The National Academies of Sciences, Engineering, and Medicine
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While computational reproducibility in scientific research is generally expected when the original data and code are available, lack of ability to replicate a previous study — or obtain consistent results looking at the same scientific question but with different data — is more nuanced and occasionally can aid in the process of scientific discovery, says a new congressionally mandated report from the National Academies of Sciences, Engineering, and Medicine. Reproducibility and Replicability in Science recommends ways that researchers, academic institutions, journals, and funders should help strengthen rigor and transparency in order to improve the reproducibility and replicability of scientific research.
Back in 2007, I first reported on an unprecedented convergence in American baby names: one letter was dominating the boys’ side. Across the style spectrum, everybody wanted their boys’ names to end in N. Almost a third of American boys were receiving -N names, making that ending more dominant for boys than the traditional -A ending was for girls. Nothing like it had ever been seen before.
This is an HTMLized version written testimony I provided on May 7, 2019, to the Senate Committee on Banking, Housing, and Urban Affairs for their hearing on Privacy Rights and Data Collection in a Digital Economy. I’ve added some hyperlinks but otherwise left it unchanged.
Some background: For the past 6-7 years, I’ve taught a variety of courses and workshops on computational social science (CSS): R, python, git, webscraping, web development, machine learning, text-as-data, etc. I’ve taught over 500 people, mostly graduate students.
Lior Shamir at Lawrence Technical University gathered the lyrics of 6,150 Billboard Hot 100 singles from 1951 to 2016 and fed them to an algorithm. The software had been previously trained identify linguistic markers of different emotional states and personality traits – including sadness, fear, disgust, joy, and extraversion. And although a computer will clearly miss some of the nuances of complex lyrics, its assessments do tend to agree with human judgements.
It correctly identified that the dominant emotion in Bonnie Tyler’s hit Total Eclipse of the Heart, for instance, was ‘sadness’, with a score of 0.51 (out of 1) for that emotion. The Village People’s YMCA, meanwhile, scored 0.65 for ‘joy’, and Queen’s We Will Rock You scored a whopping 0.85 on the scale of ‘extraversion’ – which sounds about right for the rockers’ stomping bravado.
Back in March, Apple unveiled its vision for the future of television at a star-studded event that featured everyone from Oprah Winfrey to Steven Spielberg. Now, the first culmination of the company’s revamped TV efforts are coming to light with the launch of its overhauled Apple TV app.
The new app brings a handful of changes, the biggest one being the ability to subscribe to certain channels from directly within the app. Apple’s paid original content service Apple TV Plus, which will feature programming from Winfrey and Spielberg among many other recognizable names, is not available yet but will be accessible from the app when it launches in the Fall.
“The pop-up nature of dark-web marketplaces makes tracking their participants and their activities extremely difficult,” says Charlie Dagli, a researcher in MIT Lincoln Laboratory’s Artificial Intelligence Technology and Systems Group. Dagli is referring to the fast rate at which dark-web markets close down (because they are hacked, raided, abandoned, or set up as an “exit scam” in which the site shuts down intentionally after customers pay for unfulfilled orders) and new ones appear. These markets’ short lifetimes, from a few months to a couple years, impede efforts to identify their users.
To overcome this challenge, Lincoln Laboratory is developing new software tools to analyze surface- and dark-web data.
These tools are leveraging the one benefit this whack-a-mole-like problem presents — the connections sellers and buyers maintain across multiple layers of the web, from surface to dark, and across dark-web forums. “This constant switching between sites is now an established part of how dark-web marketplaces operate,” Dagli says.
A ballpark estimate for AI diffusion across major economies is over the next 5-15 years. This is the window during which to address the range of regulatory and broader social concerns associated with widespread deployment of AI. Key here is building trust and understanding of AI. This includes ensuring that AI contributes to building democratic, transparent, and fair societies. Failure to act could lead to a backlash against AI and regulation that is overly burdensome and stifles innovation.
