Tag Archives: Hidden Figures

Communicating science effectively—a December 2016 book from the US National Academy of Sciences

I stumbled across this Dec. 13, 2016  essay/book announcement by Dr. Andrew Maynard and Dr. Dietram A. Scheufele on The Conversation,

Many scientists and science communicators have grappled with disregard for, or inappropriate use of, scientific evidence for years – especially around contentious issues like the causes of global warming, or the benefits of vaccinating children. A long debunked study on links between vaccinations and autism, for instance, cost the researcher his medical license but continues to keep vaccination rates lower than they should be.

Only recently, however, have people begun to think systematically about what actually works to promote better public discourse and decision-making around what is sometimes controversial science. Of course scientists would like to rely on evidence, generated by research, to gain insights into how to most effectively convey to others what they know and do.

As it turns out, the science on how to best communicate science across different issues, social settings and audiences has not led to easy-to-follow, concrete recommendations.

About a year ago, the National Academies of Sciences, Engineering and Medicine brought together a diverse group of experts and practitioners to address this gap between research and practice. The goal was to apply scientific thinking to the process of how we go about communicating science effectively. Both of us were a part of this group (with Dietram as the vice chair).

The public draft of the group’s findings – “Communicating Science Effectively: A Research Agenda” – has just been published. In it, we take a hard look at what effective science communication means and why it’s important; what makes it so challenging – especially where the science is uncertain or contested; and how researchers and science communicators can increase our knowledge of what works, and under what conditions.

At some level, all science communication has embedded values. Information always comes wrapped in a complex skein of purpose and intent – even when presented as impartial scientific facts. Despite, or maybe because of, this complexity, there remains a need to develop a stronger empirical foundation for effective communication of and about science.

Addressing this, the National Academies draft report makes an extensive number of recommendations. A few in particular stand out:

  • Use a systems approach to guide science communication. In other words, recognize that science communication is part of a larger network of information and influences that affect what people and organizations think and do.
  • Assess the effectiveness of science communication. Yes, researchers try, but often we still engage in communication first and evaluate later. Better to design the best approach to communication based on empirical insights about both audiences and contexts. Very often, the technical risk that scientists think must be communicated have nothing to do with the hopes or concerns public audiences have.
  • Get better at meaningful engagement between scientists and others to enable that “honest, bidirectional dialogue” about the promises and pitfalls of science that our committee chair Alan Leshner and others have called for.
  • Consider social media’s impact – positive and negative.
  • Work toward better understanding when and how to communicate science around issues that are contentious, or potentially so.

The paper version of the book has a cost but you can get a free online version.  Unfortunately,  I cannot copy and paste the book’s table of contents here and was not able to find a book index although there is a handy list of reference texts.

I have taken a very quick look at the book. If you’re in the field, it’s definitely worth a look. It is, however, written for and by academics. If you look at the list of writers and reviewers, you will find over 90% are professors at one university or another. That said, I was happy to see references to Dan Kahan’s work at the Yale Law School’s Culture Cognition Project cited. As happens they weren’t able to cite his latest work [***see my xxx, 2017 curiosity post***], released about a month after “Communicating Science Effectively: A Research Agenda.”

I was unable to find any reference to science communication via popular culture. I’m a little dismayed as I feel that this is a seriously ignored source of information by science communication specialists and academicians but not by the folks at MIT (Massachusetts Institute of Technology) who announced a wireless app in the same week as it was featured in an episode of the US television comedy, The Big Bang Theory. Here’s more from MIT’s emotion detection wireless app in a Feb. 1, 2017 news release (also on EurekAlert),

It’s a fact of nature that a single conversation can be interpreted in very different ways. For people with anxiety or conditions such as Asperger’s, this can make social situations extremely stressful. But what if there was a more objective way to measure and understand our interactions?

Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Institute of Medical Engineering and Science (IMES) say that they’ve gotten closer to a potential solution: an artificially intelligent, wearable system that can predict if a conversation is happy, sad, or neutral based on a person’s speech patterns and vitals.

“Imagine if, at the end of a conversation, you could rewind it and see the moments when the people around you felt the most anxious,” says graduate student Tuka Alhanai, who co-authored a related paper with PhD candidate Mohammad Ghassemi that they will present at next week’s Association for the Advancement of Artificial Intelligence (AAAI) conference in San Francisco. “Our work is a step in this direction, suggesting that we may not be that far away from a world where people can have an AI social coach right in their pocket.”

