Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations.
"Please think forward to the year 2030. Analysts expect that people will become even more dependent on networked artificial intelligence (AI) in complex digital systems. Some say we will continue on the historic arc of augmenting our lives with mostly positive results as we widely implement these networked tools. Some say our increasing dependence on these AI and related systems is likely to lead to widespread difficulties. Our question: By 2030, do you think it is most likely that advancing AI and related technology systems will enhance human capacities and empower them? That is, most of the time, will most people be better off than they are today? Or is it most likely that advancing AI and related technology systems will lessen human autonomy and agency to such an extent that most people will not be better off than the way things are today? Please explain why you chose the answer you did and sketch out a vision of how the human-machine/AI collaboration will function in 2030.
The Department of Computing Science at the University of Alberta invites applications for tenure-track or tenured faculty positions at all levels. Candidates with a strong research record in the area of Artificial Intelligence (AI), in particular (but not limited to) Machine Learning, Natural Language Processing, Computer Games, Visualization, Security, Planning/Heuristic Search, and Algorithmic Game Theory, will be considered for this position. According to csrankings.org the department is ranked #1 in Canada and averaged #3 in the world in terms of number of publications at top AI venues in the last 10 years, and it is also home to Amii (www.amii.ca), the Alberta Machine Intelligence Institute, formerly known as AICML. It is noteworthy that the 2017 Government of Canada Budget included an investment of $125 million into a Pan-Canadian Artificial Intelligence Strategy which features a major investment in research at the University of Alberta. According to the most recent Times Higher Education World University ranking, the department is ranked 3rd in Canada and 67th in the world.
Are you ready for artificial intelligence in schools? You may already know that researchers believe AI is likely to predict the onset of diseases in future and that you're already using AI every day when you search online, use voice commands on your phone or use Google Translate. Maybe you heard the Canadian government has invested millions of dollars in AI research during the past few years and is emerging as one of the global leaders in AI research. But did you know that some companies are developing AI for use in schools, for example in forms such as AI tutoring systems? Such systems can engage students in dialogue and provide feedback in subjects where they need extra help.