Data Science newsletter – June 22, 2021

Kyle Cranmer, CDS Professor of Data Science and Professor of Physics at the NYU College of Arts & Science, recently co-authored “Reframing Jet Physics with New Computational Methods” which is available at arXiv.org. The project was presented last month at the 25th International Conference on Computing in High-Energy and Nuclear Physics (vCHEP) by Kyle’s co-author and colleague Sebastian Macaluso, a postdoctoral associate in the NYU Physics Department.

Over the last year, a gathering parade of writers — including some of the biggest names in journalism — have abandoned traditional publications for the greener, less centralized pastures of independent newsletters. The exodus has often been driven by frustrations with the various interlopers who stand between content creators and their audiences. Newspaper editors? Social media algorithms? No need to worry about these gatekeepers, the thinking goes, when you can just email your thoughts straight to whoever wants them. … Newsletter writers talk about Gmail and its whims “the way that Greeks used to talk about Greek gods,” said one writer, who publishes a newsletter through Substack competitor MailChimp. Like some ancient, unknowable deity, Gmail “has this influence over our lives, but we don’t know … how they’re making decisions and how it will affect us from one day to another. We just know that it’s always changing, and sometimes it’s good news and sometimes it’s bad news.”

Do you like the thick brush strokes and soft color palettes of an impressionist painting such as those by Claude Monet? Or do you prefer the bold colors and abstract shapes of a Rothko? Individual art tastes have a certain mystique to them, but now a new Caltech study shows that a simple computer program can accurately predict which paintings a person will like.

Rapidly worsening drought and a mandate to bring aquifer withdrawals and deposits into balance by 2040 have ignited interest in replenishing California groundwater through managed aquifer recharge. Stanford scientists demonstrate a new way to assess sites for this type of project using soil measurements and a geophysical system towed by an all-terrain vehicle.

Nature spoke to researchers about formative collaborations that descended into author disputes. We also heard from laboratory leaders, publishers and funders who are trying to devise a fairer system of recognizing individual contributions to academic papers. Here, they outline their efforts and describe steps that researchers can take to mitigate author disputes and other tensions that can arise in collaborations. One suggestion is to have a scientific ‘pre-nup’, or team charter, spelling out roles, responsibilities and processes for conflict resolution in advance. Some interviewees requested anonymity because of concerns that sharing their stories could harm their careers.

As part of its ongoing strategic intent to provide the best possible service to the US research ecosystem, Springer Nature is launching a US Research Advisory Council (USRAC).

The USRAC was organized by a Springer Nature steering group and task force representing its diversity of research publishing and solutions activity including books, journals, magazines and databases, which included Laura Helmuth, editor in chief of Scientific American, and Magdalena Skipper, editor in chief of Nature. This new body will meet annually in a roundtable workshop format with members drawn from institutions, funders, policy makers and research-driven organizations and advise on research culture and how research contributes to a better and more equitable society. The broad topic of the Council’s first meeting will be how COVID-19 has affected research and the way it is communicated.

If you’ve ever crammed for an exam just before bedtime, you may have tried something dream researchers have been attempting for decades: coaxing knowledge into dreams. Such efforts have had glimmers of success in the lab. Now, brands from Xbox to Coors to Burger King are teaming up with some scientists to attempt something similar: “Engineer” advertisements into willing consumers’ dreams, via video and audio clips. This week, a group of 40 dream researchers has pushed back in an online letter, calling for the regulation of commercial dream manipulation.

“Dream incubation advertising is not some fun gimmick, but a slippery slope with real consequences,” they write on the op-ed website EOS. “Our dreams cannot become just another playground for corporate advertisers.”

In a paper published May 26, Jodi Halpern, professor of bioethics and medical humanities at UC Berkeley and UCSF, argued that artificial intelligence, or AI, is not a substitute for human empathy in health care.

Halpern wrote the paper with authors Carlos Montemayor and Abrol Fairweather from San Francisco State University. In the paper, they claim that simulating empathy with AI is both impossible and immoral — impossible because AI cannot experience emotion and immoral because patients deserve human empathy during times of distress.

Halpern said the paper is a response to the growth of AI in health care, especially concerning mental health.

