A lawyer known for battling tech giants over the treatment of workers has set her sights on International Business Machines Corp.
Shannon Liss-Riordan on Monday filed a class-action lawsuit in federal court in Manhattan on behalf of three former IBM employees who say the tech giant discriminated against them based on their age when it fired them. Liss-Riordan, a partner at Lichten & Liss-Riordan in Boston, has represented workers against Amazon, Uber and Google and has styled her firm as the premier champion for employees left behind by powerful tech companies.
The definition of “data science” is fuzzy for me, almost as fuzzy as the term “computational thinking.” Does data science include computer science? statistics? probability? I think the answer is “yes” to all of those, but then it might be too big to easily teach in secondary schools. If we’re struggling to teach CS to teachers, how do we teach them CS and statistics and probability?
And if budgets and schedules are are a zero-sum game, what do we give up in order to teach data science? For example, teacher preparation programs are packed full. What do we not teach in order to teach teachers about data science?
This group of experts knows a lot about what works in data science. Their opinion on what students need to know creates a useful measuring stick with which to look at the several data science classes that are being created (such as Unit 5 in Exploring CS). There’s some talk about this group of experts might develop their own course. I’m not sure that it’s possible to create a course to work internationally — school systems and expectations vary dramatically. But a framework is useful.
SAGE Publishing today launched its first preprints server for the humanities and social sciences, in partnership with Figshare.
Advance: a SAGE preprints community will provide academic researchers with a global platform to share early versions of their work ahead of formal peer review and publication. The open access platform will support original research and reviews, making content open to receiving feedback from colleagues and peers. The service enables researchers to disseminate and start communicating about their time-sensitive work and ideas faster and to garner engagement and feedback throughout their research process. All preprints published on Advance are eligible for publication in a wide range of SAGE’s portfolio of peer-reviewed journals.
Commenting on the new platform, Bob Howard, Senior Vice President of Global Journals, SAGE Publishing, remarked:
“Publishing and the dissemination of research is changing; transparency is key. Within the social sciences, moving to facilitate broad dissemination of ideas earlier in the research process will help to support wider engagement with these influential areas of research.
The newly hatched saltmarsh sparrows are helpless, all but featherless, with reddish skin, barely visible in the evening light.
Mosquitoes buzz as Samantha Apgar holds aside a tangle of marsh grass, or salt hay, to show me the hidden nest. It’s the size of half a baseball, tucked in under a tangle of grass. The incoming tide is rising over the soles of our boots and the hatchlings won’t stay dry long.
Ms. Apgar, a graduate student at the University of Connecticut, is working with Christopher Elphick, an ornithologist there, to record what happens when high tides flood the nests of marsh birds. She has automatic video cameras and is also collaborating with videographers from the Cornell Lab of Ornithology, one of whom has his camera trained on this nest and had recorded the hatching of these babies a couple of hours before.
She warns me that the outlook for these fragile hatchlings is grim. If they last through the night, they still have five days of increasingly high tides ahead of them until the new moon. “I don’t think they’re going to make it,” Ms. Apgar says.
I frequently refer to the era of big data as “the end of demographics”. By that, I mean that we now have many more features, attributes, data sources, and insights into each entity in our domain: people, processes, and products. These multiple data sources enable a “360 view” of the entity, thus empowering a more personalized (even hyper-personalized) understanding of and response to the needs of that unique entity. In “big data language”, we are talking about one of the 3 V’s of big data: big data Variety!
High variety is one of the foundational key features of big data — we now measure many more features, characteristics, and dimensions of insight into nearly everything due to the plethora of data sources, sensors, and signals that we measure, monitor, and mine. Consequently, we no longer need to rely on a limited number of features and attributes when making decisions, taking actions, and generating inferences. We can make better, tailored, more personalized decisions and actions. Every entity is unique! That marks the end of demographics.
Scientists at the Allen Institute have used machine learning to train computers to see parts of the cell the human eye cannot easily distinguish. Using 3D images of fluorescently labeled cells, the research team taught computers to find structures inside living cells without fluorescent labels, using only black and white images generated by an inexpensive technique known as brightfield microscopy. A study describing the new technique is published today in the journal Nature Methods.
Fluorescence microscopy, which uses glowing molecular labels to pinpoint specific parts of cells, is very precise but only allows scientists to see a few structures in the cell at a time. Human cells have upwards of 20,000 different proteins that, if viewed together, could reveal important information about both healthy and diseased cells.
“This technology lets us view a larger set of those structures than was possible before,” said Greg Johnson, Ph.D., Scientist at the Allen Institute for Cell Science, a division of the Allen Institute, and senior author on the study. “This means that we can explore the organization of the cell in ways that nobody has been able to do, especially in live cells.”
Ten years ago this month, Google’s first employee turned up at the garage where the search engine was originally housed. What technology at a similar early stage today will have changed our world as much by 2018? Nature asked some researchers and business people to speculate — or lay out their wares. Their responses are wide ranging, but one common theme emerges: the integration of the worlds of matter and information, whether it be by the blurring of boundaries between online and real environments, touchy-feely feedback from a phone or chromosomes tucked away on databases.
The University at Buffalo announced today that it is launching a multidisciplinary artificial intelligence institute — the University at Buffalo Artificial Intelligence Institute (UBuffalo.AI).
