In the past, technology experts have worried about a “digital divide” between those who could access computers and the internet and those who could not. Households with less access to digital technologies are at a disadvantage in their ability to earn money and accumulate skills.
But, as digital devices proliferate, the divide is no longer just about access. How do people deal with information overload and the plethora of algorithmic decisions that permeate every aspect of their lives?
The savvier users are navigating away from devices and becoming aware about how algorithms affect their lives. Meanwhile, consumers who have less information are relying even more on algorithms to guide their decisions.
Dog lovers agree: Round and fluffy, wrinkled and snub-nosed, or skinny and sleek, dogs are cute.
The question is, how does a group of canine aficionados come to a fair consensus about which wet nose and wagging tail evokes the loudest “awww!”?
A group of students at Northeastern has spent the semester trying to find out. The Democracy and Social Choice Project, a directed study better known as the Cute Dog Project, began with a simple premise: Determine who in Northeastern’s philosophy and religion department has the cutest dog. And, along the way, work through the challenges of designing a democratic voting system.
What factors will drive the development of the sixth generation of mobile technology? How will 6G differ from 5G, and what kinds of interactions and activity will it allow that won’t be possible with 5G?
Today, we get an answer of sorts, thanks to the work of Razvan-Andrei Stoica and Giuseppe Abreu at Jacobs University Bremen in Germany. These guys have mapped out the limitations of 5G and the factors they think will drive the development of 6G. Their conclusion is that artificial intelligence will be the main driver of mobile technology and that 6G will be the enabling force behind an entirely new generation of applications for machine intelligence.
Technology companies have been taking flak lately for collaborating with the U.S. military — but are they helping the Chinese government expand its surveillance state at the same time? The revelation this month that Microsoft researchers collaborated with academics at a Chinese military-run university sparked outrage from China hawks. Careful consideration would be a more prudent response.
The Financial Times reported April 10 that specialists at Microsoft Research Asia published three papers over the past year with co-writers affiliated with China’s National University of Defense Technology, controlled by the country’s Central Military Commission. Critics say the research could aid China in repressing its citizens, not to mention in throwing its Uighur minority into reeducation camps. Microsoft counters that the projects aim to solve artificial intelligence conundrums that academics around the world are working on together, and that the technologies have no closer relation to surveillance than WiFi or a Windows operating system.
Google and its sister companies, parts of the holding company Alphabet, are making a huge investment in the field, with potentially big implications for everyone who interacts with Google — which is more than a billion of us.
The push into AI and health is a natural evolution for a company that has developed algorithms that reach deep into our lives through the Web.
“The fundamental underlying technologies of machine learning and artificial intelligence are applicable to all manner of tasks,” says Greg Corrado, a neuroscientist at Google. That’s true, he says, “whether those are tasks in your daily life, like getting directions or sorting through email, or the kinds of tasks that doctors, nurses, clinicians and patients face every day.”
The Brookings Institution, Kevin C. Desouza and Kiran Kabtta Somvanshi
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As artificial intelligence technologies take over a larger number of tasks, India will face unique impacts of automation relative to other countries. With its large and young population, advances in AI will affect India in aspects from jobs to quality of life. Incidentally, the Indian economy is currently ill-equipped to face the advent of automation and AI. Though India is one of the fastest growing large economies, higher growth is not converting into more jobs. There are measures that the country must take to meet the challenges that arise as different working environments steadily automate. These include boosting employment in sectors that are least vulnerable to automation and encouraging entrepreneurship among the youth. Political will and awareness of the challenges associated with automation are key prerequisites to prepare India for automation.
Federal health officials on Monday unveiled a new primary care experiment that seeks to pay doctors for providing stepped-up services that keep patients healthy and out of the hospital, an effort they say will transform basic medical services for tens of millions of American patients.
The initiative, called CMS Primary Cares, includes five new payment options for small and large providers, allowing them to take varying levels of financial responsibility for improving care and lowering costs. It broadly seeks to change how primary care is delivered in the U.S. by rewarding doctors for improving management of patients with chronic illnesses such as diabetes and high blood pressure, and averting expensive trips to the hospital.
Beijing officials also challenged the usefulness of the U.S. data, pointing out, for instance, that the embassy sensor was in only one location and therefore could be giving an incomplete picture. In response, the embassy teamed up with U.S. Environmental Protection Agency (EPA) scientists to validate the results. “Since we were being criticized, we wanted to make sure we were doing it correctly,” says Erica Thomas, a Department of State official who led air monitoring at the embassy in Beijing from 2010 to 2014.
