Dr. John Haracz Seminar on Jan 9, 2020: “Resolving the Complexity of asset-price bubbles: Neuroimaging and digital technology for the prediction and prevention of major bubbles”

January 14th, 2020

Seminar: “Resolving the Complexity of asset-price bubbles: Neuroimaging and digital technology for the prediction and prevention of major bubbles”
Who: John Haracz, MD, PhD, MPH
When: 4:30pm – 6pm Thursday, Jan 9, 2020
Where: LKSC 130 (Stanford Medical School)

Abstract: A variety of natural complex systems can become metastable and show phase transitions arising from system components switching from one state to another. Turing Fellow Tobias Preis and colleagues proposed that scale-free power-law dynamics of stock-market price fluctuations and transaction volumes, on time scales ranging from tens of milliseconds to hundreds of days, may be generated by interacting traders switching their preferences for buying or selling stocks (Preis et al., PNAS, 2011). The authors noted that the Global Financial Crisis (GFC) may be a large representative of such financial-market fluctuations. Investor psychology is an increasingly recognized driver of asset-price bubbles, such as the stock- and housing-market bubbles preceding the GFC. The present discussion will assess the potential of using either neuroimaging or digital technology, namely web analytics of investors’ behavioral interactions with an online asset-trading platform, to achieve an early-warning signal of emerging bubble-driving psychology (i.e., investors switching from deliberation- to herding-based trading). This warning signal could enable the prevention of major asset-price bubbles by feeding back to investors the neuroimaging or behavioral sign of a developing bubble. This feedback could discourage herding-based asset purchases, thereby enabling a self-regulatory mechanism for cooling off overheated asset markets. The feedback would represent an introduction into asset markets of a potentially stabilizing negative feedback loop, analogous to the many equilibrium-oriented negative feedback systems in physiology. The broad goal of this research is to stabilize financial systems by inducing equilibria that are potentially as sustainable as the equilibria of physiology.

Working Paper: https://ssrn.com/abstract=336652

Prof. John Perry Seminar, 4/18/2019: “The Complexity of Self-Knowledge”

April 23rd, 2019

Seminar: “Self-Knowledge”
Who: Prof. John Perry (Stanford Philosophy)
When: 4:30pm – 6pm Thursday, April 18th
Where: Alway M106 (Stanford Medical School). 

LINK TO VIDEO: https://www.youtube.com/watch?v=QrNNN-CfRR4&


In this talk I will distinguish three kinds of “self-knowledge” and explain their relations.  A story Ernst Mach told about himself will motivate the distinctions.  Mach once entered a large crowded bus in Vienna by the back door.  Looking towards the front, he noticed a disheveled looking man.  “What a shabby pedagogue he is” Mach said to himself.  But in a bit he realized that he was seeing himself in the mirror that conductors use to keep track of things in the rear of the bus. At first, Mach believed that a certain person was disheveled, and that person was him.  I call this knowledge of the person one happens to be.  After he realized what was happening, he had what I call ordinary self-knowledge.  He would have said “I am a shabby pedagogue.”  I’ll claim we need to recognize a third variety, what I call primitive self-knowledge, to explain the difference. I call it primitive because animals can have it that don’t have ordinary self-knowledge — roughly, animals that don’t pass the “mirror test.”  After explaining how these three varieties of self-knowledge are related, I’ll say a few things about what the great philosophers have said about self-knowledge and the self.

May 14th seminar: Dr. Mengsen Zhang, “The Coordination Dynamics of Multiple Agents”

April 18th, 2019

~ SCG Seminar, May 14th:
Dr. Mengsen Zhang (Stanford Psychiatry & Behavioral Sciences)
Title: “The Coordination Dynamics of Multiple Agents”
Location: Alway M114 (Stanford Medical School).
Time: Tuesday May 14th, 4:30-6pm (dinner with the speaker afterwards).

