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 Open Scientist Handbook into a particular framework for science as a project, as an endeavor, and a life-way. 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; Accessed May 28, 2020).
This essay links into several other essays in the book that you can explore if you wish, when it’s convenient. 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):
“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 2005).
Nature is not entirely knowable; for very good reasons, including its emergent, adaptive complexity, and our embedded place within it (cf. Max Planck 1932/2015). Not yet knowing everything about nature and the universe 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 endeavor. 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 playing 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.”
Finite games and infinite play
The Handbook has a quibble about Carse’s use of the term “game” for what is really just infinite play: in this case, “science play.” Using the word “game” to describe an event with constantly changing rules and boundaries, where anyone can play and the more the better, and where the play never ends; this twists all meanings of the word “game” into unrecognizable knots. We all know what games are. They are defined by fixed rules, starting and ending points and, in many cases, specified boundaries. We play in them, and play at them, but they have real structures and definite rules that must be followed for the game to continue. Like infinite play, finite games are open-ended: their result is a future event. Unlike finite games, infinite play is neverending.
So the Handbook will use “game” for all the “finite” cases, where this matches every usual sense of the word game, and “play” for the infinite form. This echoes the older use the word “play” to signal skill and creativity. Learning to play is a common feature of cultures: play the violin, play the market. There is even foreplay (real open scientists excel at this). “Word play” gives us poetry. “Sword play” gives us corpses. “Science play” gives us knowledge of the universe. Infinite play includes breathing in and out until we can no longer do this. It’s a biological impulse to keep playing, understanding that when one must finally stop, others will continue.
The point of infinite science play is to keep playing science, to learn how to play better, and to add players to the mix; to sustain the play and the knowledge required to play at the highest levels; to change the rules, not to cheat, but to explore. In infinite play, your strengths are not what you are good at, but what you every so much want to get better at. That’s why you jumped head first into science.
Infinite play 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 science play, or it can get distracted by finite games of manufactured scarcity, ersatz excellence, and cumulative advantage. This is where we are and the choice we need to consider.
Because nature is intimate within infinite play, science cannot avoid playing along. Biological evolution, for example, is a theory that describes some of the adaptive and emergent possibilities of infinite play. 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 effect on the robustness of the ecosystem.
There is also some discussion in the Handbook for “play,” as we know this from childhood. You can look ahead to The practical wisdom of doing science to find out how much of the wisdom you might bring to your life you learned playing as a child. Other sections include the emotional tone of doing science (Joy, Fun, and Love), which looking into playfulness as an attribute of scientific discovery. You might not be having fun yet, but if open science blossoms, who knows?
Infinite play is an intrinsically complex knowledge-management endeavor. Recent organizational management theories, such as the Cynefin Framework (Accessed May 28, 2020) 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. Open science mines the latest complexity theories to help guide its path.
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 and practice into the 21st Century.
Nature is fantastically more complex, ambiguous (despite the claims of “natural laws”), and emergent than is our ability to understand this. Here is the asymmetry that makes science infinite play, a story instead of a recipe. The amount of knowing that happens with any new science discovery is an order of magnitude greater than the description of this “finding” in a scholarly paper. That’s why any new finding is worth a thousand conversations. The record of the finding is only the scat: the knowing is the actual beast, and needs sharing.
The asymmetry of “knowing” in a room at a science conference is enormous. The room knows orders of magnitude more about the topic than does the speaker. The larger the conference, the more this unspoken knowing—this room silenced, listening to a speaker—is wasted at the event. We never need to go back to 10,000 person science meetings. Better to have five hundred small conversations, with an online platform to capture these.
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 support science play. 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 still playing finite games.
Second: organizations that play finite games against others that use infinite play will always lose. Infinite play 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 for infinite play; 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 join into infinite play, however, science, and your workplace, needs one more thing: it needs you, and others like you, to step up and lead.
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 are equally fallible.
“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 excrement) 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.
“There are a lot of facts to be known in order to be a professional anything—lawyer, doctor, engineer, accountant, teacher. But with science there is one important difference. The facts serve mainly to access the ignorance…. You use those facts to frame a new question—to speculate about a new black cat. In other words, scientists don’t concentrate on what they know, which is considerable but also miniscule [sic], but rather on what they don’t know. The one big fact is that science traffics in ignorance, cultivates it, and is driven by it. Mucking about in the unknown is an adventure; doing it for a living is something most scientists consider a privilege (Firestein 2012).
Science is a “world-building” exercise; it strives to explain every-thing it contacts. 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. 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.
“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 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.
For now, just consider that time spent doing infinite play 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 that can compete with those moments you expand the edge of the planet’s knowledge envelope. “You get these moments of thrill. There you are, at 3:00 in the morning, and you know something about how we evolved that nobody else in the world knows. It’s a thrill of discovery. You make this breakthrough, and you find something. It’s this wonderful, wonderful scavenger hunt when you got to the end. It’s just so great to be a scientist” (Sabeti 2008; Accessed April 11, 2019).
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.
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 effect (Merton 1988) translates into cash rewards. Nearly all the current incentives for/in the academy have perverse consequences, including patents (you can look ahead to Against Patents in the Academy). 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 poor and have lots of money; “Money is just one of the many currencies you need to thrive and be happy in a world that requires and rewards attention, reputation, networks, learning, creativity, and tenacity….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).
The coming logic of abundance for science arrives sooner when you manage your own expectations. Abundance starts are the edge of “enough.” 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 around the logic of abundance (See: Abundance).
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.
“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 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. We will discover below that infinite science play removes any attachment to glory as a goal. The pursuit of glory is a finite game activity, where a few get this and use it silence the many others who don’t. Some decades ago, science was considered a pursuit best done outside of marketplace incentives:
“[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 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 own infinite play: 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 Brain Pickings 2018).
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 playing 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 through infinite play.
Doing open science means getting to dive into infinite play. 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 cumulative advantage; from all of the finite games that others use to manage your life for their goals.