AI BOOGEYMAN — The Target Audience
Often described as the next Industrial Revolution, AI-generated a huge mix of excitement AND fear — among many. Over the last number of years, hundreds of scientific studies have been conducted and we have a clear understanding of who fears job losses the most — and why.
Such stats point to who is the best audience for this book based on demographics such as age, sex, education, financial status, and more …
The aim of this book is not to educate a casual reader about AI technology. Instead, the objective is to offer advice and reassurance to those who openly voice their concerns about future jobs’ anxiety.
The influential 2013 study by Oxford University warned that AI and robots will destroy 47% of jobs — especially in the US, where the risk of automation is extremely high.
And yet, according to the OECD:
· “Across the 32 countries, close to one in two jobs are likely to be significantly affected by AI automation, based on the tasks they involve. But the degree of risk varies
· About 14% of jobs in OECD countries are highly automatable (i.e., probability of automation of over 70%)
· Although smaller than the estimates based on Oxford University, this is equivalent to over 66 million workers in the 32 countries
· In addition, another 32% of jobs have a risk of between 50 and 70% pointing to the possibility of significant change in the way these jobs are carried out as a result of automation
· The risk of AI automation is not distributed equally among workers. Automation is found to mainly affect jobs in the manufacturing industry and agriculture, although a number of service sectors, such as postal and courier services, land transport and food services are also found to be highly automatable
· The occupations with the highest estimated automatability typically only require basic to a low level of education
· Despite recurrent arguments that automation may start to adversely affect selected highly skilled occupations if anything — AI puts more low-skilled jobs at risk than previous waves of technological progress
· Whereby technology replaced primarily middle-skilled jobs creating labor market polarization — i.e. a rise in the employment share of low-skilled and high-skilled jobs and a decline in the share of middle-skilled ones
· A striking novel finding is that the risk of automation is the highest among teenage jobs. The relationship between automation and age is U-shaped, but the peak in automatability among youth jobs is far more pronounced than the peak among senior workers
· In this sense, automation is much more likely to result in youth unemployment, than in early retirements. To some extent, this higher risk of automation may be countered by smoother transitions between jobs for young people compared to older individuals
· In most countries, young people are better skilled than their older counterparts so they may find it easier to adapt to new jobs, including those created as a result of the introduction of AI technologies”
Not to be left out, PwC research found 38% of jobs in the United States were at high risk of automation by the early 2030s; and a McKinsey report found around 50% of work tasks around the world are already automatable.
A recent survey by Randstad Canada, reveals:
· “61 percent of Canadian women see themselves as risk-takers and innovators in the workplace
· 30 percent of employed women across all sectors expect they will lose their jobs within the decade due to advances in technology, such as automation and Artificial Intelligence (AI)
· Women employed in the manufacturing sector feel the greatest vulnerability: 62 percent believe their industry bears the greatest risk of job losses due to advances in technology in the next decade
· This concern is echoed by 29 percent of women working in IT and 24 percent of women working in retail
· Those employed in education, healthcare, and engineering and construction view their industries as stable by comparison
· Age is seen as a distinct disadvantage: 38 percent believe Baby Boomers have the greatest risk of losing their jobs due to technology, compared to 21 percent for Gen Xers and just 13 percent for Millennials
· Gender, by comparison, is not seen as an impediment. The majority (68 percent) believe men and women are at equal risk of losing their jobs due to automation
· Another survey showed half of the Canadian employers (49%) felt they would need fewer employees in just the next three years due to automation. Willis-Towers-Watson risk management firm produced the “Global Future of Work Survey” which involved over 900 companies worldwide including 49 in Canada
CB Insights provides detailed estimates of risks from automation, in millions, below:
As does the Economist for various professions: from recreational therapists and dentists to accountants and telemarketers:
But surveys don’t sell books — targeted marketing does!
And the widespread concern across so many professions — offers unique opportunity to reach many readers through some of the largest aggregators and influencers, such as:
· Mature Workers — Trade Unions:
o The American Federation of Labor-Congress of Industrial Organizations is the leading confederation of US trade unions such as Air Line Pilots Association, Amalgamated Transit Union, American Federation of Government Employees, American Federation of Musicians, American Federation of School Administrators, American Federation of State, County and Municipal Employees, and so much more
o The number of wage and salary workers belonging to unions, at 14.8 million in 2017, edged up by 262,000 from 2016. In 1983, the first year for which comparable union data are available, the union membership rate was 20.1 percent and there were 17.7 million union workers
· Students — Business Schools:
o As of July 2011, 633 member institutions hold AACSB Accreditation. Overall, 41 countries and territories are represented by AACSB-accredited schools. Of the accredited schools: 41 institutions have undergraduate programs only (6% of accredited members)
o The average number of applications per Business School and program: The highest average number of applications were in China and Hong Kong, both at a School (1,177) and program (407) level, closely followed by North America and the Caribbean at a School level (1,034 applications per School)
o India had the second-highest level of applications per program (308) and third-highest by School (493). Europe, Africa, Asia and the Middle East, Latin America and the UK had a similar volume of applications (ranging between 346 and 464 per school)
o Meanwhile, Oceania had the smallest average number of applications per School and program (170 per School and 72 per programme)
Most books covering AI are dealing with technology and science behind cognition. Such scientific and academic titles aim at computer science students and IT practitioners.
A whole slew of cognitive scientists, theoretical and computational psychologists, neuroscientists, mathematicians, and biomedical engineers — made remarkable discoveries and wrote about it. Such books describe how Advanced Deep Learning emerged from neural networks such as Back/Counter Propagation, Adaptive Resonance Theory, Self-Organizing Maps, Boltzmann Machines, etc., etc.
Another group of authors is addressing public policies issues and the role of AI to advance technological innovation, productivity, and competitiveness.
Many innovative technologies, such as AI, are often causing a prolonged marketing hype — and many authors are making outrageous claims to gain recognition. And since AI will affect so many economies — doomsday scenarios are easily applicable to so many occupations, industries, and workers.
My book is not aiming to cover such aspects. I’m not planning to dive-in and describe 30 years of efforts leading to creation and perfection of supervised/unsupervised, non-linear learning theories — mimicking the human brain.
Instead, I will demonstrate how my own practical experiences of using AI — point to the future powered by artificial intelligence and robotics, without higher unemployment levels in retail, transportation, finance, healthcare, energy, insurance, and more! Quite to the contrary!
Oleg Feldgajer is President & CEO of Canada Green ESCO Inc. Oleg is positioning the company to become a leader in financing AI-enhanced green energy projects and ventures. CGE’s mission is to guide DISRUPTIVE businesses in ENERGY & TRANSPORTATION toward profitable business models. Oleg is passionate about such mission and firmly believes that without AI-based innovation, we will all prematurely choke on polluted air and dirty water. CGE delivers 100% financing (levered and unlevered) to its clients — and utilizes large equity pools, and non-recourse debt. Oleg offers creative, fresh ideas to open-minded businesses — that embrace both: logic AND opportunistic intuition. CGE stands against mediocrity & its modus operandi is quite simple: If CGE is not invited to join your BOD or Advisory Board — we failed!