Video of the talk: https://www.youtube.com/watch?v=37jR5IN1x78&

A fundamental question in Complexity Science is how numerous dynamic processes coordinate with each other on multiple levels of description to form a complex whole—a multiscale coordinative structure (e.g. a community of interacting people, organs, cells, molecules etc.). This dissertation includes a series of empirical, theoretical and methodological studies of rhythmic coordination between multiple agents to uncover dynamic principles underlying multiscale coordinative structures. First, a new experimental paradigm was developed for studying coordination at multiple levels of description in intermediate-sized (N = 8) ensembles of humans. Based on this paradigm, coordination dynamics in 15 ensembles was examined experimentally, where the diversity of subjects’ movement frequency was manipulated to induce different grouping behavior. Phase coordination between subjects was found to be metastable with inphase and antiphase tendencies. Higher frequency diversity led to segregation between frequency groups, reduced intragroup coordination, and dispersion of dyadic phase relations (i.e. relations at different levels of description). Subsequently, a model was developed, successfully capturing these observations. The model reconciles the Kuramoto and the extended Haken-Kelso-Bunz model (for large- and small-scale coordination respectively) by adding the second-order coupling from the latter to the former. The second order coupling is indispensable in capturing experimental observations and connects behavioral complexity (i.e. multistability) of coordinative structures across scales. Both the experimental and theoretical studies revealed multiagent metastable coordination as a powerful mechanism for generating complex spatiotemporal patterns. Coexistence of multiple phase relations gives rise to many topologically distinct metastable patterns with different degrees of complexity. Finally, a new data-analytic tool was developed to quantify complex metastable patterns based on their topological features. The recurrence of topological features revealed important structures and transitions in high-dimensional dynamic patterns that eluded its non-topological counterparts. Taken together, the work has paved the way for a deeper understanding of multiscale coordinative structures.

March 27th 4pm Seminar ~ “The Third Space: Shifting the hierarchy of academia to release the best potential of science”

February 26th, 2019

Title: The Third Space: Shifting the hierarchy of academia to release the best potential of science

Presenters: Kennan Salinero and Doug Kirkpatrick

Date, Time, Venue: 3/27/2019 @ 4pm-5:30pm in Alway M114, Stanford Medical School. 

Followed by a small group dinner, RSVP to SCG if interested: stanfordcomplexity@gmail.com


Distributed networks, populated by individual agents following set rules, can create highly organized, scalable systems.  Indeed, many structures or patterns that mimic natural systems can be created using agent-based modeling (ABM) algorithms with scant rules – the cone shell pattern of cellular automata being one such example.  Humans, and in particular networks of humans, also exhibit patterns of behavior.  A shift in human-based systems to distributed networks for decision-making and self-organizing is part of the current cultural zeitgeist.  This can be described as a movement from top-down hierarchical systems where rules are created for each role, managing from above, to ‘flat’ organizations, where agency is given to individuals.  An extreme example of this is Morning Star, a tomato processing company, which began practicing organizational self-management in 1990.  At Morning Star, everyone is equally empowered to communicate, initiate action, innovate, and execute.  There are no bosses, only ‘colleagues.’

A common element between mathematical models for complex, self-organizing patterning and human organizational constructs in flat workplaces is the role of simple rule sets.  These rules, followed by individuals within a distributed network, create dynamic flows that can be both patterned and purposeful.  Indeed, many startups and ‘lean’ organizations are well-known for the need for individuals to wear multiple hats and fluid, fast-changing work flows, feedback loops, iterative learning curves, and rapid individual and group decision-making.

Academic science is by necessity a top-down organizational structure, investing time and attention from expert educators to educate and train the novice student-learner – or is it?  Considering the fluid nature of experimentation, discovery, and knowledge creation, academia might be better described as an open system of individual agents.

If this is so, what are the underlying decision structures in academia?  And why does hierarchy persist?

Kennan Salinero, principal founder of ReImagine Science, asserts that top research universities, while having individual areas of excellence, can be relied upon for tending to two core principles: status or reputation (supported by publication rates and other outward-facing metrics) and cash flow (in particular, grant acquisition, but also including alumni support).  Feedback loops clearly exist between these two drivers of success. Missing from this equation are self-regulators or rule sets that motivate interpersonal behaviors.  This can negatively impact cooperation and mutualism, and can lead to ‘bad behavior,’ severe power imbalances, and more.

What, then for science?  Within individual labs, the two dynamics that drive top universities similarly play out with publications as a necessary output for the success of graduate student or post-doc and the resulting success in grant acquisition for the Principal Investigator.

Doug Kirkpatrick, of NuFocus Strategic Group and the Self-Management Institute, is a recognized leader in self-managed, distributed leadership. After entrepreneur Chris Rufer founded Morning Star, the company adopted a dynamic, networked organizational system.  Almost thirty years of experience informs organizational self-management theory and practice.  The highly adaptable organization of peers that comprises Morning Star is based on two foundational principles of human interaction:  human beings should not use force or coercion against others, and people should keep the commitments they make to others. 

