Knowing and conversation in the academy

“Innovations in how we conduct conversations should be treated as art” (Schein, 2013).

Knowing

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

First we turn to look at “knowing,” which is a practice intrinsic to scientific innovation and creativity. “Knowing,” as it is used here, has its own literature in the business-management world. Like “culture,” knowing is always shared. Elsewhere we learned about celebrations of your open-science culture (Celebrate open science). Here we will look at what Isaac Asimov called “cerebration sessions”: events planned to encourage the “folly of creativity,” in small, informal groups. These events trigger (when successful) shared knowing. Note: Asimov also noted that the subsequent written outputs for these sessions are incidental. What matters is the content of conversations in the room.

“Joviality, the use of first names, joking, relaxed kidding are, I think, of the essence — not in themselves, but because they encourage a willingness to be involved in the folly of creativeness….
I would suggest that members at a cerebration session be given sinecure tasks to do — short reports to write, or summaries of their conclusions, or brief answers to suggested problems — and be paid for that, the payment being the fee that would ordinarily be paid for the cerebration session. The cerebration session would then be officially unpaid-for and that, too, would allow considerable relaxation” (Issac Asimov, 2014: MIT Technology Review; Retrieved March 8, 2020).

You already know knowing, you just don’t know it yet

The recent work of John Seely Brown and others, coming out of organizational knowledge theories in the mid 1990s (See: Boland Jr. and Tankasi, 1995), has added (or recovered) a cultural angle on knowledge management which includes not only knowledge, but knowing: because “the interplay between knowledge and knowing can generate new knowledge and new ways of knowing” (Cook and Brown, 1999). Instead of organizations stewarding an inventory of knowledge objects, what they need to do is open up contexts and spaces: events for knowing (Thomas and Brown, 2011).

“In this way, conversation affords more than an exchange in which the net sum of knowledge remains the same; it dynamically affords a generative dance within which the creation of new knowledge and new ways of using knowledge is possible.
Engaging in such conversation is a practice that does epistemic work; it is a form of knowing. Knowing entails the use of knowledge as a tool in the interaction with the world. This interaction, in turn, is a bridging, a linking, of knowledge and knowing…[Which] makes possible the generative dance, which is the source of innovation. The generative dance, within the doing of work, constitutes the ability to generate new knowledge and new ways of using knowledge — which knowledge alone cannot do. And which the organizations of the future cannot afford to neglect” (Cook and Brown, 1999).

These events for knowing are where organizations do their “sense-making” activities, and where scientists collaborate in conversation to solve — to make sense of — the emergent complexities of nature. Scientists use knowing practices every time a new experiment is made. Each time the scientist creates a new test to interrogate a piece of unknown nature, she hopes to distill a bit of new knowledge and a ray of understanding that might lead to new knowing. They share this knowing in conversations with their colleagues.

While the “official record” for a new discovery might be a published paper, open science works to accelerate sharing by promoting preprints that open up immediate opportunities for scientific conversations across the internet.

Conversations power scientific discovery

“[N]etworked markets get smart fast. Metcalfe’s Law, a famous axiom of the computer industry, states that the value of a network increases as the square of the number of users connected to it — connections multiply value exponentially. This is also true for conversations on networked markets. In fact, as the network gets larger it also gets smarter. The Cluetrain Corollary: the level of knowledge on a network increases as the square of the number of users times the volume of conversation. So, in market conversations, it is far easier to learn the truth about the products being pumped, about the promises being made, and about the people making those promises. Networked markets are not only smart markets, but they’re also equipped to get much smarter, much faster, than business-as-usual” (Levine, et al, 2009 [1999]. Emphasis added.)

The very first one of the ninety-five theses of the Cluetrain Manifesto (ibid) says this: Markets are Conversations. The “markets” for research knowledge in open science connect to the emergent abundance of research artifacts in repositories across the globe. But the knowledge that powers discovery right now lives only in the conversations available across networks of scholars. Buckheit and Donoho (1995) make the point that scientific articles rarely hold the scholarship they claim to convey: rather they are “merely advertising of the scholarship.”

The solution is two-fold: better ways of publishing results that reproduce more of the method, data, software, and ideas (open science looks to go “beyond the PDF”); and more conversations quicker and across a wider range of internet-enabled media, including online direct conversations among peer-to-peer networks. As we learned above (Science happens elsewhere), these networks create virtual “rooms” that are smarter than any of their inhabitants. Following the Cluetrain Corollary, we can assert the following:

“The level and quality of current knowing in any science discipline increases as the square of the number of scientists times the amount of available conversation.”

Through Demand Sharing and Fierce Equality, open science resets the norms for research conversations across the planet. Today, virtual science organizations can be easily bootstrapped through platform cooperatives to support active collaborations across institutions and continents.

Extra Credit: For those of you who follow recent French philosophy, these knowing events are the center of the process from which truths emerge in the philosophy of Alain Badiou. “[A] truth is sparked by an event and spreads like a flame fanned by the breath of a subjective effort that remains forever incomplete. For truth is not a matter of theory but is a ‘practical question’ first and foremost: it is something that occurs, a point of excess, an evental exception, ‘a process from which something new emerges’…” (Bensaïd, 2004; Retrieved March 10, 2020).

Of course you do not need to read French philosophy to understand what Asimov and Badiou are telling you: one great conversation (perhaps over beer at a conference, or online on a teleconference) with a colleague about the intersections of your research can be more valuable — can spark more truths about your object of study — than any article or book in your library.

References

Boland Jr, Richard J, and Ramkrishnan V Tenkasi. “Perspective Making and Perspective Taking in Communities of Knowing.” Organization Science 6, no. 4 (1995): 350–372.

Buckheit, Jonathan B, and David L Donoho. “Wavelab and Reproducible Research.” In Wavelets and Statistics, 55–81. Springer, 1995.

Cook, D.N., and John Seely Brown. “Bridging Epistemologies: The Generative Dance between Organizational Knowledge and Organizational Knowing.” Organization Science 10, no. 4 (1999): 381–400. http://www.jstor.org/stable/2640362.

Levine, Rick, Christopher Locke, Doc Searls, and David Weinberger. The Cluetrain Manifesto. Basic books, 2009.

Schein, Edgar H. Humble Inquiry: The Gentle Art of Asking Instead of Telling. Berrett-Koehler Publishers, 2013.

Thomas, Douglas, and John Seely Brown. A New Culture of Learning: Cultivating the Imagination for a World of Constant Change. Vol. 219. CreateSpace Lexington, KY, 2011.

Demand sharing unleashes the “power of pull” for your science research

“In a closed society where everybody’s guilty, the only crime is getting caught. In a world of thieves, the only final sin is stupidity” (Thompson, 1971).

“Pull allows each of us to find and access people and resources when we need them, while attracting to us the people and resources that are relevant and valuable, even if we were not even aware before that they existed” (Hagel 2010; Retrieved February 26, 2020).

Credit: Rachel Smith on Flickr. John Seely Brown talk

“Sharing” gone massively wrong: academic publishing

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Why is Demand Sharing so important to open scientists like you? We are going to explore this question here. Let’s begin with the poster-child for research-sharing-gone-wrong: “for-profit science publishing.” At the same time you’ve been perfecting your demand-sharing techniques in the classroom, you’ve surrendered your research to one of the strangest marketplace transactions in modern times.

Academics give their research to publishers; give the publishers their copyrights; and also donate an additional sixty-eight million hours a year (Nature News Sept 7, 2018: <https://www.nature.com/articles/d41586-018-06602-y>) reviewing the work of others for free. Academic libraries must each pony up millions of dollars a year to keep their subscriptions current. The public gets dinged thirty to forty dollars (US) a pop just to read a single article. The process of selecting articles often leads to months or years between discovery and publication, and warps the output toward positive (and false-positive) “sexy science” results. The remainder of research results go unpublished. “Economists may not have terms adequate to describe a market as dysfunctional as the one operating for academic publishing” Neff (2020; Retrieved February 26, 2020) notes.

How did this happen?

Potts (et al, 2017) points to a failure of the publishing capacity of academic societies to scale with the blossoming of science output after World War II:

“The wartime and post-war expansion of public research funding and consequent expansion and globalisation of research communities were soon exploited by an entrepreneur-led proliferation of increasingly specialised journals, following the lead of Robert Maxwell’s Pergamon Press (Buranyi, 2017; retrieved February 25, 2020). The small society presses, struggling to cope with growing scale, were supported and then largely supplanted by the ‘Big 5’ commercial presses: Elsevier (which acquired Pergamon in 1991), Wiley, Springer, Taylor & Francis and Sage. These newly-empowered players brought an industrial approach to the publication and dissemination process, for the first time realising the benefits that these specialised capital and skills could provide by operating at a scale that was unprecedented to that date. The successful publishers grew (and consolidated to grow further) alongside a pre-Cambrian explosion and specialisation of journals to create the modern landscape in which the majority of journals is owned, controlled or at least produced by a handful of globalised companies.”

A committee at the National Academies of Sciences (2018) offers additional historical information:

The 1990s brought a wave of consolidation among scientific publishers, as Netherlands- based Elsevier acquired Pergamon, leaving it in control of over 1,000 journals (Buranyi, 2017 [ibid]). Further increases in subscription prices and the advent of “big deal” agreements between publishers and libraries followed in the late 1990s. Under these agreements, publishers agree to provide online access to a bundle of their journals, including all back issues, priced at a discount to the sum of the individual journal subscriptions (Bergstrom et al., 2014). Despite paying lower per journal prices, total outlays by libraries increased to the point where this has been called the “serials crisis” (Panitch and Michalak, 2005[white paper is no longer online]). In 2015, Larivière et al. found that the five most prolific publishers, including Reed-Elsevier, Taylor & Francis, Wiley-Blackwell, Springer, and Sage, control over one-half of all the scientific journal market, and that the profit margins of these companies have been in the range of 25 to 40 percent in recent years (Larivière et al., 2015). According to one economist who studies the industry, this situation “demonstrates a lack of competitive pressure in this industry, leading to so high profit levels of the leading publishers that they have not yet felt a strong need to change the way they operate” (Björk, 2017a).

Both of these accounts point to older, established cultural practices based on demand sharing within the academy being disrupted and displaced by marketplace profit seeking. By the end of the Nineteenth Century, the academy had taken control of its own research sharing practice through the advent of hundreds of member-run professional societies — each with their own publishing effort. Within these societies, members freely gave up their research for review and publication. University presses added their capacity as well.

In demand sharing, a “demand” is a culturally-grounded request

As academic institutions, the societies and universities demanded research finding from their members, in much the same fashion that students can demand knowledge from their professor in the lecture hall. Sharing is both expected and normative. Merton (1973) noted that:

“The institutional conception of science as part of the public domain is linked with the imperative for communication of findings. Secrecy is the antithesis of this norm; full and open communication its enactment. The pressure for diffusion of results is reenforced by the institutional goal of advancing the boundaries of knowledge and by the incentive of recognition which is, of course, contingent upon publication.”

Societies provided both the means of building the shared, public, academic corpus, and the platform for recognition. Yet this individual recognition was also tempered with the larger sense that all knowledge is interlinked and historically accumulated. Merton (ibid) writes: “The communal character of science is further reflected in the recognition by scientists of their dependence upon a cultural heritage to which they lay no differential claims.”

Demand sharing on the open web

Open science efforts in the last twenty years have been centrally focused on refactoring the means of academic publication to take advantage of the opportunities provided by the internet, and to remove the foreign, marketplace, logic in order to reassert the “communal character” of science publishing, grounded in the logic of demand sharing (although they haven’t called it that). Unlinking the act of giving research results back to the science community — which has long been a community norm — from the more recent practice of giving away research results to the marketplace — to own from there forward — restores these results as internal “gifts” within a community guided by demand sharing. There is more. At the same time that open science releases the academy from its recent marketplace bondage (freeing up financial resources in the process), a new, networked marketplace for “ideas” in and out of the academy is also challenging the notion of organizational knowledge ownership, in favor of what Hagel (et al, 2012) calls the “power of pull.”

