Katie Bouman, the computer scientist behind the first black hole image
bbc.com
bbc.com
> Very long baseline interferometry (VLBI) is a technique for imaging celestial radio emissions by simultaneously observing a source from telescopes distributed across Earth. The challenges in reconstructing images from fine angular resolution VLBI data are immense. The data is extremely sparse and noisy, thus requiring statistical image models such as those designed in the computer vision community. In this paper we present a novel Bayesian approach for VLBI image reconstruction. While other methods often require careful tuning and parameter selection for different types of data, our method (CHIRP) produces good results under different settings such as low SNR or extended emission. The success of our method is demonstrated on realistic synthetic experiments as well as publicly available real data. We present this problem in a way that is accessible to members of the community, and provide a dataset website (vlbiimaging.csail.mit.edu) that facilitates controlled comparisons across algorithms.
What strikes me as really amazing is the cross functional nature of these modern achievements. I did not realize that this image was created with statistical image models and a Bayesian approach.
Also, this link included -> http://vlbiimaging.csail.mit.edu/ introduces the field and offers a good explanation for those interested in learning more:
> Imaging distant celestial sources with high resolving power requires telescopes with prohibitively large diameters due to the inverse relationship between angular resolution and telescope diameter. However, by simultaneously collecting data from an array of telescopes located around the Earth, it is possible to emulate samples from a single telescope with a diameter equal to the maximum distance between telescopes in the array. Using multiple telescopes in this manner is referred to as very long baseline interferometry (VLBI).
Not trained in this field, but this reads like a certain mistype. Shouldn't resolution increase with telescope diameter?
It took me several rereads and reading the comments here to understand that we want low numbers for angular resolution.
I suppose it's fairly obvious for one well-versed in optics, but to the layman (like me) it's initially opaque.
Reconstructing Video from Interferometric Measurements of Time-Varying Sources https://arxiv.org/abs/1711.01357
So maybe we will also see a video of a black hole, soon.
"Then they spent the two years parsing literal truckloads of data, some of which had to be shipped on hard drives from the South Pole and defrosted outside a supercomputer facility at MIT."
https://www.washingtonpost.com/science/2019/04/10/see-black-...
I'd love to read more about this if anyone has an article with more details.
Found it through this pdf: https://fskbhe1.puk.ac.za/people/mboett/Texas2017/Doeleman.p...
Do you understand Katie's explanation?
They have a sparse set of data that is part of an image. They have trained a model to look at the sparse set and make an educated guess about what the full image looks like. They do this by feeding it full images.
The full images you feed into the model thus have an effect on the final image generated. In order to see how large that effect is, they trained different versions of the model with different sets of complete images. Some were images of what we thought a black hole looked like. There is potential that this heavily influences the model and ensures that the output looks like what we expect it to, even if that isnt actually true.
They also trained the model with non-blackhole images. Since the output of the model was approximately the same, this indicates that the resulting output picture doesnt look like what we think a black hole looks like just because it was trained with black hole images. It likely really looks like that.
The model doesn't need to be told what a black hole looks like. The sparse measurements combined with knowledge of how sparse data can be combined to form a generic image is enough. The model learned that the sparse data is not likely pure noise, instead there are shapes and lines and gradients that relate the sparse data points to each other.
Her analogy of sketch artists is good. If you have a functionally complete description and give it to 3 sketch artists from different cultures who are used to different looking people, they will still draw the same person. However if your description isnt actually detailed enough, their sketches will significantly differ as they use their existing knowledge and bias to fill in the gaps with what they think is likely.
>They also trained the model with non-blackhole images. Since the output of the model was approximately the same, this indicates that the resulting output picture doesnt look like what we think a black hole looks like just because it was trained with black hole images. It likely really looks like that.
If you are feeding non-blackhole images in and getting blackhole results out, wouldn't that be indicative of an over-trained model? Her other analogy was we can't rule out that there is an elephant at the center of the galaxy, but it sounds like if you feed a picture of an elephant in you'll get a picture of a blackhole out?
They also showed that when they fed in simulated sparse measurements based on real full images of generic things, they got back fuzzy versions of the real image. [1] So if you put in a sparsely captured elephant (if for instance there was one at the center of the galaxy) you'd get an image of the elephant out, not this black hole.
To complete the artist analogy, imagine that the suspect that is being drawn by each artist is some stereotypical American. The description given to the artists doesnt say that, it just describes how the person looks. One of the three sketch artists is American and the others are Chinese and Ethiopian.
If the American draws a stereotypical American, how can you be sure that the drawing is accurate and thats not just what he assumed the person would look like because everyone he has ever seen looks like that?
You look at what the other two draw. If they both draw the same stereotypical American, even though they have no knowledge of what a stereotypical American looks like, you can be pretty sure that they determined that based on the description provided to them. The actual data.
They did still likely utilize some of their knowledge about what humans in general look like though. This is analogous to how the model uses its training on what a generic image looks like. For instance, maybe several sparse pixels of the same value are likely to have pixels of that same value between them. The model puts things like this together and spits out a picture of what we think a black hole looks like even though its never seen a black hole before.
Did they try to feed random noise into their trained image builder?
