“Uno no es lo que es por lo que escribe, sino por lo que ha leído” 1
(You are not what you write, but what you have read)
During the holiday season, it is not uncommon for writers and notable media figures to share lists of favorite books. Titles that are often deemed the “best of the year”. Titles that may or may not be forgotten in a few weeks’ time.
I recently asked some of my colleagues and others in the community2: Which books have continually inspired you? The books that have highly influenced the way you live or work. The books that have provided professional guidance, motivation or new perspectives on life. Books for all seasons.
The richness of the responses includes both fiction and non-fiction titles. Among the latter, there was a good diversity of subjects related to science, management, biographical, philosophy, psychology and other areas. Although a limited sample, the responses offered me a snapshot of what makes us so different, and yet, so similar in relation to general interests and concerns.
Cognizant of my biases, here is a selection of titles.
Giving due credit to scientific software development.
A substantial amount of work involved in data-intensive problem-solving is based on resources that virtually cost nothing to the end-user. Nada, gratis. You find it, you download it, you use it, and in some cases, you can modify it to tailor it to your own needs. You might even benefit from the experience of a large community of developers and users. Almost everything you need to learn or advance in your work.
Nowhere is this more apparent than in scientific research, across disciplines and application domains. The positive effects of free software and other types of open resources on scientific advancement are priceless. No single indicator of “impact” and “return on investment” could do justice to the benefits generated by such tools, languages and platforms.
Although users and other stakeholders often cite sources when reporting their work, this is not even consistently done. There are so many people (and work hours) invested in the noble idea of making and sharing code. So many anonymous contributors, unknown leaders and unselfish enablers who make such a moral choice every day. And yet, there is so much work that goes unrecognized.
The marvelous thing is that the communities that bring us all these ideas and solutions are made up of a particular kind of people. Mostly, they are people who care about societal challenges and do things just for the fun of it. They nurture projects that are fueled by unremitting passion, enjoyment and curiosity. This is not a world particularly suited to the celebrity wannabe and the bullshitter.
There is the rub: There is always the temptation to take the labors and contributions from these communities for granted. Almost a sense of entitlement among direct and indirect beneficiaries. The expectation that all those great tools and resources are self-made and self-perpetuating. The presumption that somewhere, somebody will make them for you, one way or the other.
In times of increasing excitement about “all things data”, it is crucial that stakeholders continue finding concrete ways to support, motivate or give due credit to those who create and share software. Multiple reward instruments, monetary and non-monetary, will be important. Impact assessment will also be necessary. This is more than a matter of fairness for a particular group of people. This is also about sustaining scientific and societal progress.
For now, I take a step back to tell the men and women behind the screen: It is a privilege to have access to the products of your talents and hard work. To the good people who give us the languages, databases and tools that make science happen: I am grateful to you.
The best known secret for successful collaborations with computational biologists
Computational biology enables and often drives biomedical research. The contribution of computational researchers may involve “routine” data analysis for supporting fundamental research, techniques for generating and testing complex biological hypotheses, and approaches to diagnosing diseases or guiding their treatment.
Although all of the interviewed researchers provided a good variety of insightful and practical advice, a unifying recommendation stood out: Get computational biologists involved in your research as early as possible. Moreover, it is necessary to maintain continuous, evolving interactions.
The benefits of this approach are numerous, among them:
Sound research. Early and iterative interactions with computational researchers allow the selection of suitable methodologies for generating and analyzing data. This also depends on a solid understanding of the scientific question being addressed, the limitations of existing experimental and computational techniques, and the expectations of the different research stakeholders.
Trust building. Frequent interactions based on openness and mutual respect facilitate the development of sustainable relations. This in turn creates the conditions for research environments where collaborators feel welcome to ask questions, try out new ideas and fail if necessary.
Unexpected, exciting journeys. Bringing computational researchers to the early stages of biomedical research may offer new, unanticipated ways to look at problems. Recurrent conversations may not only enrich the generation of ideas for designing and conducting a study, but also it may result in the re-framing of questions and identification of innovative applications.
Value for money. Many projects crash or waste financial resources because they begin with the generation of incorrect, highly-noisy or insufficient data for a particular type of analysis. Without the early involvement of computational researchers, opportunities for the optimal use of technologies in specific research contexts may also be missed.
These benefits can be fully realized through a strong commitment to life-long learning, a passion for tackling complex problems and the necessary doses of intellectual humility.
The take-outs from “What Is the Key Best Practice for Collaborating with a Computational Biologist?” should also be applied by computational researchers. For example, if you have an idea for a new algorithm or software application, try to obtain the input from biologists or clinical researchers as early as possible. As above, this may lead to tangible benefits in the short and longer terms, and at least new learning opportunities will arise.
These are exciting and challenging times for biomedical research. There is no time for outdated science management styles and marinated egos. If researchers do not make the most of the collaboration opportunities available, they risk missing bigger future opportunities for the benefit of society.
