The Washington Post, Monkey Cage blog, Jeffrey Adam Sachs
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Universities are supposed to be places where you confront unfamiliar and challenging ideas. According to some critics, however, students today are turning their backs on that concept of welcoming free speech. Instead, the argument goes, young people want to transform campuses into “safe spaces” where offensive speech is banned and political correctness is enforced.
There’s just one problem: This narrative is wrong. Let’s examine three myths about free speech on campus.
Myth #1: Young people in general (and college students in particular) don’t support free speech
When librarian Jeffrey Beall shut down his controversial blog listing potentially ‘predatory’ scholarly publishers and journals last year, archived copies swiftly appeared elsewhere online. More than a year later, at least one of these copycat blacklists is still growing — maintained by an anonymous website manager who says that they spend hours each weekend working on the list.
Growing interest in the site suggests that there is still an academic appetite for a public blacklist of predatory journals, says the site manager, who identified themseves as a senior research assistant in the hard sciences at a European institution. The site’s keeper corresponded with Nature by e-mail and declined to provide any further details of their identity, citing fear of harassment.
Wi-Fly would pair equipment on planes with ground antennas to provide limited internet access at low cost to rural areas. The plan could cover the entire continental US with little downtime.
The largest supermarket and private employer in the U.S., Wal-mart Stores Inc. has set its footprint this year at the Global Women in Data Science Conference with a mission: Hire more women.
The former lead to data science at Walmart, Esteban Arcaute, was looking into how to expand the leverage of data and to recruit more women in data science – and an idea clicked. He connected with Margot Gerritsen, co-chair of the Global Women in Data Science Conference, on their sponsorship this year, explained Vijay Raghavendra, senior vice president of merchant technology at Walmart Labs.
Last week, when news broke (again) that Cambridge Analytica had allegedly misused 50 million Facebook users’ data, it immediately raised a difficult question: When a company possesses information about some 2 billion people, is its chief obligation to share that information, or protect it?
The answer’s not as obvious as you might think. To social and computer scientists, Facebook is arguably the most valuable data repository on earth. Insight into many of the most pressing issues of our time, from social media’s role in political processes to technology’s impact on individual wellbeing, could well reside on the social network’s servers—a fact that has led many scientists and policymakers to call for more permeable borders between public researchers and Facebook’s private data hoard.
But then Cambridge Analytica happened, and gave a lot of researchers a scare: Tapping into Facebook’s data is already more onerous than many of them would like. How would the company’s reaction to one of its most devastating public disasters to date affect their access going forward?
Amazon, Google, and Microsoft all want to dominate the business of providing artificial-intelligence services through cloud computing. The winner may have the OS of the future.
Salesforce.com’s definitive agreement to acquire MuleSoft for approximately $6.5 billion represents the company’s biggest acquisition yet and a calculated move to consolidate it’s position as the leading enterprise software company in the Cloud. The move also illustrates that the real power in the market is quickly shifting to those vendors that can facilitate the most cost-effective flow of data across applications in an increasingly connected and complex world.
It has become a cliché in the tech world to say that “it’s all about the data”. And, as the volume of data soars as a result of social networks, online networks and advent of the Internet of Things (IoT), the demand to capitalize on this data to better serve customers and gain a competitive advantage is also escalating.
Yet, the greatest challenge facing businesses and other institutions today continues to be leveraging data to perform daily functions and achieve corporate objectives. Various market research studies suggest that only 1-10% of corporate data is being effectively utilized to satisfy today’s business needs.
Carnegie Mellon University has the nation’s best graduate program in artificial intelligence, according to a ranking released this week by U.S. News & World Report.
The university’s AI program moved from No. 2 on the list to the top spot in U.S. News & World Report’s most recent rankings, released this week .
A team of Penn State faculty, librarians, and undergraduate students was recently selected for Phase One of the $100,000 Nittany AI Challenge for their prototype that uses artificial intelligence to automate parts of the University Libraries’ digital badge program. The group will demonstrate their prototype during Penn State Startup Week on March 27 in hopes of receiving an additional $5,000 to create a minimum viable product.
The challenge, a second-year initiative from the Penn State EdTech Network, asks teams to develop artificial intelligence-based solutions that improve the student experience at Penn State, solve real problems that the University is facing, and generate innovative startup ideas.
OmniSOC at Indiana University protects five universities, hundreds of thousands of devices and tens of thousands of students and faculty from cyber threats
We’ve just completed another round of the Google Faculty Research Awards, our annual open call for proposals on computer science and related topics such as machine learning, machine perception, natural language processing, and quantum computing. Our grants cover tuition for a graduate student and provide both faculty and students the opportunity to work directly with Google researchers and engineers.
“Someone asked today about how my coordination approach dovetails with the immense complexity of the project, and I put together the following answer, which I liked, and am now sharing with y’all.”
Most data scientists have to write code to analyze data or build products. While coding, data scientists act as software engineers. Adopting best practices from software engineering is key to ensuring the correctness, reproducibility, and maintainability of data science projects. This post describes some of our efforts in the area.