Tag Archives: #scio14

Reflections on being part of a science blogging network.

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This is another post following up on a session at ScienceOnline Together 2014, this one called Blog Networks: Benefits, Role of, Next Steps, and moderated by Scientific American Blogs Editor Curtis Brainard. You should also read David Zaslavsky’s summary of the session and what people were tweeting on the session hashtag, #scioBlogNet.

My own thoughts are shaped by writing an independent science blog that less than a year later became part of one of the first “pro” science blogging networks when it launched in January 2006, moving my blog from that network to a brand new science blogging community in August 2010, and keeping that blog going while starting Doing Good Science here on the Scientific American Blog Network when it launched in July 2011. This is to say, I’ve been blogging in the context of science blogging networks for a long time, and have seen the view from a few different vantage points.

That said, my view is also very particular and likely peculiar — for example, I’m a professional philosopher (albeit one with a misspent scientific youth) blogging about science while trying to hold down a day-job as a professor in a public university during a time of state budget terror and to maintain a reasonable semblance of family life. My blogging is certainly more than a hobby — in many ways it provides vital connective tissue that helps knit together my weirdly interdisciplinary professional self into a coherent whole (and has thus been evaluated as a professional activity for the day-job) — but, despite the fact that I’m a “pro” who gets paid to blog here, it’s not something I could live on.

In my experience, a science blogging network can be a great place to get visibility and to build an audience. This can be especially useful early in one’s blogging career, since it’s a big, crowded blogosphere out there. Networks can also be handy for readers, since they deliver more variety and more of a regular flow of posts than most individual bloggers can do (especially when we’re under the weather and/or catching up on grading backlogs). It’s worth noting, though, that very large blog networks can provide a regular flow of content that frequently resembles a firehose. Some blog networks provide curation in the form of featured content or topical feeds. Many provide something like quality control, although sometimes it’s exercised primarily in the determination of who will blog in the network.

Blog networks can also have a distinctive look and feel, embodied in shared design elements, or in an atmosphere set within the commenting community, for example. Bloggers within blog networks may have an easier time finding opportunities for productive cross-pollination or coordination of efforts with their network neighbors, whether to raise political awareness or philanthropic dollars or simply to contribute many distinctive perspectives to the discussion of a particular topic. Bloggers sharing networks can also become friends (although sometimes, being humans, they develop antagonisms instead).

On a science blogging network, bloggers seem also to regularly encounter the question of what counts as a proper “science blog” — about whose content is science-y enough, and what exactly that should mean. This kind of policing of boundaries happens even here.

While the confluence of different people blogging on similar terrain can open up lots of opportunities for collaboration, there are moments when the business of running a blog network (at least when that blog network is a commercial enterprise) can be in tension with what the bloggers value about blogging in the network. Sometimes the people running the network aren’t the same as the people writing the blogs, and they end up having very different visions, interests, pressing needs, and understandings of their relationships to each other.

Sometimes bloggers and networks grow apart and can’t give each other what they need for the relationship to continue to be worthwhile going forward.

And, while blogging networks can be handy, there are other ways that online communicators and consumers of information can find each other and coordinate their efforts online. Twitter has seen the ride of tremendously productive conversations around hashtags like #scistuchat and #BlackandSTEM, and undoubtedly similarly productive conversations among science-y folk regularly coalesce on Facebook and Tumblr and in Google Hangouts. Some of these online interactions lead to face-to-face collaborations like the DIY Science Zone at GeekGirlCon and conference proposals made to traditional professional societies that get their start in online conversations.

Networks can be nice. They can even help people transition from blogging into careers in science writing and outreach. But even before blog networks, awesome people managed to find each other and to come up with awesome projects to do together. Networks can lower the activation energy for this, but there are other ways to catalyze these collaborations, too.

Brief thoughts on uncertainty.

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For context, these thoughts follow upon a very good session at ScienceOnline Together 2014 on “How to communicate uncertainty with the brevity that online communication requires.” Two of the participants in the session used Storify to collect tweets of the discussion (here and here).

