Artificial Intelligence (AI) Stats News: 120 Million Workers Need To Be Retrained Because Of AI

Recent surveys, studies, forecasts and other quantitative assessments of the impact and progress of AI highlighted the need to retrain many workers, improving AI’s score from F to A on 8th-grade science exam, and the $97.9 billion the AI market will reach in 2023.

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Expected business impact

In the next three years, as many as 120 million workers in the world’s 12 largest economies may need to be retrained or reskilled as a result of AI and intelligent automation; only 41% of CEOs surveyed say that they have the people, skills and resources required to execute their business strategies; the time it takes to close a skills gap through training has increased from 3 days on average in 2014 to 36 days in 2018 [IBM]

Top drivers for investing in robotics and automation: Reduced cost (80%), improved quality (55%), increased productivity (54%), improved capabilities of robots (54%). Top challenges: cost of robots (16%), lack of experience with automation (15%), lack of homogenous programming platforms/interfaces (13%), lack of integrators working across OEMs/geographies/industries (12%) [McKinsey online survey of 85 OEMs and users worldwide, 2018]

67% of organizations will look to AI to intelligently automate IT processes to some extent within their IT environments [ESG]

Quantified business impact

L’Oréal’s recruiters believe they saved 200 hours of time to hire 80 interns out of a pool of 12,000 candidates, using a chatbot that saves significant time in the early stages of the recruiting process by handling questions from candidates, and Seedlink, AI software that assesses their responses to open-ended interview questions [Forbes]

Infusion Software, using a chatbot from LeadsDrift.com, has reduced the number of front-line salespeople who field customer inquiries from 25 to 9 since April and expects to save $1 million a year [Wall Street Journal]

Business adoption

51% of sales organizations have already deployed or plan to deploy algorithmic-guided selling in the next five years. Algorithmic-guided selling leverages emerging artificial intelligence technology and existing sales data to guide sellers through deals, automating manual sales actions while reducing the need for individual seller judgment in the sales process [Gartner survey of 250 sales leaders worldwide]

AI research successes

The Aristo System from the Allen Institute for Artificial Intelligence, designed to answer non-diagram, multiple choice questions, correctly answered more than 90% of the questions on an eighth-grade science exam and exceeded 83% on a 12th-grade science exam; in 2016, the best AI system scored 59.3% on an eight-grade science exam challenge [arXiv]

In a Mayo Clinic study of 12,000 patients, researchers applied a machine learning algorithm from Medial EarlySign to data from a percutaneous coronary intervention (PCI) registry; compared to standard regression methods, the algorithm was proven to be a better predictor of mortality 180 days post-PCI and of 30-day rehospitalization for congestive heart failure; additionally, the algorithm successfully identified patient subgroups at an elevated risk of other post-PCI complications and readmission [Baker’s Hospital Review]

Researchers with the University of Bristol have created a AI system to automatically spot and analyze great apes in the wild; tested with 500 videos of great apes, it achieved 80% accuracy and over 90% with the addition of temporal and spatial modules [Import AI]

Consumer attitudes

59% of US adults say it is acceptable for law enforcement to use facial recognition to assess security threats in public spaces; only 15% say it is acceptable for advertisers to use facial recognition to see how people respond to public ad displays; 13% of US adults have not heard about facial recognition and 25% say they heard a lot [Pew Research Center]

42% of UK consumers are unsure or don’t feel AI will have a positive impact on life in the next five years, with a further 15% admitting they simply don’t understand the technology well enough to understand its impact; 45% are unsure or don’t feel robotics will have a positive impact within the next five years [Fujitsu survey of 2,000 UK consumers]

38% of respondents have either just heard of artificial intelligence or have no idea what it is; 52% say they feel comfortable interacting with AI; nearly 30% don’t think they would know when they’re interacting with a chatbot; 62% would trust a chatbot to schedule maintenance for their apartment or home [Entrata online survey of 1,051 adult U.S. consumers]

AI talent moving from academia to industry

180 AI faculty from North American universities accepted an industry job from 2004-2018.  In addition, there are 41 professors who founded AI startups either while employed at universities or after leaving academia. In 2018, almost 40 professors left academic positions for an industry job [University of Rochester]

“I was at MIT for another fifteen years after I graduated…twenty years after I went and asked to do my bachelor’s thesis [with Victor Zue on speech recognition], Siri comes out… twenty years ago, we [wanted to] have a device where you can talk to it and it gives you answers and twenty years later there it was. So, that, for me, that was a cue that maybe it’s time to go where the action is, which was in companies that were building these things. Once you have a large company like Microsoft or Google throwing their resources behind these hard problems, then you can’t compete when you’re in academia for that space. You know, you have to move on to something harder and more far out… So, I joined Microsoft to work on Cortana…”—T.J. Hazen

Forecasts

The worldwide market for AI systems will reach $97.9 billion in 2023, up from $37.5 billion in 2019. Spending on AI systems will be led by the retail and banking industries, each of which will invest more than $5 billion in 2019. Nearly half of the retail spending will go toward automated customer service agents and expert shopping advisors and product recommendation systems. The banking industry will focus its investments on automated threat intelligence and prevention systems and fraud analysis and investigation. The fastest spending growth will come from the media industry and federal/central governments. The three largest use cases – automated customer service agents, automated threat intelligence and prevention systems, and sales process recommendation and automation – will deliver 25% of all spending in 2019. The use cases that will see the fastest spending growth from 2018 to 2023 are automated human resources and pharmaceutical research and development [IDC]

The enterprise and automotive Internet of Things (IoT) market will grow to 5.8 billion endpoints in 2020, a 21% increase from 2019. By the end of 2019, 4.8 billion endpoints are expected to be in use, up 21.5% from 2018 [Gartner]

The AI in healthcare market worldwide is estimated to reach $19.25 billion by 2026, up from $0.95 billion in 2017 [Wiseguy Reports]

The AI for telecommunications applications market worldwide is estimated to reach more than $11.2 billion in 2025, up from $419 million in 2018 [Tractica]

AI quote of the week: “We face a choice. Either we stick with today’s approach to A.I. and greatly restrict what the machines are allowed to do (lest we end up with autonomous-vehicle crashes and machines that perpetuate bias rather than reduce it). Or we shift our approach to A.I. in the hope of developing machines that have a rich enough conceptual understanding of the world that we need not fear their operation. Anything else would be too risky”—Gary Marcus and Ernest Davis

Data is eating the world quote of the week: “Departments of Motor Vehicles in states around the country are taking drivers’ personal information and selling it to thousands of businesses, including private investigators who spy on people for a profit… DMVs sell the data for an array of approved purposes, such as to insurance or tow companies, but some of them have sold to more nefarious businesses as well. Multiple states have made tens of millions of dollars a year selling data”—Motherboard

[“source=forbes”]

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