Large corporations, fledgling start ups, and, yes, even ivory tower universities can access an explosion of shared knowledge and lateral learning when they decide to pull information from global networks. “Institutions can significantly amplify the power of pull, making it far easier to connect with a broader range of people and resources and to learn faster from each other than we ever could in the absence of institutions. We must therefore reclaim our institutions — whether from the inside of existing ones or by creating a new generation of our own.” Open science works to reclaim the academy as learning hubs that can pull information from academy commons resources across the planet.

Goldman and Gabriel (2005) observed that “innovation happens elsewhere”; that the crowd- and network effects of open communities could assemble more talent, a greater variety of knowledge, and effective collective intelligence(s) well beyond those that any company/university/lab could afford to assemble internally. Their arguments were informed by Bill Joy, a co-founder of Sun Microsystems, who wrote in the 1990s: “no matter who you are, most of the smartest people work for someone else” (Wikipedia). This is known in management theory as Joy’s law. And it holds ever more strongly for your university, your agency, or your laboratory.

Many corporate management experts point out that openly sharing ideas across corporations (Golden and Gabriel, 2005; Leadbetter, 2005 <https://www.ted.com/talks/charles_leadbeater_on_innovation?> Retrieved April 21, 2019), and gathering ideas from customers and external sources (Bissola et al, 2017), will lead to better, faster corporate innovation. In fact, you can say, with some authority, that the future of innovation in the academy will require the logic of demand sharing.

The marketplace logic of intellectual property ownership and practice of demand sharing for knowledge are antithetical. They do not play well together. For-profit efforts to include “open practices” invariably lead to open-washing, and the final closure of collected resources as intellectual property (Neylon, 2017). Open for them means “free to acquire” and mainly serves to lower their resource costs. Demand sharing is an older practice, older in the academy, and still older in the species, being a primary form of cultural practice over thousands of years. It privileges internal goods over the external goods and incentives of the market.

To understand this further, jump to (See: Deep dive: Gifting and Reciprocity), where you can explore how each act of demand sharing builds a social bond that can be used to stimulate other occasions of sharing. The academy also needs to break completely from seeking to own intellectual property inside individual organizations (Deep Dive: Against Patents in the Academy) in favor of academy-wide ownership supporting a shared resource commons for intellectual property. Current work on the creation of “Civic Trusts” offers a productive way forward for the academy (See: The Civic Trust; Retrieved February 26, 2020).

References

Bergstrom, Theodore C, Paul N Courant, R Preston McAfee, and Michael A Williams. “Evaluating Big Deal Journal Bundles.” Proceedings of the National Academy of Sciences 111, no. 26 (2014): 9425–9430.

Bissola, Rita, Barbara Imperatori, and Alfredo Biffi. “A Rhizomatic Learning Process to Create Collective Knowledge in Entrepreneurship Education: Open Innovation and Collaboration beyond Boundaries.” Management Learning 48, no. 2 (April 2017): 206–26. https://doi.org/10.1177/1350507616672735.

Björk, B.C. “Scholarly Journal Publishing in Transition — from Restricted to Open Access.” Electronic Markets 2, no. 101–109 (2017).

Goldman, Ron, and Richard P. Gabriel. Innovation Happens Elsewhere: Open Source as Business Strategy. Morgan Kaufmann, 2005.

Hagel, John, John Seely Brown, and Lang Davison. The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion. Basic Books, 2012.

Larivière, Vincent, Stefanie Haustein, and Philippe Mongeon. “The Oligopoly of Academic Publishers in the Digital Era.” Edited by Wolfgang Glanzel. PLOS ONE 10, no. 6 (June 10, 2015): e0127502. https://doi.org/10.1371/journal.pone.0127502.

Merton, Robert K. The Sociology of Science: Theoretical and Empirical Investigations. University of Chicago press, 1973.

National Academies of Sciences, Engineering, and Medicine (U.S.). Open Science by Design: Realizing a Vision for 21st Century Research. A Consensus Study Report. Washington, DC: The National Academies Press, 2018.

Neylon, Cameron. “Openness in Scholarship: A Return to Core Values?” Stand Alone, 2017, 6–17. https://doi.org/10.3233/978-1-61499-769-6-6.

Potts, J., J. Hartley, L. Montgomery, C. Neylon, and E. Rennie. “A Journal Is a Club: A New Economic Model for Scholarly Publishing.” Prometheus 35, no. 1 (2017): 75–92. https://doi.org/DOI: 10.1080/08109028.2017.1386949.

Thompson, Hunter S. Fear and Loathing in Las Vegas; a Savage Journey to the Heart of the American Dream. Random House, 1972.

Science happens elsewhere

“The smartest person in the room is the room itself: the network that joins the people and ideas in the room, and connects to those outside of it” (Weinberger, 2011).

Elsewhere: where the adjacent possible opens up to the power of pull (Hubble Telescope image)

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Goldman and Gabriel (2005) penned to phrase: “Innovation happens elsewhere” to capture the value of open-source software communities. In the academy, it doesn’t matter if you are at Oxford or in Oxnard, almost everything you need to know to make the next step in your research is also being considered at this moment: somewhere else.

In the academy, this “beyond” is a global intellectual commons now becoming abundant with open data and accessible — and reproducible (Crick, et al, 2015) — research results. Using online peer production methods (Benkler, 2016), the academy can optimize the value of this commons for innovation, knowledge, and growth. “[P]eer production practices [are] highly adept at learning and experimentation, innovation, and adaptation in rapidly changing, persistently uncertain and complex environments” (ibid).

The only competition your academy organization has is within itself. As other institutions — including new virtual science organizations — work to continuously improve on their work, your team needs to focus on leveraging the learning engine of double-loop governance to get better than your yesterday. In the infinite game of science, winning means accelerating your team’s learning and sharing capacity through what (Hagel and Brown, 2011) call a “creation net” for open innovation. Standing still is not an option when the research world is exploding somewhere else. This “explosion of creativity is taking over more and more of our world. Everyone involved in it is at the same time a producer and a consumer, a worker and a manager…. Progress in most academic disciplines now seems to move at the speed of ‘instantaneous,’ with discoveries building atop one another at a dizzying pace” (Ito and Howe, 2016).

Creation networks: open science’s network effect

A creation network is enabled by a certain quality of learning within social interactions, a greater quantity of information flows (and/or a greater attention to these), an availability of interpersonal trust (based on demonstrated skills and commitment), and an environment of reflexive involvement: all benefits of belonging to a community-led double-loop governance. “[I]nstitutions will need to become much more selective in their efforts to protect existing stocks of knowledge and much more adept in using their stocks of knowledge to contribute more actively in creation nets and to plug into promising flows of knowledge” (Hagel and Brown, 2008). Data-intensive science (Hey, et al, 2009) in a whitewater world of global research demands a nimble governance for its teams, labs, networks, societies, universities, and agencies.

Know enough to know enough

When your academy organization looks to innovate — or when your personal research is looking to find the right question to ask — in a world where multiple/large data/information inputs, and international science discoveries are coming on line, how can you stay ahead of this emergent complexity? One way to look at this problem is through Ashby’s principle/law of requisite variety, coming from cybernetic management. Ashby’s law notes that unless the control system has at least the variety of the environment it controls, it will fail; which actually means that some part of the environment will be controlled elsewhere.

You need to join the science elsewhere. Elsewhere is where other science teams are now playing the infinite game in collaboration, asking the questions that their networked teamwork generates. Elsewhere there are flows of information being shared across the planet. That is a great reason for new creation networks in the academy: for open science sharing across the academy.

Elsewhere is where innovation happens; because unless you can corral the inherent variety of the problem you face, it will be too complex for your team to innovate a response. If you are not engaged with the open-science elsewhere that is opening up today, your team will suffer. You can either go out and hire a bigger team (good luck talking your chancellor or the NSF into that), or you can borrow enough requisite variety just long enough to bring your own team up to speed by starting up or hooking into an online creation network. You can join the sharing economy, play the infinite game, and get better at it every day. Or you can rest on your (bullshit) reputation and keep on thinking the world will come to you.

When members are given license to form working teams across organizations, they also expand the extent of where their research adjacent possible is found; creative interactions and new knowledge become predictable outcomes. The larger the room, the smarter it gets. Find the room to nurture your research.

When the adjacent possible is a globally available

The “adjacent possible” is a notion that comes from biological theories of coherent change. It describes how the surrounding environment tucked between stasis and chaos provides a resource of available change. The adjacent possible enables, and almost guarantees, certain changes (while ruling out others) out of potentially infinite play of innovation.

“Biospheres, on average, may enter their adjacent possible as rapidly as they can sustain; so too may econospheres. … [T]he hoped-for fourth law of thermodynamics for such self-constructing systems will be that they tend to maximize their dimensionality, the number of types of events that can happen next” (Kauffman, 2000). Every new piece of information, each new proto-fact, expands the horizon of the infinite game of science (See: Learning to play the infinite game). The more scientists that add this new fact to their knowledge, the larger their mutual adjacent possible becomes.

Steven Johnson [Retrieved 1/15/2020], uses the metaphor of “liquid” to describe the optimal network environment to enable innovation (Johnson, 2011). “Solid” networks are too stiff to pivot toward “the adjacent possible” where new ideas sprout. “Gas” networks are too chaotic. “In a solid, the opposite happens: the patterns have stability, but they are incapable of change. But a liquid network creates a more promising environment for the system to explore the adjacent possible.” (Ibid).

More specifically, liquid networks — and the academy organizations that create these — enable individual researchers and teams to explore the adjacent possible; “When the first market towns emerged in Italy, they didn’t magically create some higher-level group consciousness. They simply widened the pool of minds that could come up with and share good ideas. This is not the wisdom of the crowd, but the wisdom of someone in the crowd. It’s not that the network itself is smart; it’s that the individuals get smarter because they’re connected to the network.” (Ibid). The room makes everyone smarter; these new everyones make the room smarter. You need to find/build that room. When you do, you use demand sharing to pull the information and knowledge you need right now to move ahead in your research (See: Demand sharing and the power of pull).

The liquid network is another way of talking about network diversity, the optimal mix of strong ties, weak ties, and strangers in direct communication (See: Ruef, 2002) that is a key predictor for innovation in the global elsewhere your research can call home. How do you get this home? The most reliable starting place is to build a culture of organizational learning into your organization. Double-loop governance is a durable platform on which to develop liquid networks across the academy, or in your lab or your department, and at your learned society.

References

Benkler, Yochai. “Peer Production and Cooperation.” Handbook on the Economics of the Internet 91 (2016).

Crick, Tom, Benjamin A Hall, and Samin Ishtiaq. “Reproducibility in Research: Systems, Infrastructure, Culture.” ArXiv Preprint ArXiv:1503.02388, 2015.

Goldman, Ron, and Richard P. Gabriel. Innovation Happens Elsewhere: Open Source as Business Strategy. Morgan Kaufmann, 2005.

Hagel, John, and John Seely Brown. “Creation Nets: Harnessing The Potential Of Open Innovation.” Journal of Service Science 1, no. 2 (2008): 27–40.

Hey, Anthony J. G., ed. The Fourth Paradigm: Data-Intensive Scientific Discovery. Redmond, Washington: Microsoft Research, 2009.

Ito, Joi, and Jeff Howe. Whiplash: How to Survive Our Faster Future. Grand Central Publishing, 2016.

Kauffman, Stuart. At Home in the Universe The Search for the Laws of Self-Organization and Complexity. Cary: Oxford University Press, USA, 2014.

Ruef, Martin. “Strong Ties, Weak Ties, and Islands: Structural and Cultural Predictors of Organizational Innovation.” Industrial and Corporate Change 11, no. 3 (2002): 427–449.

