Greer Donley is the Associate Dean for Research and Faculty Development, the John B. Nicklas, Jr. Faculty Fellow, and a Professor of Law at the University of Pittsburgh School of Law. She is one of the nation’s leading experts on abortion law, with widely cited scholarship on medication abortion, interjurisdictional conflicts, and the far‑reaching consequences of abortion bans on reproductive healthcare. Her work has been published in top law reviews and featured across major media outlets, shaping national conversations in the post‑Dobbs era. She spoke with SSRN about abortion shield laws, the evolving legal landscape, and the most pressing challenges and strategies for ensuring reproductive access today..

Q: Can you tell us about the motivation behind your recent co-authored paper, “Abortion Shield Laws in Action,” and what you see as the most significant legal challenges these laws face today?

A: David Cohen, Rachel Rebouche, and I have been thinking and writing about shield laws since their first conception. We wanted to write this paper after observing how quickly US states began implementing shield laws after Dobbs. These laws are a relatively new legal innovation, first  becoming effective in the summer of 2023. Our paper looks at how they are working a few years later. The primary purpose of shield laws is to protect providers and individuals involved in abortion care in shield states from civil and criminal liability instigated by states where abortion is heavily restricted or banned.

Since the overturning of Roe v. Wade, there was a real concern that legal and political attacks would severely limit access to abortion and threaten providers. Shield laws have played a crucial role in mitigating some of these threats. For example, recent data indicates that more than 10,000 boxes of abortion pills are mailed into restrictive states each month, providing vital access to those who cannot travel out of state, many of whom lack the resources to do so. These laws have enabled providers to continue offering care despite the legal threats.

However, the legal landscape is still very much in flux. Some early cases, like those in New York, have shown clerks refusing to file lawsuits against providers, citing shield laws’ protections. Another case in federal court is ongoing. Our hope is that these laws will continue to serve as a shield, allowing states to uphold their own abortion policies as intended, especially in a post-Roe landscape where states are increasingly diverging in their laws.

Q: Your work discusses the concept of interjurisdictional abortion wars. How do shield laws and telehealth intersect in this context, and what are the potential legal and practical implications?

A: The intersection of shield laws and telehealth is a critical aspect of the ongoing interjurisdictional battles over abortion access. These battles are complex because they involve different legal standards across jurisdictions, including federal, state, and even local laws. It’s important to clarify that shield laws address conflicts between states, not conflicts between federal and state authority. The federal supremacy clause makes clear that federal law generally trumps state law, but shield laws are designed to protect providers and patients from state-level legal actions, especially when states attempt to reach across borders to regulate out-of-state care.

Post-Dobbs, my co-authors and I anticipated and indeed observed that states would adopt divergent abortion laws, with some banning and others protecting access. This divergence enabled states to try to influence or restrict out-of-state care. For example, Texas suggested that if any part of a medication abortion was consumed in Texas, it was an illegal abortion, even if the Texas patient travelled out of state and the out-of-state provider fully followed their home state’s laws. Similarly, some states like Idaho passed laws making it illegal to help minors leave the state for abortion without parental consent, aiming to prevent out-of-state travel for abortion care.

Shield laws have evolved to address these challenges. Initially, they focused on protecting providers offering care to patients that travelled to them but returned to the ban state. But over time, some have expanded to shield providers treating patients across state lines through telehealth, even if the patient is physically located in a ban state.

Practically, this means that shield laws are becoming a vital tool to facilitate cross-border care and telehealth services, which are essential for maintaining access in a highly polarized legal landscape. The broader implication is that shield laws are becoming a key part of the legal infrastructure supporting reproductive access, especially as states attempt to regulate beyond their borders.

Q: Your paper “From Medical Exceptions to Reproductive Freedom” discusses using pregnancy complication cases as a legal strategy against abortion bans. How might this influence future litigation?

A: This paper was motivated by the observation that, despite strict abortion bans, many pregnant individuals face severe health risks or complications that require medical intervention. These cases often reveal the dangerous gaps in the bans particularly because many laws include narrow or vague exceptions for health or life, which are difficult to interpret and apply consistently.

In our analysis, David Cohen and I argue that pregnancy complication cases can be powerful legal tools to challenge these bans. They demonstrate that abortion is not just a matter of personal choice but a critical component of healthcare for everyone. Publicized cases of women denied care, suffering harm or even dying have shifted public perception by emphasizing that abortion bans threaten real lives.

