Photo Credit: Tom Hilton on Flickr
THIS IS a draft of an introductory essay for the Open Scientist Handbook… I would love to know if it’s going in an interesting direction.
There are books and libraries of books that talk about science: its history, sociology, philosophy, politics, and practice. As a scientist, you’ve likely gotten this far in life without reading any of these. You probably don’t need to start now. In this essay, a few remarks about science will help anchor the (still being written) Open Scientist Handbook into a particular framework for science as a project, as an endeavor, and a lifeway.
You are already a scientist, so you don’t need a general introduction to “science.” Also, you can learn everything you need about open science as a practice by checking out the Open Science MOOC.
WHEN THE HANDBOOK is done, this essay will have live-links into several other essays/sections in the book that you can explore if you wish, when it’s convenient. (NOTE: This handbook follows the “mullet” logic: all the great stuff up front, and the ragged details in the back.) Here you will find several Richard Feynman quotes. Do you want a good example of an open scientist? Be like Richard Feynman (who died before open science became a meme):
Feynman quote (still looking for the source):
“Physics is like sex: sure, it may give some practical results, but that’s not why we do it.”
Science plays an infinite game because nature is the infinite game.
“If it turns out it’s like an onion with millions of layers and we’re just sick and tired of looking at the layers, then that’s the way it is, but whatever way it comes out, its nature is there and she’s going to come out the way she is, and therefore when we go to investigate it we shouldn’t pre-decide what it is we’re trying to do except to try to find out more about it” (Feynman et al, 2005).
Nature is not entirely knowable; for very good reasons, including its emergent, adaptive complexity, and our embedded place within it. Not yet knowing all about nature is why science still exists. Nature not ever being knowable is the scientist’s best job security.
Nature is a great part of what James P. Carse (1987) called the “infinite game.” By studying nature, scientists get to be players in/with this infinite game. Not many humans get to do this for a living, but all of us do this because we are alive. When we stop breathing, the infinite game goes on without us.
Carse has a list of distinctions between “finite” and “infinite” games. Francis Kane’s New York Times (04/12/1987) review of Carse’s book says:
“Finite games are those instrumental activities — from sports to politics to wars — in which the participants obey rules, recognize boundaries and announce winners and losers. The infinite game — there is only one — includes any authentic interaction, from touching to culture, that changes rules, plays with boundaries and exists solely for the purpose of continuing the game. A finite player seeks power; the infinite one displays self-sufficient strength. Finite games are theatrical, necessitating an audience; infinite ones are dramatic, involving participants.”
The point of playing the infinite game is to keep playing, to learn how to play better, and to add players to the mix; to sustain the game and the knowledge required to play this at its highest levels; to change the rules not to cheat, but to evolve and explore.
The infinite game goes on even when humans are distracted by the finite games they make up to give themselves victories to distinguish their efforts. The academy can choose to invest in playing the infinite game, or it can get distracted by finite games of manufactured scarcity, ersatz excellence, and accumulated advantage. This is where we are and the choice we need to consider.
Because nature is intimate with the infinite game, science cannot avoid playing this. Biological evolution, for example, is a theory that describes some of the adaptive and emergent possibilities of the infinite game. There is no end-point to evolution; no species really wins, some of them just have the chance to keep on playing. In fact, species extinction has a general positive effect¹ on the robustness of the ecosystem.
Complexity theories for the academy
Playing the infinite game is an intrinsically complex knowledge-management endeavor. Recent organizational management theories, such as the Cynefin Framework (started at IBM), warn that there are no “best practices” to deal with the “wicked problems” of adaptive complexity. This warning includes not just the marketplace, but also nature and culture. It turns out we are surrounded by emergent forces, and 20th Century management techniques are not up to the task.
While science methods have been addressing nature’s complexity for centuries, science knowledge-management and organizational governance have not kept up. It’s not hard to imagine science as an early-enlightenment project housed in late-medieval organizations. Open science looks to bring science governance into the 21st Century.
A bit on governance
This is an essay on science, not governance. Many of the sections of the Handbook offer governance guidance. Here it is only important to relate a couple major ideas.
First: your organization’s governance needs to be playing the infinite game. If your department, university, or research lab is still talking about “excellence,” or “we are ranked # X!,” or “the average salary of our graduates is Y$,” you are playing finite games. You need to stop that. You need to build infinite-game governance. Open science is here to help.