I suspect that the output of that trained image builder is always the same "black hole", even with random noise as an input.
I think if you trained with random noise you would get random noise output.
So I assume they're simulating what an input would look like of, say, a planet or astroid or elephant or whatever, given that it was viewed through the relevant type of sensor system. Then when they feed in the black hole sensor data, they get pictures that look like the black holes we imagined. Even if we never told the model what a black hole looks like.
What does training mean?
I thought that the training means to adjust Neural Network until it learns to convert our input into expected output of "complete image".
But if thaining means to teach the model to produce expected "complete image", then how is it possible that "the output of the model was approximately the same" [for different training "complete image"s]?
The output images are approximately the same because the model is "looking" at training images at a lower level that we do. The talk says they chop the images up into small pieces. So the model never "sees" the full shapes that are in the full images. It only sees small local features. I guess it turns out that these smaller pieces are pretty generic in that they are common between images of black holes and everything else. The curve of an elephant trunk looks similar to the curve of an event horizon if you cut it out in a small enough piece.
Perhaps if they didnt do this step, then the model would be more sensitive to the images its trained on.
They don't make a habit of posting the shitty TEDx talks to the main channel, I'm guessing. (And there's plenty of those.) This is definitely high quality relative to most TEDx talks, so I understand why it was upgraded.
If Katie was a man do you think people would be going through git histories and their published papers trying to determine if she is being over-credited for her achievements?
Edit: I just checked Twitter, apparently there are thousands of idiots who believe this "850,000/900,000 lines written by Andrew, therefore he wrote the algorithm" narrative. It's amazing how willing people are to eat up a low-hanging narrative as long as it confirms their world-view. All it takes is a very crude understanding of how software development works to see through this narrative.
[0] https://www.reddit.com/r/unpopularopinion/comments/bbykvf/ka...
[1] https://www.reddit.com/r/pics/comments/bbuvff/this_is_andrew...
[0] https://www.reddit.com/r/pics/comments/bbql1i/this_is_dr_kat...
> Andrew Chael wrote 850k out of the 900k lines of code. He was also the leader of the project. Michael D. Johnson wrote 12k lines of code. Chanchikwan wrote 5k lines of code. The woman? Only wrote 2.4k lines of code.
It's a little bit unbelievable that the author of this comment (/u/dragonballcell) nailed all of these fine-grained details (red herrings, perhaps?) and yet glossed over an incredibly important and superficial/trivial detail: that Andrew Chael did not "write 850k LOC", he generated hundreds of thousands of lines of data and committed them to the repo. Needless to say, I think this whole drama is incredibly pointless.
You might as well credit the Linux operating system to only a single man, whose effort is certainly largely responsible, but for who also does not in any way represent the whole of effort.
It's the ship of Theseus all over again.
That said, if Katie was a man, her story would not be as groundbreaking in a social context, and thus she would not be as celebrated.
Can you link the HN article with the "Mohawk NASA dude". Searching on "Mohawk NASA" gave me a 1 point article that didn't get a single upvote.
Searching on "Bobak Ferdowsi" gives zero articles on HN, and I could not find any article where even comments were celebrating the achievements of Bobak Ferdowsi, and obviously no 832 point upvoted ones.
No, I must conclude that there is no articled named "Bobak Ferdowsi, the scientist behind the Curiosity rover", and definitively not one that got just as much celebration as this one.
I have no idea why people are doing this to Dr. Bouman, if it's gender related or not. Just stating my experiences.
Just so I'm fair, my GitHub does suck.
Some companies addressed it directly and some let it happen. It also was not every co-worker at every job. Just a select few personality types mainly.
It's not that they don't deserve their fair share of credit, to be clear. It's that they do not deserve the level of overwhelming credit the media intentionally tries to bestow upon them, to create an idol that sells / generates clicks.
You pretty well see it in every thread regarding those two people. The hype train tries to give them credit, whether the media or fans, and other people get annoyed by it and call it out because it's obviously ridiculous to so overly credit such vast accomplishments requiring thousands of contributors to a given individual.
On the other hand, looking at git histories is basically how the social parts of engineering (e.g., money and power) at a place like Google works, at its fundamental level.
This has persisted for a very, very long time. I still remember when people would comment things like, "I worked with so-and-so unorthodox former Google employee, and he didn't commit code."
There are a lot of Googlers on HN. There are a lot of people who work at places that culturally align themselves with how that company runs.
It probably has something to do with why some women feel underpaid or unwelcome at these places.
It definitely has something to do with people commenting things like, "So is this the case of the product manager taking credit..." The tension between the product manager who "didn't do anything" and the engineer who "did all the work" and how the "org" sees that and measures "performance" are all swimming in the back of HN people's heads when they snipe some random academic.
Settling the score in a way so reductive is extremely appealing. But at least in duels, the other person gets to fire back.
In my experience, people don't start looking into these things without some other suspicion. In a work setting, that would be things like impressions of poor productivity, claimed output not matching perceptions of competency, etc. But those involve a ton of data points, based on direct interactions with the person. In this case, the article gives us the following demographic data points:
- 29 years old
- Woman
- Computer Science doctorate from MIT
- Assistant professor of computing and mathematical sciences at the California Institute of Technology
Which of those data points suggests that her work output should be questioned?