UBuffalo.AI will explore how to combine machines’ superior ability to ingest, connect and recall information with concepts that humans excel at, such as reasoning, judgement and strategizing, to develop dynamic human-machine partnerships.
To lead UBuffalo.AI, the university recruited David Doermann, PhD, from the University of Maryland (UMD) and the Defense Advanced Research Projects Agency (DARPA).
You can think of a cell in your body like a miniature factory, creating a final product called proteins, which carry out various tasks and functions. In this cellular factory, genes control the series of sequential steps needed to create proteins, much like an assembly line moving a product along to completion. This process is known as gene expression.
Even when two cells are genetically identical and in the same environment, the amount of each protein they express can be very different. This variability—or noise—has been shown to play a role in viral infection, antibiotic resistance, and drug resistance in cancer cells.
A group of scientists led by Leor S. Weinberger, PhD, the William and Ute Bowes Distinguished Professor and director of the Center for Cell Circuitry at the Gladstone Institutes, are studying the factors within a cell that can influence noise.
Instead of blank, barren sea, the expedition, led by scientists with Stanford University and the Monterey Bay Aquarium, found a vast community of tiny light-sensitive creatures so tantalizing that the sharks cross the sea en masse to reach them.
The primary lure, scientists believe, is an extraordinary abundance of squid and small fish that migrate up and down in a little understood deep-water portion of ocean known as the “mid-water,” a region skirting the edge of complete darkness that could provide an immeasurably valuable trove of information about the ocean ecosystem and climate change.
“The story of the white shark tells you that this area is vitally important in ways we never knew about,” said Salvador Jorgensen, a research scientist for the Monterey Bay Aquarium and one of the expedition’s leaders. “They are telling us this incredible story about the mid-water, and there is this whole secret life that we need to know about.”
Dr. Brian McFee is an Assistant Professor in Music Technology and Data Science. He was previously a Moore-Sloan Data Science fellow at CDS, where his areas of interest included machine learning, music information retrieval, recommender systems, and multimedia signal processing. Before this, McFee was a postdoctoral research scholar in the Center for Jazz Studies and LabROSA at Columbia University. On August 20th, 2018, McFee discussed his new position, latest work in the field, and interests with Sabrina de Silva, CDS Content Writer.
UTSA today announced it has received a $15 million gift from San Antonio business leader Graham Weston to support the university’s proposed School of Data Science. The school is a major component in UTSA’s phased, 10-year approach to accelerating the development of its Downtown Campus as a destination for producing highly skilled professionals in big data and analytics, advancing economic development in the urban core and creating prosperity for San Antonio.
At the same time, UTSA is actively engaged in highly collaborative discussions with the City of San Antonio and Bexar County for the transfer of downtown parcels of land, valued at $13 million, to the university. Those parcels would be the sites for the new school, a National Security Collaboration Center, and for the relocation of the UTSA College of Business.
Earlier this month, The University of Texas System Board of Regents approved a $70 million Permanent University Fund (PUF) allocation for the School of Data Science and National Security Collaboration Center. Combined with the Weston gift and an additional $5 million in university funds, UTSA has now secured the $90 million needed to fully advance those two construction projects.
The University of New England has announced that it is adding a new Data Science program to its offerings.
The program, which leads to a bachelor of science degree, will be part of the Department of Mathematical Sciences, located on the university’s Biddeford Campus, according to UNE President Dr. James Herbert.
Amazon.com Inc. risks following in the footsteps of Google after the European Union’s antitrust chief said regulators are asking how the online retailer is treating smaller rivals trading on its own website.
After fining Google billions of euros, the EU is checking how Amazon gathers information on sales made by competitors on Amazon Marketplace and whether that gives it an edge when it sells to customers, EU Competition Commissioner Margrethe Vestager told reporters at a press conference in Brussels.
Meetup, Social Science, Big Data & Technology – London
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London, England November 6, starting at 6 p.m., The Stars of Kings (126 York Way Kings Cross). “This panel will highlight some of the questions around what skills future social scientists should be expected to have and how to support the development of those skills.” [free, rsvp required]
New York, NY September 26, starting at 5:30 p.m., NYU Center for Data Science (CDS Open Space, 60 5th Avenue, 7th Floor). [free, registration required]
New York, NY September 20, starting at 6 p.m., NYU Institute for People & Knowledge (20 Cooper Square, 5th Fl). “The discussion will explore how civic technology is enabling new and improved forms of citizen participation, deliberation, and collaboration between government and the public, helping public institutions to benefit from the wisdom of the crowd and empowering citizen-led community at a national scale.” [free, rsvp requested]
Since designing and launching a specialized workflow management system in 2010, a research team from the U.S. Department of Energy’s Oak Ridge National Laboratory has continuously updated the technology to help computational scientists develop software, visualize data and solve problems.
Workflow management systems allow users to prepare, produce and analyze scientific processes to help simplify complex simulations. Known as the Eclipse Integrated Computational Environment, or ICE, this particular system incorporates a comprehensive suite of scientific computing tools designed to save time and effort expended during modeling and simulation experiments.
Compiling these resources into a single platform both improves the overall user experience and expedites scientific breakthroughs. Using ICE, software developers, engineers, scientists and programmers can define problems, run simulations locally on personal computers or remotely on other systems—even supercomputers—and then analyze results and archive data. Recently, the team published an article in SoftwareX that both details the history of the system and previews the potential benefits of upcoming versions.