ARMONK, N.Y., Oct. 30,
2019 /PRNewswire/ -- IBM (NYSE: IBM) believes
100% of jobs will eventually change due to artificial intelligence,
and new empirical research released today from the MIT-IBM Watson
AI Lab reveals how. The research, The Future of
Work: How New Technologies Are Transforming Tasks, used
advanced machine learning techniques to analyze 170 million online
job postings in the United States
between 2010 and 2017. It shows, in the early stages of AI
adoption, how tasks of individual jobs are transforming
and the impact on employment and wages.
"As new technologies continue to scale within businesses and
across industries, it is our responsibility as innovators to
understand not only the business process implications, but also the
societal impact," said Martin
Fleming, vice president and chief economist of IBM. "To that
end, this empirical research from the MIT-IBM Watson AI Lab sheds
new light on how tasks are reorganizing between people and machines
as a result of AI and new technologies."
RESEARCH FINDINGS:
While most jobs will change as new
technologies, such as AI, scale, the research shows few jobs
will actually disappear. What is fundamentally changing is the
way we work. The key findings include:
Tasks are Shifting Between People and Machines – But the
Change is Slow
With strong employment growth and workforce
transformation underway, the overall demand for tasks that make up
occupations are down between 2010 and 2017. Across more than 18,500
tasks, for each occupation, on average, workers were asked to
perform 3.7 fewer tasks overall in 2017 than seven years
earlier.
Tasks that are more likely to be done by AI or
machine learning are disappearing from employers' job requirements
more often than those more likely to be done by a worker. The
decreased task requirements may likely be due to employers seeking
greater focus from workers and the early adoption of AI and machine
learning, indicating a fundamental shift in the way work gets
done.
When looking at the impact of AI and machine learning on tasks
across the seven years, the data show:
- Among tasks that are more suitable for machine learning
(e.g., scheduling, credential validation), workers, by occupation,
were asked to perform 4.3 fewer tasks.
- Among tasks that are less suitable for machine learning
(e.g., design, industry knowledge), workers, by occupation, were
asked to perform 2.9 fewer tasks.
- This reflects a 46% larger decline in demand for tasks that are
more likely to be suitable for machine learning, compared to
those that are less likely.
Tasks Increasing in Value Tend to Require "Soft
Skills"
As technology reduces the cost of some tasks, the
value of the remaining tasks that make up an occupation increases.
Tasks that are grounded in intellectual skill and insight as well
as require, to some degree, physical flexibility, common sense,
judgment, intuition, creativity, and spoken language have tended to
increase in value.
Here are a few examples across wage ranges and occupations:
- In high-wage business and finance occupations, industry
knowledge tasks are on the rise. The annual wages for industry
knowledge tasks have increased in value between 2010 - 2017 by
$6,387 on average, while the annual
wages for manufacturing and production tasks have decreased in
value by $5,218 per year, on
average.
- In low-wage personal care and services occupations
(hairstylists, recreational workers, fitness trainers, etc.),
annual wages for design tasks – like presentation design or digital
design – have increased between 2010 – 2017 by $12,000, on average among these workers.
- In fact, design tasks – graphic and visual design, industrial
design, user interface, user experience, and presentation design –
have increased in value consistently across occupations and wage
groups. In mid-wage sales occupations, the value of design tasks
increased annually by $8,522. And, in
high-wage computer and mathematics occupations, the value of design
tasks increased annually by $6,011.
These findings align with the recent IBM Institute for Business
Value (IBV) study, The Enterprise Guide to Closing the Skills
Gap, which reported the two top skills sought in 2018 were
behavioral skills – time management and willingness to be flexible,
agile, and adaptable to change.
High- and Low-Wage Jobs are Gaining Tasks and Earning
More
Among the three tiers – low-wage jobs, mid-wage jobs
and high-wage jobs – workers in the middle tier are being squeezed.
The data show:
- Tasks have shifted out of mid-wage jobs into low- and high-wage
jobs at a rate of 4-to-1.
- As a result, wages are rising faster in the low- and high-wage
tiers, than in the mid-wage tier.
- Low-wage workers gained an average of $600 in annual compensation more than mid-wage
workers. High-wage workers gained an average of $1,200 in annual compensation more than mid-wage
workers over the same period.
New technologies like AI have just begun to transform work and
while the rate and pace of change is slow now, it will likely
accelerate as more AI solutions are adopted throughout the economy.
Workers have time to adapt by learning or honing skills that
require innovation, creative thinking, or deep insight and
experience. Meanwhile, employers across all industries should begin
to focus on reskilling their workforces, redesigning job roles and
supporting career advancement.
IBM has partnered with clients to successfully complete more
than 1,000 HR transformation projects globally. By applying AI
capabilities to the employee lifecycle, IBM has helped clients
foster talent, empower their people and transform their business
for the era of AI. These services help enable companies to close
the skills gap brought on by these new technologies and help their
employees make the shift to partnering with machines.
For students, workers and life-long learners, IBM is working to
address the high-tech skills gap through a range of skills
development and education initiatives including:
- P-TECH: A public-private partnership among high schools
involving more than 75 community college partners and 600 industry
partners that is designed to address skills gaps. Over twenty-three
countries -- including France,
Australia, and Taiwan – have announced the intent to open
P-TECHs or have already opened P-TECHs. The model is designed to
help strengthen regional economies and disadvantaged populations by
fostering a more inclusive workforce and preparing students for
"new collar" jobs –such as cloud computing or cybersecurity
analysts--which are skilled, technology positions that don't
necessarily require a traditional, four-year college degree;
- Apprenticeships: In partnership with the U.S. Department
of Labor, the 12-24 month program pairs apprentices with an IBM
mentor to work on IBM projects, along with traditional classroom
learning, in technology's fastest-growing fields;
- Returnships: A six-month program created to make
rejoining the technology industry easier for people who have been
out of the workforce for at least 24 months;
- SkillsBuild: A new digital learning and education
platform that provides job seekers – including those seeking
employment, returning to work after leave, veterans, refugees, or
those changing professions – with accredited digital learning
content, personalized coaching, and practical learning experience
to help them re-enter the workforce successfully; and
- STEM Career Training for Women: Programs around the
globe to help girls earn a strong STEM foundation, and initiatives
to help women enter the technology sector.
Methodology:
The MIT-IBM Watson AI Lab
study, The Future of Work: How New Technologies Are Transforming
Tasks, applies the suitability for machine learning (SML)
rubric (Brynjolfsson, Mitchell, and Rock, 2018, What Can
Machines Learn and What Does It Mean for Occupations and the
Economy?) to 170 million U.S. online job postings provided by
Burning Glass Technologies. The primary analysis was conducted
using IBM machine learning techniques on data from 2010-2017. For
complete methodology, read the IBM Research blog or technical
paper with executive summary.
CONTACTS:
Anna Sekaran
IBM Research
203-434-3975
amsekara@us.ibm.com
MaryJo Fitzgerald
IBM Research
920-420-6832
maryjo.fitzgerald@ibm.com
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SOURCE IBM