Doug created a ‘periodic table’ of organizations and practices that concern themselves with workplace culture, which can be accessed at  http://bit.ly/KirkpatrickFutureofWorkTable; his Huffington Post blog on great workplace cultures is at http://bit.ly/GreatWorkCultures.  His two books on the subject are From Hierarchy to High Performance: Unleashing the Hidden Superpowers of Ordinary People to Realize Extraordinary Results by Doug Kirkpatrick, Bill Sanders, Dawna Jones, Ozlem Brooke Erol, Josh Levine, Sue Bingham, and Anna McGrath, and Beyond Empowerment: The Age of the Self-Managed Organization by Doug Kirkpatrick. He is about to release a third book with Forbes Books: The No-Limits Enterprise: Organizational Self-Management in the New World of Work.

Kennan Salinero has written about new approaches to ‘doing’ science in ‘ReImagining Science and the Ivory Tower’ (bit.ly/ScienceandIvoryTowers); in Change: The Magazine of Higher Learning, (2018) 50:1, 38-46.

In this interactive dialog, Doug and Kennan will present their respective experiences within both hierarchical and flat organizations, to explore, with the participants, what might be provided if a profound and courageous shift in academic structures were to emerge, to empower humanity to bring its highest intellectual and educational resources to bear on its current challenges.

“Explaining Multiple Forms of Conscious Awareness, and More,” Dr. Frank Heile, Dec. 6th, 4:30-6pm, Alway M114.

November 26th, 2018

Explaining Multiple Forms of Conscious Awareness, and More,” Frank Heile, Ph.D. (Physics, Stanford)

If you would like to attend dinner with the speaker after the seminar, please contact StanfordComplexity (at) gmail.com !!!

This talk  presents a materialistic model of consciousness that can explain the distinctions between several different forms of conscious awareness:

  • Non-human animal consciousness
  • Modern human consciousness
  • Flow state consciousness
  • “Enlightened” states of consciousness (also known as “nonduality”)
  • Consciousness experienced in Auto-Activation Deficit syndrome
  • The phenomenal consciousness vs. access-consciousness distinction proposed by NYU philosopher Ned Block
  • How spirituality developed and how its invention changed consciousness

A three-agent model of the brain, combined with the Attention Schema Theory model of awareness proposed by Princeton neuroscientist Michael Graziano, provides a framework to explain these distinctions.

Finally, this model can offer answers to the following philosophical questions:

  • Why does conscious awareness seem to be fundamentally non-physical and to not have a location in space?
  • What conditions cause conscious awareness to arise?
  • Can conscious awareness exist without a “self?”
  • Do humans have free will?

There is bound to be disagreement with the proposed answers to these questions, but these concrete answers provide a starting point for thought-provoking discussions! For more details about the proposed model, please reference an additional description here: http://complexity.stanford.edu/blog/seminar-by-dr-frank-heile-on-dec-6th-430-6pm-in-alway-m114.

“Translingual Dynamics”

November 14th, 2018

Thursday, November 29, 6:30pm-9pm.

Room: Z301 (Stanford Business School)

Link to gCal invite

Seminar by Dr. Frank Heile on Dec. 6th, 4:30-6pm in Alway M114.

October 30th, 2018

Stanford Complexity Group will host a talk by Dr. Frank Heile on Dec. 6th, from 4:30-6pm in Alway M114 (Stanford Medical School). Details of the talk follow:

Explaining Multiple Forms of Conscious Awareness, and More,” Frank Heile, Ph.D. (Physics, Stanford)

Abstract: An agent, such as a human being, is an entity that can sense the world and can act on the world, often in the pursuit of goals. Decomposing a complex agent into multiple sub-agents is one strategy for gaining insight into underlying mechanisms. The high-level functional model proposed here,decomposes the brain into three interconnected sub-agents: The Thinker, Doer,and Experiencer. The Thinker and Doer are justified because of their consistency with well-established, experimentally-derived theories of cognition in both psychology (Dual Process Theory [1]) and neuroscience (the Action-Outcome/Stimulus-Response model [2]). A theorem in control theory [3] proposes that an effective agent should contain a model of the world where the agent operates. This theorem suggests the existence of the third agent, the Experiencer; this agent would construct the model of the world that is shared by the Thinker and Doer.