Second: organizations that play finite games against others playing the infinite game will always lose. The infinite game is a “long game.” Its players don’t care what other organizations are doing. They play to get better, not to win. Over time, they will out-innovate, out-think, and out-knowledge any peer who is chasing short-term finite wins.
Third: science is already positioned to play the infinite game; it gets funding from society (science goods are public goods); it holds a long-term privileged status within society; its “foe” (nature) is formidable and pushes science to ever greater tasks; its plan is flexible, it will reinvent itself as needed; its goal is just and grand: sharable knowledge of the universe.
To play the infinite game, however, science, and your workplace, needs one more thing: it needs you, and others like you, to step up and lead. You might want to take a look at the section (being written) Leadership in the Infinite Game to discover how you can lead your team, your lab, your school, or your agency in the infinite game.
Science has never been winnable. Nobody gets to figure everything out and finish science. Every bit of new knowledge is inextricably bound with a whole lot of other bits. It is a great example of the “long game.” Likewise, any bit of learning, every insightful thought or sentence delivered in your lecture, is fully dependent on a history filled with a whole lot of other learning moments: all of which turn out to be equally fallible.
Science wallows in doubt, devours unknowns, and shits little turds of incomplete knowledge
“When Socrates taught his students, he didn’t try to stuff them full of knowledge. Instead, he sought to fill them with aporia: with a sense of doubt, perplexity, and awe in the face of the complexity and contradictions of the world. If we are unable to embrace our fallibility, we lose out on that kind of doubt” (Schultz, 2011).
Science looks squarely into the unknown. A scientist is never as interested in the work she has already published as she is in the next unknown she is tackling in her research. Science’s knowledge-mignardises (or petit fours: sounds better than turds) can and have accumulated into important and useful — but still incomplete — facts and theories about our world and ourselves. And only science can do this.
Science is a “world-building” exercise; it strives to explain every-thing it contacts. There is no alternative world out there.² There are strands of complementary knowledges or untested theoretics that could use some investigation; there are “pseudo-sciences” like Astrology; but there is no alt-science world, not even in Reddit (we checked in March of 2019). The placebo effect shows we have a lot to learn about the healing process, but does not invalidate what we know.
The main adversary to science is bad science; open science looks to remove the (perverse) incentives behind most of today’s shaky research methods and results:
“[I]n science… it is precisely when people work with no goal other than that of attracting a better job, or getting tenure or higher rank, that one finds specious and trivial research, not contributions to knowledge. When there is a marked competition for jobs and money, when such supposedly secondary goals become primary, more and more scientists will be pulled into the race to hurry ‘original’ work into print, no matter how extraneous to the wider goals of the community” (Hyde, 2009).
Science rests on the possibility that everything it knows today is wrong. As Feynman noted: “Once you start doubting, just like you’re supposed to doubt, you ask me if the science is true. You say no, we don’t know what’s true, we’re trying to find out and everything is possibly wrong” (2005). Kathryn Schultz wrote an entire book on Being Wrong; science has a central spot in this work:
“In fact, not only can any given theory be proven wrong… sooner or later, it probably will be. And when it is, the occasion will mark the success of science, not its failure. This was the pivotal insight of the Scientific Revolution: that the advancement of knowledge depends on current theories collapsing in the face of new insights and discoveries. In this model of progress, errors do not lead us away from the truth. Instead, they edge us incrementally toward it” (Schultz, 2011).
Science makes no claim to be right, but every claim to be the go-to method that can find out if something is wrong. From there, it harvests knowledge that has not (yet) been shown to be wrong; this is as close to being right/true as there is. And scientists get to have fun by being less-wrong today than yesterday. Scientists are passionate knowledge explorers.
The joy of discovery needs a home in the center of science
“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. This is a very real and important point and one which is not considered enough by those who tell us it is our social responsibility to reflect on the impact of science on society” (Feynman et al, 2005).
Science is hard. It is the hardest ongoing task in all of humanity: after child rearing. One might expect society to honor, celebrate, and reward scientists for their labor. In the (not yet complete) Section on Joy and Passion you can discover more about how much fun you might be having right now as an open scientist.
For now, just consider that time spent playing with/in the infinite game can be intrinsically rewarding. In fact, it is potentially the most fun anyone can have. There is no video game, extreme sport, puzzle, quiz, theatre experience, or physical thrill that can compete with those moments you expand the edge of the planet’s knowledge envelope.