Weinberger, David. Too Big to Know: Rethinking Knowledge Now That the Facts Aren’t the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room. Basic Books, 2011.

The Congruent Scientist: Playing the infinite game builds personal wisdom

The aikidoka does not let distraction affect her kime 決め… her focus and attention. She is congruent in her form.

“Yet notoriously the cultivation of truthfulness, justice and courage will often, the world being what it contingently is, bar us from being rich or famous or powerful. Thus although we may hope that we can not only achieve the standards of excellence and the internal goods of certain practices by possessing the virtues and become rich, famous and powerful, the virtues are always a potential stumbling block to this comfortable ambition” (MacIntyre, 1984).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Alasdair MacIntyre’s caveat rings true when applied to finite power games in and out of the academy. It’s the same “nice guys finish last” logic that your academic advisor may have given you; “practical” advice that many in the academy have used as an alibi against sharing their data and methods openly. Open scientists know better. This logic exposes how the external goods of the neo-liberal market are crowding out the internal goods so vital to the success of science as a practice. Nicholas Gruen (Retrieved February 21, 2020) puts it this way: “Here’s the serpent in paradise. External goods are necessary, but, at the same time, in tension with internal goods. This is an ethical tension. The risk is always that the pursuit of external goods compromises the pursuit of internal goods, and thus the excellence of the practice.”

Certainly, during the transition phase to open practices of Fierce Equality and Demand Sharing, there will still be games for external goods where the few consider themselves winners and all others as losers. The hyper-competition for scarce external goods in the academy is not going to simply disappear on its own. Today, dozens of open science endeavors have articulated alternative solution pathways for distributing external goods without supporting perverse incentives (Edwards and Roy, 2017; Bartling and Friesike, 2014). However, building alternative practices through intentional culture change takes time and effort. The open, infinite game of science treasures its abundant internal goods — including internal measures of recognition and modes of compensation — above money, fame, and glory. Something to remember when you have little of the latter.

One particular internal good in the academy happens when your work and your person become congruent. The practical wisdom you learn and apply to your research, and with your teammates, you can also use in your life with friends and family.

Background on the notion of congruence

In 1961, the psychotherapist Carl Rogers compiled three decades of papers into the book On Becoming a Person. The main frame of the book describes his client-centric approach to psychotherapy, how he arrived at this and what he learned as a practitioner, many of the articles — which read very much as blogs do today (and were unpublishable in the scientific journals for this reason). He then links this frame to other human endeavors. In particular, he looks to education and personal relations in organizations.

His main therapeutic process involves how the psychoanalyst as a person, develops her own personhood by becoming more congruent (more about this in a minute) and then uses this congruence as a communication tool to open up the client to the process of becoming more congruent. The therapist is really only someone further along the same road to “becoming a person.”

The process of becoming a person, of achieving more and wider congruence, and so having fewer and fewer defenses, brings the client to a better life, with less tension and fear, better communication with everyone, and new opportunities to explore each moment fully. For Rogers, congruence happens when one’s real self (the one we all start out with — all infants are congruent — also the one we can shape with our own skills and the virtues we learn) fully resembles one’s ideal self (the one we acquire from social interactions with others).

The lack of congruence leads to the need to defend the ideal self every time the real self behaves differently, or when people respond to the real self instead of the ideal self. The real self becomes hidden and, indeed, often unknowable; which forms the reason for therapeutic intervention. The goal of congruence is also extremely well aligned with the goal of “becoming a scientist:” congruence unlocks intellectual creativity.

Creativity in science is a self-therapeutic practice

“The mainspring of creativity appears to be the same tendency which we discover so deeply as the curative force in psychotherapy — man’s tendency to actualize himself, to become his potentialities.…This tendency may be come deeply buried under layer after layer of encrusted psychological defenses; it may be hidden behind elaborate façades which deny its existence; it is my belief however, based on my experience, that it exists in every individual, and awaits only the proper conditions to be released and expressed. It is this tendency which is the primary motivation for creativity as the organism forms new relationships to the environment in its endeavor most fully to be itself” (Rogers, 1961).

The ideal self represents the roles you acquire in order to play finite games in your life and career. For example, in your academic position, you are “The Scientist.” As Carse (1987) noted and Rogers might agree here, you have forgotten that you have the freedom to set aside your role. Quite the reverse: the role has become you. This is why you spend so much effort defending your ideal self/role, even (or especially) against your real self. How do you escape?

“[P]rogress in personal life and in group living is made in the same way, by releasing variation, freedom, creativity” (Rogers, 1961). The creativity you invest in the infinite game of science builds the capacity you can use to release your real self from the roles you play in finite games. You acquire the mindset of an infinite game player and become self-directed toward congruence. As Rogers notes:

“[T]he individual who is open to his experience, and self-directing, is harmonious, not chaotic, ingenious rather than random, as he orders his responses imaginatively toward the achievement of his own purposes. His creative actions are no more a chaotic accident than was Einstein’s development of the theory of relativity” (ibid).

Simon Sinek (2019) would add that your infinite game mindset is precisely what you need to succeed as a team member in 21st Century science.

Open science and an open you

How does the authenticity of doing science as an infinite game bleed over into your personal life? Can science really make you a “better person”? The skills you acquired to become a scientist, and the cultural practices of open science you are weaving into your work are tools you can use if you bring along the courage to seek change; “making courage part of your personal culture means you are always willing to keep making changes in your life until it is the life that you want and the life that you deserve. Courage in your life means you accept that there will be missteps — that constant and repeated change may be necessary, but that it is nothing to be ashamed of if it leads to a more fulfilling, positive outcome” (Dudley, 2018).

The intellectual tools of science, such as rigorous, reflexive curiosity, openness, and intellectual humility are available to the scientist for use in other circumstances. You can bring these skills home with you. The same kindness and humility you bring (one hopes) to your teaching and research can become an interactive style elsewhere.

On becoming an organization

“If things aren’t going right, the first response is: let’s make more rules, let’s set up a set of detailed procedures to make sure that people will do the right thing. Give teachers scripts to follow in the classroom, so even if they don’t know what they’re doing and don’t care about the welfare of our kids, as long as they follow the scripts, our kids will get educated. Give judges a list of mandatory sentences to impose for crimes, so that you don’t need to rely on judges using their judgment….Impose limits on what credit card companies can charge in interest and on what they can charge in fees. More and more rules to protect us against an indifferent, uncaring set of institutions we have to deal with” (Barry Schwartz, 2011 TED Talk<https://www.ted.com/talks/barry_schwartz_using_our_practical_wisdom/transcript>; Retrieved 02/17/2020.

In the Handbook’s section on Learning Organizations, we discovered double-loop learning/governance. Double-loop governance maps directly into congruence at the organizational level: the so-called “ideal” organization being the first loop, and the real organization being the second loop. Instead of hiding the real organization behind the idealized intentions of the founder, or top-down rules and regulations derived from an imperious CEO or provost, double-loop governance makes the real organization available to every member. Each member has the same view and purview of the rules and roles, the values and the vision of the organization, and also an obligation to make these congruent with the everyday activities of the organization.

The notion that your organization can also be a therapeutic setting where members can learn to become more congruent may seem peculiar today, where management mainly promotes rule-governed compliance. Barry Schwartz tells us to stop already with the rules and use our everyday interactions to grow social and personal virtues:

“Rules and incentives don’t tell you how to be a good friend, how to be a good parent, how to be a good spouse, or how to be a good doctor or a good lawyer or a good teacher. Rules and incentives are no substitutes for wisdom. Indeed, we argue, there is no substitute for wisdom. And so practical wisdom does not require heroic acts of self-sacrifice on the part of practitioners. In giving us the will and the skill to do the right thing — to do right by others — practical wisdom also gives us the will and the skill to do right by ourselves. (Barry Schwartz, 2011 TED Talk<https://www.ted.com/talks/barry_schwartz_using_our_practical_wisdom/transcript>; Retrieved 02/17/2020.

Remember also that organizational Knowing — the stock of sharable knowledge that defines your academic institution’s main research resource — is a series of conversations between two or more people. Knowing cannot be stored, only generated anew as each conversation leverages the prior ones. Your organization’s culture and governance sets up the circumstances at work where members can (or cannot) communicate effectively to share their insights and grow creativity. Mainly what they share is a specific, collective scientific ignorance.

“This [the shared ignorance in a scientific conversation] is knowledgeable ignorance, perceptive ignorance, insightful ignorance. It leads us to frame better questions, the first step to getting better answers. It is the most important resource we scientists have, and using it correctly is the most important thing a scientist does” (Firestein, 2012). Using open science and the infinite game, you can make your organization a place where each member can become more of a person. In return they will make your organization a better place in which to get science done.

Coda

You’ve likely met one or more congruent scientists. Someone who has engaged you in conversation at a workshop or conference. You walk away thinking, “She is so open and intellectually humble, knows so much, and asks really great questions. She must be such fun to work with.” You might have also sensed a wellspring of truthfulness, justice, and courage there. A corner of your ego might wonder what she thought of you. If you were playing the infinite game with her, and not trying to win points, she probably noticed.

You may also have visited a congruent organization (or, with great luck, you’ve ended up working in one), and come away wondering how they manage to avoid all the administrative bullshit you deal with every day. How do they sustain that level of creative interactions? How come everybody felt safe enough to say those things out loud? What does one need to do to get a job there?

In the Earth sciences, there’s a virtual organization called Earth Science Information Partners (ESIPfed.org). This is a great example of a congruent organization. A few years back, they hired an independent review organization to advise them what they could do to improve. The report came back: sorry, everyone who knows you, loves how you work right now. The reviewers were apologetic about not exposing a range of problems. ESIP has been a double-loop learning organization for two decades. It shows. Here’s an introduction to their bi-yearly gatherings.

The Open Scientist Handbook offers tools for you to become more congruent and to build congruent governance practices into your own academy home.

References

Bartling, Sönke, and Sascha Friesike, eds. Opening Science: The Evolving Guide on How the Internet Is Changing Research, Collaboration and Scholarly Publishing. Heidelberg: Springer Open, 2014.

Carse, James P. Finite and Infinite Games. Ballantine Books, 1987.

Dudley, Drew. This Is Day One: A Practical Guide to Leadership That Matters. First edition. New York: Hachette Books, 2018.

Edwards, Marc A., and Siddhartha Roy. “Academic Research in the 21st Century: Maintaining Scientific Integrity in a Climate of Perverse Incentives and Hypercompetition.” Environmental Engineering Science 34, no. 1 (January 2017): 51–61. https://doi.org/10.1089/ees.2016.0223.

Firestein, Stuart. Ignorance: How It Drives Science. New York: Oxford University Press, 2012.

MacIntyre, Alasdair C. After Virtue: A Study in Moral Theory. 2nd ed. Notre Dame, Ind: University of Notre Dame Press, 1984.

Rogers, Carl Ransom. On Becoming a Person: A Therapist’s View of Psychotherapy. Houghton Mifflin Harcourt, 1995.

Sinek, Simon. The Infinite Game. New York: Portfolio/Penguin, 2019.

Finite and infinite game science: what’s the difference?

Infinite gamers have more fun

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

The distinction between playing with an infinite game mindset and playing with a finite game mindset allows us to unpack how a scientist might bring an infinite mindset to “actual science:” to all those finite games of power and scarce resources scientists play today in the academy. This handbook is all about changing cultures in the academy. Some of these changes are steps forward into new opportunities, others are steps back into the core of how science was done before the recent neoconservative managers arrived on campus. Let’s look at two personas: one, a die-hard finite game player, and the other, a scientist deep into the infinite game.

The finite-game player takes on the role of “The Scientist”

Below are some signs you might be playing the infinite game of doing science as if this were a finite game: playing with a finite-game mindset.

