Five interesting findings from the AI Index 2019 report
For the past couple of years, along with several colleagues, I have been on the steering committee for the AI Index, an annual report conceived within the One Hundred Year Study on AI (AI100) and now hosted at Stanford’s Human-Centered AI Institute (HAI). We aim to ground the conversation about artificial intelligence and its progress in data.
Today, we released our AI Index 2019 Report. This year’s report has volumes of relevant data on the technical, economic and societal progress of AI. I found these 5 findings particularly interesting:
1. AI research continues its rapid growth. The share of peer-reviewed papers on AI has grown 3-fold in the past ten years, now accounting for 3 percent of peer-reviewed journal publications and 9 percent of published conference papers. China and Europe now publish more AI papers than the US.
2. Training AI systems is becoming faster – and cheaper. The time to train a large image classification system on cloud infrastructure has fallen from 3 hours in October 2017 to about 88 seconds in July 2019, and costs have fallen similarly.
3. AI-related jobs are increasing. In the US, the share of jobs in AI-related topics increased from 0.26 percent of total jobs posted in 2010 to 1.32 percent in October 2019.
4. More companies are adopting AI within their businesses. 58 percent of large firms report adopting AI in at least function or business unit in 2019, up from 47 percent in 2018. This data was collected through McKinsey’s Global AI Survey.
5. AI has the potential to contribute to social good. Drawing on MGI’s AI for Social Good research, AI use cases identified to-date could support about half of the 169 targets across each of the 17 UN Sustainable Development Goals.
You can find many more data points on the growth of and progress in AI in 2019 in the full report, available here.
At the McKinsey Global Institute, we have published a series on several different aspects of AI, in our Notes from the AI frontier series, most recently AI and bias.
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4yhttps://hai.stanford.edu/ai-index/2019 James Manyika this link is not working. James Manyika
Senior Data Center Manager at Waubonsee Community College
4yThe growth in AI is happening in China not in the US. We have buried our heads in the sand and by the time we dig ourselves out it will be too late. On another note, ANY job that is repetitive, follows a set recipe will be automated using AI so expect the employment rate to go sky high for a decade before we figure out how to employ al those people who are going to get laid off. The next recession, just around the corner is going to be worse than the ;last one.
Marriott International Reservations
4ySorry but this is going to comeback and bit us. I love new technology but your pushing people out of jobs, then their homes. Why go to school/college for this if a machine with no logic/reason or even a what if reaction is taking over Stop depending on machines for a better life, stop relying on a machine to better our lives stop (companies) so cheat and pay people what they are worth not what you think they are worth and taking the money to build machines. That probably would of help at least 30 people survive & retire. Whats next machines to fix other machines. What out CEO’s your job is next
Knowledge Economy, Innovation Economy, IP Attorney
4yJames, Nice post (I just forwarded it to both daughters), especially the link to "AI for Social Good" (I'm getting into it now). It immediately made me think about Blackbaud.Com ("the world's leading cloud software company powering social good") in Charleston, SC. McKinsey should look into partnering with Blackbaud to strengthen their AI efforts for the "Social Good" market! Reb Thomas, InnovationEconomy.Com (coming soon)