Artificial intelligence is getting cheaper, better at the tasks we assign it, and more widespread—but concerns over bias, ethics, and regulatory oversight still remain. At a time when AI is becoming accessible to everyone, the Stanford Institute for Human-Centered Artificial Intelligence put together a sweeping 2022 report analyzing the ins and outs of the growing field. Here are some of the highlights.
A growing number of publications
The number of publications alone on the topic tell a story: They doubled in the last decade, from 162,444 in 2010 to 334,497 in 2021. The most popular AI categories that researchers and others published on were pattern recognition, machine learning, and algorithms.
What’s more, the number of patent filings related to AI innovations in 2021 is 30 times greater than the filings in 2015. In 2021, the majority of filed patents were from China, but the majority of patents actually granted were from the US.
The number of users participating in open-source AI software libraries on GitHub also rose from 2015 to 2021. These libraries house collections of computer codes that are used for applications and products. One called TensorFlow remains the most popular, followed by OpenCV, Keras and PyTorch (which Meta AI uses).
Computers that analyze images and understand speech
Specifically, out of the various tasks that AI can perform, last year, the research community was focused on applying AI to computer vision, a subfield that teaches machines to understand images and videos in order to get good at classifying images, recognizing objects, mapping the position and movement of human body joints, and detecting faces (with and without masks).