November 4-5, 2020
FETFX, in collaboration with QUEST project – Quality and Effectiveness in Science and Technology communication – is organizing an online workshop on Emerging technologies in science journalism that will take place online on November 4-5.
Future technologies elicit great fascination among broad audiences. Artificial intelligence (AI) is but one example that captivates technologists and the lay person. But while journalists and science communicators have identified it as a current topic of interest to the general public, researchers are often unhappy with the way in which AI is presented in the media. Future and Emerging Technologies (FETs) can prove challenging for journalists in that their potential future impact may be massive, but their precise workings and the pathways to innovation are not very clear.
This event aims to shed light on this issue for science communication. We will take a close look at how emerging technologies have been presented to date, what new and promising ways to communicate them to broader audiences exist, and what the journalistic barriers are. We will be examining artificial intelligence as one example, but also include other FETs supported under the European Innovation Council Pathfinder and Accelerator actions and previous FET programme under Horizon 2020.
Experienced science communicators will investigate potential ways and test new tools for going beyond traditional storytelling – which can often slant towards the utopian or dystopian – with leading technology experts identified in high-risk high-gain research projects. The event will address both the simplifications often necessary for effective communication as well as the concerns of technologists that their research will be fundamentally mis-portrayed.
This two-day, online workshop will be divided into four sessions, which will include three expert panels as well as the demonstration of an exciting new research tool for journalists utilising AI currently under development by QUEST.
The workshop is organized by the FETFX project, in collaboration with the QUEST project.
For inquiries: email@example.com
This project has received funding from the European Union’s Horizon 2020
research and innovation programme under grant agreement No 824634