In pursuit of a novel tool for the research and treatment of celiac disease, scientists at the Mucosal Immunology and Biology Research Center (MIBRC) at Massachusetts General Hospital (MGH) have validated the use of intestinal organoids. These 3-D tissue cultures are miniature, simplified versions of the intestine produced in vitro. Taking tissue from duodenal biopsies of celiac and non-celiac patients, researchers created the “mini-guts” to explore how the gut epithelium and microbiota-derived molecules respond to gluten, a complex class of proteins found in wheat and other grains.
“We currently have no animal model that can recapitulate the response to gluten that we see in humans,” said Stefania Senger, co-senior author of the study, which was published in Scientific Reports this week.
Introducing a new segment of ChinAI where I’ll make a case for or against some proposition … in what follows I’m blunt and sarcastic at times toward Financial Times reporting on Western-Chinese AI research partnerships not because I don’t respect its reporting (FT is second only to the New York Times in terms of China coverage in my opinion) but rather because I think “iron sharpens iron” should apply to argumentation.
New discoveries are ushering in the era of personalized medicine, and as a person diagnosed with Crohn’s disease, this is especially good for me and others with incurable diseases. They offer the potential to be less symptomatic or perhaps even cured one day. However, clinical care is not the only area that should be rigorously applied at the individual level.
Research shows that 70 percent of what drives overall health status and costs exists outside of the clinical system and are based on a person’s environment and lifestyle. This presents a massively valuable, but under-applied opportunity for the healthcare industry to guide and support consumers’ choices that impact their health status and lower healthcare costs.
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Personalized wellbeing – systematically understanding and predicting individual needs and providing highly-relevant and actionable health and wellbeing programming that respects and complements clinical care – is no less crucial than personalized medicine! But all too often, wellbeing is overshadowed by the dramatically higher mindshare captured by the better-understood clinical world of patients.
Seven floors, and long odds, were stacked against John S. He was undergoing a test on the first floor of a Cleveland Clinic hospital when his nursing team — on the eighth floor — got a call, telling them the 57-year-old had developed a dangerously rapid heartbeat that was spiraling toward cardiac arrest.
It is a predicament that often ends badly. Only about 25 percent of U.S. patients survive when their hearts stop in hospitals. Crucial minutes elapse before help arrives, sometimes because alarms are missed amid the din of beeping monitors.
But the call that day didn’t come from within the hospital. It came from a darkened room in an office park several miles away, where a technician in the clinic’s Central Monitoring Unit (CMU) was watching the patient’s vital signs on a computer monitor and noticed the onset of ventricular tachycardia.
The Columbia Center for Children’s Environmental Health has tracked the lives of hundreds of children in New York City since 1998. Scientists have collected samples of blood, urine and even the air in children’s homes, starting when their subjects were in the womb, to tease out the health effects of chemicals and pollutants. The centre’s findings influenced New York City’s decision in 2018 to phase out diesel buses, and its staff members teach schools and community groups about the harmful chemicals and pollution that kids encounter each day.
Now, the future of the Columbia facility and a dozen like it is in doubt. Their last grants from the US Environmental Protection Agency (EPA), which has provided half of the centres’ funding for two decades, will expire in July — and the agency has decided that it will not renew its support for the facilities.
[Michael] Snyder and his colleagues published a study suggesting that big data may succeed where conventional medicine fails.
In 109 volunteers whose bodies were closely tracked and analyzed, the researchers discovered a host of hidden conditions that required medical attention, including diabetes and heart disease.
“It turns out 53 out of 109 people learned something really, really important from doing these deep profiles,” Dr. Snyder said.
The research offers an unprecedented look at how common diseases may arise in different people along different molecular paths, said Ali Torkamani, director of genome informatics at Scripps Research Translational Institute, who was not involved in the new study.