A number of smart city projects, such as smart traffic and smart lighting, have been underway for some time in cities across the globe.

Technologies like 5G and artificial intelligence (AI) are helping to drive many of these projects but, both governments and technology providers still need to overcome numerous technological obstacles as well as develop business models that will be able to deliver a clearer return on investment. So, is a fully interconnected smart city any closer to being realised?

Greg Corlis, managing director for emerging technologies at KPMG, said, “Not really. Cities are still struggling with the economics to really achieve smart city status. What we are seeing today is that most cities are still experimenting with these technologies for discrete use cases. Smart lighting is a relatively easy and safe use case for them to dip their toes in the water.”

Thus far, Google has blocked voice assistant interoperability, but a representative signaled this week that the company’s stance could evolve.

Flint in Michigan is infamous for its water crisis. From 2014, the state government decided to divert the city’s water supply through ageing pipes that contained lead, a neurotoxin, making many people unwell and leading to some deaths. Residents were left searching out water that was safe for drinking, washing and bathing. Nine public officials face criminal negligence charges around wilful neglect of duty and for allegedly concealing and misrepresenting data. A US$640-million class-action lawsuit is moving its way through the courts.

But Flint should be known for more than its public-health tragedy. Accounts of the crisis often cast pioneering scientists and physicians as lone heroes, assuming that those who documented the lead in the water and blood of Flint’s residents were the ones who brought officials to account. That assumption erases the work of community activists who got academics to look for lead and its damaging health effects in the first place. Flint is a working example of how community members and academics can collaborate on problems — such as how to collect data or develop robust models of health risks and injustices — and on finding solutions.

@CMU_MSE
researchers are integrating advanced computational techniques with hands-on experimentation.

In part, that may be because the endowment system many schools use to remain solvent brought colleges and universities significant financial rewards amid a rapid rise in stock prices. Those gains followed a major dip in the stock market immediately after the first US Covid-19 outbreaks — and quickly falling prices, in part, led to stark austerity measures.

Now, only a year after laying off hundreds of thousands of people, the higher education industry appears to be bouncing back.

The education and health services industry saw 87,000 people hired in the month of May, according to the US Bureau of Labor Statistics, and 129,000 people hired in the two months prior. And there are signs of more hiring to come. For example, the University of Michigan just announced it would be ending a year-long hiring freeze at the beginning of the 2022 fiscal year in July.

The Institute of Electrical and Electronics Engineers Communications Society recognized an Army researcher and collaborators their work on artificially intelligent techniques that will enhance Soldiers’ situational awareness in the multi-domain operating environment.

Dr. Kevin Chan, researcher for the U.S. Army Combat Capabilities Development Command, known as DEVCOM, Army Research Laboratory, and collaborators from the IBM T. J. Watson Research Center, Imperial College London and Pennsylvania State University earned the IEEE’s Leonard G. Abraham prize for for their paper, Adaptive Federated Learning in Resource Constrained Edge Computing Systems. The researchers published their findings in the IEEE Journal on Selected Areas in Communications.

According to the researchers, the collaborative effort was possible because of the lab’s Distributed Analytics and Information Science International Technology Alliance. The program seeks to develop the fundamental underpinning research required to enable secure, dynamic and semantically-aware distributed analytics for deriving situational understanding in coalition operations.

While AI and big data pave the way for such evolutionary use cases, the pair do not constitute a business strategy on their own accord. “The question is how do you use AI right or use it wisely,” said panelist Ed McLaughlin, president of operations and technology for Mastercard.

“The biggest lesson learned is how to take these powerful tools and start backward from the problem,” McLaughlin said. “What are the things you’re trying to solve for, and how can you apply these new tools and techniques to solve it better?”

In various EmTech conference tracks, experts outlined use cases where firms have effectively embedded AI into complex processes and scenarios to solve real-world business and social problems.

In our last post, ”Using OpenCV AI Kit with Modelplace.ai To Create Real-time Reaction Videos”, we wrote about how simple it is to make a real product using a model from Modelplace.AI. Today we’re continuing the series of blog posts about the Modelplace by OpenCV.AI with a look behind the scenes. One of the core features of Modelplace.AI is the custom-built testing infrastructure which helps to ensure models will work on the user’s end device.