10 organizations leading the way in ethical AI

AI is susceptible to misuse and has been found to reflect biases that exist in society. Fortunately, there are a number of organizations committed to addressing ethical questions in AI. We list our top 10.

Book review: The code: Silicon Valley and the remaking of America by Margaret O’Mara

In The Code: Silicon Valley and the Remaking of America, Margaret O’Mara provides a new account of the region’s evolution that brings the US government into the story. The book offers a compelling narrative that tracks the key players and events that have underpinned Silicon Valley’s tremendous, but messy, rise, writes Robyn Klingler-Vidra, while also underscoring the gender imbalance and casual misogyny that has been a longstanding characteristic of its culture.

Interning at SAGE Ocean: My experience

This summer we've had the pleasure of welcoming four Masters students from UK universities to work with the SAGE Ocean team. All four students have been quite incredible, and have managed to produce a variety of outputs and substantially contribute to our work. In this blog post, they share testimonials of their time in the team.

The five pitfalls of document labeling - and how to avoid them

Whether you call it ‘content analysis’, ‘textual data labeling’, ‘hand-coding’, or ‘tagging’, a lot more researchers and data science teams are starting up annotation projects these days. Many want human judgment labeled onto text to train AI (via supervised machine learning approaches). Others have tried automated text analysis and found it wanting. Now they’re looking for ways to label text that aren’t so hard to interpret and explain.

SMaPP-Global: An interview with Josh Tucker and Pablo Barbera

In April this year a special collection examining social media and politics was published in SAGE Open. Guest edited by Joshua A. Tucker and Pablo Barberá, the articles grew out of a series of conferences held by NYU’s Social Media and Political Participation lab (SMaPP) and the NYU Global Institute for Advanced Study (GIAS) known as SMaPP-Global. Upon publication Joshua Tucker said ‘the collection of articles also shows the value of exposing researchers from a variety of disciplines with similar substantive interests to each other's work at regular intervals’. Interdisciplinary collaborative research projects are a cornerstone of what makes computational social science such an interesting field. We were intrigued to know more so caught up with Josh and Pablo to hear more.

No more tradeoffs: The era of big data content analysis has come

For centuries, being a scientist has meant learning to live with limited data. People only share so much on a survey form. Experiments don’t account for all the conditions of real world situations. Field research and interviews can only be generalized so far. Network analyses don’t tell us everything we want to know about the ties among people. And text/content/document analysis methods allow us to dive deep into a small set of documents, or they give us a shallow understanding of a larger archive. Never both. So far, the truly great scientists have had to apply many of these approaches to help us better see the world through their kaleidoscope of imperfect lenses.

Instead of seeing criticisms of AI as a threat to innovation, can we see them as a strength?

At CogX, the Festival of AI and Emergent Technology, two icons appeared over and over across the King’s Cross location. The first was the logo for the festival itself, an icon of a brain with lobes made up of wires. The second was for the 2030 UN Sustainable Development Goals (SDGs), a partner of the festival. The SDG icon is a circle split into 17 differently colored segments, each representing one of the goals for 2030—aims like zero hunger and no poverty. The idea behind this partnership was to encourage participants of CogX—speakers, presenters, expo attendees—to think about how their products and innovations could be used to help achieve these SDGs.

2018 Concept Grant winners: An interview with MiniVan

Following the launch of the SAGE Ocean initiative in February 2018, the inaugural winners of the SAGE Concept Grant program were announced in March of the same year. As we build up to this year’s winner announcement we’ve caught up with the three winners from 2018 to see what they’ve been up to and how the seed funding has helped in the development of their tools.

In this post we chatted to MiniVan, a project of the Public Data Lab.

Social media data in research: a review of the current landscape

Social media has brought about rapid change in society, from our social interactions and complaint systems to our elections and media outlets. It is increasingly used by individuals and organizations in both the public and private sectors. Over 30% of the world’s population is on social media. We spend most of our waking hours attached to our devices, with every minute in the US, 2.1M snaps are created and 1M people are logging in to Facebook. With all this use, comes a great amount of data.

SAGE Campus announces two new courses

SAGE Campus are pleased to announce that we are launching two new courses to our suite of online data science courses for social scientists. The new short courses, Research Design in Social Data Science and Collecting Social Media Data, are aimed at those studying, teaching or working in social science disciplines who are looking to take their first steps toward working with big-data driven approaches to social science research.