Respect, decorum and civility are not only disappearing from the political discourse. It is not just about the incessant demonization of immigrants, criminalization of dissenting views and assaults on reason. It is also about the public and private interactions among workers of the so-called “knowledge economies”, which include scientists and entrepreneurs (or their wannabes).
Robert Sutton’s The No Asshole Ruledefines the “Dirty Dozen”, a top-12 list of everyday actions that toxic, abusive workers exercise. It ranges from personal insults and threats (verbal and nonverbal) to “status slaps” and public shaming. I would also add various creative uses of passive aggression, distortions of reality, bullshitting tactics and shameless lies thrown in your face or behind your back. You also have those individuals who are “not rude” but keep telling people to “suck it up”, to get “their act together” or to believe that disrespect is just a question of interpretation.
This type of behavior is not only inappropriate and unfortunate. It can have negative consequences on individuals, organizations and societies. It is not only about ignoring rights and dignity, which should greatly matter anyway, but also about destroying trust and productivity. This “way of life” can be witnessed in physical and more virtual settings, including emails, discussion forums and social media.
A polite asshole is still an asshole
Civility is more than being polite. I have encountered a good number of “polite” and smiling fools, who have mastered an astounding capacity for incivility. Politeness can be manipulated to befriend the hypocrite and the conceited, who repeatedly destroy and vilify.
Civility means bringing discussion of problems to a ground where people emphasize arguments and the evidence to support or refute the arguments. I remember a particularly poisonous character who, when confronted with critical views of his actions, replied with statements such as “she said that because she is a woman” or “I do it because I am in charge”. There are also those who exploit “friendly” appearances to backstab you and get away with it because of their status in the “authority” or ass-kissing heap. What about those who condescend behind a mask of politeness?
Civility also requires (and benefits from) conversations that are based on facts or reproducible observations. Because of this, civility can enrich efforts to resolve conflicts or tough disagreements. Civility is also about making people feel safe in their work environments. Environments where privacy, diversity of ideas and fairness are more than corporate soundbites. Civility can also involve strong, argumentative and even witty deliberation, without having to recur to veiled threats. Civility also flourishes in organizations with a zero-tolerance to unfounded accusations, exaggerated claims and disregard for people’s basic needs.
Disagreement and debate, and even a good dose of confrontation, are crucial in public discourse, especially that engaging scientists and potential innovators. However, this does not mean that we should accept incivility as a natural consequence of modern times, or that there is little we can do about it. This is actually too important to let a few noxious people to hijack public or more circumscribed interactions for their selfish gains.
Now, more than ever, there is a need to stand up to jerks and other self-centered dunces. This must be done in firm and rational ways. I recently witnessed a good example of how to do it well.
A colleague of mine stood up to an instance of abusive (email-driven) behavior directed to a third person, and his response displayed features that are worth highlighting:
Straight to the point. My colleague clearly and succinctly explained why an inappropriate behavior occurred and what motivated him to respond.
Do not lose your cool. My colleague did not use expressions that could be interpreted as ill-mannered or derogatory.
Separate people from the problem. My colleague’s response focused on the fact that a behavior was uncivil, without shaming or attacking the person behind the behavior.
Reduce escalation. Although my colleague was quick and firm in his response, he made it clear (in words and with actual actions) that he did not intend to further add to the exchange. Moreover, he avoided threats or expressions of provocation.
You are a decent person. You speak out because it is the right thing to do for the good of your community.
We cannot let incivility tear us apart. Incivility is in the road to destruction. We have had enough of that.
There are reasons for achieving greater diversity in science. Diversity in the widest sense, including gender, ethnic and social background diversity. This is not simply a matter of justice, which by itself should represent a sufficient argument for defending diversity. Actually, it goes beyond such an “ideal” into the accomplishment of “practical” purposes. Prerequisites that are crucial for advancing knowledge and generating socio-economic advantages.
Scientific progress depends on openness. The openness that allows deeper examination of evidence against, or in favor, of a hypothesis. The openness needed to verify and reproduce results. A condition that is essential to understanding a problem and finding possible solutions without having to revert to notions of faith or ideological loyalties. Openness is strengthened by a diversity of ideas, and at the same time openness encourages new perspectives that are worth investigating.
Scientists, as well as all types of innovators, benefit from context awareness. This refers to understanding the background underlying a specific problem. This is also related to empathy: our capacity to be sensitive to the needs and experiences of others. Based on such awareness, scientists and innovators can come up with new applications that are both novel and relevant to humanity. These abilities are less likely to be developed in highly homogeneous or uniform organizations.
Scientific research and innovation are cooperative enterprises. Discovering and exploiting new knowledge typically involves interactions among people of diverse socio-economic backgrounds and cultures. Challenges of local and global significance, such as those concerning human health and the environment, demand the combination of resources and expertise that cannot always be linked to a single institution or geographical region. Moreover, intellectual and economic outputs may target varied stakeholders worldwide. Therefore, improving diversity is a necessary step towards properly framing complex questions and identifying what is needed to reach a solution.