About a month later, this does less to answer the question of the session title than to give you a peek into my thoughts about science and uncertainty. This may be what you’ve come to expect of me.

Humans are uncomfortable with uncertainty, at least in those moments when we notice it and where we have to make decisions that have more than entertainment value riding on them. We’d rather have certainty, since that makes it easier to enact plans that won’t be thwarted.

Science is (probably) a response to our desire for more certainty. Finding natural explanations for natural phenomena, stable patterns in our experience, gives us a handle on our world and what we can expect from it that’s less capricious than “the gods are in a mood today.”

But the scientific method isn’t magic. It’s a tool that cranks out explanations of what’s happened, predictions of what’s coming up, based on observations made by humans with our fallible human senses.

The fallibility of those human senses (plus things like the trickiness of being certain you’re awake and not dreaming) was (probably) what drove philosopher René Descartes in his famous Meditations, the work that yielded the conclusion “I think, therefore I am” and that featured not one but two proofs of the existence of a God who is not a deceiver. Descartes was not pursuing a theological project here. Rather, he was trying to explain how empirical science — science relying on all kinds of observations made by fallible humans with their fallible senses — could possibly build reliable knowledge. Trying to put empirical science on firm foundations, he engaged in his “method of doubt” to locate some solid place to stand, some thing that could not be doubted. That something was “I think, therefore I am” — in other words, if I’m here doubting that my experience is reliable, that I’m awake instead of dreaming, that I’m a human being rather than a brain in a vat, I can at least me sure that there exists a thinking thing that’s doing the doubting.

From this fact that could not be doubted, Descartes tried to climb back out of that pit of doubt and to work out the extent to which we could trust our senses (and the ways in which our sense were likely to mislead us). This involved those two proofs of the existence of a God who is not a deceiver, plus a whole complicated story of minds and brain communicating with each other (via the wiggling of our pineal glands) — which is to say, it was not entirely persuasive. Still, it was all in the service of getting us more certainty from our empirical science.

Certainty and its limits are at the heart of another piece of philosophy, “the problem of induction,” this one most closely associated with David Hume. The problem here rests on our basic inability to be certain that what we have so far observed of our world will be a reliable guide to what we haven’t observed yet, that the future will be like the past. Observing a hundred, or a thousand, or a million ravens that are black is not enough for us to conclude with absolute certainty that the ravens we haven’t yet observed must also be black. Just because the sun rose today, and yesterday, and everyday through recorded human history to date does not guarantee that it will rise tomorrow.

But while Hume pointed out the limits of what we could conclude with certainty from our observations at any given moment — limits which impelled Karl Popper to assert that the scientific attitude was one of trying to prove hypotheses false rather than seeking support for them — he also acknowledged our almost irresistible inclination to believe that the future will be like the past, that the patterns of our experience so far will be repeated in the parts of the world still waiting for us to experience them. Logic can’t guarantee these patterns will persist, but our expectations (especially in cases where we have oodles of very consistent observations) feel like certainty.

Scientists are trained to recognize the limits of their certainty when they draw conclusions, offer explanations, make predictions. They are officially on the hook to acknowledge their knowledge claims as tentative, likely to be updated in the light of further information.

This care in acknowledging the limits of what careful observation and logical inference guarantee us can make it appear to people who don’t obsess over uncertainties in everyday life that scientists don’t know what’s going on. But the existence of some amount of uncertainty does not mean we have no idea what’s going on, no clue what’s likely to happen next.

What non-scientists who dismiss scientific knowledge claims on the basis of acknowledged uncertainty forget is that making decisions in the face of uncertainty is the human condition. We do it all the time. If we didn’t, we’d make no decisions at all (or else we’d be living a sustained lie about how clearly we see into our future).

Strangely, though, we seem to have a hard time reconciling our everyday pragmatism about everyday uncertainty with our suspicion about the uncertainties scientists flag in the knowledge they share with us. Maybe we’re making the jump from viewing scientific knowledge as reliable to demanding that it be perfect. Or maybe we’re just not very reflective about how easily we navigate uncertainty in our everyday decision-making.