Tensions came to a head in late 2011, when Beijing’s smog got so bad that its airport canceled hundreds of flights. Based on monitoring of larger particles, municipal authorities insisted that the air was only “slightly polluted”—provoking ridicule from bloggers citing U.S. data. “It was the straw that broke the camel’s back,” says Angel Hsu of Yale University, an expert on pollution in China. Days later, China proposed new air quality standards that included PM2.5 for the first time. It now runs the biggest PM2.5 monitoring system in the world.
Community forums held last week for the MIT Stephen A. Schwarzman College of Computing working groups addressed how new ideas for its curriculum, research, infrastructure, and operations can best serve the community and society.
In February, MIT charged five working groups with generating ideas for the structure and operation of the new college. The groups are: Academic Degrees, Social Implications and Responsibilities of Computing, Organizational Structure, Faculty Appointments, and Computing Infrastructure. The groups each have two co-chairs and anywhere from about a dozen to more than 20 other members, representing many departments, labs, and centers across the Institute. The groups meet regularly, and will soon submit a report to MIT administration that outlines many potential ideas for their respective assignments.
Overpumping in California’s Central Valley has depleted groundwater storage capacity and caused the land to sink. A new model based on remote sensing data could help zero in on where water managers can replenish aquifers by flooding fields.
Once the very embodiment of Silicon Valley venture capital, the storied firm has suffered a two-decade losing streak. It missed the era’s hottest companies, took a disastrous detour into renewable energy, and failed to groom its next-generation leadership. Can it ever regain the old Kleiner magic?
Our “Digital Transparency in the Public Realm” project brought people around the world together to co-create a visual language to demystify the tech in cities.
To machine learning pioneer Terry Sejnowski, the mathematical technique called stochastic gradient descent is the “secret sauce” of deep learning, and most people don’t actually grasp its true significance.
In recent years, researchers and journalists have highlighted artificial intelligence sometimes stumbling when it comes to minorities and women. Facial recognition technology, for example, is more likely to become confused when scanning dark-skinned women than light-skinned men.
Last week, AI Now, a research group at New York University, released a study about A.I.’s diversity crisis. The report said that a lack of diversity among the people who create artificial intelligence and in the data they use to train it has created huge shortcomings in the technology.
For example, 80% of university professors who specialize in A.I. are men, the report said. Meanwhile, at leading A.I. companies like Facebook, women comprise only 15% of the A.I. research staff while at Google, women account for only 10%.
Seattle, WA May 15, starting at 7:30 p.m. “Hidden beneath the surface of the web, there is an unseen workforce of proofreaders, designers, and content watchdogs who make the internet seem smart. Co-authors Mary Gray and Siddharth Suri take the stage to shine a light on these laborers in Ghost Work: How to Stop Silicon Valley from Building a New Global Underclass.” [$]
Columbia University, Graduate School of Journalism
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New York, NY May 9, starting at 10 a.m. “A symposium to kick off the Craig Newmark Centers at Columbia Journalism School and the Poynter Institute” [free,registration required]
Cambridge, MA May 3-5, at MIT Media Lab. “Join MIT Hacking Medicine for one of the largest healthcare hackathons in the world! This is the weekend to brainstorm and build innovative solutions with hundreds of like-minded engineers, clinicians, designers, developers and business people. Within our four themes, there is sure to be a healthcare challenge for everyone!” [application required]
“Registrations to participate in the prediction markets are administered via the sign-up form at the bottom of the page. A PhD degree (or currently being a PhD candidate) or a comparable level of expertise in neuroscience or related fields is required for participating to ensure expertise in the field. Registration to participate in the markets will close on April 29, at 4pm UTC.”
“Oceanhackweek is a 5-day learning hackathon aimed at exploring, creating and promoting effective computation and analysis workflows for large and complex oceanographic data. By democratizing data access and increasing exposure to technological assets, our goals are to accelerate research, promote collaboration and cultivate data science literacy among the ocean sciences community.” Deadline to apply is May 13.
“The CCA Pre-Doctoral Program will enable graduate student researchers from institutions around the world to participate in the CCA mission by collaborating with CCA scientists for a period of 5 months on site.” Deadline to apply is May 31.
Much of the innovation in information retrieval and recommender systems focuses on better targeting in order to improve relevance. Those of us who develop such systems often take for granted that the axiomatic goal of relevance is to deliver the right content to the right people at the right time. We debate the means to achieve that goal, but we rarely debate the goal itself.
But we do need to question the unstated assumption that relevance should be our overarching goal. Optimizing for relevance can lead us to dark places.