AI Stats News: 64% Of Workers Trust A Robot More Than Their Manager

Recent surveys, studies, forecasts and other quantitative assessments of the progress of AI highlighted workers' positive attitudes toward AI and robots, challenges in implementing enterprise AI, the perceived benefits of AI in financial services, and the impact of AI on the business of Big Tech. Google's Natural Language Processing (NLP) model BERT was added to its set of search algorithms and will help it better understand one in 10 searches in the U.S. in English ("With the latest advancements from our research team in the science of language understanding--made possible by machine learning--we're making a significant improvement to how we understand queries, representing the biggest leap forward in the past five years, and one of the biggest leaps forward in the history of Search") [Google Keyword] Across more than 18,500 tasks, for each occupation, on average, workers were asked to perform 3.7 fewer tasks in 2017 than seven years earlier. When looking at the impact of AI and machine learning on tasks across seven years, the data show that among tasks that are more suitable for machine learning (e.g., scheduling, credential validation), workers, by occupation, were asked to perform 4.3 fewer tasks. Conversely, among tasks that are less suitable for machine learning (e.g., design, industry knowledge), workers, by occupation, were asked to perform 2.9 fewer tasks. This reflects a 46% larger decline in demand for tasks that are more likely to be suitable for machine learning, compared to those that are less likely.