Maybe there’s a better way to keep track of these, but in the meantime, here’s some media appearances I’ve done for outreach lately!
Yeah, I said it.
Brilliant. Famed. Genius. Hailed. Innovative. Transformed. Singlehandedly. Greatest Physicist. Magnum Opus.
These are the words that the students in my Astronomy Communication class use to talk about Einstein. And they’re not alone, of course! They didn’t pull these ideas out of thin air.
Einstein has been revered in popular culture in almost every medium imaginable, from symphonies to museums to a banger of a Kansas song that I loved in 8th grade. In fact, in high school I had an Einstein t-shirt that I wore to death – none of us are immune from hero worship.
I pulled the following quote from the advertising materials for National Geographic’s Genius: Einstein
Fiercely independent, innately brilliant, eternally curious, Einstein changed the way we view the universe.
Let me say this up front: I’m not saying that Einstein’s work wasn’t important. His papers laid the foundation for almost all of modern physics, and that’s, well, not nothing. In fact, I have no problem with Einstein himself; or, more precisely, Einstein himself is not the point. I hear similar sentiments about other physicists as well, and those sentiments as a genre are what I’d like to address in the meat of this post. However, I think it’s fascinating to dig into why Einstein shows up so much more often in this context than, say, Schrodinger or Rutherford or Feynmann, so let’s take a short journey.
I am certainly not the first one to muse on this topic, but I wanted to take some time to speculate on why my students clutch onto their ideas of Einstein and will not let them be pried away, even upon pain of a deduction for citing “people not papers”.
The Draw-a-Scientist Test provides one fascinating metric of cultural perceptions of science across students of different ages and nationalities. The test, often mentioned in the context of science education, is straightforward: ask groups of people to draw a picture of a scientist, and then analyze their interpretations. These studies have been going on for decades, and I could write a whole blog post solely on the gender aspect of the results. But here I want to focus on a particular quote from the meta-study “Using the Draw-a-Scientist Test for Inquiry and Evaluation” (Meale 2014)
The overwhelming majority of the images [drawn by a class of undergraduates] were White (95%) males (90%) with wild hair (71%) in lab coats (71%) and wearing eyeglasses (81%), in percentages remarkably similar to those seen among middle school students by Finson et al. (1995)
In addition, I treat you to Figure 1 from Meale 2014, partially because it is deeply funny to me.
Typical Einstein imagery.
Those far more qualified than I am have noted that his visage was a “cartoonist’s dream come true”. Cartoonist Sidney Harris has mused that the ideological stickiness of Einstein’s appearance is probably in the hair or the eyebrows.
I think it’s significant that Einstein’s image got entangled with other stereotypical scientist characteristics like lab coats and glasses, when they have nothing to do with him. Einstein’s appeal is partially because he has become the embodiment of science iconography (in the religious icon sense) – a highly stylized symbol with easily drawn characteristics that connect to neural shortcut “knowns” about who scientists are and what they do.
I’ll go one further and postulate that Einstein’s image now subtly reinforce the maleness of the stereotypical imagery that incorporated it. Just imagine a woman with hair as wild as Einstein’s – the only associations my own brain digs up are witches, villainesses, and someone who has stuck their finger into an electrical socket, none of whom you would expect to see at the front of a lecture hall.
Even if you don’t know any physics, you probably have some mental connection between Einstein and the phrase “Theory of Everything” – what a slick piece of mental marketing that phrase was! The TOE gets described as the “holy grail” of physics (again, religious iconography), and the idea and quest for a universal solution is super cool in a pure physics sense. But the key with the TOE is that people who are not physicists are invested in it. Thus, with its mental link to Einstein, non-physicists know and care about Einstein. What the TOE really does is to provide a narrative that human brains crave – the And-But-Therefore a la Randy Olson, one nice package that lets us know that the universe was understandable after all, a solved problem, a collective sigh of relief. And it signifies itself as important right off the bat with the word everything. You don’t need to know what quantum mechanics or gravity are, you don’t even need to have taken a physics course, to want to participate in the knowledge that everything has been solved. The fact that Einstein never actually got to a unifying theory is peanuts in comparison to the power of that narrative; more is better, everything is best, so therefore Einstein is best as well.
I won’t say too much on this point, but there are so many apocryphal tales and misattributed quotes about Einstein that he acts as more of a folk-hero in the social sphere than a physicist, which very few physicists have achieved (Feynmann? Sagan?). Here are a smattering of my favourite stories: “Einstein failed math” (he didn’t), “Einstein forgot what his destination was while he was on a train” (likely apocryphal), and “Einstein once switched places with his chauffeur for a talk” (actually a variant on an old tale from Jewish folklore). For more on the question of the quotable Einstein, I direct you to an essay that’s much better than this one. But once a character has transcended reality and become a folk hero, all of society is helping to make them as funny and likable and witty as possible, which creates an idol.
So why am I being such a grump about Einstein? It’s good that people like a scientist and find them charismatic and memorable… right? Better than the alternative, at least?
Well, in a way, yes, but I think we have culturally done our students a disservice by propagating a linear, innate, single-actor view of science history. I want to take some time to push back against the words that we use when talking about Einstein, because I think they have unintended and harmful consequences on science attitudes in the public, and also in aspiring scientists.