Legally, these cases can be used to expose the flaws and inconsistencies in the laws. For example, some laws have vague language that leaves too much to interpretation, draw arbitrary lines, and prioritize secular exceptions over religious ones. We suggest strategies like challenging laws based on vagueness, religious discrimination, and rationality. These cases can serve as a wedge to argue that abortion bans violate constitutional rights by endangering health and life for all. They can also help shift the legal narrative from abstract rights to concrete health and safety concerns, making it harder for courts to justify bans that cause harm. We hope that ultimately, they can also be used down the road to challenge Dobbs itself as unworkable.

Q: Your chapter in “Regulation in a Turbulent Era” examines the regulatory landscape post-Dobbs. What do you see as the biggest hurdles for regulators trying to adapt to this rapidly changing environment?

A: The post-Dobbs environment presents a host of complex challenges for law makers, and these hurdles differ depending on which side of the debate you’re on. For anti-abortion lawmakers, the primary concern has been how to “expand” exceptions without undermining the core restrictions. They are trying to craft laws that appear to provide some leeway for health-or-life exceptions but are often so narrowly defined that they effectively do almost nothing to expand access.

Supporters of reproductive rights, on the other hand, are focused on expanding abortion access. Shield laws are a key part of this puzzle. Many advocates are pushing to expand and strengthen these laws to better protect providers and patients. Some states are experimenting with innovative measures, such as removing provider names from pill bottles. But there are other critical efforts too, like expanding state Medicaid coverage for abortion or removing unnecessary state abortion restrictions.

Another layer is the broader regulatory landscape, where federal agencies such as the FDA are involved in shaping the environment. The rapid pace of legal and policy changes makes it difficult for regulators to keep up, and there are tremendous threats to the agencies’ independence. Overall, it is a big challenge to navigate this shifting terrain balancing legal risks, public health considerations, and political realities while trying to ensure access and safety for those seeking reproductive care.

Q: You played a key role in drafting Connecticut’s abortion shield law and other legislative efforts. What have been some of the most important lessons learned from these advocacy efforts?

A: It’s been interesting and exciting to have our scholarship turn into a real-world impact. It has been a privilege for me and my co-authors, David and Rachel. We feel the responsibility of wanting shield laws to remain effective over the long run.

I teach a course on legislation and regulation, which focuses on how courts interpret statutes. For me, it’s been really rewarding to bring real-world experience into the classroom, something that complements my scholarly work. Having done some actual bill drafting, I can provide students with an inside perspective on how the process works, which I think students have enjoyed.

Q: Given your experience with drafting laws and amicus briefs, what advice would you give to legal scholars and practitioners interested in influencing reproductive health policy? 

A: I think it’s important for legislators to communicate with a wide range of stakeholders. Talking to advocates is crucial, but it’s also valuable for legislators to engage with academics, healthcare providers, and others who serve different roles within a movement.

Being open to creative ideas is also important. For example, when shield laws first emerged, they were often packaged with other bills aimed at reducing unnecessary abortion restrictions or funding reproductive health services. Combining related issues can be an effective strategy.

Reproductive rights have been less in the spotlight recently, but I hope people continue to prioritize reproductive rights, as they remain critically important and currently endangered.

Q: Your work often discusses the intersection of law, ethics, and medicine. How can these fields collaborate more effectively to advance reproductive justice?

A: I’m currently starting several new projects related to the fetal personhood movement. It’s been an exciting time to revisit my background in philosophy and ethics. I previously completed a fellowship in bioethics, which I really enjoyed, and I’m now exploring questions like: if the fetus is not considered a person under the Constitution, then what is it? This question intersects law and philosophy and has been both challenging and intellectually stimulating.

I also do a lot of work at the intersection of law and medicine. For example, after Dobbs, I had the opportunity to work with rheumatologists whose rheumatoid arthritis patients were struggling to access a common medication called Methotrexate, which can also cause abortions. Collaborating with them helped me understand the legal issues and communicate how certain patients are facing difficulties accessing these drugs.

Additionally, I am part of a centre at the University of Pittsburgh called CONVERGE, an interdisciplinary hub focused on sexual and reproductive health equity. It includes members from the Schools of Medicine, Public Health, Psychiatry, and Law. Collaborating with colleagues across these fields has been very rewarding and enriching for various projects.

Overall, I think reproductive rights and justice are inherently interdisciplinary fields, and the more that experts from different fields work together, the better the work will be.

Q: What do you think are the most common misconceptions the public or policymakers have about abortion laws and their impacts?

