A team of researchers from Brown, Baylor University, University of California at San Diego and Qualcomm has been working in the past four years on a new approach to interface with the brain. So far BCIs make use of electrodes (implanted, or positioned inside/outside the skull) that can sense electrical activity created by surrounding neurones (and in some cases also deliver electric currents to stimulate those neurones). For obvious reasons the numbers of electrodes is limited and their position restricted to a specific area, particularly if the electrodes are implanted.
This team has explored the possibility of creating very small sensors, look at the photo to get a sense of their dimension, packaged with a chip that can communicate wirelessly. The resulting micro devices are called “neurograins” and are spread onto the cerebral cortex. Each neurograin communicate wirelessly with a thumb size patch places, like a bandaid, on the head, its position is irrelevant. This patch gather the signals and relay them to a nearby computer with software that can analyse the signals. This software can also work out where the signals are coming from and keep and updated map of the location of each neurograin (if it happens to move the software can track the displacement to keep the map up to date).
The researchers have now announced that they have a viable system: it has been tried on a mouse brai
The Conversation; Cason Schmit, Brian N. Larson, Hye-Chung Kum
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When we talk about data, we generally mean the information that is collected when people receive services or buy things in a digital society, including information on health, education and consumer history. At their core, data protection laws are concerned with three questions: What data should be protected? Who can use the data? And what can someone do with the data?
Our team conducted a survey of over 500 U.S. residents to find out what uses people are most comfortable with. We presented participants with pairs of 72 different data use scenarios. For example, are you more comfortable with a business using education data for marketing or a government using economic activity data for research? In each case, we asked participants which scenario they were more comfortable with. We then compared those preferences with U.S. law – particularly in terms of types of data being used, who is using that data, and how.
Under U.S. law, the type of data matters tremendously in determining which rules apply. For example, health data is heavily regulated, while shopping data is not.
National Bureau of Economic Research, Working Paper, H. Spencer Banzhaf
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The Value of Statistical Life (VSL) is arguably the most important number in benefit-cost analyses of environmental, health, and transportation policies. However, agencies have used a wide range of VSL values. One reason may be the embarrassment of riches when it comes to VSL studies. While meta-analysis is a standard way to synthesize information across studies, we now have multiple competing meta-analyses and reviews. Thus, to analysts, picking one such meta-analysis may feel as hard as picking a single “best study.” This paper responds by taking the meta-analysis another step, estimating a meta-analysis (or mixture distribution) of six meta-analyses. The baseline model yields a central VSL of $7.0m, with a 90% confidence interval of $2.4m to $11.2m. The provided code allows users to easily change subjective weights on the studies, add new studies, or change adjustments for income, inflation, and latency.
Health and wellness wearable technology has grown beyond shiny accessories. Companies are developing and testing clothing-oriented wearables to enhance remote monitoring for critical healthcare needs.
“I’d say we are in the third generation of wearables, and the industry is converging the best of both the medical and wellness sides,” says Venk Varadan, co-founder and CEO of Nanowear. “It is really going to be transformative in healthcare.”
This next iteration of wearables is going beyond well-known devices such as smartwatches and exploring other clothing options to gather more detailed data and become more user-friendly.
The Nebraska Governance and Technology Center is now supporting the student organization, Broader Considerations of Technology, through their relationship with the Robert J. Kutak Center for the Teaching and Study of Applied Ethics at the University of Nebraska–Lincoln.
BCT was co-founded and is currently led by Colton Harper, a doctoral student at Nebraska from Hutchinson, Kansas. The organization has strong ties to Computer Science and Engineering. BCT’s main focus is drawing attention to the various social, political and moral concerns that arise from technological advances, especially the design and implementation of computer-based technologies.
Placed behind a transparent wall for all to see, the robot chef can make up to three pizzas at a time. The choreography is well-oiled – the robot picks up a ball of dough and flattens it with a red cylinder, covers it with sauce and toppings and puts it in the oven. After a few minutes, it puts the pizza in a box and then pops it through an opening for customers to collect. Orders are also placed digitally via a self-service terminal. Everything is automated, but under the constant supervision of human employees.