Brilliant, innate, genius
If you aren’t familiar with the idea of fixed vs. growth mindsets, I recommend that you check out the work of psychologist Carol Dweck (the first page of this paper has a nice introduction to mindsets). Briefly, if you have a fixed-mindset about intelligence, you believe that intelligence is a quality which is inherent and cannot change. If you fail at a task, you have reached the end of your ability and attempts at improvement will be futile. If you have a growth-mindset about intelligence, on the other hand, you focus on learning as a process and understand that competence at a task can be learned, practiced, and developed. Mindsets do influence outcomes such that students with growth-mindsets perform better than their fixed-mindset classmates. This, in a meta way, points to the growth model as a more correct model of intelligence [this idea is much more complicated in the literature of course, with all of us having various degrees of “fixedness” in our mindsets that vary for different topics].
So my first critique of classical Einsteinian descriptors is of innate, which perpetuates untrue ideas about who can do physics. Struggle and failure are normal, competence and fluency can be taught, and it is harmful and scientifically unfounded to insinuate that those without some “gifted” ability are doomed to fail.
The idea that we’re discouraging our students is bad enough, but of course that discouragement is not distributed equally. Another fascinating series of studies has discovered that math-intensive STEM fields like physics and computer science are more likely to be perceived as requiring brilliance to succeed, which are in-turn linked to lower senses of belonging from non-male and non-white students, and lower diversity in the field overall. And culturally, we’ve all been trained to link brilliance and maleness (specifically, white maleness), an idea that is already rooted in children as young as 6 years old.
Whether we talk about it or not, brilliant carries a white male connotation that translates to measurable impacts on the inclusivity of our field.
The word genius is often applied universally. Sometimes we specify with phrases like “genius mathematician” or “musical genius”, but oftentimes it just gets short-handed down to genius. Unfortunately, a word that’s applied without specification is sometimes perceived as applicable universally, when it’s really not. The effect I’m discussing is similar to the Dunning-Kruger effect, but not quite similar enough that I could find any literature on it (other than a mildly related TVTrope). I am specifically talking about “genius” scientists who stray too far out of their area of expertise, and the peril that can result by uncritically trusting their untrained opinion. As some anecdotal evidence, Elon Musk may have built some successful companies in Silicon Valley, but he is woefully ignorant when it comes to epidemiology. Freeman Dyson was perhaps as close as you could get to a modern polymath, and love him though I do, I don’t defend his startlingly bad takes on climate change. And Stephen Wolfram made Mathematica (cool) but also keeps touting, to great fanfare, a Theory of Everything that has never been through peer review. As per Ryan Mandelbaum’s Gizmodo article linked in the previous sentence:
In Wolfram’s case, at best the work is correct, and history will remember Wolfram’s name for research that was done by many people as part of the Wolfram Physics Project. At worst, countless hours of scientists’ time have been devoted to one rich man’s monomaniacal pursuit of explaining the universe in a way that looked nice but didn’t work at all. These are resources that could have instead been divided among countless other viable ideas.
And no, of course you can’t be a genius in everything at once: that’s the whole point of this section. But this causes issues when a) you think you are a genius in everything and b) other people think they should listen to you because of the g-word. My two favourite four-letter comics (XKCD and SMBC) have something to say on this topic as well, if you’d like a more humourous take (ah, heck, here’s a second XKCD while I’m at it).
As a final aside: Brilliant and genius also come out as excuse words when scientists are caught engaging in unacceptable behaviour. In spite of what my grumpy shelter-in-place mood might tell me, a scientist’s brain does not sit in a box all day and spit out new theories without ever encountering another human being. Science is a human endeavor that requires human interaction. It turns out that, when it comes to being a decent human being, some revered figures are stupid and toxic, and their fields would have advanced further if they had never existed (regardless of how good they were at, say, integral calculus or constructing spectrographs). This topic is vitally important to understand, but also exhausting to deal with. I don’t think I could write about the topic any better than this Scientific American post by the wonderful organization 500 Women Scientists, so I’ll leave it there.
Single-handedly, transformed
The word single-handedly really has no place in science. Unless you want to derive your entire project from first principles without talking to anyone ever [you don’t, and no one wants to see you do it, either], your science can never be single-handed.
To get the history straight, even Einstein could not have accomplished his work in relativity without his friends, mentors, intellectual precursors, and colleagues. A fascinating Nature history post by Janssen and Renn in 2015 deconstructs the myth of Einstein as a lone genius. To highlight a particular part of this complex narrative:
Legend has it that Einstein often skipped class and relied on Grossmann’s notes to pass exams. […] The relevant mathematics was Gauss’s theory of curved surfaces, which Einstein probably learned from Grossmann’s notes.
Even based only on the shortened version of the narrative presented in the previously-mentioned Nature paper, Einstein couldn’t have done what he did without:
Relativity was created by not one, but dozens of hands. This essay, by the way, ends with an illuminating quote that I just had to share:
As with many other major breakthroughs in the history of science, Einstein was standing on the shoulders of many scientists, not just the proverbial giants.
Einstein’s greatest strength probably wasn’t some weird property of his brain, but instead a property of his attitude towards his field. Tenille Bonoguore, in a post discussing more of Renn’s work, phrases this particularly eloquently:
None of this diminishes Einstein’s genius, Renn says. In fact, it helps underscore his brilliance, as he drew on and transmuted the knowledge accumulating in various branches of classical physics: “Einstein was a convergence thinker. He brought different traditions together.”