A:  One of the most common misconceptions about abortion, reflected in recent polling, is that people have abortions for selfish reasons or because they are irresponsible. These gendered biases influence public perception. For example, a late-2024 poll found that about 57% of likely voters – both pro-choice and anti-abortion — believed most abortions are obtained for selfish reasons. I was surprised by how widespread this misconception is.

Most people seek abortions because they cannot afford to have a child. Many are already mothers struggling to care for their existing children. Others feel they are not emotionally, financially, or physically capable of being the parent they want to be. There are also medical reasons and a variety of other circumstances that lead to abortion. Framing any of these reasons as selfish is simply incorrect. There are also deep stereotypes about why women get pregnant, such as the idea that pregnancy is their fault or that they were irresponsible. These biases are ingrained, and supporters of abortion rights are working to correct them.

Historically, during the Roe era, much of this discussion was silenced; people who had abortions did so quietly. Since Dobbs, however, more open conversations are happening, which I believe will lead to greater understanding. I hope this will help people see why abortions happen and understand that all abortions are health saving. Pregnancy is physically and emotionally demanding, more than many realize.

Having been pregnant myself, I can say that pregnancy’s physical demands can be overwhelming, even when the pregnancy is wanted. Whether someone seeks an abortion because they don’t want to be pregnant or for other reasons, they are making a medical decision that prioritizes their health. Pregnancy is physically and emotionally challenging, even under the best circumstances. Addressing gender biases and misconceptions about abortion is crucial for changing hearts and minds. Doing so is essential for protecting abortion rights and recognizing abortion as a fundamental healthcare issue.

Q: What are the next big questions or challenges in abortion law that you hope to explore in your future research?

A: I’m currently working on a two-part series that argues against the fetal personhood movement. I see the anti-abortion movement as being on the defensive right now; they are surprised and struggling with the deep unpopularity of their abortion bans. However, their long-term goal remains to ban abortion nationwide. If they can’t achieve this through legislation, they will try to do so through the courts, using fetal personhood. I’m working on some papers related to this.

Additionally, I’ve done a lot of work on medical exceptions in pregnancy and plan to continue exploring that area. I also work extensively on FDA regulation of abortion pills, and there could be significant developments in that area in the coming year.

Q: What do you think SSRN contributes to the world of modern legal research and scholarship?  

A: When my co-authors and I uploaded our paper “The New Abortion Battleground” to SSRN, it was downloaded around 10,000 times in just six months. That was incredible. It’s a great example of how SSRN provides free, open access to legal scholarship, allowing ideas to reach media, policymakers, and the public. It’s rare for an academic work to have that kind of immediate impact: where people want to read, discuss, and engage with your ideas.

I’m very grateful for SSRN because it helped get our paper out into the world. In law, posting drafts on SSRN is common, and it’s especially important because our paper was even cited by the Supreme Court’s dissent in Dobbs, when it was still a draft. Without SSRN, it wouldn’t have been accessible at that stage.

Beyond that, the habit of posting drafts fosters a vibrant exchange of ideas. I subscribe to various legal journals and receive updates on what scholars are working on, which helps me stay informed and share my own work. It encourages collaboration and the flow of ideas, with many of us working together (consciously or not) in part of larger effort to restore lost rights.

More About GREER DONLEY

Professor Greer Donley’s scholarship and advocacy have been influential in courtrooms, legislatures, and public discourse. Her work has appeared in leading journals including the Stanford Law Review, Columbia Law Review, and Duke Law Journal and her public writing is has been featured in outlets such as The New York Times, The Atlantic, The Washington Post, and Slate. Donley co‑authored the widely discussed paper The New Abortion Battleground, which was cited by the U.S. Supreme Court’s dissent in Dobbs v. Jackson Women’s Health Organization. Beyond scholarship, she has played a central role in drafting transformative reproductive‑rights legislation, including Connecticut’s pioneering abortion shield law. Before joining academia, she practiced at Latham & Watkins and clerked on the U.S. Court of Appeals for the Second Circuit. She is a graduate of the University of Michigan Law School, where she served as Editor‑in‑Chief of the Michigan Journal of Gender & Law. Her work continues to shape the national landscape of reproductive health, law, and policy.

You can see more work by Greer Donley on her SSRN Author page here.

Bent Flyvbjerg is a pioneering scholar and leading authority in the field of megaproject management and urban planning. As a professor at Oxford, Copenhagen, Delft, and Aalborg, Bent has dedicated his career to improving the delivery and success of large-scale projects worldwide. In this interview, Bent shares his expertise on managing megaprojects, addressing common misconceptions, and exploring the future of project management, offering valuable lessons in the challenges and opportunities of large-scale urban and infrastructure development.