As a participant tells a story, the system can analyze audio, text transcriptions, and physiological signals to determine the overall tone of the story with 83 percent accuracy. Using deep-learning techniques, the system can also provide a “sentiment score” for specific five-second intervals within a conversation.

“As far as we know, this is the first experiment that collects both physical data and speech data in a passive but robust way, even while subjects are having natural, unstructured interactions,” says Ghassemi. “Our results show that it’s possible to classify the emotional tone of conversations in real-time.”

The researchers say that the system’s performance would be further improved by having multiple people in a conversation use it on their smartwatches, creating more data to be analyzed by their algorithms. The team is keen to point out that they developed the system with privacy strongly in mind: The algorithm runs locally on a user’s device as a way of protecting personal information. (Alhanai says that a consumer version would obviously need clear protocols for getting consent from the people involved in the conversations.)

How it works

Many emotion-detection studies show participants “happy” and “sad” videos, or ask them to artificially act out specific emotive states. But in an effort to elicit more organic emotions, the team instead asked subjects to tell a happy or sad story of their own choosing.

Subjects wore a Samsung Simband, a research device that captures high-resolution physiological waveforms to measure features such as movement, heart rate, blood pressure, blood flow, and skin temperature. The system also captured audio data and text transcripts to analyze the speaker’s tone, pitch, energy, and vocabulary.

“The team’s usage of consumer market devices for collecting physiological data and speech data shows how close we are to having such tools in everyday devices,” says Björn Schuller, professor and chair of Complex and Intelligent Systems at the University of Passau in Germany, who was not involved in the research. “Technology could soon feel much more emotionally intelligent, or even ‘emotional’ itself.”

After capturing 31 different conversations of several minutes each, the team trained two algorithms on the data: One classified the overall nature of a conversation as either happy or sad, while the second classified each five-second block of every conversation as positive, negative, or neutral.

Alhanai notes that, in traditional neural networks, all features about the data are provided to the algorithm at the base of the network. In contrast, her team found that they could improve performance by organizing different features at the various layers of the network.

“The system picks up on how, for example, the sentiment in the text transcription was more abstract than the raw accelerometer data,” says Alhanai. “It’s quite remarkable that a machine could approximate how we humans perceive these interactions, without significant input from us as researchers.”

Results

Indeed, the algorithm’s findings align well with what we humans might expect to observe. For instance, long pauses and monotonous vocal tones were associated with sadder stories, while more energetic, varied speech patterns were associated with happier ones. In terms of body language, sadder stories were also strongly associated with increased fidgeting and cardiovascular activity, as well as certain postures like putting one’s hands on one’s face.

On average, the model could classify the mood of each five-second interval with an accuracy that was approximately 18 percent above chance, and a full 7.5 percent better than existing approaches.

The algorithm is not yet reliable enough to be deployed for social coaching, but Alhanai says that they are actively working toward that goal. For future work the team plans to collect data on a much larger scale, potentially using commercial devices such as the Apple Watch that would allow them to more easily implement the system out in the world.

“Our next step is to improve the algorithm’s emotional granularity so that it is more accurate at calling out boring, tense, and excited moments, rather than just labeling interactions as ‘positive’ or ‘negative,’” says Alhanai. “Developing technology that can take the pulse of human emotions has the potential to dramatically improve how we communicate with each other.”

This research was made possible in part by the Samsung Strategy and Innovation Center.

Episode 14 of season 10 of The Big Bang Theory was titled “The Emotion Detection Automation”  (full episode can be found on this webpage) and broadcast on Feb. 2, 2017. There’s also a Feb. 2, 2017 recap (recapitulation) by Lincee Ray for EW.com (it seems Ray is unaware that there really is such a machine),

Who knew we would see the day when Sheldon and Raj figured out solutions for their social ineptitudes? Only The Big Bang Theory writers would think to tackle our favorite physicists’ lack of social skills with an emotion detector and an ex-girlfriend focus group. It’s been a while since I enjoyed both storylines as much as I did in this episode. That’s no bazinga.

When Raj tells the guys that he is back on the market, he wonders out loud what is wrong with his game. Why do women reject him? Sheldon receives the information like a scientist and runs through many possible answers. Raj shuts him down with a simple, “I’m fine.”

Sheldon is irritated when he learns that this obligatory remark is a mask for what Raj is really feeling. It turns out, Raj is not fine. Sheldon whines, wondering why no one just says exactly what’s on their mind. It’s quite annoying for those who struggle with recognizing emotional cues.