I think people let their own personal biases destroy their impartiality. Replace her name with Musk, algorithm with science/engineering, and 'image of a black-hole' with reusable rocket. The article would (and does) read like something posted by a sycophantic fanboy. It wouldn't be doing him any favors, and certainly isn't doing her any favors. However, I also do not think this article is representative of her in any way, shape, or form.
For instance it tries to frame things in the most narcissistic way possible. They found one image posted where the developer stated, "Watching in disbelief as the first image I ever made of a black hole was in the process of being reconstructed." So she made that image. Not a team, not the project of a coordinate global effort, no - she made that image. Even the image framing itself is indicative. It's a tiny out of focus image of a laptop and a giant in focus image of her with an artificial pose. The article itself continues with a similar narrative in all the eye-catching spots such as the headline and image captions: "Katie Bouman designed an algorithm that made the image possible" "Katie Bouman: The woman behind the first black hole image", and so on.
But as mentioned, I doubt this is indicative of the developer herself. She's probably just being used by the media. She's attractive, young, and has the right genitalia = stories that'll get a million clicks and shares = $$$. When you actually read the very small number of quotes from her, they seem much more realistic and in stark contrast to the media sensationalism:
- "No one of us could've done it alone. It came together because of lots of different people from many different backgrounds."
- "We're a melting pot of astronomers, physicists, mathematicians and engineers, and that's what it took to achieve something once thought impossible".
Also if she was a man her story and contribution wouldn't be as sensationalized as has been done.
Well, I take part of that back. He did have some personal pieces about "he's the guy that's a bully of the project" (when he took a personal hiatus from the project)
So yes, that happens a lot.
>to the exclusion of the algorithm designer and the primary software author?
How can you possibly infer that from a git history?
I mean hard to imagine such a large project being taken up, for the benefit of public being able to see a picture of the black hole.
Would this kind of multi telescope effort be capable of producing surface images of extra solar planets for example?
And yes, this is one way of representing the data. I'm not sure exactly what your question is though, as actually getting this data is really important to confirm a variety of theories and also to potentially open up new avenues for investigation. And this cost orders of magnitude less than Hubble, whose purpose was also to generate photographs, seeing as how they simply connected together existing radio telescopes.
The point was to demonstrate that this technique is feasible. Now they can use it to image all sorts of other stuff and learn lots more.
So a photograph.
Is it wrong to say this is a logical improvement, extension of radio interferometry?
Or gather data that will help us study blackholes?
Because the press is largely focusing on the picture and not telling much else detail.
And is Boumans contributions to do with the making of this image?
As I understand it, the notability of the project is that it found a novel way to process data from coordinated data collectors scattered around the earth into a single coherent data set (with more resolution than any single collector could gather).
Katie's paper on VLBI reconstruction: https://arxiv.org/abs/1512.01413
This is how I learned about the topic and I think it's well suited for computery folks, since it was published in CVPR.
Similarly the title suggests she worked alone on the project. Which seems exceedingly unlikely given the need for telescope time and computing time and the wide range of disciplines I imagine the project covers ... did she work alone. That must be almost unique in experimentalism nowadays?
So I'm certain those authors did their part, so maybe yes, I should have linked this as "Bouman et al." but I wouldn't expect this to be six equal contributions either.
That all being said, she's certainly standing on the shoulders of a pyramid of giants there.
Edit: to the people downvoting the parent, maybe explain? I didn't take this as a bad faith comment. It can be genuinely confusing to someone who doesn't know the ins and outs of academic attribution...
It's interesting considering how many modern scientific endeavors are dependent on new innovative algorithms, software, and computing techniques in both experimental and theoretical work then its frequently just hand-waved away as "technology."
I'm not saying such contributions (typically, though they can,) lay groundwork for an experiment or theory in another domain, but I am saying active CS involvement/expertise is typically critical to many scientific endeavors' success these days. If a project is interdiscipinary, there's probably a computer scientist on the team helping out.
I think society implicitly assumes that there has been a tone of people backing up a single individual towards their main achievements and that the individual is humble enough to know and to try - ever so slightly - to show appreciation.
Somehow though my facebook feed is already littered with images saying she was single-handedly responsible and no one's talking about her.
Huh, I wonder how accurate this is. All the code is beyond me in any case, I'm in no position to judge the relative value of any of it.
* achael 566 commits 850,275 ++ 131,044 --
* klbouman 90 commits 2,410 ++ 1,265 --
However, at least at the level of reading the commit messages, Katie's are pretty math heavy:
"fixed bug in the fake briggs weighting"
"starting to fix chirp problems with polrep"
"made it possible to do a min uv cut on closure phase when adding it a..."
While Andrew's lean frequently toward code maintenance:
"updated some docstrings in imager_utils"
"moved imgsum to plotting.summary_plots"
"modified README"
That said, Andrew and others seem to have pretty good insight too.
But what could possibly qualify you to say that "Andrew is definitely smart (smarter than an average HN user) and his code is very important"?
There are no woman scientists, science has no gender.
The article is sexiest not people who are curious what Dr. Bouman actually did to be honored to mention in BBC article.