Q: Your work has extensively addressed issues like strategic misrepresentation and optimism bias in megaprojects. How can policymakers and practitioners better implement your reference class forecasting methods to improve project outcomes?
A: Strategic misrepresentation is a behavior, while reference class forecasting is a forecasting method. They are related because reference class forecasting can help identify potential strategic misrepresentation. Once identified, you can consider ways to prevent it. However, the forecasting method alone does not prevent strategic misrepresentation; incentives are needed to discourage such behavior. Since we’re dealing with behavior, it’s important to promote actions that disincentivize deliberate misrepresentation, which involves intentionally providing false information.

Q: Given your pioneering research in behavioural science and phronetic social science, what do you believe are the biggest challenges in translating social science insights into practical management strategies?
A: The biggest challenge is that human behavior is very difficult to change. Good behaviours are hard to alter, which is beneficial, but bad behaviours, such as those that  make large projects, policies, and plans wasteful are particularly problematic because people tend to be very set in their ways.

To address this, we need mechanisms that can influence and change behavior. One key factor, supported by research, is “skin in the game,” meaning individuals have something at stakes, such as rewards if things go well and losses if they don’t. When people have their own assets at risk, they are more likely to act responsibly.

Therefore, it’s essential to create incentive structures that encourage desired behaviours and discourage misconduct. Simply using forecasting methods like reference class forecasting isn’t enough; you must also consider the incentives that will lead to the outcomes you want. Understanding the most likely future and aligning incentives accordingly is crucial to achieving the desired results

Q: How do you add personal accountability to a megaproject?
A: By establishing incentive structures that promote responsible behavior, encouraging desirable outcomes and discouraging non-desirable ones. This is achievable, but it requires strong support from top management.

The entire organization must view this as a strategic priority aiming to foster behaviours that prevent project failures. It involves careful planning at all levels: individual, group, and organizational. It’s essential to consider how to incentivize people to act in ways that secure desired outcomes.

Every organization should address this, and successful ones do so effectively. We have seen organizations that get it right and understand the importance of aligning incentives with strategic goals.

Q: You’ve advised numerous governments and organizations on megaproject delivery. Can you share a particularly challenging project you worked on and what lessons it taught you about managing complexity and risk?
A:The most challenging but ultimately also most rewarding example I mention in my book, How Big Things Get Done,was a project to build 20,000 schools and classrooms in Nepal. This was particularly difficult because it was in remote areas of the country, where the terrain is rugged, to say the least, with no roads but only footpaths and very limited infrastructure.

Nepal’s government, along with development organizations including the Danish International Development Agency (for whom I worked), aimed to build many of these schools in areas with no existing educational facilities. Despite the challenges, the project succeeded, and this success has been independently studied and evaluated, including by the Bill and Melinda Gates Foundation. They recognized it as a model for creating local schools that increased general, and especially girls’ enrolment, which is crucial in developing nations.

The key to success was a focus on two main principles: technical and social. Technically, we designed simple, modular schools built from standardized units of one classroom, or multiple classrooms for larger schools using local materials and labour. This standardization allowed local teams to improve their skills through repetition, as they built the same type of school many times, rather than doing bespoke projects each time, which often leads to problems.

On the social side, we learned that ownership and responsibility mattered. Inspections revealed that buildings built and handed over without community involvement often deteriorated quickly. Conversely, buildings where the local community was involved in their construction were better maintained. This taught us to involve local people in building their schools, fostering a sense of ownership and responsibility.

These two principles, standardized technical design and community involvement were crucial in overcoming the project’s difficulties and ensuring its success.

Q: Your recent papers explore the fat-tailed distribution of project risks, especially in IT projects. How do these findings influence your approach to project risk management and forecasting?
A:  Data shows that most projects outcomes, not just for IT projects, are fat-tailed, meaning their risk distributions have long, heavy tails. Only a few project types – about three or four out of twenty-three – are not fat-tailed. The majority are fat-tailed, making risk management challenging. In some cases, risks are so extreme that they are effectively infinite, meaning they cannot be predicted.

Fat tails with infinite variance are particularly problematic because traditional project risk management methods assume normal (Gaussian) or near-normal distributions with thin tails. These methods become useless when risks are infinite or extremely high, as they underestimate the true risk.