Bonoguore also discusses the intellectual contributions of Mileva Maric, a mathematician and fellow university student who was married to Einstein for awhile. Unfortunately, we don’t have records of her contributions to the early work that is now credited to Einstein, but she likely assisted in some capacity between sounding-board and co-author.
And it is more difficult now, in the modern scientific world, to transform anything on your own than it ever was in the early 20th century. The last Decadal Survey in Astronomy from 2010 had an entire chapter called “Partnership in Astronomy and Astrophysics: Collaboration, Cooperation, Coordination“. The Decadal points out that the astronomy landscape is changing: authors in astronomy journals have become majority non-American in the last few decades, the best telescope locations are distributed indifferently to national boundaries, and funding for new resources is now of a scale to require multi-national collaborations (ex. NASA/ESA). And of all of the sciences, doesn’t it intuitively make sense that astronomy needs international collaboration, when your position on the globe determines which slice of the universe is visible in the sky above your head?
Greatest physicist, Magnum Opus
Wouldn’t it be nice if we could just see objective stats on everything? Where we could know 100% that we made the right choice out of two career options, that the charity we picked was objectively the one that would do the most good*, that we could tell which research group would be the best use of funding just by plugging in some numbers?
Well, unfortunately, we can’t.
Science can’t be ranked, and it never turns out well when we try.
One way that people have tried to quantify a scientist’s impact is through something called an h-index: what is the maximum number h for which you have written h papers with h citations each? If a single number to describe the quality of an entire academic career sounds like an oversimplification, that’s because it is. Funnily enough, Einstein and Feynmann’s h-indexes are both ~40, which isn’t super impressive in many fields today. The h-index is biased against young researchers, prone to skewness from self-citation (men self-cite more than women, by the way), its arbitrary formulation can cause rankings to shift if you use ex. h -> h+1, it exacerbates existing institutional gender discrimination, and I could go on. On Google Scholar, I get ~25,000 hits for “alternative h-index”, which in my mind is comedically missing the point. You just can’t reduce an entire career to a single number, even if it would be very convenient to think you had done so (looking at you Physics GRE).
So who is the greatest physicist? Is it the person who created the first law in a field, even if it was incorrect at the time? Is it the person with the highest h-index, but whose inappropriate behaviour forced dozens of young physicists out of the field? Is it the one with the most citations on a first-author paper – what if that paper was from a multi-author collaboration? Is it the person whose mentorship inspired an entire generation of young physicists? Is it the instrument-builder or the observer or the theorist or the data-reducer or the journal editor?
It’s none of them, because the premise is inherently flawed. Science is an ecosystem, and it doesn’t make sense to elevate any one person any more than it makes sense to discuss a species as if it was distinct from its environment.
I’m not going to say too much about the choice of the words Magnum Opus, except that it dices the multi-layered, collaborative nature of good science into yet smaller pieces. It implicitly downweights the work of someone who contributes moderately to many different sub-fields across their career in favour of someone who contributes a large tome to one, once. Great science comes from both.
If you type in “astronomy scientist” into Google (because “astronomer” doesn’t register, for some reason?) you have to scroll past ~50 men, some of whom I didn’t encounter until a brief appearance in a single grad school lecture, to find Jocelyn Bell, Margaret Burbidge, and Vera Rubin. Honestly, pretty demoralizing.
I’m not going to blame all of gender-discrimination in physics on scientific hero-worship, or sillier still, on Einstein. But the single-actor, portraits-in-the-hall, birth-and-death-dates narrative of physics history certainly doesn’t align with the reality of the field’s history, or the inclusive goal of the field’s future. And I think we should drop it, even though the portraits fit nicely on your PowerPoint slides for Astro 5. Instead, show how ideas are interconnected in astronomy and physics, teach how they appear across the world many times in fits and starts, acknowledge the community of people (many unappreciated) around the man the law is named after, and emphasize a growth mindset in your students.
And, for those of you who are as nit-picky about words at I am, I want to be clear that my connotations of these words are my own thoughts and interpretations. For example, I’m not here to tell you that you should never use the word brilliant. Brilliant is a fun word! It’s a compliment! But it carries weight when you use it, especially in academic contexts, and I’d like you to be aware of that.
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This post was inspired by a great Penn State Women and Underrepresented Genders in Astronomy (PSU W+iA) discussion on hero worship in the sciences, especially in our introductory astronomy courses.
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*Some friends of mine might argue on the charity point, so I’ll direct you towards the wonderful organization GiveWell, who are taking a good crack at it.
This post is a layperson’s explanation of my paper Choosing a Maximum Drift Rate in a SETI Search: Astrophysical Considerations. Seem familiar? This particular essay is cross-posted on the Berkeley SETI Research Center blog here.
Let’s do a thought experiment.
Imagine you’re out in space with your friend and they shine a green light at you. If your friend starts travelling towards you at a constant speed, that green light will appear a little bluer (called a blueshift) as the wavelengths of light get compressed. If they instead start travelling away from you at a constant speed, the green light will appear a little closer to yellow (called a redshift).