The robot’s skills don’t stop at pizza making – while working on the dough, it can also embark on elaborate choreographies to the rhythm of music blasted from the restaurant’s speakers.
“We took a chapter from show cooking and ran with it,” said Sébastien Roverso, one of Pazzi’s founder.
Artificial intelligence tools in hiring have so far remained unregulated by U.S. civil rights agencies, despite growing use and potential discrimination risks. One EEOC official wants that to change.
“What is unfair is if there are enforcement actions or litigation, both from the government and from the private sector, against those who are using the technologies, and the federal agency responsible for administering the laws has said nothing,” Keith Sonderling, a Republican commissioner on the U.S. Equal Employment Opportunity Commission, told Bloomberg Law in an exclusive interview.
BT, the Grammy-nominated composer of 2010’s These Hopeful Machines, has emerged as a world leader at the intersection of tech and music. Beyond producing and writing for the likes of David Bowie, Death Cab for Cutie, Madonna, and the Roots, and composing scores for The Fast and the Furious, Smallville, and many other shows and movies, he’s helped pioneer production techniques like stutter editing and granular synthesis. This past spring, BT released GENESIS.JSON, a piece of software that contains 24 hours of original music and visual art. It features 15,000 individually sequenced audio and video clips that he created from scratch, which span different rhythmic figures, field recordings of cicadas and crickets, a live orchestra, drum machines, and myriad other sounds that play continuously. And it lives on the blockchain. It is, to my knowledge, the first composition of its kind.
Could ideas like GENESIS.JSON be the future of original music, where composers use AI and the blockchain to create entirely new art forms? What makes an artist in the age of algorithms? I spoke with BT to learn more.
Northwestern Kellogg School of Business, Kellogg Insight
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In some respects, there has never been a better time for marketers to learn about their customers. The amount of data available to companies can help them keep tabs on how well their initiatives are working; experiment with new products, services, or delivery methods; or find new sources of growth. But the large amount of data is less likely to be effective if you don’t have a plan for putting it to use.
In their new book, The AI Marketing Canvas: A Five Stage Roadmap to Implementing Artificial Intelligence in Marketing, Raj Venkatesan of the University of Virginia and his coauthor Jim Lecinski, a clinical associate professor of marketing at the Kellogg School, lay out an action plan for chief marketing officers to plan and implement a sustainable AI-driven marketing function within their organizations.
Science fiction is becoming fact, according to United States Rep. Jim Langevin (D-RI) — and as a result, he and fellow U.S. Rep. Elise Stefanik (R-NY) have successfully added 11 artificial intelligence (AI)-focused amendments to the National Defense Authorization Act for Fiscal Year 2022.
While the larger legislation remains in committee, the successful amendment additions — passed by voice vote — represent forward momentum for a series of recommendations made by the National Security Commission on Artificial Intelligence. These include questions of workforce, modifications to strategy, investment and ethical use.
“Tomorrow’s battlefield will not be about a particular platform or weapons system, but about how we connect those systems, analyze data from hundreds of sensors, and help commanders make better tactical and strategic decisions,” Langevin, chairman of the House Armed Service Committee’s Cyber, Innovative Technologies and Information Systems subcommittee, said. “To stay ahead of our adversaries, we must innovate faster. We must streamline our acquisition policies. And we must have an AI-ready defense workforce — from the lab experts to generals and admirals who understand what is possible.”
FiveThirtyEight; J. Nathan Matias, Neil Lewis Jr. and Elan Hope
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When she was hired as a professor by Harvard University in 2013, Lorgia García Peña was the only Black Latina on a tenure track in the university’s Faculty of Arts and Sciences. But in 2019, she was denied tenure even though her department chair and two deans had told her that she should apply for early tenure. Her tenure committee also unanimously recommended she be promoted, and another committee above that endorsed its recommendation. About two years later, famed professor and public intellectual Cornel West announced that he, too, was leaving Harvard after the university refused to grant him tenure. And of course, this spring we learned that Pulitzer Prize-winning, MacArthur Fellowship recipient Nikole Hannah-Jones was denied tenure by the board of trustees at the University of North Carolina — after the university’s journalism school had recruited her to become its Knight Chair in Race and Investigative Journalism. That decision was later reversed, but by that point, it was too late to convince her to stay.