Even less extreme fat tails classified as high or extreme risk are still problematic because conventional methodologies assume near-normal distributions. This leads to a dangerous disconnect: project managers often believe risks are small and manageable when, in reality, they are extreme and unmanageable.

This misperception is a major issue in project management. Many practitioners rely on risk assessment methods based on normal or near-normal distribution assumptions, which ignore fat-tailed risks. This results in underestimating the true risk, sometimes worse than having no risk assessment at all, because it provides a false sense of security.

In summary, the standard practices in project management are based on flawed assumptions, and this disconnect between reality and methodology is a significant and widespread problem, highlighted by our data

Q: How do you think the concepts of phronesis, and practical wisdom can be integrated into the education and training of future project managers and city planners?
A: Practical wisdom, or common sense, should be emphasized more in education. While courses in analysis, statistics, and econometrics are valuable, they are most effective when used by people without practical wisdom. As the saying goes, “A fool with a tool is still a fool.” Educating only on tools without teaching wisdom results in ineffective use.

We need to cultivate practical wisdom, which is often overlooked because it’s seen as non-quantitative, yet, good management and leadership depend on it. Practical wisdom involves applying heuristic rules of thumb that guide decision-making. For example, “Think from right to left” – start with the goal and work backward – and “Your biggest risk is you.”

In How Big Things Get Done, we present 11 rules of thumb based on common sense and practical wisdom. These are designed to complement data and forecasting models, including reference class forecasting. The most successful project leaders are those who combine practical wisdom with data and models.

Q: Your research emphasizes the importance of accountability and transparency in reducing misinformation. What practical steps can organizations take to foster a culture of honesty and accuracy in project planning?
A:First, there has to be a genuine desire within the organization to promote integrity, ideally from everyone, and certainly from top management. Without top management’s commitment, success is unlikely. This desire should be embedded in the organization’s policies and strategy.

Second, it’s essential to make it difficult for bad behavior to occur by establishing disincentives for misconduct and positive incentives for good behavior. This system must be continuously monitored and improved, as loopholes can always emerge.

Fortunately, many honest organizations and individuals worldwide demonstrate that it’s possible to succeed. However, human nature means there will always be some bad apples, and sometimes many, in this line of work.

Q: In your opinion, what is the most significant misconception about megaprojects that still persists in both academia and practice?
A: We published an article earlier this year in Harvard Business Review titled The Uniqueness Trap. The core idea of the article is that the common conception that projects are inherently unique is a misconception. The belief is very common, especially in megaprojects, but it also applies to smaller projects. People tend to think that what they are doing is one-of-a-kind.

This, we argue, is a human tendency – a behavioural bias. We all tend to see ourselves as more unique than we are, and this extends to our children, our projects, and our products. The article documents that the more people believe their projects are unique, the worse the projects perform. This is a significant finding: for instance, the perception of uniqueness correlates with much higher cost overruns for projects.

When project leaders think their project is so unique that they cannot learn from others, they often fail to seek previous examples or lessons learned from similar projects. This lack of learning from past experiences leads to repeated mistakes. The most critical issue with this bias is that it prevents project teams from looking at previous projects to avoid making the same errors.

In essence, the uniqueness trap causes people to overlook valuable lessons from history, resulting in consistently poorer performance, especially in large, complex projects. Recognizing and overcoming this bias is crucial for improving project outcomes.

Q: How do you envision the future of megaproject management evolving with the integration of new technologies like AI and big data analytics?
A:AI and big data are already widely used across many fields. I published an article titled AI as Artificial Ignorance on SSRN, which is available for free. The main argument of the article is that current AI, particularly large language models like ChatGPT and Perplexity, do not work very well because they lack any concept of truth. These models are essentially guessing words, they predict the most likely next word or phrase, which is not a reliable basis for decision-making. It often results in strange or incorrect outputs. I illustrate some of these issues in the article, and I emphasize that everyone can test this for themselves.

The key point is that AI should be used in areas where we are highly knowledgeable. When we do so, we can immediately spot its many and significant mistakes. Since these models are just predicting the most probable text, they often produce outputs that are disconnected from reality or factual accuracy. This is the core problem with AI today, in my judgment.

However, I believe the real danger isn’t AI itself, but humans trusting and believing in AI outputs blindly. Our biggest risk is ourselves and how we choose to use AI. The same applies to megaprojects: the challenge isn’t just the technology, but how we rely on it and interpret its results. For the time being, we need to be very cautious and critical in our use of AI, especially in high-stakes contexts.