Now let’s take this a little further: imagine your friend starts at a standstill with their green light, and then starts accelerating towards you, moving faster and faster. What will you see? The light will start as green, and shift bluer and bluer as time goes on. This effect is called a Doppler acceleration, and it happens to any electromagnetic wave whose source is accelerating towards or away from you – including radio waves.
But let’s continue this analogy in visible wavelengths of light. Let’s say you’re looking for a flashlight from an extraterrestrial intelligence (ETI). We don’t know what color to expect – red, yellow, blue, purple, who knows what color the ETI have chosen. So we tell our computers* to search for bright spots in every color that our telescope can collect. But we have to be careful – if the color is changing throughout the observation, because of Doppler acceleration, the computer might miss it because it’s just looking for signals of a single color!
Okay, but why would the ETI’s transmitter (the radio equivalent of our flashlight from before) be accelerating in the first place?
Turns out, space is full of things that are constantly accelerating towards and away from us (radial acceleration). A planet orbiting a star is accelerating. A transmitter on the surface of a rotating planet is accelerating. A transmitter that’s orbiting a planet like a satellite is accelerating. Earth is accelerating around its rotation axis and around the sun as we try to take our data, causing the same issues via symmetry!
All of these effects stack, and cause a transmitter that is sending out a single wavelength of light to appear to change drastically over time.
In our new paper, we wanted to calculate exactly how drastically the wavelengths would change over time. We can tell our computers to search for these drifting signals through time, but we have to give them a maximum limit of how much drift to expect. So what’s the maximum?
To answer that question, we considered every planet in our solar system, every known exoplanet, all of the asteroids and comets in our solar system, orbits around main sequence stars, neutron stars, and even black holes. We calculated the fastest acceleration we would expect in each case, and what its expected Doppler drift would be.
In the end, we found that the searches for extraterrestrial intelligence in the past have used a maximum Doppler drift rate that was too small, leading to the potential for missed signals. Luckily, with the new guideline (200 Hz/s at 1 GHz, for those of you who want units) we should be able to catch signals from ETI no matter what the acceleration is like in their home system!
The new paper has been accepted to the Astrophysical Journal and is also available on the arXiv preprint server.
*there’s waaaay too much data for our team to go through it all by eye, so we have to write algorithms to find interesting signals for us
Welcome to my third and final post about Breakthrough Discuss 2019 (here’s Part 1 and Part 2)! It’s time to get ~meta~.
As scientists, we spend a good deal of our professional energy on conferences. We prepare (never early enough) for talks and posters, we spend packed days in conference rooms frantically networking and scribbling notes and eating pastries, and we build and leverage those professional connections and collaborations over time. Conferences are important. And that’s why conferences need to be equally accessible to all professionals in the field regardless of their career stage or identity.
In addition, we take days out of our very busy research, teaching, and outreach schedules in order to attend these events. Ask any scientist anywhere: neglecting your inbox for even a few days is a virtual disaster when you return. So these events need to be productive enough to offset the lost time, spent money, and additional stress of travel.
For both of these reasons, I wanted to reflect on the conference from a meta-level. How can conferences be more inclusive, and where did this one fail to be? How can we make more scientific progress in the couple days most conferences allow us? I don’t have full answers to these questions, but here are a few of my thoughts.
Questions are vital to a healthy conference. They help clarify things from presentations, inspire avenues for new work, spread knowledge and expertise, and create connections between people and ideas. However, we all know that most conferences run behind, so only 1-2 questions usually get asked per talk. And those questions, per Chelsea Troy’s world-changing blog post on caucus-style meetings, usually get asked by people who raise their hands the fastest and talk over anyone who tries to stop them. The worst part is: these questions are usually not even good.
As the conference progressed, I began to make a list in my notebook whenever a particularly useless question was asked. Then I grouped them into the following “Terrible Question Bingo” categories.
Terrible Question Bingo
Just wanted to shout out a couple things I loved seeing at Breakthrough Discuss 2019. We have a lot of work to do, but it’s not all bad!
I’m still distilling this useful/useless question dichotomy in my head, so keep an eye out for further discussions on the topic!
In summary: I learned a lot from Breakthrough Discuss 2019, and I had a great time. I think there are many ways to improve the atmosphere of the conference for future years, both in terms of productivity and inclusivity (which is also productivity by the way), and the best way to start that is by talking about it.
Welcome to Part 2 of 3 of my Breakthrough Discuss 2019 series (start with Part 1). This post focuses on concepts that I didn’t know before, pieces of information that caused me to change my perspective on something, and questions that I’m still thinking about post-conference. So without further ado:
One operative definition for intelligent lifeforms could be “physical systems who understand how the physical universe works”. As with any definition for life, refinements and counterexamples can be quickly dreamed up, but understanding and quantifying natural laws (physics etc.) is an interesting criterion. This was brought up by Sara Walker with the example of “anti-accretion”: the way that humans have sent mass up into Earth orbit from its surface, based on our understanding of the law of gravitation. Perhaps I’d add a caveat to this definition: “physical systems who understand how the physical universe works and use that to affect significant change in their environment“… but maybe that’s just the technosignature hunter in me!
