“2100 AI: Reflections on the mechanisation of scientific discovery” is a paper submitted to the RE-CODING BLACK MIRROR Workshop co-located with the International Semantic Web Conference (ISWC) 2017, 21-25 October 2017, Vienna, Austria.
Andrea Mannocci, Angelo Salatino, Francesco Osborne and Enrico Motta
The pace of nowadays research is hectic. Datasets and papers are produced and made available on the Web at a rate so unprecedented that digesting the information conveyed by such a “data deluge” stretches far beyond human analytical capabilities. Data science, artificial intelligence, machine learning and big data analytics are providing researchers with new methodologies capable of coping and getting insight in an automated fashion from the overload of information conveyed. Nonetheless major advances in AI solutions for knowledge discovery risk to exacerbate some negative phenomena, which are already observable on a global scale and disrupt irremediably the way of doing science as we know it.
Download paper (from ORO): link
Download paper (from CEUR-WS): link
— Angelo A. Salatino (@angelosalatino) October 22, 2017
— Mathieu d’Aquin (@mdaquin) October 22, 2017