Algorithms, Automation, and News

This special issue examines the growing importance of algorithms and automation in the gathering, composition, and distribution of news. It connects a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these articles share some of the noble ambitions of the pioneering publications on ‘reporting algorithms’, such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems, to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematize computational journalism by, for example, pointing out some of the challenges inherent in applying AI to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner

Sensitivity studies for r-process nucleosynthesis in three astrophysical scenarios

In rapid neutron capture, or r-process, nucleosynthesis, heavy elements are built up via a sequence of neutron captures and beta decays that involves thousands of nuclei far from stability. Though we understand the basics of how the r-process proceeds, its astrophysical site is still not conclusively known. The nuclear network simulations we use to test potential astrophysical scenarios require nuclear physics data (masses, beta decay lifetimes, neutron capture rates, fission probabilities) for all of the nuclei on the neutron-rich side of the nuclear chart, from the valley of stability to the neutron drip line. Here we discuss recent sensitivity studies that aim to determine which individual pieces of nuclear data are the most crucial for r-process calculations. We consider three types of astrophysical scenarios: a traditional hot r-process, a cold r-process in which the temperature and density drop rapidly, and a neutron star merger trajectory.Comment: 8 pages, 4 figures, submitted to the Proceedings of the International Nuclear Physics Conference (INPC) 201

The Availability Heuristic, Intuitive Cost-Benefit Analysis, and Climate Change

Because risks are on all sides of social situations, it is not possible to be “precautionary” in general. The availability heuristic ensures that some risks stand out as particularly salient, whatever their actual magnitude. Taken together with intuitive cost-benefit balancing, the availability heuristic helps to explain differences across groups, cultures, and even nations in the assessment of precautions to reduce the risks associated with climate change. There are complex links among availability, social processes for the spreading of information, and predispositions. If the United States is to take a stronger stand against climate change, it is likely to be a result of available incidents that seem to show that climate change produces serious and tangible harm