AI safety research needs social scientists to ensure AI succeeds when humans are involved. That's the crux of the argument advanced in a new paper published by researchers at OpenAI ("AI Safety Needs Social Scientists"), a San Francisco-based nonprofit backed by tech luminaries Reid Hoffman and Peter Thiel. "Most AI safety researchers are focused on machine learning, which we do not believe is sufficient background to carry out these experiments," the paper's authors wrote. "To fill the gap, we need social scientists with experience in human cognition, behavior, and ethics, and in the careful design of rigorous experiments." They believe that "close collaborations" between these scientists and machine learning researchers are essential to improving "AI alignment" -- the task of ensuring AI systems reliably perform as intended.

Annual salaries for data scientists and machine learning engineers vary significantly across the world. Based on a 2017 Kaggle survey of data professionals, countries with the highest paid data scientists and machine learning engineers (in USD) were: US ($120K), Australia ($111K), Israel ($88K), Canada ($81K) and Germany ($80K). Countries with the lowest annual salaries were: Brazil ($35K), Poland ($29K), Ukraine ($25K), India ($14K) and Russia ($13K). In my last post, I compared at annual salaries of different data professionals in the US. Data scientists and machine learning engineers from the US reported some of the highest salaries among different data professionals.