Do people like Linus deserve less credit now that he isn't the leader on the commit scoreboard ?
Writing code is easy, figuring out complex algorithms is something very different, and does not require coding knowledge
one commit with 524,306 additions. adding a model.
If I read it right, she mentioned and praised her team as well.
In particle physics, these practices evolved over decades, when specific individuals tried to claim credits for discoveries in an unfair way(Nobel dream by Gary Taubes gives a beautiful account of this). Many particle physics collaborations now have detailed constitution and guidelines on what images/graphs they can show to the public. Someone who first made the first Higgs mass plot which shows a 5 sigma evidence of Higgs observation could not have leaked that plot on social media.
However this narrative is inspiring and perhaps motivate many young woman to take up careers in science and promote a more welcoming atmosphere for women in STEM.
[1] https://cdn.cnn.com/cnnnext/dam/assets/190410153403-katie-bo...
https://www.bbc.co.uk/iplayer/episode/m00042l4/how-to-see-a-...
Jeez why the downvotes? It's a legitimate question I had.
For the people questioning if she’s receiving unfair attention because of her gender they view you comment as an attack on the establishment ala: “How dare they exclude her!? Is it just because she’s a woman?” And downvote you. For the people arguing that her media coverage is being unfairly criticized because she’s a woman they view your question as an attack on the assertion that she deserves the attention so they downvote you.
In either case I think it’s interesting to ask why the proclaimed “woman behind the image” wasn’t there for the unvailing of the image.
She’s not an astronomer?
I am a postdoctoral fellow with the Event Horizon Telescope and will be an Assistant Professor in the CMS department at Caltech beginning in 2019.
https://www.wsj.com/articles/computer-scientists-play-key-ro...
<sarcasm> I just wish they had used a camera from this century </sarcasm>
https://github.com/achael/eht-imaging/graphs/contributors
I didn't realize this was public code.
It looks like one "achael" is the author of this, though.
Never have men at large objected to such bias when women have cited theories and concepts discovered by men to publish papers and win medals in the field of mathematics. That is something naysayers should ponder over.
All the documentaries, autobiographies, and famous books that peered deep into the lives of those inspirational people always give proportionate credit to those contributors of success either by these people or the authentic researchers. Katie was no less enthusiastic when it was her turn.
But these news agencies play with people's emotions, desires,aspirations, etc. These news agencies are capitalistic and optimize over consumerism. These news agencies are shameless whores to betray the principles of intellectual honesty and journalistic ethics in dissemination of facts by kowtowing to the appeasement of the disgruntled - who happen to be majority of their viewers.
But? We, the layman, are hapless to (1) gain knowledge from immediate sources (2) draw immediate conclusions from these sources. We can't be blamed for not putting efforts to gain complete picture or check the veracity of middlemen called the media. We run forward the self fulling prophecy originating from media. The trust was put in reputed media and that is why the media should care for its reputation. That trust was put in the media because it was touted as fourth pillar of democracy who can't commit hypocrisy in its main endeavors to expose the truth.
Whereas otherwise, the organization Katie Bouman is working, official representatives such as MIT blogs, and TED talks have all credited to the development of original algorithm, though when it was at nascent stage, to THE Katie Bouman, while at the same time to her team for handling in subsequent parts.
I salute her. With relevant degree and using her education in imaging black holes, she set the discourse of the main branch that others picked up. If the idea and algorithm germinated in her mind, she should get credit for it, simple. All she needed is few people to delegate implementation of her ideas or modify it for sustenance. If somebody furthered her ideas enough that it can be versioned as 2.0 or 3.0, then they get equal credit and status as her in final mission[1]. She can patent her invention rightly for conjuring the initial stages of algorithm using all of her own cognitive capabilities.
But we should go only so far. Even women aspirants will get disheartened and show recidivism by wrongly strengthening the bias that they are somehow less capable in attaining pinnacles of STEM, when they learn that the achievements of women in reality is not what media portrays. This is why I consider the twitter photo of her being placed aside Margaret Hamilton as the efforts are no way comparable ceteris paribus.
Moreover, if lack of minority role models is enough of a reason to discourage that aspiring minority from their passions, then it would be no less effective in discouragement of non-minority's passions when there is lack of attention and acknowledgement to non-majority's achievements. I mean how did Katie meander through her success to begin with, if there were no role models to her in the field she is working, in the first place?
People say that men had plenty of men in annals of history to look up to, but I'd contend that women aren't in anyway stopped to take inspiration and pique their curiosity in men's achievements just like men take inspiration from Marie Curie or Hedy Lamarr apart from the sea of men.
[0]rationalwiki.org/wiki/Tu_quoque
[1] I mean Prof Falcke.
It sounds pretty improbable and I believe it's just an urban myth.
References a paper from 2009 (classified research could well have been much earlier):
https://medium.com/war-is-boring/the-u-s-navys-next-hawkeye-...
Guess what emits UHF/VHF? Terrestrial TV stations and 900Mhz and 700Mhz cell phone towers , like Sprint and Nextel used to operate in the USA before their spectrum was traded/sold back to the government.
China claims can track F22 fighter even in stealth configuration: https://news.yahoo.com/stealth-no-more-china-claims-02470090...