  • The role of “The Scientist” is just a role. You are free to throw this aside at any time. You always have this freedom. At some point you forgot this fact.
  • By forgetting you create a necessity to this role in your life: not for science, however, but for being The Scientist.
  • Entering grad school on a fellowship, you identified avenues of influence you could tap into: you picked a famous scholar to be your committee chair and selected a hot research topic, instead of one from your own interests.
  • You had three papers published by the time you completed your PhD. At least one of these used text “borrowed” from a colleague.
  • Your old committee chair had an inside track to a funding agency that you learned about and cultivated as a post-doc.
  • You jumped into an entry tenure-track position at a different university when your first research proposal was funded, taking your funding with you.
  • At annual meetings of your learned society, you work the publisher booths at to find a sympathetic editor at a high-prestige journal.
  • You push your funded research team of grad students, post-docs, and research staff to make discoveries, or hack the data, to fit the needs of the field’s top impact-factor journal.
  • You ignore those students who don’t perform to your demands and self-funded graduate students, who should realize they don’t belong.
    You shift your lab’s research focus in response to the funder’s new five year strategic plan.
  • When you take on peer review assignments, you are particularly harsh on any work that intersects your own but doesn’t cite you, while you soaked up any useful information about their research methods and findings.
    You leverage your funded research to minimize your teaching load, and you weasel the chair into handing over your undergrad survey class to adjuncts.
  • You use the same textbook for your upper division class that you had as an undergrad.
  • You grade easy to avoid hassles with undergrads.
  • Your graduate methods seminar class promotes your own methods, and critiques others.
  • The platform of your early career wins became a launching pad to grab career advantage over your peers. You search for other early-career winners, and avoid those who aren’t.
  • You constantly eye openings for jobs at higher ranked universities. You make sure you schmooze their department heavy-weights at learned society meetings.
  • You worm your way into volunteer leadership jobs at your learned society, hoping to fast-track recognition.
  • You sit on a couple of major campus-wide strategy committees, instead of curricular or other social committees.
  • Your chancellor gives you opportunities to speak at campus events, where you highlight the research findings you’ve maneuvered to be most glamorous.
  • You mold a social media persona around popular science issues.
  • You craft a high H-index by having your grad students write review articles, which you attach your name to as first author.
  • You haven’t done fully original research or used a new methodology in five years.
  • You carefully hoard your lab’s data, and only publish in journals that do not require open data.
  • You evaluate your colleagues as winners or losers, and steer clear of the latter.
  • You talk about meritocracy in the academy, and believe that’s why you got tenure.
  • You laugh off talk of “work-life balance.” Your work is your life.
  • You fit fully into the role of “The Scientist.” As it colonizes your future, the role of “The Scientist” becomes everything you are and ever wanted. But then you realize you haven’t yet been elected a fellow of your learned society. You worry that you haven’t spent enough time cultivating connections society board members.
  • You’ve never reflected on how your need to harvest your accumulated advantage impacted the quality of your science outputs, nor the career costs of the grad-students you’ve abandoned because they didn’t follow your lead. You never stopped to count the dreams you killed along the way.
  • Because you feel you must play The Scientist continually, you are unable to play science as an infinite game. There is no joy in your work. There is a constant fear that your research results will be proven illegitimate.

A few of the the above activities might be pursued as a finite game by a scientist with an infinite mindset (See: Science is an infinite game). Every scientist is confronted by an academy infested by conflicts of interest and internally validated perverse incentives. As open science works to change the culture, scientists must still forge their careers.

For every finite-game science player who “wins,” dozens more need to “lose.” Scarcity in the system demands this. “Losers” have their careers side-tracked at some point. Their dissertations do not result in high-impact journal articles. Their post-doc opportunities (if available) become dead-ends. The funding agency denies their last-chance research proposal. They migrate away from research institutions to other jobs in and out of academia. The enthusiasm and hope they brought with them as students no longer sustains the energy they need to compete in the finite games of science. They go off and do other work. This is one reason why science loses every time finite-game science player wins.

B) The infinite player does science and plays with the role of “The Scientist.”

Freedom of thought is a fundamental academic freedom. Because science is always shared, this first freedom includes freedom of speech. Freedom is central to infinite game play, where boundaries and horizons, rules and roles, histories and futures are all in flux. Freedom of thought is the infinite-minded scientist’s chief weapon against the silence of nature. Like water, science flows against nature and finds the low spots where new knowledge lurks. Freedom interrupts scientific rigor and intention with the serendipitous discovery.

The infinite player is fully aware that a finite academy game she agrees to play carries a role she admits only to others. She is never “The Scientist” even when she plays one. She does science. She wears the white coat. She shares her findings, her data, her methods, her ideas. She teaches classes that open up infinite play to her students. She talks about awe and about doubt, about method and precision, and how doing science is something more than doing anything else; and it is more, because she plays the infinite game. And when her corner of nature’s mysteries remains silent over months and year, she persists. She knows the game will last when she is gone.

There are finite games in which she has zero interest (to the annoyance of her Chair). She sees no point in crafting a “sexy” P-hacked paper for a high-impact journal. At conferences, she spends most of her time on conversation with students at their posters, or with a few colleagues who occupy the same corner of nature as does she. Chancellors and deans fail to recruit her to campus committees. She risks tenure by focusing on her teaching and her idea of research, on her students and their needs, and on the infinite play that fills her mind day and night. If she must leave this university, she will seek out a college somewhere, with the help of her ex-students, and continue to play.

Still, the innovative thrust of her experiments, the transparent rigor of her methods, the quality of her data (which she freely shares) and the unexpected results these reveal keep getting noticed. Despite her inattention to them, her metrics are stellar. Her generosity is widespread, and well known. She simply lets go of the science goods that are most important to her, knowing that others will remember, and send her new ideas to try out. She is a giver, a genius-maker:

“In Multipliers, former Oracle executive Liz Wiseman distinguishes between geniuses and genius makers. Geniuses tend to be takers: to promote their own interests, they ‘drain intelligence, energy, and capability’ from others. Genius makers tend to be givers: they use their intelligence to amplify the smarts and capabilities’ of other people, Wiseman writes, such that ‘lightbulbs go off over people’s heads, ideas flow, and problems get solved’” (Grant, 2013).

She was denied tenure at her university for ignoring many of the hoops through which she was expected to jump; and immediately hired with tenure at a different university, on the weight and the promise of her research, and the stories about her teaching and mentoring, volunteered from her ex-students. She commonly refuses awards and honors; she calls them distractions.

Even the awe and joy of infinite game play can be easily forgotten; scientists can get lost when they play only finite games with scientific methods and organizational power. These finite games pull their logics from other finite games outside of the academy. These logics tear the academy away from the freedoms that science needs to play its infinite game. The more that the academy is trapped into finite games, the less it gains through open sharing and new opportunities for collaboration and innovation.

The Just Cause(s) of Open Science

“In life, unlike chess, the game continues after checkmate” (Isaac Asimov).

Open science exists to return the everyday life of scientists to infinite game play, to find paths to justice, and to support teaching and research opportunities for scientists everywhere on the planet, in any open institution that will house their work. Open science builds academy commons (plural) where scientists can govern themselves and their resources, maintain and care for their goods and each other, provision their work, and build an abundant future for the infinite game of science across the globe.

Playing the infinite game requires and rewards, demands and builds, encourages and exercises practical wisdom inside science. This type of caring, pragmatic wisdom can carry a scientist, a science team, a laboratory, a school, a university, an agency: any all academy organizations, toward open science, where sharing and caring a not reserved for losers. Where there are no winners, only players. And that is the whole point.

References

Grant, Adam M. Give and Take: A Revolutionary Approach to Success. New York, N.Y: Viking, 2013.

Science is an infinite game you can play

You’ve played this game all your life. When did you decide to stop?

“If there are at least two players, a game exists. And there are two kinds of games: finite games and infinite games.
Finite games are played by known players. They have fixed rules. And there is an agreed-upon objective that, when reached, ends the game. Football, for example, is a finite game. The players all wear uniforms and are easily identifiable. There is a set of rules, and referees are there to enforce those rules. All the players have agreed to play by those rules and they accept penalties when they break the rules. Everyone agrees that whichever team has scored more points by the end of the set time period will be declared the winner, the game will end and everyone will go home. In finite games, there is always a beginning, a middle and an end.
“Infinite games, in contrast, are played by known and unknown players. There are no exact or agreed-upon rules. Though there may be conventions or laws that govern how the players conduct themselves, within those broad boundaries, the players can operate however they want. And if they choose to break with convention, they can. The manner in which each player chooses to play is entirely up to them. And they can change how they play the game at any time, for any reason….
Infinite games have infinite time horizons. And because there is no finish line, no practical end to the game, there is no such thing as ‘winning’ an infinite game” (Sinek, 2019).

In Finite and Infinite Games, James Carse (1987) makes a number of statements about culture and nature, and about human endeavors that include a wide range (perhaps very wide) of everyday human situations.

Here we attempt to insert science as an endeavor into the scheme Carse outlined, with the purpose of grounding the norms of science — however these are described — within science’s infinite play with nature. Of course any scientist — as a biological organism — plays in nature at the same time she plays with nature. To play with nature as a profession is a privilege scientists all share. The finite games of finance or technology might bring in more (perhaps a lot more) money, but the struggle with universal unknowns has its own rewards. The infinite game, as we will see, also ties in complexity theories, emergent systems, explanation and narrative.

Today, science is an endeavor housed in organizations where we find game logics that are mainly finite (When is the next RFP coming out? What’s your H-Score?). This circumstance is in direct conflict with research needs that must — this is the main assertion here — include and support playing the infinite game of science.

Norms point to the infinite game

The notion of the infinite game of science may seem foreign to scientists coached to win finite games to secure their careers. And yet all attempts to capture the normative culture of science hint at an underlying, non-finite game. What we find today is an academy trapped in the contradictions between these two mindsets: the poetry of discovery, the awe of nature, the joy of intellection, and the satisfactions of mentoring have been pushed aside, displaced by the rush for reputation in a now-harshly-competitive system of scarce resources and narrow opportunities.

These contradictions have been noted for decades in articles and books that contrast science’s putative norms with the observable organizational practices of science. Sociologists and critics of science practice point to the realities of doing science in today’s world. “Science claims X, but in practice we find Y.” Ziman (2002) makes this contrast more than seventy times. These observations now share the discourse with a chorus of observations about “bad science:” unreproducible findings, plagiarized and repetitive science articles, ersatz statistics (p-hacking, etc.), systemic biases and conflicts of interest in funding and advancement, public distrust of science findings, and a profiteering publishing industry.

The reality of doing science today seems fundamentally out of step with how good science needs to happen. “Real science” is still distinguished by normative behaviors and values that are regularly called upon to counter deviation into “bad science” (See: Zimring 2019 <https://blogs.scientificamerican.com/observations/were-incentivizing-bad-science/> Retrieved November 8, 2019). But when the incentives are perverse and pervasive, resistance is a challenge that overlays and undermines the challenges of doing infinite-game science. So, what happens when the reality of being a scientist fails to support “real science”?

Doing the right science or doing science right?

“When you rely on incentives, you undermine virtues. Then when you discover that you actually need people who want to do the right thing, those people don’t exist because you’ve crushed anyone’s desire to do the right thing with all these incentives” (Barry Schwartz in Zetter, 2009 <https://www.wired.com/2009/02/ted-barry-schwa/> Retrieved 12/16/19).

Much of the “How” science is played as an infinite game is discussed within the philosophy of science, and the “What” of science fills books in the sociology of science. The infinite game of science explores the “Why” and the also the “just causes” (Sinek, 2019) of science. The “Why” brings us a narrative of science up until this moment, which illuminates its horizon. Science’s just causes point us at the thousands of mysteries, the unknowns that scientists confront today; each mystery offers a bit of new knowledge to be discovered, and the benefits of new understanding. Every unknown also carries a moral load, and the need for judgement in pursuit of justice (more about this below), given that there are many consequences to new knowledge.