Attention Schema Theory [4] proposes a model of awareness comprised of three objects: the agent’s self-model, the agent’s attention schema (which is a model of the neurological attention mechanism), and the representation of the attended object. This awareness model is applied to each of the three proposed sub-agents to describe the agent’s forms of awareness about external objects, and the types of self-awareness each agent would experience. The result is three different forms of conscious awareness. One of these forms would be the consciousness that non-human animals (and ancient humans) would experience. The second is the default awareness of modern humans. The final form of awareness corresponds to some of the experiences that occur in transient “flow states” or the more persistent “enlightened consciousness states.” In addition, this three-agent model clarifies the distinction, proposed by philosopher Ned Block, between phenomenal consciousness and access consciousness [5].

This three-agent proposal can also explain the rare neurological syndrome of Auto-Activation Deficit [6]—a specific type of apathy where patients can sit for hours, not moving or talking. Surprisingly, this inertia is immediately reversed when the patient is asked to perform some activity or to answer a question. Additionally, many of these patients have blunted affect and report that they do not experience thoughts. This three-agent model interprets all of these symptoms as evidence that these patients are suffering from a disabled Thinker.

Finally, this model explains the reasons for the development of both theistic and non-theistic spiritual traditions, and the efficacy of spiritual practices. Attend this session to explore a novel approach to assessing scientific or philosophical theories of consciousness, and the questions of agency and free will.


[1] Kahneman, D., 2011. Thinking Fast and Slow. New York: Farrar, Straus and Giroux.

Evans, J. S. B. T. & Frankish, K., 2009. In Two Minds, Dual Processes and Beyond. Oxford, UK, Oxford University Press.

[2] Yin, H. H. & Knowlton, B. J., 2006. The role of the basal ganglia in habit formation. Nature Reviews Neuroscience, Volume 7, pp. 464-476.

[3] Conant, R. C. & Ashby, W. R., 1970. Every Good Regulator of a System Must Be a Model of That System. Int. J. Systems Sci.,, 1(2), pp. 89-97.

[4] Graziano, M. S. A. & Webb, T. W., 2015. The attention schema theory: a mechanistic account of subjective awareness. Front. Psych., 6(500).

[5] Block, N., 1996. How can we find the neural correlate of consciousness?. Trends in Neurosciences, 19(11), pp.456-459.

 [6] Habib, M., 2004. Athymhormia and Disorders of Motivation in Basal Ganglia Disease. The Journal of Neuropsychiatry and Clinical Neurosciences, 16(4), pp. 509-524.

      Laplane, D. & Dubois, B., 2001. Auto-Activation Deficit: A Basal Ganglia Related Syndrome. Movement Disorders, 16(5), pp. 810-814.

“DAO Democracy” Seminar, Ralph C. Merkle – Oct. 18, 2018.

October 7th, 2018

“DAO Democracy”, Ralph C. Merkle
October 18st @ 4-5:30pm.
Venue: LKSC 120 (Medical School)

Event Video:


Dr. Ralph Merkle is a Senior Research Fellow at the Institute for Molecular Manufacturing, and a true pioneer in various areas of engineering and computer science. He will be giving a talk about the potential uses of new decentralized digital technologies to improve our democratic systems.

Read Dr. Merkle’s recent publication on DAO Democracy here (page 28).

All are welcome to attend this exciting lecture, it will be in a large lecture hall. 

Abstract: In a democracy, ordinary citizens decide complex, fateful issues by voting. Recent history suggests this process is less than optimal. Analysis of voting usually concludes it provides negligible economic value to the voter. Voter turnout is therefore highly dependent on emotional factors (“rallies”, “peer pressure” and the like). Voters are often ignorant of basic facts, and are subjected to sophisticated misinformation campaigns. Half of voters are below average. Elected officials have been known to ignore their promises once in office, and the mechanisms of government are not always transparent in their operation. This combination of weaknesses makes current democracies grossly inefficient at best, and prone to catastrophic failures at worst. A combination of ideas that includes prediction markets, Decentralized Autonomous Organizations (DAOs), ideas from the wisdom of crowds and futarchy, can be combined into what might be called a DAO Democracy, a form of government that appears to solve most of these ills.

SCG Seminar on 10/1/2018 – Dr. Toby Lowe – Complexity & Public Management

August 27th, 2018

SCG presents a special seminar by Dr Toby Lowe (Newcastle University Business School, Open Lab).