Lo and behold, Bernadette recently read about a gizmo that was created for people who have this exact same anxiety. MIT has a prototype, and because Howard is an alum, he can probably submit Sheldon’s name as a beta tester.

Of course this is a real thing. If anyone can build an emotion detector, it’s a bunch of awkward scientists with zero social skills.

This is the first time I’ve noticed an academic institution’s news release to be almost simultaneous with mention of its research in a popular culture television program, which suggests things have come a long way since I featured news about a webinar by the National Academies ‘ Science and Entertainment Exchange for film and television productions collaborating with scientists in an Aug. 28, 2012 post.

One last science/popular culture moment: Hidden Figures, a movie about African American women who were human computers supporting NASA (US National Aeronautics and Space Agency) efforts during the 1960s space race and getting a man on the moon was (shockingly) no. 1 in the US box office for a few weeks (there’s more about the movie here in my Sept. 2, 2016 post covering then upcoming movies featuring science).  After the movie was released, Mary Elizabeth Williams wrote up a Jan. 23, 2017 interview with the ‘Hidden Figures’ scriptwriter for Salon.com

I [Allison Schroeder] got on the phone with her [co-producer Renee Witt] and Donna  [co-producer Donna Gigliotti] and I said, “You have to hire me for this; I was born to write this.” Donna sort of rolled her eyes and was like, “God, these Hollywood types would say anything.” I said, “No, no, I grew up at Cape Canaveral. My grandmother was a computer programmer at NASA, my grandfather worked on the Mercury prototype, and I interned there all through high school and then the summer after my freshman year at Stanford I interned. I worked at a missile launch company.”

She was like, “OK that’s impressive.” And I said, “No, I literally grew up climbing on the Mercury capsule — hitting all the buttons, trying to launch myself into space.”

She said, “Well do you think you can handle the math?” I said that I had to study a certain amount of math at Stanford for economics degree. She said, “Oh, all right, that sounds pretty good.”

I pitched her a few scenes. I pitched her the end of the movie that you saw with Katherine running the numbers as John Glenn is trying to get up in space. I pitched her the idea of one of the women as a mechanic and to see her legs underneath the engine. You’re used to seeing a guy like that, but what would it be like to see heels and pantyhose and a skirt and she’s a mechanic and fixing something? Those are some of the scenes that I pitched them, and I got the job.

I love that the film begins with setting up their mechanical aptitude. You set up these are women; you set up these women of color. You set up exactly what that means in this moment in history. It’s like you just go from there.

I was on a really tight timeline because this started as an indie film. It was just Donna Gigliotti, Renee Witt, me and the author Margot Lee Shetterly for about a year working on it. I was only given four weeks for research and 12 weeks for writing the first draft. I’m not sure if I hadn’t known NASA and known the culture and just knew what the machines would look like, knew what the prototypes looked like, if I could have done it that quickly. I turned in that draft and Donna was like, “OK you’ve got the math and the science; it’s all here. Now go have fun.” Then I did a few more drafts and that was really enjoyable because I could let go of the fact I did it and make sure that the characters and the drive of the story and everything just fit what needed to happen.

For anyone interested in the science/popular culture connection, David Bruggeman of the Pasco Phronesis blog does a better job than I do of keeping up with the latest doings.

Getting back to ‘Communicating Science Effectively: A Research Agenda’, even with a mention of popular culture, it is a thoughtful book on the topic.

Movies and science, science, science (Part 1 of 2)

In the last few years, there’s been a veritable plethora of movies (and television shows in Canada and the US) that are about science and technology or have a significant  component or investigate the social impact. The trend does not seem to be slowing.

This first of two parts features the film, *Hidden* Figures, and a play being turned into a film, Photograph 51. The second part features the evolving Theranos story and plans to turn it into a film, The Man Who Knew Infinity, a film about an Indian mathematician, the science of the recent all woman Ghostbusters, and an ezine devoted to science films.

For the following movie tidbits, I have David Bruggeman to thank.

Hidden Figures

From David’s June 21, 2016 post on his Pasco Phronesis blog (Note: A link has been removed),

Hidden Figures is a fictionalized treatment of the book of the same name written by Margot Lee Shetterly (and underwritten by the Sloan Foundation).  Neither the book nor the film are released yet.  The book is scheduled for a September release, and the film currently has a January release date in the U.S.