And this is what is publicly released for public consumption...
There have been countless threads over the years where a man gets the credit for something a team has worked on and there is practically never any comments about this. For once a woman gets credit and this thread is full of people complaining that there was an entire team.
Yes, there was a team, but that doesn't matter. For once a woman is getting credit for the great work they've done and this should be applauded. Stories like this help bring more women into STEM fields. Anyone who is complaining about the lack of fairness in this is making themselves look ignorant by ignoring the last thousand years of scientific progress.
I think it's just that many people feel threatened or inadequate when they (naturally) compare themselves to these people. It's tempting to put them down so that we feel better about ourselves. I think most of us here on HN like to think that we're clever but when people like Katie Bouman get under the spotlight suddenly most of us realize that we're not such hot shots after all.
It's probably worse when it's a woman/child/minority/... because it gives us the convenient excuse of "this is probably a PR stunt" to dismiss them. It's lazy and it's intellectually dishonest but it's also very human unfortunately.
This leads to people getting rejected thinking it's part of some culture war, when the truth is that most people get rejected, some of those people would have been brilliant in the role they got rejected for and it's exactly the same brutal industry that it was in the 1980s.
For an example of this that involves a male, the media has been hyping the Ocean Cleanup project because it provides them with a great prodigy story, but people on HN have been rightly pushing back against its merits.
I think in this particular case, I have no problem with it. One, she obviously had a big part in it. Maybe it is blow back because they feel a picture of the inside of a black hole isn't a big deal and people are making it into something big? In my opinion, it is. I remember middle school teachers almost scoffing at the idea of a picture of a black hole and yet, 25 years later, here we are. Regardless, she in her twenties has generated something that researchers spend a lifetime trying to find so kudos to her. I'm sure there is a certain gendered element to it in both cases (for and against) and it'd probably be naive to think there wasn't.
Even if this were a smaller aspect of what these researchers were aiming for, I'd love to see a documentary series on what various team members worked on (and in her case, discovered). An image generated by radio waves and she (maybe with others?) was able to construct an image out of that? That's impressive. Probably not, but I'd be curious if this kind of thing could be localized in a way that it could be the "sound to visual model" element of a system so that blind people could make out the world a bit more directly (obviously, there'd need to be a means for them to consume said model. All of this is way above me and my pay grade).
Damned if you do and damned if you don't.
Anyway, I do not want to sidetrack from this amazing achievement.
I kinda hate the recent trend to focus more on gender or race if somebody achieves anything. Look what Morgan Freeman said about racism [0]. Is it really important that she is a woman? Do people think a lot of women can't achieve these things? And if 1 woman achieved this, all women are better than men? Do everybody just expect men to be smarter and if they do something outstanding it's ok, but when a woman does it, it's extraordinary... Why focus so much on this?
In discussions like this we should really focus on the person (and also the team behind her/him, I doubt she could do it alone without the team), not the gender or race or whatever.
I really hope this positive discrimination hype dies out, it doesn't help anybody. Let the best person for the job get the job.
There are regularly posts here linking to articles about misattribution of credit in science and technology, the problem with the "great man theory," laments about the role of social media in creating hype, and there are plenty of male figures discussed here who engender bitter discussions about how credit should be assigned. I honestly don't see any difference between this discussion and any other discussion. I seem to remember similar discussions emerging about discovery of the Meltdown and Spectre hardware vulnerabilities, and many other physics discoveries involving large teams of researchers, just to take a few examples.
The way credit is assigned in science is a significant moral crisis in my opinion (as it is in work in general; cf. rampant income inequality), and it really doesn't matter what the genders of the individuals involved are. Strangely enough, I think attention is being paid to this argument here because of her gender. It's one of these unfortunate circumstances where I think two competing ethical goals are kind of conflicting, one being the better representation of women and minorities in science, the other being lack of fair representation for all in credit.
The sheer toxicity of many of the comments is something I haven't seen for a long time. They really hate that a women is getting credit and that others aren't getting the same level of attention.
I wonder how those same people think about Elon Musk, Bill Gates, Steve Jobs etc. They had huge teams behind them as well.
For every extraordinarily recognized academic/professional person, there’s always going to be many times more people who are never publicly recognized for their achievements.
Maybe they fly under the radar, maybe they picked the wrong subject to focus on or industry for career, maybe their timing is bad, maybe there’s nothing wrong with them.
I’m proud of this (stranger to me) girl for accomplishing something so large at this age. Being about the same age, I’m not jealous - but it is one more reminder that somewhere along the line my record-player skipped a few years. My 20s disappeared too quickly, or maybe I was focused on the wrong things (work) instead of passion.
As someone who's been interested in astronomy my entire life, and considered getting a degree in it but only ended up with a minor since I sensibly prioritized CS and wanted to graduate in four years, this is an awesome, amazing, really clever accomplishment. And yet many of the comments here are just so negative, either outright sexist, picking nits and trying to argue that it isn't a big breakthrough or anything, or going through code contributions line-by-line trying to establish that really someone else had more to do with it.