*** Watch the video of this talk at: https://www.youtube.com/watch?v=ZS97cAizcYk

TItle: “Why trust helps us to manage better in complex environments:exploring a complexity-informed Public Management paradigm”

Date, Time, Venue: 10/1/2018 @ 4pm-5:30pm in Alway M106 (Medical School). 


Currently, public management (sometimes called public administration) is dominated by a paradigm based on linear notions of change. This paradigm, called “New Public Management”, rests on the idea that work towards the achievement of social goals is best undertaken by setting targets for desired outcomes (like “higher rates of employment amongst a target group” or “fewer recorded crimes in a neighbourhood”), and then managing the performance of those who are tasked with delivering those goals by measuring the amount of progress which has been made, using agreed proxy measures. It seeks to hold people/organisations accountable for achieving desired outcomes.

This paradigm is failing. Rather than create real improvements on the ground, evidence suggests that instead it promotes “gaming” amongst those who are managed in this way – it turns social action into a game which is ‘won’ by producing data which makes it look like your programme is succeeding. In other words, this paradigm turns everyone’s job into the production of good-looking data, rather than addressing complex, real-world social problems.

A new complexity-informed paradigm

Complexity explains why this paradigm fails. The social outcomes we seek (like higher employment rates, or less crime) are not delivered by organisations. They are emergent properties of complex systems. Complexity explains why proxy measures are not effective substitutes as performance feedback mechanisms. And it explains why it is folly to hold people/organisations accountable for producing desired social outcomes, when those outcomes are beyond the control of particular actors in those systems.

Consequently, a new complexity-informed public management paradigm is emerging (https://collaboratecic.com/a-whole-new-world-funding-and-commissioning-in-complexity-12b6bdc2abd8 ) This new paradigm asks: how do we shape and influence the behaviour of complex systems in order to produce desired results?

This new paradigm places trust at the heart of the distribution and performance management of resources for social action. It is based on three key shifts:

    • Recognition of the intrinsic motivation of people who undertake social interventions
    • Using learning (rather than vertical accountability) as the driver of performance improvement
  • Funders/Public bodies taking responsibility for the health of the eco-systems from which positive outcomes emerge

If you would like to join in with others who are exploring this new paradigm beforehand, you can become part of the conversation at: https://khub.net/group/complexity-friendly-system-oriented-commissioning-pilot-project

Cultural fit and Complexity

March 29th, 2018

Interview with Professor Amir Goldberg on cultural fit

What it means to “fit in” and why it matters

Almost everyone has had the experience of what it feels like to try to fit in to a new social environment. Companies consider cultural fit of applicants when making hiring decisions. Cultural fit can even be used as an argument in court: in 2012, Ellen Pao lost her discrimination case against the venture capital firm Kleiner Perkins based in part on an argument that she was denied a promotion not based on her gender but rather that she had a poor cultural fit.

Associate Professor in the Stanford Graduate School of Business Amir Goldberg argues that cultural fit matters for the social group and the individual. Professor Goldberg spoke at the Stanford Complexity Symposium on November 14, 2017, describing his work related to measuring cultural fit. Drawing on previous research on cultural fit from managerial science as well as psychology and sociology, Professor Goldberg outlines the difference between cognitive cultural fit- how one’s private self adheres to the surrounding culture- and behavioral culture fit- how one’s behaviors adhere to the surrounding culture.

His 2017 paper with Sameer B. Srivastava, V. Govind Manian, and Christopher Potts, on which his symposium talk is focused, introduces an innovative method for measuring cultural fit, in which they consider “culture” to emerge from individual interactions. The method used in this paper compared the language use of incoming and outgoing messages between employees at the same company. They measured the similarity of different “lexicographic units”, i.e. the usage of different words as well as punctuation etc.

To illustrate how different cultural norms are reflected in lexicographic unit usage differences, consider these starkly different example emails from executives at Sony and Enron.

Figure from Sameer B. Srivastava, Amir Goldberg, V. Govind Manian, Christopher Potts (2017) Enculturation Trajectories: Language, Cultural Adaptation, and Individual Outcomes in Organizations. Management Science. For details on the standardization of the timeline, see their paper below

Using this method, their work demonstrates how, in a corporate setting, an individual’s cultural fit can change over time. They found that a person’s cultural fit when they joined an organization didn’t matter as much for their success at the company as their cultural fit trajectory over time. Those who were let go tended to decrease their cultural fit over time. Those who stayed tended to increase their cultural fit. A third group, who quit, increased then decreased their cultural fit.

