the future of work: technology and the workforce · 2019-04-22 · the future of work: technology...

Copyright © AGS Data Systems, 2019

The Future of Work:

Technology and the WorkforceHow to Consider the Impact of AI and Automation

in the Context of Curriculum Development

Derrick EdwardsPresident and Chief Technology Officer

AGS Data Systems / G*STARS

NCWE New Workforce Professionals Academy

April 11-12, 2019


Resources at https://GSTARS.com/nwpa2019.html

https://gstars.com/nwpa2019.html


What brings me here…

President and CTO, AGS Data Systems (19 years)

Academic and commercial background in Data Analysis, Commercial Software Development, Machine Learning

Involved in workforce data management system (WIA, WIOA) development since 1996, most recently with the develop of grant tracking systems for SWFI, APG, TAAACT, TechHire, Scaling Apprenticeships

Chair, University of Wisconsin System Advisory Board for BS in Applied Computing

Advisory Board, University of Wisconsin River Falls Masters in Computer Science program.

Originator and Co-Principal Investigator, University of Wisconsin System, Bridgeway Scholars Program (hybrid academic / industry model for STEM based education)

Instructor, Data Analysis and Ethics, NCWE New Workforce Professionals Academy


A Lot of Noise About Robotics and Automation

“13 Jobs That Robots, AI, And Automation Won’t Steal” – Forbes

“3 Reasons You Won’t Mind When AI Replaces Half of All Jobs” – Inc.

“AI Will Put 10 Million Jobs at High Risk” – CBInsights

“10 Jobs That AI Will Replace” – Hubspot

“Robots taking jobs in five year is BS, GE CEO says” – CNBC

“Robots Have been Taking American Jobs, Study Says” – US News

“Automation Taking Jobs” – C-Span


Take Away from Today

Working definitions for robotics, automation, AI, etc.

Technological change and the Fourth Industrial Revolution

Career pathways at risk, not at risk, and changing

Framework for describing subjectivity to Automation

Outline for evaluating curricula relative to these topics


Definitions

Automation

Any machine that performs a job with reduced levels of human interaction

Most impactful on physically repetitive or predictable work

Robotics ( = automation )Subset of Automation, where manipulation and mobility are involved

Most impactful on complex repetition and social interaction

Artificial Intelligence (AI) and Machine Learning (ML)

Allows computer to learn a task even if humans can’t explain the task

Impacts information processing and remote social interaction


Robotics in Construction, Video Links

Brick Laying Robot One

Brick Laying Robot Two

Timber Building Robot

Drywalling Robot

Atlas Robot 2016

Atlas Robot 2018

http://www.construction-robotics.com/video/

https://www.youtube.com/watch?v=ir54GLUDXac

https://www.youtube.com/watch?v=iOVzFokUHxo

https://www.youtube.com/watch?v=TJNDBdzTiWU

https://www.youtube.com/watch?v=rVlhMGQgDkY

https://www.youtube.com/watch?v=LikxFZZO2sk


Fourth Industrial Revolution

First: Steam and mechanization, 1800*

Second: Electrification and mass preproduction, 1900*

Third: Computerization and electronics, 1975*

Fourth: Automation and machine intelligence, 2010*

Fifth: Gene editing and quantum computing, ?

* all dates are “ish”


Fourth Industrial Revolution

Will come all at once, everywhere

Will, interestingly, have a positive, relative, impact on production costs for advanced economies

May drive adoption of the Universal Basic Income


Most Impactful Technologies

Block Chain / Smart Contracts Every Industry, greatest digital transformation since the internet itself

AI / Machine Learning Every job with an analytical component

Automation / Robotics Every job with a physical component

Quantum Computing Will drive entirely new industries and material sciences

Gene Editing Technology such as CRISPR allows of the editing of humans (see, He Juinkui and CCR5 gene)

IOT Coupled with Big Data Signals the end of privacy as we have always understood it