Q: What are some of the most exciting upcoming projects or research initiatives you are currently involved in or looking forward to?
A: Currently, I’m exploring the fundamental root causes of why some projects succeed while others fail. It turns out that this is a very basic yet powerful explanation that can even account for China’s current success and why they are outperforming the rest of the world both geopolitically and economically in areas like green energy, batteries, EVs, robots, robotaxis, and more.

Discovering fundamental insights like this is incredibly exciting. It’s rare to work on something that offers such a clear explanation for major global phenomena. That’s what I’m deeply engaged with at the moment, and it excites me the most. But there will undoubtedly be many other interesting things ahead even if what I’m doing here and now is what truly motivates me.

Q: What do you think SSRN uniquely contributes to the world of modern research and scholarship, and how do you see it supporting the dissemination of innovative ideas like those in your recent work?
A: I believe SSRN is a tremendous contribution. It’s impossible to overstate how important SSRN and similar platforms are for making knowledge freely and easily accessible worldwide. The platform has a truly global reach, allowing research and ideas to circulate in places where they previously might not have. This broad dissemination can have enormous benefits, both for scholars and for society at large.

For me as a researcher, SSRN is an invaluable tool to share my work and reach readers across the globe. It’s an efficient and highly appreciated way to disseminate knowledge. I’m genuinely grateful that it exists, as it significantly enhances the accessibility and impact of academic work.

Of course, I’m biased as a university person, but the importance of knowledge to human development and progress cannot be overstated. SSRN plays a crucial role in advancing and spreading knowledge, and I see it as a vital part of that broader mechanism.

More About Bent Flyvbjerg

Bent Flyvbjerg’s work has had a profound impact on the fields of project management, infrastructure, and city planning. He is the most cited researcher in the world on megaprojects and has authored or edited ten books and over 200 papers, translated into 22 languages. His research in behavioral science includes the study of strategic misrepresentation, uniqueness bias, optimism bias, the planning fallacy, and the development of reference class forecasting methods that have significantly improved project accuracy and accountability.

Bent’s approach is rooted in his development of phronetic social science, a methodology that emphasizes practical wisdom, power dynamics, and rationality in social science research. His work highlights the importance of transparency, accountability, and incentives in reducing misinformation and improving project outcomes. He has advised governments, organizations, and C-suites worldwide, and is chairman of Oxford Global Projects.

You can see more work by Bent Flyvbjerg on his SSRN Author page here.

Ian McCarthy is a Professor of Innovation and Operations Management at Simon Fraser University and Luiss. His research and teaching focus is on operations management, change and innovation management, and social media. He has published many well-cited articles and has been asked to speak at industry and academic events across the world. He spoke with SSRN about the functional building blocks of social media, how lying and bullshitting differ, and the role changing technology plays into all of this.

Q: You’ve done research on many interesting subjects, like workplace bullshit, gamification, crowdsourcing, deep fakes, understanding the fundamentals of social media, and more. What would you say are some of the underlying themes that tie together the different topics you’ve taught and written about?

A: Technology and control. I’m originally a professional industrial engineer and professor of industrial engineering. When we think about industrial engineering and the business equivalent, operations management, it’s about how we control resources to produce outputs. About 25 years ago, I switched more to innovation and technology management but still interested in how we design technology processes to control the movement of raw material, the behaviors of people, and the flow ideas to produce outcomes which are valuable to the firm and to society. That’s what brings it together: it’s innovation management that spans marketing, operations, and information systems.

Q: Is there a common motivator that influences your decision to study something new?

A: I look at how interesting an issue or problem will be in terms of impact, i.e. how the audience of researchers and practitioners is interested in the knowledge and how beneficial it will be to them. I’m less interested in crafting incremental tweaks to theories. The research opportunity must be an enduring and important practical problem or an emerging phenomena or problem. Some of my most successful papers have helped society to understand the rise of social media, the mechanics of deep fakes, and the power of bullshit: understanding these during times of COVID and political elections, and in a world of misinformation and disinformation.

Q: In your paper “Confronting Indifference Toward Truth: Dealing With Workplace Bullshit,” you and your co-authors make a distinction between lying and bullshitting, saying that “the liar knows the truth and willfully distorts it, while the bullshitter simply doesn’t care about the truth.” Talk a little bit about your framework for dealing with workplace bullshit and in what circumstances it can be most effective.

A: That paper is a practitioner paper. It explains that often when we think our colleagues are lying to us, they’re not really lying to us, they’re just making stuff up. This distinction is important for how we work together.