Figure from Sameer B. Srivastava, Amir Goldberg, V. Govind Manian, Christopher Potts (2017) Enculturation Trajectories: Language, Cultural Adaptation, and Individual Outcomes in Organizations. Management Science. Sony and Enron emails are referenced from publicly available archives.

Professor Goldberg’s talk sparked an interesting discussion at our symposium about how culture is a complex system, how this insight helps us to better understand culture, and what the implications of this work could be. Stanford Complexity Group (SCG) sat down with Professor Goldberg to learn more.


[Interview has been edited for clarity and length]

SCG: You talk about the cultural norms as an emergent process from these individual interactions. Could you speak on how that might be different in terms of top-down cultural norms? For example, people say that at Amazon they believe in frugality as an important value, which could be like a cultural norm.

Prof. Goldberg: First, you want to ask yourself: where does culture exist? Who defines culture- is it CEOs? Priests? Soviet idealogues? Or is culture actually what happens on the ground? The way that culture matters is how the translation from beliefs to behaviors is distributed across a population.


Where does culture exist?


Even if the corporation leader says that the ethos is “frugality” and whether the ethos is “frugality” is only the ethos insomuch as it’s what people believe is a desirable behavior and that’s what they pursue. It’s an empirical question. The fact that Amazon believes in frugality and Jeff Bezos tells us that’s what they believe, that tells us nothing about how they behave unsupervised. What really matters is the extent to which there’s buy-in and the extent to which this buy-in is held together in equilibrium with the normative behaviors of others.

No one at Enron said the ethos was to cheat and to steal money. They had very beautiful “serve the customer” or whatever that they put on their walls. But there’s a big difference between saying it and creating the normative environment that actually rewards those behaviors.

I think every culture is a complex system and is a complex equilibrium of norms, where the norms are are basically the enacted behaviors and beliefs, which the privately held perceptions that lead to these.

SCG: You mention here the difference and relationship between cognitive and behavioral cultural fit. When you’re measuring people’s emails in this research project, that’s their behavioral cultural fit, right? Could you please explain how cognitive and behavioral cultural fit are related and how the differences between them may end up mattering, for a company or for an individual’s success?

Prof. Goldberg: The prior we come into in the research is that they’re correlated, but the more we’re scraping beneath the surface we realize that that assumption may be incorrect. And this harkens back to some of the most fundamental work in sociology by an ethnographer, Erving Goffman: The Presentation of Self in Everyday Life. He has this metaphor of the backstage and the front stage. It’s known as the “dramaturgical model” of social interaction- that basically every interaction is a form of performance and in every interaction people present themselves. When they interact there are lots of thoughts going on in their heads that they are not communicating and their “performance” in the interaction needs to adhere to a certain code about what’s appropriate and what’s not.

One thing that came out of that research were these “breaching experiments”. When people behave in really weird ways. There are very clear expectations about what is appropriate behavior and what are various signals about one’s expectations about how they expect from their interlocutor to behave, even in a transient interaction. I think it’s those moments where these codes are breached that make salient to us how much of these behaviors is codified.  

One of the realizations we’ve come up to in the work we’ve done is that an important dimension is a person’s capacity to read the code- to understand what is appropriate and normative and to have a mental model of what the other expects.

SCG: In an organization, would you say that only the behavioral cultural fit matters?

Prof. Goldberg: It’s not the only thing that matters. It matters for the individual because that is what others see. That’s what’s communicated about the implied beliefs of the individuals. We know there are some people who are chameleons, they’re very good at adapting. They think to themselves, “I don’t buy into this place. I hate this place. But I’m going to behave as if I do.”

This is often referred to in psychology as “self-monitoring”. It’s one’s capacity to monitor their authentic self and to present themselves in a way which is congruent with what their interlocutor’s expectations are. And how do you infer what their interlocutor’s expectations are? As a function of their interlocutor’s behavior as well. So there’s a delicate equilibrium, and as long as the expectation is held, those who are capable of strategic action, those who are good code readers, will behave in a way that is congruent with the code, irrespective of their private beliefs.


Culture can sustain a handful of people who are fakers, but overall it is difficult.


On average you would expect if there is a significant incongruence between beliefs and behaviors across the population then that culture is not sustainable. Culture can sustain a handful of people who are fakers, but overall it is difficult.