These stories made headlines and sparked outrage, especially among academics, in part because they were some of the biggest “no-brainer” tenure cases — those three scholars are among the most famous and well-regarded in their respective fields. Denying them tenure is functionally equivalent to having MVP-caliber athletes on your roster but sending them to play for another team.
Bloomberg Wealth, Patricia Hurtado and Janet Lorin
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The “Varsity Blues” sting exploded into public view in 2019, with dozens of parents across the U.S. arrested for allegedly paying hundreds of thousands of dollars to get their kids into elite universities.
Now, the first parents go on trial in Boston, accused of taking part in the scandal that revealed a tawdry underbelly of the U.S. college admissions process in which “donations” lined the pockets of middlemen and faked athletic prowess or altered test scores opened doors for the children of the wealthy to attend the school of their choice.
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Jury selection is set to begin Wednesday for the case against John B. Wilson, 62, a private equity investor, and Gamal Abdelaziz, 64, a former executive for Wynn Resorts Ltd. Both have pleaded not guilty, and are among a select few who have elected to fight their case in court. Thirty-three other parents accused of taking part in the scandal have pleaded guilty, serving sentences that range from two weeks to nine months in jail. Four more parents are scheduled to go on trial next year.
When Covid-19 hit Spain last spring, the country quickly hit breaking point. In Madrid, doctors described an “avalanche” of patients as they practised “combat medicine” and emergency triage in intensive care units that were operating on a war-like footing. The first Covid-19 death was recorded on March 1. A month later, just under a thousand people were dying each day. Ambulances choked hospital approach roads and ice rinks were transformed into morgues.
In mid-March, as the virus spread to all regions of Spain, Nuria Oliver realised that this poorly understood threat required immediate action. And Oliver, who is a data scientist, felt particularly well qualified to help with this public health crisis: in her previous roles at telecoms giants, she had developed tools using GPS data to track the spread of H1N1 influenza in Mexico, Ebola in the Democratic Republic of Congo, and malaria in Mozambique. “The context was there, and the timing was right,” she says. Oliver reached out to her local government contacts in the region of Valencia, explaining how data might help combat the unfolding crisis.
A native of Alicante, Oliver had earned a PhD in 2000 from the Massachusetts Institute of Technology. For her thesis she had created algorithms that used video and other sensory inputs to automatically detect, recognise, and predict various forms of human interaction. She subsequently spent more than seven years on a research team at Microsoft, then took on senior positions at telecoms firms Telefonica and Vodafone – where she gained a global reputation for her work modelling human behaviour – before returning to her hometown for personal reasons.
MLOps is the art and science of bringing machine learning to production, and it means many things to many people. The State of MLOps is an effort to define and monitor this market.
One of the popular memes in literature, movies and tech journalism is that man’s creation will rise and destroy it. Lately, this has taken the form of a fear of AI becoming omnipotent, rising up and annihilating mankind.
The economy has jumped on the AI bandwagon; for a certain period, if you did not have “AI” in your investor pitch, you could forget about funding. (Tip: If you are just using a Google service to tag some images, you are not doing AI.)
However, is there actually anything deserving of the term AI? I would like to make the point that there isn’t, and that our current thinking is too focused on working on systems without thinking much about the humans using them, robbing us of the true benefits.
The Pew Charitable Trusts, Stateline, Christine Vestal
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Daniel Daltry, Vermont’s chief of disease investigation, knows exactly what his department is going to do with the extra $1 million it’s slated to receive from the federal government every year for the next five years: “We’re going to hire 10 more of me,” he said.