Mindsets and practices

Finite and Infinite Games goes into great detail to expose the two mindsets: finite and infinite. These are fundamentally different, and in ways that illuminate many of the issues plaguing the academy today. Here we note only a few key points. First, finite players (players with a finite mindset) play their roles in full seriousness, acquiring their parts as actual and necessary: even when they are always fully free to step out of their parts. They need to forget this freedom in order to play to win. This is really important to keep in mind: finite game players assume their roles as essential parts of who they are, even though they always have the freedom to abandon their role. This mindset lards the role of “scientist” with unnecessary seriousness.

On the other hand, players in an infinite game play with the rules, instead of assuming roles. These rules are constantly changing as players move the boundaries of the game. Infinite games are rule-creating games. The players do not need to accept a set of rules to play. Without stable rules, roles make no sense. Best practices do not apply. Every new experiment opens up its own horizon. In terms of complexity theory, the infinite game demands that you probe, sense and respond (Laloux, 2014, Kurtz and Snowden, 2003) each time you play.

When an infinite player (someone with an infinite mindset) plays a finite game within the infinite game, they do so fully understanding they are simply acting their role, and that they have the freedom to walk away. Yet they still have the capacity to play any finite game to its limit. They can accept the rules in order to play. However, winning or losing has no meaning for them. This may mean they play with greater freedom and abandon, improving their chance of winning.

To remind scientists that their research is an infinite game is to reconnect them to the “one long experiment” (Martin, 1998) that is science. Recent organizational management theories (Sinek, 2019) have put infinite game play and sense-making for complexity (Snowden, 2002; Kurtz and Snowden, 2003; Ito and Howe, 2016) at the center of their recommendations for 21st Century organizational governance. Getting good in the infinite game of science could also build skills that scientists can use to govern their labs, universities, and agencies.

This handbook will help you create new practices that can recenter your university’s values and vision around infinite game play as a strategy for long-term success. Open science is a cultural platform that will connect infinite game players across the globe. You and your organization can join this, or you can continue to play the same bullshit “excellence” games (Moore, et al, 2017; also Neylon[Retrieved Feb. 7, 2020]) you take far too seriously today. And have more fun in your research too.

Science is a war with one long battle

Science, the infinite game, was there with Aristotle and Plato, Bacon and Galileo. With Neuton and Boyle, Einstein and Feynman. And now here, this very moment, with every scientist in and out of the academy. The infinite game of science lies beneath the norms that Merton and others have used to delineate science’s core ethos. The infinite game stands behind every experimental hypothesis and laboratory method. Every time a scientist battles with some mystery of nature, the infinite game continues.

Science works toward horizons and not within boundaries. Scientists see boundaries around them and laugh as they violate these. They go beyond. Any scientist can change the horizon of science and modify the rules of science (for example, by improving a method of observation). Each change in the horizon of science changes the horizon of every scientist.

“The scientist has a lot of experience with ignorance and doubt and uncertainty, and this experience is of very great importance, I think. When a scientist doesn’t know the answer to a problem, he is ignorant. When he has a hunch as to what the result is, he is uncertain. And when he is pretty darn sure of what the result is going to be, he is in some doubt” (Feynman, et al, 2005).

The scientist eats unknowns, and is never full. She sweats doubt. The products of science are not science. These can be destroyed or forgotten and science will continue. Science means challenging the known. Scientists understand how little science knows; that the mysteries they face are mighty. Each scientist picks her own mystery, her own just cause to pursue.

“The earth’s history has been only long experiment, poorly constrained in a reductionist’s eyes. How impoverished the earth would be if had been otherwise” (Martin, 1998).

Science is nature made into poetry

No single scientist speaks for science. No scientist speaks for nature. The speech given by the award winner at the annual convention is not any more scientific than the poster presented by the graduate student. The questions of a student can negate an entire history of discovery.

Unlike the history of society where politics is theatrical and works to close its history (against culture, which keeps this open), the history of science is always dramatic. It is formed by events that must repeat themselves again and again while remaining open to failure, open to a moving horizon that might, and probably will, change and render them false. After that, they join the past history of science and are merely theatrical. One can repeat a failed experiment only as historical theater. The science present moves on in dramatic fashion.

The goods of science inform the knowledge inventory of the world within which science is played. They push science to remake its horizons. They are not unimportant to science but they are not science in the infinite game. Finite-science players want to own these products, in order to garland themselves with prizes. Prized science goods require durability for the value of their prizes to endure. Finite-science players choose to defend their own goods by silencing others and gathering supporters. They seek a past that is closed and known, with their own goods at its front end.

“One must keep in mind that senior faculty probably hold their current positions through their success in the game, which may or may not have been achieved by using the most ethical ways” (Chapman C.A., et al, 2019).

Infinite science players — who know their own research best — interrogate their own findings in search of a larger knowledge horizon. They push the game forward and their egos to the side. They open up to collaborations and seek out conversations with those who disagree with their findings.

Prizes bind science to a known past. This past is carried by science institutions, such as those learned societies that sponsor prizes. These societies also need to endure so that the prizes of finite-science players retain their value. Prize winners and “fellows” carry the weight if ensuring the society persists, warranting the currency of their prizes. However, the continuity of science is not based on an attachment to its past or even it current goods — on the closing of its history — but rather, on a continual openness to surprise, to experiment (Schulz, 2011). Science is based on the nearly universal ephemerality of its findings. Science has always been the child of an open history that will never close.

“[W]hat resounds most deeply in the life of Copernicus is the journey that made knowledge possible and not the knowledge that made the journey successful” (Carse).

Science doesn’t just have a culture. Science also is culture (in Carse’s sense). Like any culture, science is “itself a poiesis, all of its participants are poietai — inventors, makers, artists, storytellers, mythologists. They are not, however, makers of actualities, but makers of possibilities. The creativity of [science] has no outcome, no conclusion” (Carse; paraphrase).

Scientists are ImagiNatives. Poets of the natural world. Makers of possibilities. “It’s been said that science fiction and fantasy are two different things: science fiction, the improbable made possible; fantasy, the impossible made probable” (Rod Serling,“The Fugitive”. The Twilight Zone. Season 3. Episode 25. March 9, 1962. CBS.) Science is nature made into poetry.

“The physicist who sees speaks physics with us, inviting us to see that the things we thought were there are not things at all. By learning new limitations from such a person, we learn not only what to look for with them but also how to see the way we use limitations. A physics so taught becomes poiesis” (Carse).

You cannot do science alone in isolation; do science only in your own mind. This does not mean that you cannot be solitary in your imagination, but only that science happens when you share this with at least one other person. A poet who does not speak has no poetry to speak of. Science happens between and among infinite game players.

The infinite play of science allows no personal power or authority. In a finite game, power always requires opposition and an audience. Neither is available within science. In finite games, winning silences the loser. The personal power that a title conveys; this authority means nothing to science, and usually far too much for scientists. Competition feeds arbitrary power in the academy and defeats science itself, silencing the many to praise the few.

Finite games of prestige in the academy are failings of the academy. Finite games of personal influence and authority contradict the inherent authority of science methods. Scientists are known by their names, not their titles. If your method is transparent and well-founded, your science goods need no amplification beyond their public sharing. The audience that power seeks is not found in science. An infinite game allows no audience. There is no vote that can elevate one science good above another.

Science does not belong to any one society. Science flows across the globe. Change for science has no location, it is always everywhere. Change is always surprising, and so never a surprise. “To be prepared against surprise is to be trained. To be prepared for surprise is to be educated” (Carse). To invite and welcome surprise is to do science. Science creates its activities through fluid consensus, not from any established doctrine, but in response to surprises that happen whenever science moves its horizon.

“[As it is in nature, so] also in [science]. Infinite players understand that the vigor of [science] has to do with the variety of its sources, the differences within itself. The unique and the surprising are not suppressed in some persons for the strength of others. The genius in you stimulates the genius in me” (paraphrase: Carse).

Every science effort begins and ends in surprise. Because the next instant of knowing is always open, the moment of discovery is always surprising. This is a source of joy for the scientist. If the object of research were already known or fully predictable, the research is unnecessary. Reproducibility means that the same effort must result in the same surprise. The first effort exposes the scientist to this surprise. The second time gifts this surprise to science.

In the infinite game, science invests more authority on the rigor of its methods than it does in the sagacity of its practitioners. The results of well-constructed experiments are all discoveries, even when the results are null. Each experiment extends the horizon of the game.

Who wants yesterday’s findings?

The final page of science will never be written. A new finding is lightly penciled in after the previous paragraph on the current page. Every infinite player brings their own eraser to this book. Chapters long settled and well considered can be erased in a single day. That is a joy for science. New pages open up then. New horizons emerge. The game accelerates. More players find ways to add new paragraphs to this ledger. Ever since Bacon, yesterday’s findings hold less knowledge than tomorrow’s.

Scientific surprise is mainly retold as serendipity. Serendipity, the unexpected confluence of curiosity and sagacity, is just another way of announcing that scientists are playing the infinite game.

“The paradox in our relation to nature is that the more deeply [science] respects the indifference of nature, the more creatively it will call upon its own spontaneity in response. The more clearly we remind ourselves that we can have no unnatural influence on nature, the more our [science] will embody a freedom to embrace surprise and unpredictability” (paraphrase) Carse.

What is real science again?

“The notion that academic scientists have to be humble and disinterested… seems to contradict all our impressions of the research world. Scientists are usually passionate advocates of their own ideas, and often extremely vain” (Ziman, 2002).

We have all read studies and stories of “actual” science that highlight how scientists live and work in the “real world.” Today, scientists labor within the pragmatic circumstances of the increasingly neo-liberal academy — surrounded by an increasingly neo-liberal global economy: a world of intense competition for fame and funding, a space of accumulated advantages for a few, and increasing precarity for the rest. Yet the moments of science, the methodic but often serendipitous event of discovery, yank the scientist back into a different “real” — the real task of uncovering new knowledge about the actual “real world” — the natural universe. To do science is to play an infinite game with nature.

References

Carse, James P. Finite and Infinite Games. Ballantine Books, 1987.

Chapman, Colin A., Júlio César Bicca-Marques, Sébastien Calvignac-Spencer, Pengfei Fan, Peter J. Fashing, Jan Gogarten, Songtao Guo, et al. “Games Academics Play and Their Consequences: How Authorship, h -Index and Journal Impact Factors Are Shaping the Future of Academia.” Proceedings of the Royal Society B: Biological Sciences 286, no. 1916 (December 4, 2019): 20192047. https://doi.org/10.1098/rspb.2019.2047.

Feynman, R.P., J. Robbins, H. Sturman, and A. Löhnberg,. The Pleasure of Finding Things Out. Nieuw Amsterdam, 2005.

Ito, Joi, and Jeff Howe. Whiplash: How to Survive Our Faster Future. Grand Central Publishing, 2016.

Kurtz, Cynthia F, and David J Snowden. “The New Dynamics of Strategy: Sense-Making in a Complex and Complicated World.” IBM Systems Journal 42, no. 3 (2003): 462–483.

Laloux, Frederic. Reinventing Organizations: A Guide to Creating Organizations Inspired by the next Stage in Human Consciousness. Nelson Parker, 2014.

Martin, Ronald E. One Long Experiment: Scale and Process in Earth History. Columbia University Press, 1998.

Moore, S., C. Neylon, M.P. Eve, D.P. O’Donnell, and D Pattinson. “‘Excellence R Us’: University Research and the Fetishisation of Excellence.” Palgrave Communications 3 (2017): 16105.

Schulz, Kathryn. Being wrong: Adventures in the margin of error. Granta Books, 2011.

Sinek, Simon. The Infinite Game. New York: Portfolio/Penguin, 2019.

Snowden, David. “Complex Acts of Knowing: Paradox and Descriptive Self-Awareness.” Journal of Knowledge Management 6, no. 2 (2002): 100–111.

Ziman, John. Real Science: What It Is and What It Means. Cambridge University Press, 2002.