I see this firsthand when my “Ethics in Science” students grapple with ethics case studies. At first they are freaked out by the missing details, the less-than-perfect information about what will happen if the protagonist does X or if she does Y instead. How can we make good decisions about what the protagonist should do if we can’t be certain about those potential outcomes?

My answer to them: The same way we do in real life, whose future we can’t see with any more certainty.

When there’s more riding on our decisions, we’re more likely to notice the gaps in the information that informs those decisions, the uncertainty inherent in the outcomes that will follow on what we decide. But we never have perfect information, and neither do scientists. That doesn’t mean our decision-making is hopeless, just that we need to get comfortable making do with the certainty we have.

How to be ethical while getting the public involved in your science

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At ScienceOnline Together later this week, Holly Menninger will be moderating a session on “Ethics, Genomics, and Public Involvement in Science”.

Because the ethical (and epistemic) dimensions of “citizen science” have been on my mind for a while now, in this post I share some very broad, pre-conference thoughts on the subject.

Ethics is a question of how we share a world with each other. Some of this is straightforward and short-term, but sometimes engaging each other ethically means taking account of long-range consequences, including possible consequences that may be difficult to foresee unless we really work to think through the possibilities ahead of time — and unless this thinking through of possibilities is informed by knowledge of some of the technologies involved and of history of what kinds of unforeseen outcomes have led to ethical problems before.

Ethics is more than merely meeting your current legal and regulatory requirements. Anyone taking that kind of minimalist approach to ethics is gunning to be a case study in an applied ethics class (probably within mere weeks of becoming a headline in a major news outlet).

With that said, if you’re running a project you’d describe as “citizen science” or as cultivating public involvement in science, here are some big questions I think you should be asking from the start:

1. What’s in it for the scientists?

Why are you involving members of the public in your project?

Are they in the field collecting observations that you wouldn’t have otherwise, or on their smart phones categorizing the mountains of data you’ve already collected? In these cases, the non-experts are providing labor you need for vital non-automatable tasks.

Are they sending in their biological samples (saliva, cheek swab, belly button swab, etc.)? In these cases, the non-experts are serving as human subjects, expanding the pool of samples in your study.

In both of these cases, scientists have ethical obligations to the non-scientists they are involving in their projects, although the ethical obligations are likely to be importantly different. In any case where a project involves humans as sources of biological samples, researchers ought to be consulting an Institutional Review Board, at least informally, before the project is initiated (which includes the start of anything that looks like advertising for volunteers who will provide their samples).

If volunteers are providing survey responses or interviews instead of vials of spit, there’s a chance they’re still acting as human subjects. Consult an IRB in the planning stages to be sure. (If your project is properly exempt from IRB oversight, there’s no better way to show it than an exemption letter from an IRB.)

If volunteers are providing biological samples from their pets or reports of observations of animals in the field (especially in fragile habitats), researchers ought to be consulting an Institutional Animal Care and Use Committee, at least informally, before the project is initiated. Again, it’s possible that what you’ll discover in this consultation is that the proposed research is exempt from IACUC oversight, but you want a letter from an IACUC to that effect.

Note that IRBs and IACUCs don’t exist primarily to make researchers’ lives hard! Rather, they exist to help researchers identify their ethical obligations to the humans and animals who serve as subjects of their studies, and to help find ways to conduct that research in ways that honor those obligations. A big reason to involve committees in thinking through the ethical dimensions of the research is that it’s hard for researchers to be objective in thinking through these questions about their own projects.

If you’re involving non-experts in your project in some other way, what are they contributing to the project? Are you involving them so you can check off the “broader impacts” box on your grant application, or is there some concrete way that involving members of the public is contributing to your knowledge-building? If the latter, think hard about what kinds of obligations might flow from that contribution.

2. What’s in it for the non-scientists/non-experts/members of the public involved in the project?

Why would members of the public want to participate in your project? What could they expect to get from such participation?