It is a privilege to be paid to spend your time in this pursuit. The privilege may not come with the type of salary/lifestyle society offers other occupations, but it does come with the freedom and the time to explore your own interests in nature/culture and the universe. This may be the best reason to keep the academy away from the logic of the marketplace, where freedom and time belong to others, where finite games fill your days and take you away from the very serious task of playing with nature.
Looking for the next patent, weapon design, or mass-consumable gadget or drug might make you rich, but it’s not science.
Using science resources and funding for science to accomplish these things, and their like, fits extremely well into the neoliberal logic of the marketplace. The incentives and rewards are nicely lined up. These finite games have obvious winners, and lots of losers too. Here is where the Matthew effecttranslates into cash rewards. Nearly all the current incentives for/in the academy have perverse consequences, including patents (See: Against Patents in the Academy[to be finished]). Marketplace counter-norms have already won, so it seems. Your “Research Excellence Framework” score matters a lot more than the actual new knowledge you and your colleagues have assembled.
This is why open science looks to build internal economies with its own logic, norms, principles, and rewards. There are lots of ways to be rich without much money; one key here is to manage your own expectations. Having “few needs, easily met” lets you locate a range of opportunities you might have overlooked. Here you might want to remember that open science is not just about publication access, it is about refactoring the academy to eliminate the sources for bad science, to accelerate the sharing of science objects across the planet, and to reboot the cultural DNA of academic organizations.
People will ask you, “how do you incentivize scientists to do the right thing […when the wrong thing pays off so well]?” You might respond by saying something like:
“How about giving scientists the means to do exceptional work, to have this work shared across the planet, to gather instant feedback from peers around the world, to live simply with plenty of time to do research without racing for funding, to have security of income and access to research tools.”
Time to do what you are passionate about is a great luxury, and has been for centuries. Setting your own goals, choosing yourself as the person who can contribute and accomplish great work, mentoring others to secure the future of science: these are incentives you can own.
Being a scientist is…
“Feynman always said that he did physics not for the glory or for awards and prizes but for the fun of it, for the sheer pleasure of finding out how the world works, what makes it tick” (Feynman et al, 2005).
At this point you might be thinking that the science described in this framework is not what you wake up and do every day. Your life may be dominated by demands from your organization for high productivity scores, funded research proposals, and publications in high impact journals; editors nudging you for your peer reviews; assistant vice chancellors pestering you with patent forms to fill out; constant rejections (curse you, reviewer three!) and revisions in your own output; courses to teach, lectures to prepare, and grades to give; and, right… home life. All this talk about joy and fun may seem oblique to your actual life.
Have hope. The high-pressure, low-fun career for scientists is not what science needs, and not how it was (and perhaps will not be again soon) designed to operate. Some decades ago, science was still considered a pursuit done best outside of the marketplace:
“[Vannevar] Bush convened a panel of leading academics to formulate a vision for postwar science policy. In July 1945, the panel produced a 192-page document dramatically titled Science: The Endless Frontier. Heralding basic science as the ‘seed corn’ for all future technological advancement, the report laid out a blueprint for an unprecedented union between government and academia — a national policy aimed at fostering open-ended blue-sky research on a massive scale. Though he was a conservative, Bush laid a groundwork for what Linda Marsa aptly termed a ‘New Deal for science,’ seeking to preserve a realm where university research was performed free of market dictates.
’It is chiefly in these [academic] institutions that scientists may work in an atmosphere which is relatively free from adverse pressure of convention, prejudice, or commercial necessity,’ wrote Bush in Endless Frontier, ‘Industry is generally inhibited by preconceived goals, by its own clearly defined standards, and by the constant pressure of commercial necessity.’ Of course there are exceptions, he acknowledged, ‘but even in such cases it is rarely possible to match the universities in respect to the freedom which is so important to scientific discovery’” (Washburn, 2008).
This freedom is what you’ve lost; what open science is determined to regain. You can find a lot of discussions around “academic freedom.” Being a scientist carries a great responsibility to maintain a specific variety of this. Again, here’s Feynman:
“It is our responsibility as scientists, knowing…the great progress that is the fruit of freedom of thought, to proclaim the value of this freedom, to teach how doubt is not to be feared but welcomed and discussed, and to demand this freedom as our duty to all coming generations” (Feynman et al, 2005).