First of all, lying involves subverting the truth and is much shadier. If I know nothing about you, I can make stuff up about you. For example, if I say that you support the Boston Red Sox, I have no idea whether it’s correct or wrong. I just made it up. But for me to lie about what baseball team you like, I need to know what team you like. I need to have done research on you to lie about you. I must know you, and that’s harder. Lying requires work, bullshittng does not.

In the workplace, when we have meetings, communicate, and do work, it’s probably underestimated how often we just make stuff up and present it as if it’s truth. Why does it happen? We have a number of reasons. One, we want to be inclusive. We want everyone to attend every meeting and have a voice, and we often think that those voices are always truth-based, rather than hunch and opinion-based. Then we have workplaces where it’s uncomfortable for people to say, “I don’t know,” and “I shouldn’t really be at this meeting,” because it makes you feel incompetent or you’re perceived to be incompetent. So, psychological safety is a big issue. To what extent can we call out a colleague or a boss on their logic and their evidence for something that they’ve offered as fact?

To help confront indifference to truth in the workplace, we developed the C.R.A.P. framework, a playful tribute to the phenomenon of bullshit. The C is comprehend, R is recognize, A is act, and then P is what we can do to prevent it. It starts with comprehending the difference between bullshit, lying, and other forms of misinformation and disinformation we call misrepresentation. Once we comprehend that there’s a difference, then how do we recognize the presence of bullshit? Well, usually it’s appealing. It wants to catch our attention, please us and persuade us.

Then, we talk about how people react to it in the workplace. If the bullshit is appealing to you and rewarding to you because it’s supporting your department, supporting your particular job… you’re more likely to believe it, circulate it, add to it, and be supportive of it. If you work in an organization where you have psychological safety, then you might call it out, saying, “I don’t think this is correct,” or even saying, “I don’t understand this. Can you explain this?”

And then another [response] is to just disengage, keep your head down and check out. For some people who don’t like the levels of bullshit, if they have opportunities they will exit, they leave the organization. That’s how people react. Those [are] consequences of bullshit in the workplace.

Then we talk about how to prevent it, … which is, be careful about who you invite to meetings. Create a culture of psychological safety, limit jargon, restrict acronyms, create a culture where people value expertise and data. […] It’s appropriate to be able to offer imperfect opinions, hypotheses and hunches, as long as they are offered as that, and you’re not making decisions based on things that people are asserting as truths, when they’re just making stuff up.

Q: In terms of the prevention aspect, does the effectiveness of that depend at all on the size of an organization? Does it become harder as you add more people?

A: It may not depend on the size but instead the culture in terms of leadership and industry and professional expectations for truth. Why do we bullshit? We bullshit to persuade, and we bullshit to impress. We bullshit to avoid getting caught out.

Let’s take different professions, within and across organizations. In accounting, there are more absolutes – they rely on numbers – but still, these data are not always perfect absolutes. Similarly, you’d hope in science-based and analytical-based professions that there would be more focus on saying “I don’t know,” and questioning the veracity and integrity of the information they rely on. Whereas [it’s different] in marketing where they want to convince consumers to buy, [and] they need to persuade, and often ‘puff’ up claims. And consider politics, and even entrepreneurship, where they’re pitching policies and ventures, …they’re making very future forward statements, where the truth is always evolving.

Also, consider how bullshit propensity varies from North American to South American cultures, to Asian cultures to North European to South European cultures. One very interesting study that came out of Switzerland presented teenagers in the English-speaking world with a mathematical problem that couldn’t be solved. The non-bullshit answer is, “this can’t be solved” or “I don’t know how to do it” and the bullshit answer is, “here’s is the solution” and claiming that it is correct, [usually] with some persistence. From many the tens of thousands of teenagers in English-speaking countries, boys were found to be more likely to bullshit than girls, and teenagers from privileged backgrounds and private schools were more likely to bullshit than those not.

Which country has the highest proportion of teenage bullshitters, and which country has the lowest? […] Well, the highest, in this one study, is Canada and number two is the U.S. and… the lowest by far is Scotland. That study is not testing causal mechanisms and saying “why.” But hunches and hypotheses around why Canada is so high is that they don’t like to upset people, they don’t like to tell it as it is, and they would much rather be nice than share uncomfortable truths or unpleasant opinions, even though they might be true. Scotland is the opposite. They don’t mind actually upsetting people. They don’t mind telling you how it is.