Maybe they enjoy being outdoors counting birds (and would be doing so even if they weren’t participating in the project), or looking at pictures of galaxies from space telescopes. Maybe they are curious about what’s in their genome or what’s in their belly-button. Maybe they want to help scientists build new knowledge enough to participate in some of the grunt-work required for that knowledge-building. Maybe they want to understand how that grunt-work fits into the knowledge-building scientists do.

It’s important to understand what the folks whose help you’re enlisting think they’re signing on for. Otherwise, they may be expecting something from the experience that you can’t give them. The best way to find out what potential participants are looking for from the experience is to ask them.

Don’t offer potential diagnostic benefits from participation in a project for which that information is a long, long way off. Don’t promise that tracking the health of streams by screening for the presence of different kinds of bugs will be tons of fun without being clear about the conditions your volunteers will undergo to perform those screenings.

Don’t promise participants that they will be getting a feel for what it’s like to “do science” if, in fact, they are really just providing a sample rather than being part of the analysis or interpretation of that sample.

Don’t promise them that they will be involved in hypothesis-formation or conclusion-drawing if really you are treating them as fancy measuring devices.

3. What’s the relationship between the scientists and the non-scientists in this project? What consequences will this have for relationships between scientists and the pubic more generally?

There’s a big difference in involving members of the public in your project because it will be enriching for them personally and involving them in your project because it’s the only conceivable way to build a particular piece of knowledge you’re trying to build.

Being clear about the relationship upfront — here’s why we need you, here’s what you can expect in return (both the potential benefits of participation and the potential risks) — is the best way to make sure everyone’s interests are well-served by the partnership and that no one is being deceived.

Things can get complicated, though, when you pull the focus back from how participants are involved in building the knowledge and consider how that knowledge might be used.

Will the new knowledge primarily benefit the scientists leading the project, adding publications to their CVs and helping them make the case for funding for further projects? Could the new knowledge contribute to our understanding (of ecosystems, or human health, for example) in ways that will drive useful interventions? Will those interventions be driven by policy-makers or commercial interests? Will the scientists be a part of this discussion of how the knowledge gets used? Will the members of the public (either those who participated in the project or members of the public more generally) be a part of this discussion — and will their views be taken seriously?

To the extent that participating in citizen science project, whatever shape that participation may take, can influence non-scientists’ views on science and the scientific community as a whole, the interactions between scientists and volunteers in and around these projects are hugely important. They are an opportunity for people with different interests, different levels of expertise, different values, to find common ground while working together to achieve a shared goal — to communicate honestly, deal with each other fairly, and take each other seriously.

More such ethical engagement between scientists and publics would be a good thing.

But the flip-side is that engagements between scientists and publics that aren’t as honest or respectful as they should be may have serious negative impacts beyond the particular participants in a given citizen science project. They may make healthy engagement, trust, and accountability harder for scientists and publics across the board.

In other words, working hard to do it right is pretty important.

I may have more to say about this after the conference. In the meantime, you can add your questions or comments to the session discussion forum.

The line between persuasion and manipulation.

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As this year’s ScienceOnline Together conference approaches, I’ve been thinking about the ethical dimensions of using empirical findings from psychological research to inform effective science communication (or really any communication). Melanie Tannenbaum will be co-facilitating a session about using such research findings to guide communication strategies, and this year’s session is nicely connected to a session Melanie led with Cara Santa Maria at last year’s conference called “Persuading the Unpersuadable: Communicating Science to Deniers, Cynics, and Trolls.”

In that session last year, the strategy of using empirical results from psychology to help achieve success in a communicative goal was fancifully described as deploying “Jedi mind tricks”. Achieving success in communication was cast in terms of getting your audience to accept your claims (or at least getting them not to reject your claims out of hand because they don’t trust you, or don’t trust the way you’re engaging with them, or whatever). But if you have the cognitive launch codes, as it were, you can short-circuit distrust, cultivate trust, help them end up where you want them to end up when you’re done communicating what you’re trying to communicate.

Jason Goldman pointed out to me that these “tricks” aren’t really that tricky — it’s not like you flash the Queen of Diamonds and suddenly the person you’re talking to votes for your ballot initiative or buys your product. As Jason put it to me via email, “From a practical perspective, we know that presenting reasons is usually ineffective, and so we wrap our reasons in narrative – because we know, from psychology research, that storytelling is an effective device for communication and behavior change.”