All I know is, she must be insanely intelligent and hard-working. What an awesome PhD project, and at MIT no less!, an institution that I have enormous respect for and that I somewhat identify with because my dad attended and I've been there for many events. I'm jealous. This would've been the exact kind of thing I'd have gone into in astronomy for (because of my background in programming) had I seriously pursued it, but I know I'm just not diligent enough to have seen it through. And being honest, I didn't apply myself well enough in undergrad to have gotten good enough grades to get into a good grad school.
It sucks that so many people jump into "push people down" mode instead of "life people up" mode in these kinds of situations rather, because this is an amazing scientific accomplishment that deserves celebrating. One of the PIs in one of the press conferences said that this was the most important accomplishment in astronomy since 2014 [when Rosetta landed a probe on a comet], and I tend to agree. It's not just about this one image, but about establishing the feasibility of a virtual planet-sized radio telescope that is capable of imaging lots more than just black holes. A lot more discoveries are likely to come out of this technique, and guess who came up with the algorithm to make sense of all those petabytes of data?
1) Look back at any physic journal for similar stories of experimental success (example gravitational waves), you won't find news stories of focus pieces on a single team member because it is a COLLABORATIVE effort. The only cases were single people get recognition is for theorists like Prof Higgs, Hawkings etc, but not for the individual experimentalists at the LHC or other astronomical projects.
2) The idea of focussing on a single team member is a technique for creating a clear narrative that readers can follow. The story would get less interest if you were told about the live and works of all of the team members.
It's not all hate :)
I think it's friggin awesome to see women in science. But even if Bouman was male I would still be cautious of attributing so much of an international collaboration to one person in the form of "Meet the _____ behind the first black hole image". That phrasing disregards too much hard work. I see no reason to offer Bouman special treatment in this regard at the expense of others solely because of her gender. That isn't equality.
1/ She led the team and was first author on the image reconstruction paper
2/ She gave a Ted talk on the topic a while back
3/ There's a brilliant photo of her initial reaction to the image that captures the excitement of scientific discovery circulating on the internet
I don't think I've ever seen so many people suddenly desperately concerned that the Little People get a mention, and I'm at least part-way convinced that gender (and maybe youth? she's 29...) has a good deal to do with it (apparently the other thing that triggers the "harrumph, what about the team" crowd are stories about child prodigies, according to another thread).
Imagine you had just had your invention create a picture of a black hole, you wrote the paper where you were the first author describing this and then the press came knocking: would you be as gracious as she has been? Or would you feel like the fucking rockstar you would, in fact, be?
Dr. Bouman is a talented, enthusiastic and no doubt indispensable force on the larger team responsible for this achievement. Her role is as a co-lead for one small team which is responsible for one algorithm (out of four) used for imaging, as well as for an imagine verification algorithm (with Dr. Bouman's focus more on the latter). The larger imaging group (about 45 people by my rough count, led by Drs. Michael Johnson and Kazunori Akiyama) is itself one part of the analysis group, which has three other working groups, and then the analysis group is one of a half dozen larger groups in the EHT project which produced this result.
So it's not a case of the project lead being presented as the face of the project, which is par for the course in academia (and the outside world). It is a postdoc one level above the grad students who form the least-senior rung of the project, and many levels from the top suddenly being misleadingly presented as the key figure in a major result.
Imagine you worked on a small team of a couple of postdocs and a few grad students near the bottom of a hierarchy of teams involving hundreds of people, and then came in one day and your colleague and co-lead at the same level as you was suddenly presented as the face and key contributor for not only your small slice of things, not even the larger component to which the slice belongs, but the entire project?
You'd probably be pretty happy for them, but also confused as to why the many people with the actual role as overall group leaders or the project leaders aren't mentioned. One might also note how distant the general public is from the machinations of the academic world that no one is asking how a 20-something CS postdoc ended up leading a multinational astronomy project involving top faculty from top institutions? In terms of notability and improbability, that would probably be a bigger story than any image produced by the group!
Explaining her actual position and contribution is not in any way to detract from her contributions: only to clarify the record in the face of an onslaught of misleading media articles, which seemed to largely sourced (transitively) from a few misleading tweets, themselves triggered by a viral image.
On top of that, none of this is doing Dr. Bouman any favors. Although they are mostly silent, no one in the EHT project is confused about her role, and none of the other people in her faculty or almost anyone else who matters will be under any misconception despite the headlines. If anything, academia is even more picky than other fields when it comes to attribution, so any type of misplaced credit can be viewed very negatively and can attach itself to a person indefinitely. Now she hasn't invited this or propagated this story, so one should consider her a blameless victim here: but not everyone in a position to care will necessarily remember that subtlety.
One needs to just look at another large thread that generated controversy to get an idea of the growing trend [1].
Which means one has to ask themselves: Is HN cultivating an environment that's only going to get worse? And personally, I think the answer would be yes.
She definitely did something amazing and unfortunately it turned political because it fits the narrative that some people love to push currently.
I'm not a fan of the liberal agenda of positive//negative discrimination. I really believe that it is making everyone worse off, especially women that are being treated like little kids that need to be shown the correct path.
We just want to show that you if you accomplish something in tech you aren't going to be diminished or dismissed simply because you're a woman.
How do you know?