An operative definition for life in general, put forth in the second panel, was “a unique chemical process with a boundary condition separating entity from non-entity”. Again, there are issues with it, but I like thinking about the “boundary condition” argument and, in the way of a good SETI scientist, wondering what it would look like if that assumption was broken. We definitely spend some time thinking about what would happen if, temporally, there was a gradient between non-life and life. But what if there was a spatial gradient? There’s a sci-fi short story in here somewhere…
We cannot accurately retrieve atmospheric compositions of exoplanets even if we have JWST and TMT observations without knowing the mass of the exoplanet first (degeneracies appear because of mass – log(g) – temperature – scale height relationships). I didn’t realize until this conference that the precise determination of masses would be so vital for atmospheric studies (ex. biosignature gas searches).
In one of the panel discussions, it was brought up that Earth life has an eerie tolerance for vacuum. Upon hearing this, of course, I immediately got excited. However, it was quickly pointed out that this is likely because vacuum-tolerance (and radiation tolerance) is related to the same mechanisms that protect against dehydration on Earth: very good DNA repair. So it’s not quite evidence for panspermia, but it does make me feel more optimistic about life surviving such a seemingly inhospitable journey in the first place.
But, to my surprise, it turns out that microbial communities and biofilms are far more important in thinking about how bacterial life survives than the analysis of a single microbial genome. The focus on single genomes is an incorrect simplification. Most bacterial strains cannot be cultivated in the lab because they are missing molecules from their original environment, a physical site of a certain structure to attach to, or another organism making something they need. If we ever send life elsewhere, we’ll need to send a full microbial community. This additional complexity is both beautiful and frustrating (to a non-biologist!).
Almost as a consequence of that realization, it’s also possible that Earth life may’ve spent too long adapting to Earth to be useful in a bioengineering (for ex. Mars terraforming) sense. Starting from scratch with synthetic minimal cells (customizable molecular machines that can be built with simple modular recipes) might be easier in the long run. These synthetic minimal cells could be pluripotent, could perform horizontal gene transfer, and could function as genetic circuits (biocomputing) or nutrient/chemical factories. I find not only the possibilities fascinating, but also the outlook of those performing this research; their synthetic cells are just little biochemical machines, and are not alive in any reasonable sense of the word. Oooh, biology is squishy…
Microorganisms are not primitive, they have as much evolutionary history as humans and are exceedingly complex, hardy, and good at what they do. I’m definitely guilty of underappreciating them, and I think this conference is a good reminder that non-intelligent, single-celled life is still fascinating.
With a sample size of one, it’s hard to know what properties of life are universal, and which are just funny terrestrial adaptations or random consequences of our particular evolutionary path. For example, are assumptions that all life must have a backbone, a motor, and a ribosome just physics… or terrestrial arrogance?
Let’s assume abiogenesis is pretty hard and happens slowly and rarely. Then the earlier life is detected on Earth, the more attractive panspermia becomes, which is a cool test! Except it assumes abiogenesis is hard, which is a pretty big assumption.
The rate at which we see life in the universe is a product of the rate at which it emerges and the rate at which it migrates. High origination negates the need for panspermia as a theory. If panspermia did happen in this scenario, any place that the migrating life landed would already be inhabited by lifeforms, thus leaving the rate at which we see life in the universe unchanged. On the other hand, high migration rates can spread life through the universe even if origination rates are low, so panspermia could provide astrobiologists an escape hatch from a tough abiogenesis situation.
At this conference I learned that we are growing embryonic stem cells from humans, apes, etc. into “organoid” brains. Not only can we grow these organoids, but we can also use CRISPR to see what happens to them if you modify parts of the genome. Turns out, if you use CRISPR to take out the NOTCH2NL gene, the organoids develop small and stunted – NOTCH2NL appears to be responsible for macrocephaly. It’s amazingly cool that we can determine this experimentally. On the other hand, these organoids produce some amount of electrical activity. Messing around with brain organoids that are evidently active without knowing much about the development of consciousness/intelligence seems reckless. Admittedly, I don’t have any background knowledge here, so maybe I’m making an ethical quandary out of a molehill, but I’m still very surprised about the lack of a single slide about the ethics; it wasn’t in the dialogue at all.
A large, fun part of the conference was focused on the possibility that an extraterrestrial intelligence could have seeded the Earth / solar system with life long ago, and left us a message hidden in our genetic code. It sounds very sci-fi, but as with all things sci-fi, there’s no harm in giving it some methodological scientific thought.
However, messages hidden in genomes require a lot of assumptions. ETIs have to exist. Things have to be able to reasonably move from one stellar system to another. An ETI will need biological mastery greater than we have, and will need to have some motivation for bio-based messaging in the first place. They will also have to determine that the best possible way to message is through genetic code (this feels like the weak part to me, see next paragraph). And they will have to assume that living systems are inherently narcissistic in a way, to reasonably want to leave a message “inside” instead of “outside”. This large string of assumptions makes me pretty suspicious about the prospect.
The big scientific hurdle for bio-based messaging is mutation. Mutations happen a lot in biology. In fact, standard DNA codons have adapted to this by having a very specific set of characteristics to minimize the damage caused by random mutations. In other words, a mutation in the code rarely leads to a different amino acid being produced because there’s a lot of redundancy built in. So mutations happen, and then they stay, which is bad for messaging because it will scramble your message over time. On the bright side, we are already able to code something that will instantly stop replicating when a mutation occurs by immediately leading to an “error” or empty codon. This can currently be done with the production of only 15 amino acids, so a limited palette compared to what life has, but it seems possible that bio-engineering could lead to humans being able to leave a bio-based message in this way.