“That way, when the next crisis hits those 10 people will be able to hire and train 10 more people under them.”
With 624,000 residents, Vermont will receive the minimum state allocation from a $1 billion fund included in this year’s American Rescue Plan Act, the most recent COVID-19 relief package. Nationwide, the funds are designed to more than double the number of disease investigators and contact tracers working at state and local health agencies. And that money is just one part of the $7.6 billion fund included in the package for public health workforce development.
Whoop is one of the most valuable fitness-wearable startups in the world, topping $3.6 billion in value with its latest investment round last week. Elite athletes like Michael Phelps, Patrick Mahomes, and Justin Thomas flash the devices on their wrists. The COVID-19 pandemic has unlocked some clinical applications for the product. And on Wednesday, the company released its most advanced products yet, with new tracking features in its wrist band and an apparel line that lets users embed sensors in workout garments.
Related: Fitness wearable company Whoop raises $200 million, now valued at $3.6 billion
Whoop was founded back in 2012. It was Ahmed’s brainchild, born out of his desire to track how efficiently he was working out. A college athlete and government major with little science background, Ahmed said he read hundreds of medical papers. In study after study, he found that if athletes rigorously tracked certain metrics, like the variability in their heart rate, they could learn if their body was ready to work out or needed rest.
Online October 14, starting at 10 a.m. Eastern. “O’Reilly Radar: Data & AI will showcase what’s new, what’s important, and what’s coming in the field. It includes two keynotes and two concurrent three-hour tracks—designed to lay out for tech leaders the issues, tools, and best practices that are critical to an organization at any step of their data and AI journey. You’ll explore everything from prototyping and pipelines to deployment and DevOps to responsible and ethical AI.” [free]
BWH/HMS Computational Neuroscience Outcomes Center
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Boston, MA, and Online November 5, starting at 8 a.m. “he 2021 focus is Digital Phenotyping & personal sensing in health.” Deadline for submissions is October 5.
“The Swedish COVID-19 Data Portal invites researchers and general public to take part in the COVID-19 Data & Code Reuse Competition. Participants should complete small-scale projects that make use of publicly shared data and/or code to combat the COVID-19 pandemic or any future pandemics.” Deadline for submissions is December 5.
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The eScience Institute’s Data Science for Social Good program is now accepting applications for student fellows and project leads for the 2021 summer session. Fellows will work with academic researchers, data scientists and public stakeholder groups on data-intensive research projects that will leverage data science approaches to address societal challenges in areas such as public policy, environmental impacts and more. Student applications due 2/15 – learn more and apply here. DSSG is also soliciting project proposals from academic researchers, public agencies, nonprofit entities and industry who are looking for an opportunity to work closely with data science professionals and students on focused, collaborative projects to make better use of their data. Proposal submissions are due 2/22.
Uncomfortable conversations are inevitable in many research and professional relationships, including statistical collaborations. Topics can vary widely due to the different backgrounds and expectations of researchers. Common discussions include those about coauthorship, the role of the statistician, and even technical concepts. Reasons for discomfort can include misaligned expectations, the tone of either participant in the conversation, and particular topics or words (e.g., bias) that might escalate the conversation from congenial to difficult.
Although it feels difficult, it is important to navigate our way through uncomfortable conversations with the goal of ending in mutual understanding and a clear path forward. In The Champion Forum podcast, Jeff Hancher argues that avoiding difficult conversations is a disservice to everyone and gives the following five reasons we should have them:
To build mutual trust – As collaborative statisticians, we build trust and respect by being honest with our collaborators, even around difficult topics.
To communicate value – We show collaborators we value them enough to have tough conversations.
To clarify the future – Without having a conversation, each party is left to their own interpretation and conclusions, which can be misunderstood and result in misaligned expectations.
To increase self-awareness – It is important to come to an understanding of where their (or our) understanding may be falling short.
To stretch our leadership – With each difficult conversation we have, our ability to have productive conversations improves and the range of topics we are confident in tackling expands.