This “freedom of thought” extends to ideas shared freely within the academic community as gifts from scientists to the entire community. Hyde notes that this “gift” logic runs counter to the logic of the marketplace:
“A gift community puts certain constraints on its members, yes, but these constraints assure the freedom of the gift. ‘Academic freedom,’ as the term is used in the debate over commercial science, refers to the freedom of ideas, not to the freedom of individuals. Or perhaps we should say that it refers to the freedom of individuals to have their ideas treated as gifts contributed to the group mind and therefore the freedom to participate in that mind” (Hyde, 2009).
Being a scientist means giving what you learn, the best you have, to your peers in a sharing community, with the expectation that they will do the same. It is beneficial to remember that when your mother or grandfather was doing science, the academy’s position as external to the marketplace was valorized and celebrated. Being a scientist means you can demand the freedom, the time, and the resources to investigate your part of the infinite game: the object of your own study and your singular passion and potential joy.
“There can be occasions when we suddenly and involuntarily find ourselves loving the natural world with a startling intensity, in a burst of emotion which we may not fully understand, and the only word that seems to me to be appropriate for this feeling is joy” (McCarthy, 2015; see also: https://www.brainpickings.org/2018/06/07/michael-mccarthy-the-moth-snowstorm-nature-joy/).
Doing science is…
Science is the most difficult, most ambitious, most challenging pursuit that the human species has ever attempted. Every unknown is integrally linked to the entire infinite game that is the universe in which we swim. So your unknown — that bit of the game you have chosen to interrogate — is just as important as the next bit. Tackling your unknown is difficult by default (if it wasn’t this would already be a “known”). What is really painful is not being in constant, constructive contact with the five, or twelve, or a hundred other scientists somewhere on the planet who are, at this moment, running the exact same thoughts through their minds as you hold in yours.
Open science means you no longer need to consider these colleagues as your “competition.” A goal of open science is to connect you with these, your disciplinary siblings, and help you work faster, work better, and have more fun discovering more by working together than you can on your own. These are the people who can help you the most, and who need your expertise the most. Together you can make science stand up and dance in the infinite game.
Doing science means getting to play the infinite game for real. Doing science means unleashing your passion for knowledge exploration and diving into your research. Doing science means sparking the same passion for learning in your students. The role of open science in your life and for your research and teaching — and through the places where you work and collaborate — is to release you from manufactured scarcity, ersatz excellence, and the quest for accumulated advantage; from all of the finite games that others use to manage your life for their goals.
Carse, James P. Finite and Infinite Games. Ballantine Books, 1987.
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.
Hyde, Lewis. The Gift: Creativity and the Artist in the Modern World. Vintage, 2009.
McCarthy, Michael. The Moth Snowstorm: Nature and Joy. New York Review of Books, 2015.
Schultz, K. Being wrong: Adventures in the margin of error. Granta Books, 2011.
Taleb, N.N. Antifragile: Things That Gain from Disorder (Vol. 3). Random House Incorporated, 2012.
Washburn, Jennifer. University, Inc.: The Corporate Corruption of Higher Education. Basic Books, 2008.
 The infinite game is anti-fragile. This is another reason for its unknowability and another clue that it’s a long-game. Shane Parrish in the Farnam Street Blog <https://fs.blog/2014/04/antifragile-a-definition/> describes Nasim Taleb’s ( 2012) concept of “antifragility” this way:
“Antifragility is beyond resilience or robustness. The resilient resists shocks and stays the same; the antifragile gets better. This property is behind everything that has changed with time: evolution, culture, ideas, revolutions, political systems, technological innovation, cultural and economic success, corporate survival, good recipes (say, chicken soup or steak tartare with a drop of cognac), the rise of cities, cultures, legal systems, equatorial forests, bacterial resistance … even our own existence as a species on this planet. And antifragility determines the boundary between what is living and organic (or complex), say, the human body, and what is inert, say, a physical object like the stapler on your desk.”
 Science is bounded to concepts/theories that can be “falsified”:
“Ever since the 1930s, when Karl Popper first argued for falsification as the main criterion for demarcating science from nonscience, the topic of “pseudoscience” has played an important role in the philosophy of science. Just because someone claims to be doing science or to be a scientist does not mean they are. Popper argued that if the theory did not put forth predictions that were “brittle” and potentially “falsifiable,” then they were not science. Theories that can be twisted post hoc to explain any kind of experimental outcome are not science” (Feist, 2006).