Thanks to new machine-learning tools, researchers and police departments can use behavioral data to find the earliest signs an officer may be flouting policy or at risk of shooting an unarmed civilian. To build the algorithms that may one day be able to create a sort of “risk score” for police, researchers are using familiar tools: data from police body cameras and squad cars, and the internal reports usually kept locked in police departments away from researchers, including information on officer suspensions and civilian complaints.
Of all this information, body cameras—which were purpose-built to create an objective and unaltered record of an officer’s every move on the job—may be the most valuable.
New York, NY June 4, starting at 6:30 p.m. “Before the event, you’ll be connected with a mentor based on your interests and experiences. At Data Science for All, alongside your mentor, you’ll learn and practice new data science skills through a learning session and an open-ended project. In addition, you’ll connect with other aspiring and experienced data scientists throughout the event.” [registration required]
University of Washington, School of Public Health, Department of Biostatistics
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Seattle, WA July 8-24, University of Washington School of Public Health. “The Summer Institute in Statistics and Modeling in Infectious Diseases (SISMID) is designed to introduce infectious disease researchers to modern methods of statistical analysis and mathematical modeling and to introduce statisticians and mathematical modelers to the statistical and dynamic problems posed by modern infectious disease data.” [$$$]
London, England September 9-10. “The world-renowned Deep Learning Summit is returning to London, this time accompanied by the AI Assistant Summit, the AI in Retail and Advertising Summit and Deep Dive sessions.” [$$$]
New York, NY August 12-13 at New York University. “This conference will feature advances in both computational and experimental methods, including single cell analysis, genetic engineering, population genetics, and statistical and deep learning.” [$$$]
New York University, Institute for Public Knowledge
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New York, NY May 16, starting at 1:30 p.m., NYU Institute for Public Knowledge (20 Cooper Square, 5th floor). “What exactly, when we tune in to the Women’s World Cup this summer, are we watching unfold? How has the growing success of women in professional soccer, as players and coaches, affected female youth players? And what can we expect for the future of women’s soccer? Please join us as we explore these questions and so much more with our esteemed guests on the eve of this great tournament: the Women’s World Cup!” [rsvp required]
Bristol, England October 3, starting at 9 a.m. “Our conference will bring together anthropologists and technologists to foster dialogue and collaboration across the disciplines.” [$$$]
“The purpose of this RFI is to seek input from industry, institutions of higher education (IHEs), non-profits, government entities, and other interested parties on future NSF Convergence Accelerator tracks within these two Big Ideas, within other Big Ideas, or on other topics that may not relate directly to a Big Idea but that may have national impact.” Deadline for submissions is June 24.
The workshop will take place at IEEE VIS 2019. “This workshop will focus on the contributions possible from the information visualization and visual analytics communities to advance visual analytics of Multilayer Networks. The workshop provides a platform for short presentations on urgent challenges, innovative ideas, new frameworks, novel design concepts, fundamental requirements, and work in progress related to the workshop topic.” Deadline for submissions is June 30.
Machine Learning in Julia (MLJ) provides “a uniform interface enabling users to easily train, evaluate, and tune machine learning models. This open-source framework is written in the high-performance scientific programming language Julia.”
“We’re excited to make two announcements: initial support for WebGL-powered data visualization with the open source deck.gl library, and beta release of the next version of the Maps SDK for Android.”
“When school let out for summer on Wednesday, close to 100 Yalies left campus with a virtual toolbox in hand — a starter pack of data science methods, excellent for digging into whichever academic fields await them.”
“These students were enrolled in the first semester of ‘YData: An Introduction to Data Science,’ Yale’s new data science gateway course, co-taught by Jessi Cisewski-Kehe, assistant professor of statistics and data science, and John Lafferty, the John C. Malone Professor of Statistic and Data Science. A few dozen among them also signed up for one of three half-credit seminars, where they applied the skills they’ve learned in YData to text analysis, exoplanet astronomy, or political campaigns.”