From the abstract:
" Consistent with the importance of exposure effects in career selection, women and disadvantaged youth are as underrepresented among high-impact inventors as they are among inventors as a whole. These findings suggest that there are many “lost Einsteins”—individuals who would have had highly impactful inventions had they been exposed to innovation in childhood—especially among women, minorities, and children from low-income families."
[1] https://academic.oup.com/qje/article-abstract/134/2/647/5218...
But in a published headline, one ought to be addressed by their formal title.
Differences exist between casual conversation and publication. A distinction I shouldn’t have to point out as one that exists.
However, I think to call her "the woman behind the first black hole image" is a hyperbole. It makes it sound as if she was _the one person_ responsible that all this came about. -- But that is not the case. Arguably, there are others who have contributed as much if not more. This is what makes me somewhat feel that this focus on her is not quite fair.
Coverage in mainland Europe has been different so far: Prof Falcke gets a lot of credit for the image/project. Falcke is heading one of the major teams that contributed to the project. In fact, many here attribute the conception of the project to him. But how many in the English speaking sphere have heard or will ever hear about Falcke? Why is that?
My personal guess is that the reason for this is: 1) The Anglo-american media were looking for inspiring EHT scientists from the English-speaking world. 2) Bouman fit that description best.
So, imv, something like "The inspiring story of Katie Bouman" and some credit to some of the other major figures like Falcke would have been fairer.
Thought experiment: if you saw an article titled "Jony Ive: The Man Behind The iPhone" would you be commenting on how unfair it is to single him out? After all, he just designed the thing, a huge team of people built the software and the hardware that actually made it possible.
Yes, and that’s what happens in each of those hyperbolic articles (that are mostly about Jobs, but same thing)
first: by alluding to Ive, you insert a gender component. i don't want to make this about gender - which is what happened itt. as mentioned, i think the difference in focus is because of geo-cultural reasons. another piece of evidence for this hypothesis comes from the following: over here, the EU also gets a lot of praise for providing the main chunk of the funding for the project. a quick check tells me that this detail is often omitted in US articles about the project. also, a note on myself: i work in a field where the majority of people are female. so is my boss. her work is great and i love working here. at the same time, i am aware that the bar to get here was higher for my female colleagues than it is for men. also, i see the glass ceiling having an effect on the careers of my sisters and my female friends. and i am painfully aware of the struggles that my mum and other women of her generation had/have to go through. so i consider myself a feminist, in the sense that i believe that we should have full equality and that we do not have it yet.
second: think iphone, i think jobs. so what "Jony Ive: The Man Behind The iPhone" would imply to me is that Ive is _the one person_ that had the biggest impact on the development of the iphone. i don't know enough about Ive to evaluate this. but here's the thing: if it turned out that another person contributed as much if not more than Ive, then i'd say: hey, it's nice that the article introduces Ive and gives him some credit, but let's not exaggerate and let's not forget about the other people who have also greatly contributed to the project.
edit: to clarify: i find it hard to say, because it's somewhat hypothetical. i truly hope for myself that i would react the same way / that gender has no impact on my thought process.
Make a BBC Horizon story about how he came to his best work and about him. That's cool. But to frame it as just being him and not the others behind the work.. it's nothing but hero worship.
I get it. I truly do.
But consider the context: This picture of a blackhole is going around along with an iconic picture of a woman with a ton of hard-drives that resembles the iconic picture of Margaret Hamilton with a stack of papers. Put yourself in the shoes of someone who knows little to nothing about this project. What questions do you think people have?
Headlines have to create irresistible questions that lure people in and this one is using the tried and true "Who's this genius?" formula.
Once they've grabbed this casual reader (see headline), they're not going to dive too deep into the project. This isn't serious science journalism, this is a human interest story in the science section.
Why did they pick her? Because she lead the team and was a key figure in conceiving and implementing the algorithm. Because she was already the face, spokesperson and active promoter for this project. Look at her TED talk from 2017.
I get it. Tons of people deserve credit. More importantly, the story of how this team collaborated should be told. But that's not what this profile piece is about.
But let's get serious. You're critiquing the accuracy of a very casual profile piece for average readers. Most of them really don't care what statements are slightly hyperbolic, they just want to understand the gist of the project and her role.
I don't think anybody truly believes that taking images of black holes is a one-person job. And the title doesn't imply that. Neither does the next, boldface paragraph in the article:
> A 29-year-old computer scientist has earned plaudits worldwide for helping develop the algorithm that created the first-ever image of a black hole.
Immediately followed by:
> Katie Bouman led development of a computer program that made the breakthrough image possible.
It doesn't say that though. It says she was behind the image. And as I understand she lead one of the teams responsible for creating the image from the data. So I don't think that is particularly inaccurate as far as headlines go.
"But Dr Bouman, ...insisted the team that helped her deserves equal credit."
You're thinking like a programmer. Think not like a programmer and then explain why the original headline is better.
Why was the article written?
Of the 129 comments on that story, not one discussed how software development at Microsoft is always a team effort. Or checked any repositories counting LoC to quantify the value of his contribution.
Meanwhile, in this thread, I see 6 of 73 comments as of now not discussing a woman's relative contribution to a team effort, and how she does or does not deserve praise.