Instead of looking for “hello there” or pi or whatever else hidden in our genome, some suggestions have been made about looking for a “left turn” in our evolutionary pathway for no apparent reason. So something SETI-like to look for in a genome might be an infusion of information in the past that seems to hold a bad assumption and come out of nowhere (ex. a large piece of junk DNA coding for genes important for survival in an atmosphere that Earth has never had). I don’t quite buy this argument, it seems rather contrived, but I like the idea of it.
The discovery of a carbon-based lifeform inside the solar system would not be enough to prove a second genesis of life, but, according to the second panel, the discovery of a lifeform with ribosomes would be. At what point between those two things do we stop expecting convergent evolution to be a reasonable explanation? I would love to get more input from biologists on this idea!
As soon as you produce a single piece of waste on a spacecraft, you have introduced a rate-limiting factor. We are working on ways to turn human waste into plastic, with the eventual goal of a 0 waste spacecraft. Even then, however, what happens if you forget something or encounter new and unforeseen needs on your journey? Do we bring DNA with us? Or chemicals/molecules/bases as building blocks? Or protons and electrons as building blocks for those?
Recently I’ve been mulling over the idea of domains in which a single bad actor can ruin everything. I have the following list so far:
I’m trying to think about the synergies in what seem like a very diverse set of endeavors, but this is probably a project for a game theorist, not me!
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Part 3 of this blog series will provide perhaps my most important conference summary – a look at some meta-conference commentary. How can we make future conferences more productive and more inclusive? Stay tuned!
Over the past few days, I’ve been attending the Breakthrough Discuss 2019 conference in Berkeley, California. In general, the conference focuses on space exploration and the search for life in the universe, and this year’s theme was “Migration of Life in the Universe”. As of a few months ago, I’ve been trying a new strategy of condensing my conference thoughts into blog posts in order to record and order my thoughts and share the things I learned. I’m already behind – my AAAS 2019 series is unfinished, first post here. This time, however, I’ve decided to publish all three of my posts about Breakthrough Discuss at once.
This first post is a scattershot of interesting one-off notes: facts and figures that I learned, papers and resources that I will refer to in the future, quotes I liked from the speakers, and new jargon that I absorbed.
Numbers I learned:
Facts I learned:
Papers I’m interested in reading:
Resources I became aware of:
https://learning.qagoma.qld.gov.au/artworks/map-of-technological-ethics/
Great quotes:
And my personal favourite:
New jargon I learned:
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Part 2 of this blog series provides a more in-depth look at some conceptual ideas that I’ve been thinking about since the conference!
Welcome to Part 3 of my AAAS 2019 conference series! For more background on the conference, see the first post in this series.
This post will be structured a little differently because the event was a topical lecture instead of a multi-presenter panel. This research was partially conducted by and entirely presented by Dr. Susan Goldin-Meadow, Professor of Psychology at the University of Chicago.
New Jargon I Learned:
Overall Theme: There is a fundamental difference between gesture and communication, even if that communication is being accomplished via signing. Gesture is a more foundational link to how our brains are actually processing material than speech, and gestures both reflect and change what we know.
3 Interesting Study Topics in This Field:
Fun Fact I Learned: Gesturing is natural even for people who are blind (and have never seen another person gesture in their life) or deaf (in an act entirely separate from signed communication).
Application: These studies (especially the one about gesture-speech mismatches) can help us improve education. Gesture lets us express ideas in an imagistic manner, while words let us express ideas in a categorical manner. Having an understanding of a topic on both levels will lead to deeper learning. From what I gathered here, allowing students to learn kinesthetically (ex. practicing explaining topics on a blackboard, a setting with natural gesturing) may prove more effective than solely stationary methods.
Here’s the second part of a multi-part series on the things I learned from the AAAS 2019 conference. For more background on the conference, see the first post in this series.
Without further ado, here are some fun facts, resources, themes, solutions, and jargon that I learned at AAAS about…
Fun Facts I Learned:
Resources I Found:
Good Quotes:
New Jargon I Learned:
Short-Term Solutions:
Overarching Themes:
Best Moment: Learning that because violinists use one hand (their chording hand) more than the other, the “violin” region of the brain on the dominant side grows to be larger – in proportion to the experience of the violinist! The regions that correspond to the thumb and pinky finger (we have the resolution to see this!) literally grow farther apart in the brain, and there’s a correlation between that distance and the number of years that the violinist has been playing.
Personal Action Items Inspired by These Talks:
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This session had more of a panel format, and I didn’t catch the names of everyone involved, but here are the names of the three speakers on the program.
Presenters:
Here’s the first part of a multi-part series on the things I learned from the AAAS 2019 conference. AAAS is the American Association for the Advancement of Science (not to be confused with the astronomers’ AAS) which works on science policy, education, advocacy, and diversity and inclusion issues. I primarily attended the conference as the co-leader of Penn State’s Women and Underrepresented Genders in Astronomy Group (W+iA) along with my colleague and fellow co-leader Emily Lubar.
Originally, I was going to have each day of the conference be a separate post, but there was far too much information in each day to make that in any way tractable. So instead, I’m breaking it down by topic – this particular topic only had one session, but future posts may combine multiple sessions on the same topic.