The practical wisdom in doing science

Science calls for wisdom in the face of wicked problems

“If you compromise your integrity and principles on minor issues, it gets easier to make bad choices on the big issues” (Dunwoody and Collins, 2015).

“Do the right thing. It will gratify some people and astonish the rest” (Mark Twain, attrib.).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

The current research on “wisdom” defines this in approximately as many ways as there are wisdom researchers (Sternberg, 1990). Fortunately, we do not need to lock down a definition of wisdom here to see its lack in the academy, and the benefits of promoting this as one more measure of what it means to do science and to be a scientist today. Most of the research on practical wisdom confirms what you already think about this. People who are wise in this way know how and when to do the right thing in a broad range of circumstances.

It’s not all that simple, of course. Doing the right thing is not merely “being right,” and most certainly is not thinking you’re right, and convincing everyone else how wrong they are. Practical wisdom operates in the infinite game of open, complex intellectual and normative choices, and conflicting and ambiguous circumstances.

The “right thing” is rarely an easy binary operation and it often requires insights and emotional commitments beyond a simple logic. It may also be an action that goes against the immediate best interests of others or the wise person. “[M]any who have written on wisdom have identified it with the ability to develop and defend good judgments about the difficult, wicked-decision problems characteristic of adult life” (Kitchener and Brenner, 1990).

Mostly, practical wisdom examples involve interpersonal or socioeconomic decisions. These examples map how individuals wend their life together with others and the world. This part of practical wisdom encompasses careers in and out of the academy. You can explore the more general forms of practical wisdom literature elsewhere (Practical wisdom: The right way to do the right thing by Schwartz and Sharpe (2010) is a good place to start, also Barry Schwartz’s TED talk [Retrieved January 7, 2020] or his WIRED interview). So, what forms of practical wisdom are peculiar to doing science?

In finite games, where arbitrary scarcity and external incentives warp the moral fabric of interaction, practical wisdom often gives way to self-promotion strategies. Somebody has to lose. Actually, most people need to lose in order for winning to matter. In the infinite game of science, nobody wins or loses, and the main strategies include sharing knowledge and adding new players to the mix. Science loads additional wicked-problem solving on top of the adult life problems of work and home. Wise researchers confront the silent unknowns of a complex and emergent natural world.

The ability to start from observations and data about the world and transform these into information, knowledge, and understanding is an inherently moral activity; each bit of new knowledge — big or small — changes existing rules for every scientist and expands the envelope of possible human action. Medical science practice is often cited as a key discipline in need of practical wisdom because of its everyday moral decision making (See: Branch and Mitchell, 2011; Kaldjian, 2010; and Jeste, et al, 2019). All science domains are similarly implicated when they enter into infinite game play.

How does practical wisdom improve research?

Judith Glück (2017) makes a case for practical wisdom in the academy. The first behavior is a desire for a deep understanding of complex emergent systems, instead of a personal claim about some potentially universal truth. This is precisely the difference between playing the infinite game of science, and playing a finite zero-sum game. “Over time, wise researchers’ desire to thoroughly understand should lead them to develop an extraordinary amount of knowledge: a broad and deep integrative understanding of a subject matter that includes a keen awareness of what they do not (and may never) know” (ibid). In short, they become intellectually humble.

“[Humble intelligence is] a method of thinking. It’s about entertaining the possibility that you may be wrong and being open to learning from the experience of others. Intellectual humility is about being actively curious about your blind spots. One illustration is in the ideal of the scientific method, where a scientist actively works against her own hypothesis, attempting to rule out any other alternative explanations for a phenomenon before settling on a conclusion. It’s about asking: What am I missing here?” (Resnick, 2019 <https://www.vox.com/science-and-health/2019/1/4/17989224/intellectual-humility-explained-psychology-replication> Retrieved June 7, 2019).

Practical wisdom in the academy is built upon the humble intelligence of each scientist. As science becomes more collaborative, networking and teamwork bring new demands on the practical wisdom of every member. As we first learned in Ten activities to work on, Tangney (2000) proposes that intellectual humility requires five abilities:

A. the ability to acknowledge mistakes and shortcomings;

B. openness to perspective and change;

C. an accurate view of the self’s strengths;

D. ability to acknowledge and experience life outside the direct consciousness of the self; and,

E. the ability to appreciate the worth of all things.

Each of these abilities adds value to any academy collaboration effort. Open science captures this value by promoting equality of access and networked collaborative opportunities.

The greater good

The second wise-researcher behavior is a high level of concern and care for the “greater good”: for the welfare of the entire “Republic of Science” (Polanyi, 1962), of the next generation of scientists, and of the planet:

“Wise researchers will be concerned with the well-being of others, ranging from their students to the world at large. Inside the university, wise researchers will care about the quality of their teaching. … Wise researchers are also caring, generative mentors who seriously work on supporting the career development of their mentees and genuinely enjoy their success”(Glück, 2017).

The care that wise researchers bring to their science reflects their ability to set their own ego aside. Many of the distinctions between practical wisdom and general intellectual accomplishment pivot on this attention to the greater good: to the underlying reasons, the overarching effects, the larger, messier, more complex consequences of new knowledge.

Open-access science publishing can support the wise researcher looking to share their whole research in exchange for access to the research of their colleagues. New evaluation tools that reward ethical behaviors and a much greater variety of goals and social activities would support the efforts of those with a recognized concern for the welfare of their mentees and for the research success of others. Assessment tools that capture a diverse and incremental landscape of work outputs and socially-supportive activities are already being developed in the workplace outside the academy (See: Buckingham and Goodall, 2019).

Practical wisdom is also an antidote to assholes in the academy. The Handbook deals with assholes elsewhere (See: The Need for a Zero-Asshole Zone). Most wisdom research concludes that you cannot have practical wisdom and also be an asshole or evil (See: Stanford Encyclopedia of Philosophy: Wisdom, 2002). In part, this is because you cannot have practical wisdom without actually using your practical wisdom. As noted elsewhere in the Handbook, much of the assholic behavior in the academy is learned and rewarded today; and so, most academy assholes are not irredeemable. They learn and use bad behavior to win the finite games currently infecting the academy. They can unlearn these behaviors and gain some practical wisdom over time. Some, however, are true assholes, and will not change (See: The bright and the dark). These will resent and resist change when your new open-science cultural practices no longer support their bad behavior.

How do we build the practices of humble intelligence and a care for the greater good into the academy? Such is the project of this Handbook, a guide to changing culture in your precinct of the academy, wherever this is. Open science builds fierce equality into the academy as a normative behavior that expresses intellectual humility and inclusiveness. In the infinite game of science new knowledge can be found by anyone in the Republic of Science. Open science uses demand sharing to support the greater good. As a sharing economy, the academy’s goods gain value across time and space. Science is the hardest thing you can do (after child rearing). Take a minute to remember how challenging science really is. Doing science really well will change you as a person, even as you change the world of science through your efforts.

The starting point for culture change is, as always, changing yourself. Apart from a few dark-core types, everyone can gain practical wisdom, even tenured faculty. Start today. Be wiser tomorrow.

Wisdom learning starts in childhood, but need not end there

Some researchers point out that a fair amount of practical wisdom is learned throughout childhood, mostly during play (See: Feist, 2006; Brown, 2009; Carlson and White, 2013; and Sharma and Dewangan, 2017). If you are no longer a child as you read this, do not worry, you can still catch up. To begin with, play is always available even for adults (See: <https://eachother.org.uk/the-right-to-play-adults/> Retrieved January 5, 2020).

While the “skills” of practical wisdom — and wisdom in general — cannot be gained through the same type of specific practice as, say, a violin, or a golf swing, practical wisdom is similarly experience-based (Cantrell and Sharpe, 2016). Like most cultural practices, you can get better at practical wisdom through practice, it is not an inherent trait. You are not born with all the wisdom you can have nor what you might really need to use for your career in the academy.

Glück and Bluck (2103) demonstrate a model for acquiring personal wisdom based on a “strong sense of mastery, high levels of openness, a reflective attitude, and emotion regulation skills combined with empathy.” This “MORE” model can be used in “leadership” curriculum development at the undergraduate level (Sharma and Dewangan, 2017). The Phronesis Project [Retrieved January 8, 2020] at the University of Virginia School of Medicine is pioneering practical wisdom training in its curriculum. Just remember that you can also have fun while becoming wiser, you enjoy learning, after all, so learning practical wisdom is an opportunity to master another life skill:

“Another value of science is the fun called intellectual enjoyment which some people get from reading and learning and thinking about it, and which others get from working in it” (Feynman, et al, 2005).

Schwartz and Sharpe (2010) find that institutions that manage behaviors through rigid rules or laws crowd out opportunities for members to gain wisdom from self-governed interactions. “[I]t’s important to resist those rules and incentives that eviscerate discretion and threaten wisdom. That’s why we need to reform those institutions that are driving wisdom out.” It could be that your institutions would benefit from more democracy and healthy arguments, and fewer rules. The Handbook sections on Learning Organizations are a good place to start.

References

Branch Jr, William T, and Gary A Mitchell. “Wisdom in Medicine.” Pharos Alpha Omega Alpha Honor Med Soc 74 (2011): 12–17.

Brown, Stuart L. Play: How It Shapes the Brain, Opens the Imagination, and Invigorates the Soul. Penguin, 2009.

Buckingham, Marcus, and Ashley Goodall. Nine Lies about Work: A Freethinking Leader’s Guide to the Real World. Boston, Massachusetts: Harvard Business Review Press, 2019.

Cantrell, Deborah J, and Kenneth Sharpe. “Practicing Practical Wisdom.” Mercer L. Rev. 67 (2015): 331.

Carlson, Stephanie M, and Rachel E White. “Executive Function, Pretend Play, and Imagination.” The Oxford Handbook of the Development of Imagination, 2013, 161–174.

Dunwoody, Ann, and Tomago Collins. A Higher Standard: Leadership Strategies from America’s First Female Four-Star General. First Da Dapo Press edition. Boston, MA: Da Capo Lifelong, a member of the Perseus Books Group, 2015.

Feist, Gregory J. The Psychology of Science and the Origins of the Scientific Mind. New Haven: Yale University Press, 2006.

Feynman, R.P., J. Robbins, H. Sturman, and A. Löhnberg,. The Pleasure of Finding Things Out. Nieuw Amsterdam, 2005.

Glück, Judith. “… and the Wisdom to Know the Difference: Scholarly Success From a Wisdom Perspective.” Perspectives on Psychological Science 12, no. 6 (November 2017): 1148–52. https://doi.org/10.1177/1745691617727528.

Glück, Judith, and Susan Bluck. “The MORE Life Experience Model: A Theory of the Development of Personal Wisdom.” In The Scientific Study of Personal Wisdom, 75–97. Springer, 2013.

Jeste, Dilip V., Ellen E. Lee, Charles Cassidy, Rachel Caspari, Pascal Gagneux, Danielle Glorioso, Bruce L. Miller, et al. “The New Science of Practical Wisdom.” Perspectives in Biology and Medicine 62, no. 2 (2019): 216–36. https://doi.org/10.1353/pbm.2019.0011.

Kaldjian, L. C. “Teaching Practical Wisdom in Medicine through Clinical Judgement, Goals of Care, and Ethical Reasoning.” Journal of Medical Ethics 36, no. 9 (September 1, 2010): 558–62. https://doi.org/10.1136/jme.2009.035295.

Kitchener, Karen Strohm, and Helene G Brenner. “Wisdom and Reflective Judgment: Knowing in the Face of Uncertainty.” Wisdom: Its Nature, Origins, and Development, 1990, 212.

Polanyi, M. “The Republic of Science: Its Political and Economic Theory.” Minerva 1 (1962): 54–73.

Schwartz, Barry, and Kenneth Sharpe. Practical Wisdom: The Right Way to Do the Right Thing. Penguin, 2010.

