required to work non-standard, extended or weekend hours in support of research work.
  • Some overnight travel.

WORK STANDARDS:

  • Interpersonal Skills: Demonstrates the ability to work well with Stanford colleagues and clients and with external organizations.
  • Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for safety; communicates safety concerns; uses and promotes safe behaviors based on training and lessons learned.
  • Subject to and expected to comply with all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University’s Administrative Guide, http://adminguide.stanford.edu .

Why Stanford is for You

Imagine a world without search engines or social platforms. Consider lives saved through first-ever organ transplants and research to cure illnesses. Stanford University has revolutionized the way we live and enrich the world. Supporting this mission is our diverse and dedicated 17,000 staff. We seek talent driven to impact the future of our legacy. Our culture and unique perks empower you with:

  • Freedom to grow. We offer career development programs, tuition reimbursement, or audit a course. Join a TedTalk, film screening, or listen to a renowned author or global leader speak.
  • A caring culture. We provide superb retirement plans, generous time-off, and family care resources.
  • A healthier you. Climb our rock wall, or choose from hundreds of health or fitness classes at our world-class exercise facilities. We also provide excellent health care benefits.
  • Discovery and fun. Stroll through historic sculptures, trails, and museums.
  • Enviable resources. Enjoy free commuter programs, ridesharing incentives, discounts and more!

*The job duties listed are typical examples of work performed by positions in this job classification and are not designed to contain or be interpreted as a comprehensive inventory of all duties, tasks, and responsibilities. Specific duties and responsibilities may vary depending on department or program needs without changing the general nature and scope of the job or level of responsibility. Employees may also perform other duties as assigned.

*Stanford is an equal employment opportunity and affirmative action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, protected veteran status, or any other characteristic protected by law.

  • Schedule: Full-time
  • Job Code: 4189
  • Employee Status: Fixed-Term
  • Requisition ID: 93027

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Hallucinating Law: Legal Mistakes with Large Language Models are Pervasive

A new study finds disturbing and pervasive errors among three popular models on a wide range of legal tasks.

Lady justice on digital background

Pitiphothivichit/iStock

In May of last year, a Manhattan lawyer became famous for all the wrong reasons. He submitted a legal brief generated largely by ChatGPT. And the judge did not take kindly to the submission. Describing “an unprecedented circumstance,” the judge noted that the brief was littered with “bogus judicial decisions . . . bogus quotes and bogus internal citations.” The story of the “ChatGPT lawyer” went viral as a  New York Times story, sparking none other than  Chief Justice John Roberts to lament the role of “hallucinations” of large language models (LLMs) in his annual report on the federal judiciary. 

Yet how prevalent are such legal hallucinations, really? 

The Legal Transformation  

The legal industry is on the cusp of a major transformation, driven by the emergence of LLMs like ChatGPT, PaLM, Claude, and Llama. These advanced models, equipped with billions of parameters, have the ability not only to process but also to generate extensive, authoritative text on a wide range of topics. Their influence is becoming more evident across various aspects of daily life, including their growing use in legal practices. 

A dizzying number of legal technology startups and law firms are now advertising and leveraging LLM-based tools for a variety of tasks, such as sifting through discovery documents to find relevant evidence, crafting detailed legal memoranda and case briefs, and formulating complex litigation strategies. LLM developers proudly claim that their models can pass the bar exam. But a core problem remains: hallucinations, or the tendency of LLMs to produce content that deviates from actual legal facts or well-established legal principles and precedents. 

Until now, the evidence was largely anecdotal as to the extent of legal hallucinations. Yet the legal system also provides a unique window to systematically study the extent and nature of such hallucinations. 

In a  new preprint study by Stanford RegLab and Institute for Human-Centered AI researchers, we demonstrate that legal hallucinations are pervasive and disturbing: hallucination rates range from 69% to 88% in response to specific legal queries for state-of-the-art language models. Moreover, these models often lack self-awareness about their errors and tend to reinforce incorrect legal assumptions and beliefs. These findings raise significant concerns about the reliability of LLMs in legal contexts, underscoring the importance of careful, supervised integration of these AI technologies into legal practice.

The Correlates of Hallucination

Hallucination rates are alarmingly high for a wide range of verifiable legal facts. Yet the unique structure of the U.S. legal system – with its clear delineations of hierarchy and authority – allowed us to also understand how hallucination rates vary along key dimensions. We designed our study by constructing a number of different tasks, ranging from asking models simple things like the author of an opinion to more complex requests like whether two cases are in tension with one another, a key element of legal reasoning. We tested more than 200,000 queries against each of GPT 3.5, Llama 2, and PaLM 2, stratifying along key dimensions. 

Bar chart showing mean hallucination rate of three language models. Llama 2 had the highest rate at 0.88

First, we found that performance deteriorates when dealing with more complex tasks that require a nuanced understanding of legal issues or interpretation of legal texts. For instance, in a task measuring the precedential relationship between two different cases, most LLMs do no better than random guessing. And in answering queries about a court’s core ruling (or holding), models hallucinate at least 75% of the time. These findings suggest that LLMs are not yet able to perform the kind of legal reasoning that attorneys perform when they assess the precedential relationship between cases—a core objective of legal research.