Here are some fun facts, resources, themes, solutions, and jargon that I learned at AAAS about…
Fun Facts That I Learned:
Resources I Found:
Overarching Themes:
Short-Term Solution:
Long-Term Solution:
New Jargon I Learned:
Best Moment: According to Bot-O-Meter, my heavily themed Twitter account (@SETIPaperReacts) is probably a bot – 45% “Complete Automation Probability”. I only wish I could automate my paper reading!
Other Uncategorized Thoughts:
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It’s very hard to keep track in my notes of exactly who said what, but I want to give credit to the three presenters in this session, listed below!
Presenters:
If you are a research group that wants time to observe with the Hubble Space Telescope (HST), you need to submit a proposal to the Telescope Allocation Committee (TAC). Once a year, the TAC receives, in a usual cycle, proposals for 4-5X the amount of time it actually has to offer [1]. Hence, the allocation process.
But the allocation is not perfect because it, as with science in general, is a human endeavor; as much as some would like to deny it, TACs are a subjective process. Studies have shown that if two different panels review the same set of proposals, they usually only agree on about 50-60% of them [3]. Even more disconcertingly, the HST TAC consistently under-accepts proposals with female PIs, on average about by about 5% compared to proposals with male PIs [3], which comes out to a 6-10 proposal offset [4]. If no systematic bias was present, we would expect this percentage to fluctuate, some years favouring female PIs and other years favouring male PIs. But in the ten years studied by [3], the proposals with female PIs were under-accepted every time.
A more detailed look at the data (done by [3]) reveals trends which may or may not be meaningful, some more surprising than others. The offset is unaffected by the gender distribution of the review panel or the geographic origin of the proposal. The rates for recent graduates are more comparable; senior female PIs bear the brunt of the selection bias. The relative number of proposals with female PIs is increasing over time (due to demographic shifts), but the Large proposal category is disproportionately dominated by male PIs. Stars and cosmology have the worst acceptance offsets, while galaxies are more equal. The higher the proportion of senior members on the panel, the worse the acceptance rates for proposals with female PIs, while panels with junior members tend to have smaller offsets.
The most important outcome of this study, though, is this: the offset is only slightly present before the panel discussion phase of the proposal review, and suddenly spikes in the final selections by the TAC [3]. So what’s happening in these panel discussions that’s causing the discrepancy?
Before proposal Cycle 21, the name of the PI was all over a proposal submission: in the name of the file and in the first words on the proposal itself. In addition, every member of the proposal was identified by both first and last name, allowing the reviewers to assume (explicitly or implicitly) the gender and ethnicity of the PIs and co-Is.
Once the Space Telescope Science Institute realized that there was systematic bias pervading their review process, they took some small steps to try to fix the issue. In Cycle 22-23, they removed the PIs name from the filename and the first page, and identified the PIs and co-Is by first initial and last name only (removing the first names). In Cycle 24-25, they listed the authors alphabetically, still without first name, with no PI identified.
These measures didn’t solve the problem, as shown in the figure below.
According to the data, the remedial measures in Cycles 22-25 didn’t work, and we knew that the problem had to be in the panel review itself. So STScI had Dr. Stefanie Johnson of the Leeds School of Business at the University of Colorado and her graduate student Jessica Kirk sit in on the HST Cycle 25 TAC, with an eye on applying the results to the first set of JWST proposals (sad). The results of the report were surprising in illuminating the depth of the problem, if not the breadth.
According to their report, almost 50% of the discussions in the HST Cycle 25 TAC included a focus on personnel that detracted from the science [2]. Overheard statements from the panel reviews included “He [the author] is very well qualified” and “My group has benefitted a lot from previous work from this team” [5]. The panel members even pulled up research articles and noted citation counts from the groups submitting the proposals [5].
With this new information, STScI formed a Working Group on Anonymizing Proposal Reviews (APR) to make changes for Cycle 26.
This year’s TAC was a little different. It was four months later than usual (causing the submission of 489 proposals and a skyrocketed oversubscription rate of 12:1 [1]), it focused on bigger proposals, and it implemented a dual-anonymous system proposed by the APR Working Group.
The dual-anonymous system means that not only do the proposers not know who their reviewers are, but the reviewers don’t know who their proposers are. This is the first time this has been done for a large-scale proposal in the physical sciences [1]. The Working Group also had a few specific suggestions to make the process run as smoothly as possible. They added “levelers” to the discussions: personnel whose job it is to step in if the discussion veers away from the science itself [1]. They also added a “Team Expertise and Background” section that is only made available after the rankings are finalized (in order to preserve anonymity). At the stage where the TE&B section becomes available, proposals can be rejected if it’s determined that the proposers don’t have the necessary resources and experience to carry out the proposed science. But the rankings themselves cannot be changed based on the new information, except to pull proposals out of the list if they don’t seem feasible [1].
Some criticisms of the new system, and replies that address them, are shown below:
“This won’t work for astronomy because the field is too small – we’ll be able to tell who it is anyway!”
Studies from other fields suggest that the PIs identity is still secret 60-75% of the time [2]. And even if it isn’t perfectly anonymous, it shows a dedication to improvement and equity.
“How will we properly assess if the authors have the resources and experience they need to carry out the proposed science?”