Sharma, Ankita, and Roshan Lal Dewangan. “Can Wisdom Be Fostered: Time to Test the Model of Wisdom.” Edited by Feng Kong. Cogent Psychology 4, no. 1 (September 21, 2017). https://doi.org/10.1080/23311908.2017.1381456.

Sternberg, Robert J. Wisdom: Its Nature, Origins, and Development. Cambridge University Press, 1990.

Tangney, June Price. “Humility: Theoretical Perspectives, Empirical Findings and Directions for Future Research.” Journal of Social and Clinical Psychology 19, no. 1 (2000): 70–82.

Kindness, Culture, and Caring: The Open Science Way

Time for dignity and fairness: and the value of caring. Artwork by Kelvy Bird: https://www.kelvybird.com/

“So it’s kind of like if your house catches on fire. The bad news is there is no fire brigade. The good news is random people apparate from nowhere, put out the fire and leave without expecting payment or praise. …I was trying to think of the right model to describe this form of random acts of kindness by geeky strangers. …You know, it’s just like the hail goes out and people are ready to help. And it turns out this model is everywhere, once you start looking for it.” Jonathan Zittrain, Ted Talk 2009 <https://www.ted.com/talks/jonathan_zittrain_the_web_is_a_random_act_of_kindness?>

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon. All comments are welcome! Revised from a talk at the ESIP 2019 Summer Meeting. With travel support from the Alfred P. Sloan Foundation. Arigatou!

There are lots of ways that the rational, logical, hyper-competitive, winner-take-all, zero-sum, prisoner’s dilemma, nice-guys-finish-last, single-bottom-line, annual-productivity ratchet — or add your adjective here — mindset is just wrong for sustaining the academy and bad for science. For decades now, the same neo-liberal economic schemes that have been used to reshape how governments budget their funds have also made dramatic and disturbing inroads into university budgets and governance. Open science can show how that trend is a race to the bottom for universities. What do you say, we turn around and go another way?

“I have learnt silence from the talkative, tolerance from the intolerant and kindness from the unkind.” Khalil Ghibran, Sand and Foam.

A century without kindness: the impact of external logics

The banishment of kindness as a necessary part of being an academic, — just one more feature of adopting the neoliberal marketplace logic, and another effect of hyper-masculinity in the workplace — allows academics to defer judgements about kindness:

“We want to argue, however, that although kindness is a commonplace in pedagogical encounters, easily recognisable by its presence or absence, attending to it can be subversive of neo-liberal assumptions that place value on utility and cost above other human values” (Clegg and Rowland, 2010).

The word for kindness in Latin is humanitas: kindness makes us human. “[T]he Roman Emperor Marcus Aurelius, a leading Stoic philosopher, speaks of kindness as ‘mankind’s [sic] greatest delight’ (Phillips and Taylor 2009, 18). In Aristotle’s teachings, kindness is a component of phronesis: an entire type of “practical wisdom” that we’ve slowly devalued over the past 300 years (Juarrero, 1999) [ and you can blame Hume and Kant and all the usual suspects for this]. Phronesis combines virtue with a notion of adult comprehension: a way of knowing the right thing to do in all circumstances. It has little to do with intellection, and everything to do with broad experience and learning.

The road to a doctorate is long and difficult, and so adding another layer of learning to the process might seem short-sighted. And yet avoiding learning phronesis in your daily life is probably not any easier than practicing this, since the absence of phronesis leads to serial mistakes in moral and practical judgement, any one of which can be “career defining” in a negative sense. “Practical wisdom” is integral to “doing the right thing” while you learn to “do the thing right.” Doing the right thing often includes knowing how to exercise kindness with others.

A child can show kindness, and we welcome this. An adult (one who has learned some phronesis) can act kinder than a child, because this adult is experienced in a broader range of social circumstances and personal relationships. An adult can be — to use the Yiddish — a mensch. And a mensch can be kinder than a non-mensch or a proto-mensch. Lesson: be an open science mensch.

Kindness starts with intention

Real kindness begins with a clear intention. This adds an important aspect of self-judgement to its base. Without this aspect you cannot actually be kind, even if others might interpret what you are doing as being kind. How do you actually judge your intentions, particularly in relationships with other people and things? Something to contemplate. Also note: Clegg and Rowland (2010) remind us that kindness is not equated with leniency or “being nice.” Real kindness uses courage to articulate accurate observations and open learning moments that can be difficult and painful for both parties.

Kindness is something you learn and do

Kindness is a normative human practice in a wide range of social frames: parenting, friendship, governance, teaching, caregiving, civil interactions. Zittrain (above) reminds us that the internet was built on kindness and generosity. In nearly every human social endeavor, kindness matters. Even in highly-competitive sporting events, “sportsmanship” is highly valued, and is actually an internal normative form of kindness. Why should kindness, and critical interrogations about its role, be absent from research and management in the academy?

Like rationality, kindness is a form of practice, not an emotion. You can no more “feel” kind than you can “feel” rational. Unlike rationality, kindness necessarily involves others, their perspectives and needs. Kindness can and will also be judged by others for its qualities. Is it genuine? Is it motivated by a need to be perceived as kind? Is it effective in performing its intention? What is its intention? In the academy where intellectual judgements run wide and deep, kindness opens up another opportunity to be judged. But so does being unkind. Or it should. For decades, the lack of kindness in our research institutions and workplaces has gone unremarked. It is time to remark these.

Culture provides meaning to intentions

Again, kindness begins with intention. The same activity with different intentions can be a kind, caring conversation, or it can be a cruel interrogation. Intentions are themselves colored by culture. Culture provides a layer of shared meaning/learning that helps the individual (both the intend-er and the intend-ee) discover and interpret shared meaning as intended. You and the other person can answer the question: what did you mean?

The social world always contains this layer of culture. There is no society without it. Individuals hold this layer as a shared/learned resource. The cultural values (See: Values, freedoms and principles) you bring to your open science organization can assemble the meanings that add clear intentions to shared kindness. Just as some institutional cultures today — and inside the academy — support bullying and demeaning actions (NAS et al, 2018).

One feature of kindness is that it enables both halves of the double meaning of the term “care.” To really care about someone or something, you need to tap into genuine kindness. To care for someone or something can merely be a job. But this job is also reduced without the impulse of kindness. That is why it is time to…

Put care back in your career.

“[B]y infusing bureaucratic maintenance work with an ethic of care, we can challenge contemporary workplace attitudes surrounding “productivity” and “efficiency,” moving toward the recognition of maintenance itself as a valued contribution. We can also broaden access to systems of information, thereby supporting its generative value…” (Maintainers et al, 2019).

The Maintainers <http://themaintainers.org/> extend an ethic of care to each other and to their work: they keep everything running, instead of inventing new stuff. This ethic is born in kindness, and requires a level of humility not casually found in the academy, where intellectual heroics overshadow moral choices.

Nel Noddings, who is a “care theorist,” someone who makes “the caring relation basic in moral theory” (2003), looks to recenter care as a normative behavior in education and the academy. She also separates the care that is expected in work (for example, doing something really well, or managing the needs of a student/patient) as a conformity to a workplace ethic, from caring: human acts “done out of love and natural inclination” (Noddings, 1988). What really works — in teaching and learning, and in team dynamics for collaborative research — is not completing the task of due-diligence, but rather building a framework of mutual caring nurtured from authentic kindness.

Bringing care into this discussion has now moved us away from communities, cohorts, and institutions. Care directs us back to intentions that are articulated in culture, but which also speak to being human in a mutually responsible human environment: a phrase not usually descriptive of the academy. “[W]e are led to redefine responsibility as response-ability, the ability to respond positively to others and not just to fulfill assigned duties” (ibid).

Open science is also science done through care and kindness: science that much more resembles the model of peer production within a commons, than it does a winner-take-all corporate struggle. “[W]ithout receiving conventional, tangible payments or favors in return, peers exercise kindness, benevolence, charity and generosity” (Benkler and Nissenbaum, 2006). Open science demands new levels of response-abilities: based on new and expanded academic freedoms (See: Values, freedoms and principles) and internet-enabled collaborations.

Coda: There are a lot more articles and books (such as Phillips and Taylor (2009): On Kindness) about the history of kindness and care that point out how these virtues were heralded as the basis of human happiness for centuries, and only recently (last 3–400 years) have these been eclipsed by more individualistic moral models (thanks to Hobbes, Kant, etc. — the usual suspects). So… practicing open science may also be good for your happiness. Doing open science can improve your happiness, and the happiness of those around you. How about that?

References

Benkler, Yochai, and Helen Nissenbaum. “Commons-Based Peer Production and Virtue.” Journal of Political Philosophy 14, no. 4 (2006): 394–419.
Clegg, S., and S. Rowland. “Kindness in pedagogical practice and academic life.” British Journal of Sociology of Education 31, no. 6 (2010): 719–735.
Juarrero, Alicia. Dynamics in Action. Cambridge, Ma: MIT Press, 1999.
National Academies of Sciences, Engineering, and Medicine, NAS Committee on the Impacts of Sexual Harassment in Academia, Committee on Women in Science, Engineering, and Medicine, and Policy and Global Affairs. Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine. Edited by Paula A. Johnson, Sheila E. Widnall, and Frazier F. Benya. Washington, D.C.: National Academies Press, 2018. https://doi.org/10.17226/24994.
Noddings, Nel. “An Ethic of Caring and Its Implications for Instructional Arrangements.” American Journal of Education 96, no. 2 (1988): 215–230.
— — — . Happiness and Education. Cambridge University Press, 2003.
Phillips, Adam, and Barbara Taylor. On Kindness. 1st American ed. New York: Farrar, Straus and Giroux, 2009.

10 things every open-science culture-change agent needs to know about.

Here are the 10 things you need to know about to be an open-science culture-change agent. Pick the ones you want to challenge yourself to master.

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon.

Sharing starts everything Photo: Steve Jurvetson on Flickr.

1. Open science culture starts with the logic of demand sharing:

This is the same logic used to teach science in classrooms: knowledge gains value when it is shared. The more it is shared the more it is worth; the faster it is shared the greater its impact; the wider it is shared the better the chance that someone else will improve upon it, and share this improvement back with you.

2. Intellectual humility is integral to open science:

“The humility of scientific genius is not simply culturally appropriate but results from the realization that scientific advance involves the collaboration of past and present generations” (Merton, 1973).

Here are some aspects of humility and reasons why this is a great fit with open science, and a powerful agent against bullshit prestige (Moore, et al, 2017) and narcissism (Lemaitre, 2015) in the academy. Tangney (2000) constructed a working definition of humility, one that is not simply philosophical, but also informed by social and interpersonal circumstances. This definition rejects humility as a psychological weakness, instead, humility demonstrates a range of abilities highly valuable in the conduct of science. According to Tangney, humility has five elements:

A. the ability to acknowledge mistakes and shortcomings;
B. openness to perspective and change;
C. an accurate view of the self’s strengths;
D. ability to acknowledge and experience life outside the direct consciousness of the self; and,
E. the ability to appreciate the worth of all things.

As an open scientist (or just someone who wants to do science really well), you might consider how to develop all of these capabilities. You acknowledge your mistakes in order to learn new facts; you broaden your perspectives on your topic to achieve a wider level of understanding; you evaluate your own skills to discover where you must improve your methods; you journey into the unknowns in your field to stretch the envelope of our knowledge; and you reserve judgement on the work of others long enough to fully grasp their meanings. You also give others more attention and respect. This does not mean you respect yourself any less. You just learn to step around your ego to see others and their work as more valuable. Recent research has found that intellectually humble individuals may acquire new knowledge better than others (Krumrei-Mancuso, et al, 2019). Also note: “only humility can navigate complexity” (Fred Kofman <http://www.youtube.com/watch?v=80vYx7ufzZI&feature=relmfu> Retrieved September 14, 2019).