Q: One of your most recent papers on SSRN, “The Risks of Botshit,” discusses the dangers of made-up, inaccurate, and untruthful chatbot content that humans use for tasks and how it can negatively impact businesses: reputation, safety, legality, economic factors, decision-making, etc. Do you see this as the technological equivalent of the bullshit we were just talking about?

A: People might think that large language models and chatbots are bullshitting machines, and to some extent, they do help with that process, but… while human bullshitters can bullshit knowingly and unknowingly, large language models don’t have the capability of knowing. They are forecasting models, they are prediction machines, they are not knowing machines.

Large language models… are trained on human data, a lot of which comes from social media platforms. Think about the quality of that social media data and other online data produced by humans, and the extent to which it has, for some time now, been infiltrated by bots producing misinformation and everything else. So, the short answer is, they’re very bullshit-like but they’re not technically bullshitters. What we argue in the botshit paper is that when humans use AI outputs for work that are contaminated with flaws, errors, and misinformation, they are spreading botshit because they didn’t generate or make up the flaws themselves. They just uncritically use and spread the flaws.

Q: The paper “Social Media? Get Serious! Understanding the Functional Building Blocks of Social Media” introduces a framework of defining social media using seven functional building blocks: identity, presence, relationships, reputation, groups, conversations, and sharing. A few years later, your paper “Social Media? It’s Serious!: Understanding the Dark Side of Social Media” looks at the darker impacts of social media through that same honeycomb framework. Social media has changed a lot in the past decade and a half. Which specific parts of this framework do you think are most important to consider now, in 2026, given the way the landscape of these platforms has changed?

A: The honeycomb framework was a simple functional framework which helped people to understand how, back in 2010, social media platforms varied and evolved over time to do different things. Facebook was originally just a photo-sharing and ranking application, and now we can use it for messaging, dating, promotion, selling, forming groups, and all sorts of things. It relies on user-generated content, where users are sharing content and opinions to appeal to other humans, but also causing addiction, misinformation, privacy issues, and cyberbullying.

At the moment, we engage with these platforms using keyboards, cameras, microphones and GPS. There will come a point when we are engaging with them in augmented and virtual reality ways, resulting in different ‘metaverse realms’ for distinct, immersive user interaction and value creation. We will be wearing or even embedding technology in our bodies to allow us to immerse ourselves in a metaverse realm. The realm will track our body and facial movements and record our heart rates as we explore and engage in the realm. It will be listening to the tone and inclination of our voice and learning when we are happy, when we are annoyed.

Q: My questions have really only scratched the surface of your work, so there’s a lot we haven’t touched on. What papers or other research that we haven’t discussed do you want to highlight as particularly interesting or timely?
A: I’m doing an interesting project where… we study chief information officers (CIOs) and their approach to cybersecurity. We interviewed them, and asked them to complete a survey, and found the presence of ‘illusory superiority’ which is a decision-making bias in which people overestimate their own abilities, skills, or qualities relative to those of their peers, regardless of their actual competence level.

We then presented the same interview and survey questions to different large language models and asked them to be CIOs, and found that they provided very similar answers to human CIOs and also exhibited illusory superiority. This means that large language models can mimic nuanced human behaviors, including cognitive biases like illusory superiority, suggesting they could sometimes replace humans in interview and survey-based research. This could make studies faster, cheaper, and more accessible globally, but raises concerns about response homogenization, probabilistic and unpredictable outputs, and diminished human roles in research.

Q: What do you think SSRN contributes to the world of modern research and scholarship?

A: It makes it more open, more accessible, and more real-time. I think that the original vision of SSRN, with accessibility and openness in providing that information, has a valuable mission, which I’ve been happy to participate in. I read papers on SSRN, which are released early and not yet available via the publishers’ paywalls, and I share as much of my work as possible so that it’s accessible.

---

More About Ian McCarthy

Ian McCarthy is the W.J. VanDusen Professor of Innovation and Operations Management at Simon Fraser University (SFU) and a Professor at the Center in Leadership, Innovation and Organisation (CLIO) at Luiss University. He came to SFU from the University of Warwick, England where he was a Reader and Head of the Organizational Systems Strategy Unit. He worked for several years as a manufacturing engineer before earning his Ph.D. in operations strategy from the University of Sheffield. He was also a Fulbright Scholar at the Georgia Institute of Technology, studying the impacts of university innovation on local and national economies. He studies and teaches operations management, innovation management, change management, social media, creative consumers and the world of management education and has published well-cited articles about these subjects.

You can see more work by Ian McCarthy on his SSRN Author page here