This is a fair criticism, and was the main reason that the final TE&B stage in the above review process was added.
“Won’t this make it harder for me to get time?”
The same amount of time is being given and thus, the same amount of proposals are being funded. It works the same as always: think of a great idea then write a great proposal [2]. You’ll only see a change in your outcome if you were coasting on your privilege and reputation instead of your actual science in the first place.
This cycle’s TAC met in October 2018 to try out the new system. Only one proposal was thrown out because it was anonymized incorrectly – it seems that the proposal writers adapted well to the new guidelines [1]. The panelists said it was “almost liberating” to focus on the science instead of the people, and the “levelers” only rarely had to intervene [1]. In the end, no proposals got rejected during the TE&B phase: all highly-ranked proposals were still considered feasible after their groups’ expertise and resources became known [1].
The topics of the selected proposals were as wide-ranging and interesting as ever and included gravitational wave follow-up, constraining cosmic distance scales, Jupiter’s magnetosphere, habitability near Proxima Cen, mass outflows from Betelgeuse, and mapping the Local Group.
So did the dual-anonymous system actually diminish the acceptance gap? I’ll let the numbers speak for themselves.
It has been shown in other fields that dual-anonymity decreases bias related to gender, institution, prestige, age, and nationality [2], and the graphs above show first-impression evidence that this is true in astronomy as well. Given these preliminary results, the Space Telescope Users Committee is recommending that the changes to the process stay – the next TAC meeting (June 2019) will keep the same dual-anonymous format [1]. Even more excitingly, the success of this program might make the process standard for the JWST TACs as well [2]!
The final success of these procedures will be judged on other factors as well as just pure acceptance rate: productivity, diversity, gender balance, number of new proposers, and the success rates of junior and senior PIs will all be examined in the future [2]. The final impact may take a few years to determine, given our reliance on publication and citation rates as proxies for success.
Knowing this, we can’t just be happy that the future of astronomy proposals look more equal – we also need to extrapolate back into the past. The number of accepted proposals was a statistic that supposedly marked an “objectively” good researcher, but now we know that the number is implicitly biased. Faculty hiring committees, for example, will now need to take this into account when comparing applicants. Although many of us knew that this problem existed before now, having the results from Cycle 26 just makes it crystal-clear that we were not comparing scientists on a level playing field.
As a side note (this is basically a “Discussion” section now), it has been shown that men and women take advantage of optional dual-anonymous review for Nature journals at the same, low rates [6]. This may be surprising on the surface, but can be attributed to a perception that the deliberate selection of a dual-anonymous procedure option could backfire on the author [6]. The solution to this problem is to stop putting the onus on the authors who are already disadvantaged by the system and to make dual-anonymous procedures standard in science.
I hope it’s pretty clear why this all matters, but let’s be explicit. Gender diversity leads to greater innovation. The dual-anonymous system focuses attention on the quality of the science and creates more equal opportunities for HST [2]. If you are still not convinced, Reid calls the constant acceptance offset a “canary in the coalmine” [4] that proposals are not being compared on their actual merits: that the process is riddled with implicit biases that undermine the goal to produce the best science. We ignore the canary at our peril.
[1] Reid, N. (2018). Hubble Cycle 26 TAC and Anonymous Peer Review. STScI Newsletter, 35(4). Retrieved December 16, 2018, from http://www.stsci.edu/news/newsletters/pagecontent/institute-newsletters/2018-volume-35-issue-04/hubble-cycle-26-tac-and-anonymous-peer-review.html
[2] Garnavich, P., Johnson, S., Lopez-Morales, M., Prestwich, A., Richie, C., Sonnentrucker, P., . . . Reid, N. (2018, May 14). Recommendations of the Working Group on Anonymizing Proposal Reviews. Retrieved December 16, 2018, from https://outerspace.stsci.edu/display/APRWG
[3] Reid, N. (2014). Gender-Correlated Systematics in HST Proposal Selection. Publications of the Astronomical Society of the Pacific, 126(944), 923-934. doi:10.1086/678964. https://lavinia.as.arizona.edu/~gbesla/ASTR_520_files/Reid2014_HSTStats%20copy.pdf
[4] Reid, N. (2017, December). HST Proposal Demographics. Presentation for the Anonymizing Proposal Reviews Working Group. STScI. https://outerspace.stsci.edu/display/APRWG?preview=/11665517/11667175/proposal%20statistics.ppt
[5] Johnson, S. (2017). Going Blind to See the Stars: Removing PI Name Decreases Gender Bias in Hubble Proposal Ratings. Presentation for the Anonymizing Proposal Reviews Working Group. STScI. https://outerspace.stsci.edu/display/APRWG?preview=/11665517/11667176/Hubble%20Presentation.pptx
[6] Enserink, M. (2017). Few authors choose anonymous peer review, massive study of Nature journals shows. Science. doi:10.1126/science.aaq0322. https://www.sciencemag.org/news/2017/09/few-authors-choose-anonymous-peer-review-massive-study-nature-journals-shows
[7] Leitherer, C. (2018, November 13). Cycle 26 Summary and Plans for Cycle 27 [HST TAC Summary Document]. http://www.stsci.edu/institute/stuc/fall-2018/HSTTAC.pdf
Dr. Sofia Z. Sheikh 