Humility helps you learn. Humility enables your research. You are a scientist: you have the freedom to be humble about it. It’s not modesty. Nobody is asking you to be modest. Think of it more as “hum-ability”.

In Aikido, humility becomes hum-ability. Open science is the same.

3. Intentional kindness is the platform for open science culture:

“The power of happiness, kindness and humility in the competitive academic environment is underrated, but I firmly believe that they are a force for change for the good of scientific practice. In my opinion, widespread application of these principles could vastly improve the quality of life of scientists and university professors worldwide” (Maestre 2018).

Kindness in open science (end elsewhere) begins with intention. Intentions are themselves colored by culture. Culture provides a layer of shared meaning/learning that helps us discover and interpret and map shared meaning as intended. The same conversation with different intentions can be a kind, caring dialogue, or it can be a cruel interrogation. The cultural values (See: Values, freedoms and principles) you bring to your open science organization can assemble the meanings that add clear intentions to acts of kindness, and to the generosity that all science requires. Just as some institutional cultures today — and inside the academy — support bullying and demeaning actions (NAS et al, 2018). Note: kindness does not mean weakness.

Shared kindness is a platform that lifts open science up to new potentials for sharing knowledge. In the academy, kindness is a radical form of courage. Everyone here is smart. If you want to truly distinguish yourself: be kind.

Kindness flows from a concern for the whole science community and the planet, not just your own lab or students. The best teachers are already kind in their classrooms. Bring that kindness to your research too. Don’t be that one asshole who makes others stop sharing. Kindness is not optional.

4. Open science means really open:

Open science may have started by opening up paywalled publication workflows, but it only succeeds when open extends back through the whole research process. Open is a manner of doing research that seeks to reveal as much of itself as it can or might, to promote shared knowing and reproducibility. Open is a transparently governed and democratic workplace in your organization. Open is open across the planet.

5. Open-science culture change starts with you:

Now is the time for you to lead your own open-science cultural change project. When you look around, you might be dismayed by the (dead) weight of organizational culture in your workplace. You can start small, and you can recruit others. The goal is to get back to the way science is meant to be pursued: to play the infinite game against intractable unknowns, to squeeze new knowledge from observations and information.

Remember first that leadership means humble conversations (Deep Dive: Humble Conversations ), fear-free interactions (Deep Dive: The Fear-Free Organization), democratic participation (Deep Dive: Democracy). You provide the compass (an informed open-science perspective), not a map. You and your colleagues are on a new learning curve toward a workplace where the only fear you find is the joyful thrill of playing with nature and data to unlock new insights. Open science needs you to find this kind of leadership inside and bring it to the academy.

6. Open science culture is learned:

You learn culture just like you do science, only you started early on, and without knowing this. That’s what this handbook is for. Disney and the Boy Scouts have been conscious, intentional, culture-learning organizations for decades. So too has the US Navy (for example), and your elementary school. This Handbook and hundreds of web resources are available help you discover more about open science and how to be an open scientist.

Culture is not just some subliminal vibe that you soaked up somehow (although you did a lot of culture learning really early on, and it seems like it was just soaked up). You are an adult. You are now responsible for your cultural behaviors. You can bring your focused intention and behavioral skilling to the goal of becoming more open each day. You succeed as an open scientist (and, in some fashion, as a person) by being more open today than you were yesterday.

7. Open science culture is an on-going conversation:

Make it a point to talk and question others about open science culture. The more people who talk the talk, walk the walk, and share what they value most, the better science will become. As John Wilbanks once said: “the opposite of ‘open’ is not shut. The opposite to open is broken.” Share your open science practices and stories. Keep talking with one another as you build common agreements.

8. Open science culture must be transmitted:

Teach your students to be open scientists. Talk to you children about how science really works in the open. Talk to their science teachers about the benefits of open science. Be an open-science mom or dad. Don’t have kids? Make sure the freshmen in your class know the difference between old-science and open science. The next generation of open scientists will need to assemble their own cultures. You can give them a head start.

9. Open science means open to all:

Not just to the “Republic of Science,” to the long-tail and beyond. Publication works when anyone on the planet can find your knowledge and share theirs with you. Do not worry; technology will help provide filters to keep you from drowning in information you do not need. Technology is one side of being open. Culture is the other side. The entire planet gets into the act at some point.

Future open scientists. Photo: Steve Jurvetson on Flickr.

10. Open science culture will become your culture too:

You get to grow your own personal virtues aligned with the shared virtues you use in your work. You get to add passion (and nuance too) to how you realize your own cultural flavors within your various social/workplace groups. Open science wants as much of you as you care to bring to it. You can take and carry away as much open science culture as works for you. You can own your unique style of open science. Grow it. Show it off. Add new thoughts to the mix. Make a ruckus with it.

References

Krumrei-Mancuso, Elizabeth J., Megan C. Haggard, Jordan P. LaBouff, and Wade C. Rowatt. “Links between Intellectual Humility and Acquiring Knowledge.” The Journal of Positive Psychology, February 14, 2019, 1–16. https://doi.org/10.1080/17439760.2019.1579359.
Lemaitre, Bruno. An Essay on Science and Narcissism: How Do High-Ego Personalities Drive Research in Life Sciences? Bruno Lemaitre, 2015.
Maestre, Fernando T. “Seven Steps towards Health and Happiness in the Lab.” Nature, November 23, 2018, d41586–018–07514–17. https://doi.org/10.1038/d41586-018-07514-7.
Merton, R.K. The Sociology of Science: Theoretical and Empirical Investigations. University of Chicago press, 1973.
Moore, S., C. Neylon, M.P. Eve, D.P. O’Donnell, and D Pattinson. “‘Excellence R Us’: University Research and the Fetishisation of Excellence.” Palgrave Communications 3 (2017): 16105.
National Academies of Sciences, Engineering, and Medicine, NAS Committee on the Impacts of Sexual Harassment in Academia, Committee on Women in Science, Engineering, and Medicine, and Policy and Global Affairs. Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine. Edited by Paula A. Johnson, Sheila E. Widnall, and Frazier F. Benya. Washington, D.C.: National Academies Press, 2018. https://doi.org/10.17226/24994.
Tangney, June Price. “Humility: Theoretical Perspectives, Empirical Findings and Directions for Future Research.” Journal of Social and Clinical Psychology 19, no. 1 (2000): 70–82.

Is My Learned Society Obsolete?

“[M]any people, especially those in positions of influence, strive to ‘do things better,’ which in practice amounts to ‘do obsolete things better’”(Ted Dintersmith, What School Should Be, 2018).

PLEASE NOTE: This is a draft of a bit of the Open Scientist Handbook. There are references/links to other parts of this work-in-progress that do not link here in this blog. Sorry. But you can also see what the Handbook will be offering soon. AND you can help by adding your comments now.

But we do such good work…

Is my learned society obsolete? This is just one question any open scientist hired on staff, or volunteering as a leader at a learned society needs to ask herself, and then others. In the last century and before that, learned societies flourished as homes for disciplinary, sub-disciplinary (and sub-sub-disciplinary) journals and annual conversations. They also provide a lobbying voice for their segment of the science endeavor, which itself may be obsolescent. They offer a place for new scholars to meet established scholars, and they recognize and reward exemplary work.

Michelle Brook <https://quantumplations.org/> did a count of learned societies in the UK, and found more than eight-hundred of these. Across the globe there are thousands. One can imagine that each one of these does some good within its purview. The other side this good, however, is the opportunity cost of their work (members might get more value elsewhere), and their relative ability to contribute to and benefit from open science. In the face of opportunities and change, these societies will all need to find nimble footing going forward:

“[L]earned societies are part of the UK’s knowledge economy and they can expect to see the pace of change and external competition increasing, so having a forward-thinking, adaptable and change-welcoming culture is important to their future survival (Gardner, 2013).

If your learned society is, in part, or on the main, obsolete, then making these obsolete bits better is the wrong way to spend your energies. Instead, you need to start the process of replacing obsolete practices, behaviors, and attitudes. This will be hard, but there are good resources here in the Handbook to help you out. So, what does obsolescence look like in the academy?

Note: there are lots of other (organizational, attitudinal, etc.) ways that your society may be obsolete. Here we will just list some of the ones that impact its role in open science.

Seven obsolete features still found in learned societies:

1. Journals/monographs that are based on the production of a paper product, and distributed through a subscription model

The form of a paper journal creates an arbitrary scarcity to the publication. It’s like you are publishing and privatizing the work of your members at the same time. University libraries are cajoled into subscriptions that must then be renewed for continuity. Members are tasked to provide peer review. Most likely you already do a digital version, anyhow.

Step away from the cellulose and subscriptions and use the Internet. It’s been around for decades. Your scientist readers around the globe will approve. Do you pay for what you do (outside of publishing/privatizing the journal) with moneys from subscriptions? First, you’ve been charging too much. Second, if what you do (scholarships, prizes, lobbying) is valuable to your members then charge them a membership fee. There are new business plan ideas that can help wean your society from its subscription addiction. Check out Harvard’s Societies and Open Access Research (Retrieved June 24, 2019).

2. Conferences with more than 300 participants

This is not to say that you should not offer co-present events. If you are running a conference with a couple thousand members (or more, or many more), you are complexifying the central reason people have flown into your meeting: to find each other, and make new, or revive old, personal associations. Stepping into a big-city convention center with your colleagues may feel good, for about the first hour. After that it’s all random noise.

Your conference carbon footprint is inexcusable. You should respect and support members who pledge to not fly at all (See: should climate scientists fly Retrieved June 24, 2019). Find creative ways to split up large national/international meetings into a number of smaller meetings with better focus and a lot more interpersonal time.

3. Poster sessions with no digital archive

Posters are a good way to show off work in progress, and an opportunity for small-group interactions. They do take a significant amount of time to produce, so they deserve a permanent home on the internet. If the way you do your poster session is obsolete, you can fix that. Find an open online platform for poster sharing and use it well. And use better poster design requirements (Retrieved June 24, 2019; video here) to help start conversations.

4. Meetings dominated by plenary talks and sessions devoted to individuals presenting papers

Apart from a few plenary talks curated to help the room consider new technologies and findings that stimulate conversations, most talks can be recorded and posted online before the meeting, and not take up the agenda. Instead, do workshops and panels that provoke discussions and learning moments. Use conversation models (such as the world cafe <http://www.theworldcafe.com/key-concepts-resources/world-cafe-method/>) to bring together early and late career professionals. Long breaks, good food, nearby coffee houses, and beer also help.

5. No support for member collectives/clubs

A mailing list is not a “community.” You need to broadcast less and listen more. Your members need to find others working in very similar research arenas, and to have peer-to-peer online collaboration tools. Help them do this. Become research match-makers and coordination masters. That’s your new value proposition.

Are your association’s membership numbers a metric for you? Is bigger really better? Remember that the r/science sub-reddit <https://www.reddit.com/r/science/> has twenty million members. Theirs is bigger than yours. Go online and build active communication/collaboration resources for your members. There is a Deep Dive for this: Collectives, assemblages, communities.

6. No support for cross-disciplinary assemblages

Real innovation happens when people bridge between disciplinary/domain-specific silos. The least your society can do is open up its digital holdings to be indexed broadly by others. The clubs that your society supports need to find clubs in other societies to share their issues and problems. You can seek out venues and avenues for conversations (online or in person) with other societies. No society is alone in the global science endeavor.

7. Perhaps your whole learned society is obsolete

You may need to visit the “realm of chaos,” (See: The Work of Culture) at a board retreat somewhere, and rethink the entire purpose and vision for your society. If this society was created in a previous century to support a then-new sub-disciplinary journal, it may be a good time to pass this responsibility over to a pre-print repository and go home. Got some endowment money left over? Do a final meeting, make it free for graduate students and early-career folks, and challenge them to come up with the next best thing. Roll over the endowment to that. Got a big, fancy building for yourself? (Good for you!) Put it on the market, and use the funds to help all your employees find good jobs elsewhere.