SCG: Is this something that you’re working on?

The science is relatively early in understanding what are the conditions in which there is or is not congruence between the private and the public self and what are the implications. We have a new paper that is precisely about that. We call it “lifting the curtain”. It’s about this metaphor.

Thinking about complexity, in the aggregate these are nonlinear relationships. Imagine you can measure the difference between the behaviors and the private beliefs of an individual and average them across the organization. I imagine there would not be a linear relationship between that and the strength of the culture, or between that and the likelihood of that culture collapsing. We know with complex systems, these complex interactions can lead to phase transitions.

SCG: Can you talk how your research might be applied in a corporate setting? When we’re talking about cultural fit there are also other demographic factors that affect whether or not someone fits in. If someone is 65 and they work at Snapchat, they may have difficulty fitting in because they’re misreading cues but they also might not be fitting in because they’re 65 and the average age is something like 22. You also mentioned in your talk that women tend to match better but tend to be rewarded for it less.

Prof. Goldberg: There’s a relationship between socio-demographics and cultural preferences. Sometimes, socio-demographics are good proxies for cultural preferences but sometimes they’re not. This is different than saying that people interact with people of different social categories in discriminating or compensating ways. So some people might be gender discriminatory in certain ways and that’s going to be irrespective of that woman’s behaviors towards them. But when we think more broadly about what are the implications, we have a more refined tool looking at cultural fit above and beyond crude socio-demographic categories. There’s a way to see first of all to test which social categories are homogenous or not homogenous in their capability to fit or things of that sort.

I think the example that I gave about gender is not so much related to women’s capability of women’s ability to read the code, it’s about gendered biases about how the behaviors of women are interpreted. That are not specific to this firm but are specific to American culture- one of the most gender-equitable cultures but is still a misogynistic culture- there’s probably a lot of variance in misogyny or whatever you want to call it across organizations.


I don’t want someone to create a Minority Report kind of world.


But I’m a little wary about implications. I don’t want someone to create a Minority Report kind of world where they come into an organization and fire people because our algorithm suggests that they’re going to get fired later.

In terms of the implications, what is my responsibility here? I think scientists need to think about the implications of what they do. So, I’m not going to give myself a free pass. That’s why it’s important whenever I talk in public to say I would be averse to having this technology being used in any way, shape, or form to affect the lives of individuals. I think it would be a diagnostic tool for understanding organizations or maybe measuring the cultural health of an organization but I would be strongly opposed to it being used to determine the fates of individuals.

I think one message that comes out of our study is that the vast majority of the way corporate leaders think about culture is that they think about cultural fit. For example, they hire for cultural fit. I think that’s a part of it, yes, but another really important part but that there are people who are capable of adapting. We might call it faking it which might seem like a bad thing, but if we accept that all interactions are a performance, we’re all faking it all the time. So, maybe it’s important to have people who are capable of faking.

I think it’s easier to measure cultural fit at entry, it’s harder to measure people and to think systematically how they’re fitting in over time. I think that’s one implication is that we need to think about how to manage our organization that’s attentive to post-hire cultural change. I think it is my responsibility and it’s important to consider implications because the finding are sexy, the curves are beautiful. But a 95% confidence interval is a 95% interval. There a lot of people who fall outside of the confidence interval and we need to remember that. Small changes might have phase transition effects and I don’t want anyone to get fired for being slightly outside the confidence interval.


Data is not panacea.


Data is not panacea. The thought that we would just come with algorithms and solve all our problems is a frightening and misconceived thought. First of all, data is only as good as the quality of real phenomena that it represents. But second, it’s only as good as the analysis it’s applied to. Every analysis through modelling decisions makes assumptions. If we then take the results of these modellings as objective truths about the world without assuming that our assumptions are built into them, and we affect people’s lives, then we create a terrible world. So, I’m all in favor of people analytics. But only insofar as they’re deployed responsibly and when there’s human decision involved in the process. I do not want to concede authority to bots and algorithms, including the ones that I’ve produced.


To learn more about Professor Goldberg’s work you can check out his talk from the Stanford Complexity Symposium on November 14, 2017 (https://www.youtube.com/watch?v=BvdAjwDjeJo) or see his 2017 paper, “Enculturation Trajectories: Language, Cultural Adaptation, and Individual Outcomes in Organizations” (https://pubsonline.informs.org/doi/pdf/10.1287/mnsc.2016.2671).