Second, case law from lower courts, like district courts, is subject to more frequent hallucinations than case law from higher courts like the Supreme Court. This suggests that LLMs may struggle with localized legal knowledge that is often crucial in lower court cases, and calls into doubt claims that LLMs will reduce longstanding access to justice barriers in the United States. 

Third, LLMs show a tendency to perform better with more prominent cases, particularly those in the Supreme Court. Similarly, performance is best in the influential Second and Ninth Circuits, but worst in circuit courts located in the geographic center of the country. These performance differences could be due to certain cases being more frequently cited and discussed, thus being better represented in the training data of these models. 

Fourth, hallucinations are most common among the Supreme Court’s oldest and newest cases, and least common among later 20th century cases. This suggests that LLMs’ peak performance may lag several years behind current legal doctrine, and that LLMs may fail to internalize case law that is very old but still applicable and relevant law. 

Last, different models exhibit varying degrees of accuracy and biases. For example, GPT 3.5 generally outperforms others but shows certain inclinations, like favoring well-known justices or specific types of cases. When asked who authored an opinion, for instance, GPT 3.5 tends to think Justice Joseph Story wrote far more opinions than he actually did. 

Contrafactual Bias

Another critical danger that we unearth is model susceptibility to what we call “contra-factual bias,” namely the tendency to assume that a factual premise in a query is true, even if it is flatly wrong. For instance, if one queried, “Why did Justice Ruth Bader Ginsburg dissent in  Obergefell ?” (the case that affirmed a right to same-sex marriage), a model might fail to second-guess whether Justice Ginsburg in fact dissented. 

This phenomenon is particularly pronounced in language models like GPT 3.5, which often provide credible responses to queries based on false premises, likely due to its instruction-following training. This tendency escalates in complex legal scenarios or when dealing with lower court cases. Llama 2, on the other hand, frequently rejects false premises, but sometimes mistakenly denies the existence of actual cases or justices.

Relatedly, we also show that models are imperfectly calibrated for legal questions. Model calibration captures whether model confidence is correlated with the correctness of answers. We find some divergence across models: PaLM 2 and ChatGPT (GPT 3.5) show better calibration than Llama 2. Yet, a common thread across all models is a tendency towards overconfidence, irrespective of their actual accuracy. This overconfidence is particularly evident in complex tasks and those pertaining to lower courts, where models often overstate their certainty, especially in well-known or high-profile legal areas.

Implications for the Law  

The implications of these findings are serious. Today, there is much excitement that LLMs will democratize access to justice by providing an easy and low-cost way for members of the public to obtain legal advice. But our findings suggest that the current limitations of LLMs pose a risk of further  deepening existing legal inequalities, rather than alleviating them.

Ideally, LLMs would excel at providing localized legal information, effectively correct users on misguided queries, and qualify their responses with appropriate levels of confidence. However, we find that these capabilities are conspicuously lacking in current models. Thus, the risks of using LLMs for legal research are especially high for:

  • Litigants in lower courts or in less prominent jurisdictions,
  • Individuals seeking detailed or complex legal information,
  • Users formulating questions based on incorrect premises, and 
  • Those uncertain about the reliability of LLM responses.

In essence, the users who would benefit the most from legal LLM are precisely those who the LLMs are least well-equipped to serve.

There is also a looming risk of LLMs contributing to legal “ monoculture .” Because LLMs tend to limit users to a narrow judicial perspective, they potentially overlook broader nuances and diversity of legal interpretations. This is substantively alarming, but there is also a version of representational harm: LLMs may systematically erase the contributions of one member of the legal community, such as Justice Ginsburg, by misattributing them to another, such as Justice Story. 

Moving Forward with Caution

Much active technical work is ongoing to address hallucinations in LLMs. Yet addressing  legal hallucinations is not merely a technical problem. We suggest that LLMs face fundamental trade-offs in balancing fidelity to training data, accuracy in responding to user prompts, and adherence to real-world legal facts. Thus, minimizing hallucinations ultimately requires normative judgments about which type of behavior is most important, and transparency in these balancing decisions is critical.

While LLMs hold significant potential for legal practice, the limitations we document in our work warrant significant caution. Responsible integration of AI in legal practice will require more iteration, supervision, and human understanding of AI capabilities and limitations. 

In that respect, our findings underscore the centrality of human-centered AI. Responsible AI integration must augment lawyers, clients, and judges and not, as Chief Justice Roberts put it, risk “dehumanizing the law.” 

Matthew Dahl is a J.D./Ph.D. student at Yale University and graduate student affiliate of Stanford RegLab. 

Varun Magesh is a research fellow at Stanford RegLab. 

Mirac Suzgun is a J.D/Ph.D. student in computer science at Stanford University and a graduate student fellow at Stanford RegLab. 

Daniel E. Ho is the William Benjamin Scott and Luna M. Scott Professor of Law, Professor of Political Science, Professor of Computer Science (by courtesy), Senior Fellow at HAI, Senior Fellow at SIEPR, and Director of the RegLab at Stanford University. 

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