Do we understand this problem? Is this the right technique? Should we move in this direction? These are questions that researchers address on a daily basis. To answer them, scientists pursue their own perspectives and methods, while simultaneously considering competing approaches and explanations. Thus, finding “truth” entails a persistent effort to reject partial views influenced by individual assumptions, historical circumstances or particular organizational settings.
To better understand the world and bring greater benefits to people, researchers must fight preconceptions that are imposed by the narrowness of their own knowledge and experiences. The restraints forged from our ignorance. However, to effectively struggle against such biases, we need more diverse research environments and leaderships, not less.
The date for your PhD thesis defense is approaching. In many ways you have already started your preparation: the thesis writing and submission, going through the administrative procedures, verifying conclusions, refreshing your knowledge and rehearsing for the big day.
It is likely that you have already been there through the eyes of another student. First: A stuffy room, the presentation that is seemingly a mere formality, those yawns from the audience, the nervous smiles from your supervisor.
And then, here comes the part you really have been waiting for. The moment when the thesis committee is no longer a list of names: it is question time.
Questions: The ceremonial ones, the easy ones, the “good” ones, the difficult ones. What about those harsh questions? The dry mouth, the perspiration, someone playing drums with a pen and desk, the laser pointer moving like crazy all over the screen. Also you have wondered: What’s with the little tapping on the microphone? Is she about to have a stroke? Give that man a glass of water please!
Until now you have hoped for the best.
But are you adequately prepared for the worst?
Trying to anticipate all possible types of situations during your PhD defense is a wishful, almost hopeless, task. But envisioning “worst” possible scenarios and considering the actions typically leading to such undesirable situations are both feasible and necessary. These are relatively common and preventable mistakes that students can make, time and again, in different doses and combinations. A selection of them and accompanying advice follows.
1. Huh? I don’t know. Here is the question, and you may not know the best possible answer, or you think that it is outside the scope of your research. Nothing wrong with it. Unfortunately, your gestures, words or even tone can tell the committee a more troubling story: you are not sufficiently concerned with the point made by the examiner. A simple “maybe, I don’t know” or “this is outside the topic of my research” are more than unsatisfactory replies. Although honesty should be at the center of your responses, such simplistic answers are also different ways to say: I do not care enough. A rephrasing of the question may make things clearer to you, and at least it will buy you some time to think about what to say next.
2. The dog ate my data. Gone are the days when you could blame the dog for eating your homework or announce the death of your grandmother for the third time. During your PhD, blunders or omissions may rightly be explained by different factors: Lack of funding, “unforeseen” mishaps, supervision problems and family issues. But regardless of whether or not they represented major obstacles to your work, never use them as an easy way out of your individual responsibility or to shift it on to others. It is alright to explain the conditions that influenced a particular outcome, an obstacle that you had to overcome or a difficult turn that you had to make. However, even if you are still recovering from these complications or you feel that you were treated unfairly: focus on the problem and your approach to dealing with it. Even better, tell the audience how you adapted to new circumstances, and outline the lessons you learned.
3. Nah, it is not so bad. An effective way to piss off committee members is to downplay the significance or seriousness of their concerns. If something in your work looks to them “surprising” or “weaker”, then for a moment consider that there must be some truth to their criticism. If you disagree with the reviewer’s position, then respond to it as you are expected to do: through argument based on the most solid evidence available. All of this without forgetting that in research there is always some room for improvement.
4.Duh, obviously. Even if you think that a reviewer asked you a trivial or obvious question, never express this view (either in words or mannerisms) to the committee. It’s the reviewer’s job to assess your knowledge irrespective of whether you or anyone else believe that you know the answer. If you have the impression that the committee is testing you, well that’s right, get over it. This is also related to another not less common situation: the candidate displaying hints of exasperation or amusement when asked questions that, at least in the candidate’s opinion, have already been addressed during the defense. These reactions not only may be seen as impolite to the reviewers, but also they offer a negative glimpse at your intellectual maturity.
5. I showed it in the thesis. It is not unusual for students to answer a question by simply indicating that a particular point was already explained in the thesis. Never assume that the reviewers will remember everything from your thesis. Even if they have amazing memory powers, the reviewers are there to ask anything considered relevant for evaluating the quality of your research. In some cases, they just want you to refer to a specific thesis section to obtain further clarification. So, focus on the question and answer it, even if the answer is impeccably clear in the thesis.
During and after your PhD defense you may feel that you did not offer the best answer to one or several questions. That could be especially frustrating if you are confident that you had the necessary knowledge to make it better. This is perhaps unavoidable and will represent a recurrent theme in your research career. Moreover, error and failure are inescapable realities in science. However, what you should not contemplate is ignoring basic recommendations that are known to be conducive to a professional, and hopefully less painful, discussion.
Keep up the hard work on route to your PhD defense. Celebration will be coming next.