Both the film and the book focus on the story of African American women who worked as computers for the government at the Langley National Aeronautic Laboratory in Hampton, Virginia.  The women served as human computers, making the calculations NASA needed during the Space Race.  While the book features four women, the film is focused on three: Katherine Johnson (recipient of the Presidential Medal of Freedom), Dorothy Vaughan, and Mary Jackson.  They are played by, respectively, Taraji P. Henson, Octavia Spencer, and Janelle Monae.  Other actors in the film include Kevin Costner, Kirsten Dunst, Aldis Hodge, and Jim Parsons.  The film is directed by Theodore Melfi, and the script is by Allison Schroeder.

*ETA Oct. 6, 2016: The book ‘Hidden Figures’ is nonfiction while the movie is a fictionalized adaptation  based on a true story.*

According to imdb.com, the movie’s release date is Dec. 25, 2016 (this could change again).

The history for ‘human computers’ stretches back to the 17th century, at least. From the Human Computer entry in Wikipedia (Note: Links have been removed),

The term “computer”, in use from the early 17th century (the first known written reference dates from 1613),[1] meant “one who computes”: a person performing mathematical calculations, before electronic computers became commercially available. “The human computer is supposed to be following fixed rules; he has no authority to deviate from them in any detail.” (Turing, 1950) Teams of people were frequently used to undertake long and often tedious calculations; the work was divided so that this could be done in parallel.

Prior to NASA, a team of women in the 19th century in the US were known as Harvard Computers (from the Wikipedia entry; Note: Links have been removed),

Edward Charles Pickering (director of the Harvard Observatory from 1877 to 1919) decided to hire women as skilled workers to process astronomical data. Among these women were Williamina Fleming, Annie Jump Cannon, Henrietta Swan Leavitt and Antonia Maury. This staff came to be known as “Pickering’s Harem” or, more respectfully, as the Harvard Computers.[1] This was an example of what has been identified as the “harem effect” in the history and sociology of science.

It seems that several factors contributed to Pickering’s decision to hire women instead of men. Among them was the fact that men were paid much more than women, so he could employ more staff with the same budget. This was relevant in a time when the amount of astronomical data was surpassing the capacity of the Observatories to process it.[2]

The first woman hired was Williamina Fleming, who was working as a maid for Pickering. It seems that Pickering was increasingly frustrated with his male assistants and declared that even his maid could do a better job. Apparently he was not mistaken, as Fleming undertook her assigned chores efficiently. When the Harvard Observatory received in 1886 a generous donation from the widow of Henry Draper, Pickering decided to hire more female staff and put Fleming in charge of them.[3]

While it’s not thrilling to find out that Pickering was content to exploit the women he was hiring, he deserves kudos for recognizing that women could do excellent work and acting on that recognition. When you consider the times, Pickering’s was an extraordinary act.

Getting back to Hidden Figures, an Aug.15, 2016 posting by Kathleen for Lainey Gossip celebrates the then newly released trailer for the movie,

If you’ve been watching the Olympics [Rio 2016], you know how much the past 10 days have been an epic display of #BlackGirlMagic. Fittingly, the trailer for Hidden Figures was released last night during Sunday’s Olympic coverage. It’s the story of three brilliant African American women, played by Taraji P Henson, Octavia Spencer and Janelle Monae, who made history by serving as the brains behind the NASA launch of astronaut John Glenn into orbit in 1962.

Three black women helped launch a dude into space in the 60s. AT NASA. Think about how America treated black women in the 60s. As Katherine Johnson, played by Taraji P Henson, jokes in the trailer, they were still sitting at the back of the bus. In 1962 Malcolm X said, “The most disrespected person in America is the Black woman, the most unprotected person in America is the Black woman. The most neglected person in America is the Black woman.” These women had to face that truth every day and they still rose to greatness. I’m obsessed with this story.

Overall, the trailer is good. I like the pace and the performances look strong. …

I’m most excited for Hidden Figures (as Lainey pointed out, this title is THE WORST) because black girls are being celebrated for their brains on screen. That is rare. When the trailer aired, my brother Sam texted me, “WHOA, a smart black girl movie!”

*ETA Sept. 5, 2016: Aran Shetterly contacted me to say this:

What you may not know is that the term “Hidden Figures” is a specific reference to flight science. It tested a pilot’s ability to pick out a simple figure from a set of more complex, difficult to see images. http://www.militaryaptitudetests.com/afoqt/

Thank you Mr. Shetterly!