>It's a miserable language, full of unexpected behaviors and badly designed features.
I agree. That no one is tearing apart the horribly written python in the git repo is extremely sexist.
Holy shit, you're using comments as version control, the 70s called and what their code practices back.
Oh my god, did you even read the thread? It gets better with each post:
>I haven't met a single person who likes PowerShell. It's perhaps the textbook example of ugly design that looks technically consistent but utterly unfriendly and mind bogglingly verbose. [...] The designers of this thing should have been demoted, let alone making them "Distinguished Engineer".
>PowerShell is one of the few bits of software which has actually made me throw a computer in anger. The idea has potential but the implementation is just bad.
And they go on and on.
I wouldn't expect the answer to "who is the person behind the first black hole image?" to be so clear.
However, this is such a great achievement. Would be awesome to learn more about the algorithm.
It specifically lists the teams in the article.
[0]https://hn.algolia.com/?query=%27the%20man%20behind%27&sort=...
But uh oh, now there's a woman behind something all of a sudden it's a huge problem and the thread is packed with complaints about it. I wonder why that is?
"A 29-year-old computer scientist has earned plaudits worldwide for helping develop the algorithm"
Or even a few sentences in:
"There, she led the project, assisted by a team from MIT's Computer Science and Artificial Intelligence Laboratory .."
But hey who needs to read articles when you can jump to conclusions and surface your clear biases.
There, she led the project, assisted by a team from MIT's Computer Science and Artificial Intelligence Laboratory, the Harvard-Smithsonian Center for Astrophysics and the MIT Haystack Observatory.
But Dr Bouman, now an assistant professor of computing and mathematical sciences at the California Institute of Technology, insisted the team that helped her deserves equal credit.
The effort to capture the image, using telescopes in locations ranging from Antarctica to Chile, involved a team of more than 200 scientists.
"No one of us could've done it alone," she told CNN. "It came together because of lots of different people from many different backgrounds."
Katie's lines of code did two things: 1) integrated the code of others 2) allowed you to change the font-size
Does it really count as an image of a black hole? Since no light is reflected by the black hole, all we see is light bend by the gravity of the black hole.
Haven't we seen that before? I have the strong feeling there have been photos of star constellations that seem distorted because of black holes.
A quick googling brings up this article from 2014 for example:
https://edition.cnn.com/2014/08/12/tech/black-hole-nasa-nust....
"Black hole bends light, space, time -- and NASA's NuSTAR can see it all unfold"
Because it's nitpicking[0]. When scientists show you results of several years of work of many people, you effectively chose to ask question like "Is it really violet? Seems more purple to me". You don't contribute anything to discussion, but just want to sound smart-ass.
[0] https://www.urbandictionary.com/define.php?term=nitpicking
My understanding now is that this is the first time we've observed one accurately enough to get a picture of the Einstein ring around a black hole. And even there, it's heavily reconstructed using machine learning, which I wouldn't call a "photo", more of a "AI artist rendition".
The link says nitpicking is "Looking for small or unimportant errors".
That is certainly not what I want to do.
The press is full of articles about this "First photo of a black hole". This seems to imply that it is somehow important. But so far, I fail to see what is important about it.
So my question still stands. I would really like to know in what sense this is the first image of a black hole. And if there is something we can learn from looking at it.
My first impression is "Yeah, it's round. I would have thought so." :)
EDIT: In Dr Bouman's TED talk, she notes that there are an infinite number of ways the sensor data could be constructed into an image, and that they were looking for a construction that looks like what they expect things in our universe look like. So, there's some ambiguity in the definition of "photograph"
We do the same thing with digital cameras, X-rays, MRI, etc.
Edit: While I'm being rapidly downvoted, I'd like to clarify that I didn't mean to demean this because it's a female nor any of the feat this research has achieved. My point was only about why is it reported as if individual feat while many of such things are a strong team work.
For some other questions - will you say the same about Elon musk - of course i've argued this among my peers and that's exactly why I called it similar to `Jobsism`
To Quote: Another recent incident, While AI Godfathers got Turing award, many questioned why this person hasn't got and that person hasn't got.
My idea for this comment was a constructive discussion but it took a different spin that my comment is against this woman which definitely not my intention.
The effort to capture the image, using telescopes in locations ranging from Antarctica to Chile, involved a team of more than 200 scientists.
"No one of us could've done it alone," she told CNN. "It came together because of lots of different people from many different backgrounds."
How would you rate "Meet Robert Oppenheimer, father of the bomb"?
I'd also love anyone to point me to any similar discussion on Elon Musk and one of his companies.
https://m.facebook.com/story.php?story_fbid=1021332602552304...
People I right, I made an assumption based on the title and not the content.
- When an individual/team's work is emphasized by their biological characteristics, it is often meant for clicks or to drive emotions (positive & negative)
- When that happens, ask yourself whether the author of the paper did it for nefarious reasons or not.
- If the cause doesn't seem nefarious, ask yourself whether the society around you has outgrown the biases towards X biological characteristics
- When interacting with others, do not base your actions and thoughts on their biological characteristics.
- Celebrate, debate and criticize the work that the individual/team did, the work the author of the article did and the comments.