Still, using a “trick” to get your audience to end up where you want them to end up — even if that “trick” is simply empirical knowledge that you have and your audience doesn’t — sounds less like persuasion than manipulation. People aren’t generally happy about the prospect of being manipulated. Intuitively, manipulating someone else gets us into ethically dicey territory.

As a philosopher, I’m in a discipline whose ideal is that you persuade by presenting reasons for your interlocutor to examine, arguments whose logical structure can be assessed, premises whose truth (or at least likelihood) can be evaluated. I daresay scientists have something like the same ideal in mind when they present their findings or try to evaluate the scientific claims of others. In both cases, there’s the idea than we should be making a concerted effort not to let tempting cognitive shortcuts get in the way of reasoning well. We want to know about the tempting shortcuts (some of which are often catalogued as “informal fallacies”) so we can avoid falling into them. Generally, it’s considered sloppy argumentation (or worse) to try to tempt our audience with those shortcuts.

How much space is there between the tempting cognitive shortcuts we try to avoid in our own reasoning and the “Jedi mind tricks” offered to us to help us communicate, or persuade, or manipulate more effectively? If we’re taking advantage of cognitive shortcuts (or switches, or whatever the more accurate metaphor would be) to increase the chances that people will accept our factual claims, our recommendations, our credibility, etc., can we tell when we’ve crossed the line between persuasion and manipulation? Can we tell when it’s the cognitive switch that’s doing the work rather than the sharing of reasons?

It strikes me as even more ethically problematic if we’re using these Jedi mind tricks while concealing the fact that we’re using them from the audience we’re using them on. There’s a clear element of deception in doing that.

Now, possibly the Jedi mind tricks work equally well if we disclose to our audience that we’re using them and how they work. In that case, we might be able to use them to persuade without being deceptive — and it would be clear to our audience that we were availing ourselves of these tricks, and that our goal was to get them to end up in a particular place. It would be kind of weird, though, perhaps akin to going to see a magician knowing full well that she would be performing illusions and that your being fooled by those illusions is a likely outcome. (Wouldn’t this make us more distrustful in our communicative interactions, though? If you know about the switches and it’s still the case that they can be used against you, isn’t that the kind of thing that might make you want to block lots of communication before it can even happen?)

As a side note, I acknowledge that there might be some compelling extreme cases in which the goal of getting the audience to end up in a particular place — e.g., revealing to you the location of the ticking bomb — is so urgent that we’re prepared to swallow our qualms about manipulating the audience to get the job done. I don’t think that the normal stakes of our communications are like this, though. But there may be some cases where how high the stakes really are is one of the places we disagree. Jason suggests vaccine acceptance or refusal might be important enough that the Jedi mind tricks shouldn’t set off any ethical alarms. I’ll note that vaccine advocates using a just-the-empirical-facts approach to communication are often accused or suspected of having some undisclosed financial conflict of interest that is motivating them to try to get everyone vaccinated — that is, they’re not using the Jedi mind trick social psychologists think could help them persuade their target audience and yet that audience thinks they’re up to something sneaky. That’s a pretty weird situation.

Does our cognitive make-up as humans make it possible to get closer to exchanging and evaluating reasons rather than just pushing each other’s cognitive buttons? If so, can we achieve better communication without the Jedi mind tricks?

Maybe it would require some work to change the features of our communicative environment (or of the environment in which we learn how to reason about the world and how to communicate and otherwise interact with others) to help our minds more reliably work this way. Is there any empirical data on that? (If not, is this a research question psychologists are asking?)

Some of these questions tread dangerously close to the question of whether we humans can actually have free will — and that’s a big bucket of metaphysical worms that I’m not sure I want to dig into right now. I just want to know how to engage my fellow human beings as ethically as possible when we communicate.

These are some of the questions swirling around my head. Maybe next week at ScienceOnline some of them will be answered — although there’s a good chance some more questions will be added to the pile!