Photograph 51 (the Rosalind Franklin story)

Also in David’s June 21, 2016 post is a mention of Photograph 51, a play and soon-to-be film about Rosalind Franklin, the discovery of the double helix, and a science controversy. I first wrote about Photograph 51 in a Jan. 16, 2012 posting (scroll down about 50% of the way) regarding an international script writing competition being held in Dublin, Ireland. At the time, I noted that Anna Ziegler’s play, Photograph 51 had won a previous competition cycle of the screenwriting competition. I wrote again about the play in a Sept. 2, 2015 posting about its London production (Sept. 5 – Nov. 21, 2015) featuring actress Nicole Kidman.

The versions of the Franklin story with which I’m familiar paint her as the wronged party, ignored and unacknowledged by the scientists (Francis, Crick, James Watson, and Maurice Wilkins) who got all the glory and the Nobel Prize. Stephen Curry in a Sept. 16, 2015 posting on the Guardian science blogs suggests the story may not be quite as simple as that (Note: A link has been removed),

Ziegler [Anna Ziegler, playwright] is up front in admitting that she has rearranged facts to suit the drama. This creates some oddities of chronology and motive for those familiar with the history. I know of no suggestion of romantic interest in Franklin from Wilkins, or of a separation of Crick from his wife in the aftermath of his triumph with Watson in solving the DNA structure. There is no mention in the play of the fact that Franklin published her work (and the famous photograph 51) in the journal Nature alongside Watson and Crick’s paper and one by Wilkins. Nor does the audience hear of the international recognition that Franklin enjoyed in her own right between 1953 and her untimely death in 1958, not just for her involvement in DNA, but also for her work on the structure of coal and of viruses.

Published long after her death, The Double Helix is widely thought to treat Franklin unfairly. In the minds of many she remains the wronged woman whose pioneering results were taken by others to solve DNA and win the Nobel prize. But the real story – many elements of which come across strongly in the play – is more complex*.

Franklin is a gifted experimentalist. Her key contributions to the discovery were in improving methods for taking X-ray pictures of and discovering the distinct A and B conformations of DNA. But it becomes clear that her methodical, meticulous approach to data analysis – much to Wilkins’ impotent frustration – eventually allows the Kings ‘team’ to be overtaken by the bolder, intuitive stratagem of Watson and Crick.

Curry’s piece is a good read and provides insight into the ways temperament affects how science is practiced.

Interestingly, there was a 1987 dramatization of the ‘double helix or life story’ (from the Life Story entry on Wikipedia; Note: Links have been removed),

The film tells the story of the rivalries of the two teams of scientists attempting to discover the structure of DNA. Francis Crick and James D. Watson at Cambridge University and Maurice Wilkins and Rosalind Franklin at King’s College London.

The film manages to convey the loneliness and competitiveness of scientific research but also educates the viewer as to how the structure of DNA was discovered. In particular, it explores the tension between the patient, dedicated laboratory work of Franklin and the sometimes uninformed intuitive leaps of Watson and Crick, all played against a background of institutional turf wars, personality conflicts and sexism. In the film Watson jokes, plugging the path of intuition: “Blessed are they who believed before there was any evidence.” The film also shows why Watson and Crick made their discovery, overtaking their competitors in part by reasoning from genetic function to predict chemical structure, thus helping to establish the then still-nascent field of molecular biology.

You can find out more about the stars, crew, and cast here on imdb.com

In addition to Life Story, the dramatization is also sometimes titled as ‘The Race for the Double Helix’ or the ‘Double Helix’.

Getting back to Photograph 51 (the film), Michael Grandage who directed the stage play will also direct the film. Grandage just made his debut as a film director with ‘Genius’ starring Colin Firth and Jude Law. According to this June 23, 2016 review by Sarah on Laineygossip.com, he stumbled a bit by casting British and Australian actors as Americans,

The first hurdle to clear with Genius, the feature film debut of English theater director Michael Grandage, is that everyone is played by Brits and Aussies, and by “everyone” I mean some of the most towering figures of American literature. You cast the best actor for the role and a good actor can convince you they’re anyone, so it shouldn’t really matter, but there is something profoundly odd about watching a parade of Lit 101 All Stars appear on screen and struggle with American accents. …

That kind of casting should not be a problem with Photograph 51 where the action takes place with British personalities.

Part 2 is here.

*’Human’ corrected to ‘Hidden’ on Sept. 5, 2016.