stanford's AI index may be useful as a compendium of data

https://hai.stanford.edu/research/ai-index-2021

some takeaways. where is india in AI? we're losing the plot here. there were some noises from niti ayog, and then a rival national AI plan from some other entity, i forget which. net result: stasis. sigh. 

• Private investment in AI substantially increased – despite the COVID crisis negatively impacting the economy in other ways. 
• China surpassed the U.S. in significant scholarly work. Chinese-affiliated scholars were cited in more peer-reviewed journals than any other country's scholars, indicating China's AI research has increased in quality and quantity. However, the United States has consistently (and significantly) more cited AI conference papers than China over the last decade.  
• Synthetic media, colloquially known as deepfakes, are on the rise, with breakthroughs in the generation of synthetic text, imagery, and video demonstrating the progress of AI but also highlighting the potential for unethical or dangerous use.
• Ethical challenges of AI applications have become a bigger focus for the AI community, with a significant increase in papers mentioning ethics and related keywords between 2015 and 2020.
• Diversity in AI is low – in 2019, 45% of new AI PhD graduates who stayed in the United States were white, while 2.5% were African American and 3.2% were Hispanic. AI researchers are forming more affinity groups to try to improve diversity in the field, and these groups are seeing significant growth in their membership and impact: Black in AI members had twice the number of papers accepted at NeurIPS in 2019 compared to 2017, and participation at workshops held by the Women in Machine Learning Group has grown from under 200 participants in 2014 to more than 900 in 2020. 
• Since Canada published a national AI strategy in 2017, other nations have followed, with more than 30 countries committing to national AI strategies by 2020.
• More AI PhDs took jobs in private industry rather than academia, and professors continued to leave higher education for roles in corporations. 
• Corporations have come to dominate the tools that AI researchers use, with corporate-backed software libraries (Google's TensorFlow and Keras, and Facebook's PyTorch) becoming the most popular frameworks on GitHub.
• Government interest in AI continues to be significant, with the U.S. government spending billions of dollars across civil and non-civil uses of AI. AI has been mentioned three times more in this Congress than in the previous one.