Careers Being Negatively Impacted

Predictable and Repetitive Actions

Garment Manufacturing

Brick Laying

Dental Lab Technician

Information Collection and Analysis

Tax Preparation

Insurance Underwriting

Financial Planning

Limited Scope Human Interaction

Customer Service

Home Health Care


Five Types of Impact

Job Growth – working with automation (e.g. CNC Operators)

Job Loss – due to automation (e.g. Automotive Welders)

Economic Growth without job growth – warehouse robotics

Income Divergence – warehouse humans

Demand Cascade – top down pressure on existing jobs


Traditional Forecasting Tools Have Issues

Key indicators with historical correlations

Census and surveys of employers

Industry-specific growth estimate research

“A rise in [ fill_in_the_blank ] growth equals an increase in job growth”

Models have a hard time seeing disruptive forces


Analyzing Susceptibility to Automation

“Highly Cited…”

The Future of Employment: How Susceptible Are Jobs To Computerization?

Carl Benedikt Frey and Michael A. Osborne

Oxford University, 2013

http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf

http://www.oxfordmartin.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf


The Future of Employment: How Susceptible Are Jobs To Computerization?

Rank Probability Occupation

702 0.99 Telemarketers

701 0.99 Title Examiners, Abstractors, and Searchers

700 0.99 Sewers, Hand

699 0.99 Mathematical Technicians

698 0.99 Insurance Underwriters

697 0.99 Watch Repairers

696 0.99 Cargo and Freight Agents

695 0.99 Tax Preparers

694 0.99 Photographic Process Workers and Processing Machine Operators

693 0.99 New Accounts Clerks

692 0.99 Library Technicians

691 0.99 Data Entry Keyers

690 0.98 Timing Device Assemblers and Adjusters

689 0.98 Insurance Claims and Policy Processing Clerks

688 0.98 Brokerage Clerks

687 0.98 Order Clerks

686 0.98 Loan Officers

685 0.98 Insurance Appraisers, Auto Damage

684 0.98 Umpires, Referees, and Other Sports Officials

683 0.98 Tellers

682 0.98 Etchers and Engravers

681 0.98 Packaging and Filling Machine Operators and Tenders

680 0.98 Procurement Clerks

679 0.98 Shipping, Receiving, and Traffic Clerks

678 0.98Milling and Planing Machine Setters, Operators, and Tenders, Metal and Plastic

Rank Probability Occupation

1 0.0028 Recreational Therapists

2 0.003 First-Line Supervisors of Mechanics, Installers, and Repairers

3 0.003 Emergency Management Directors

4 0.0031 Mental Health and Substance Abuse Social Workers

5 0.0033 Audiologists

6 0.0035 Occupational Therapists

7 0.0035 Orthotists and Prosthetists

8 0.0035 Healthcare Social Workers

9 0.0036 Oral and Maxillofacial Surgeons

10 0.0036 First-Line Supervisors of Fire Fighting and Prevention Workers

11 0.0039 Dietitians and Nutritionists

12 0.0039 Lodging Managers

13 0.004 Choreographers

14 0.0041 Sales Engineers

15 0.0042 Physicians and Surgeons

16 0.0042 Instructional Coordinators

17 0.0043 Psychologists, All Other

18 0.0044 First-Line Supervisors of Police and Detectives

19 0.0044 Dentists, General

20 0.0044 Elementary School Teachers, Except Special Education

21 0.0045 Medical Scientists, Except Epidemiologists

22 0.0046 Education Administrators, Elementary and Secondary School

23 0.0046 Podiatrists

24 0.0047 Clinical, Counseling, and School Psychologists

25 0.0048 Mental Health Counselors

Top 25 Bottom 25


Wages Rates Are a Weak Predictor

Source: O*NET 2014 and McKinsey & Company Analysis

https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/four-fundamentals-of-workplace-automation


Geography Is No Predictor

Source: Joshua Wright, EMSI, 2014“Low-Skill Jobs Are Booming, But They’re

at Greatest Risk for Automation”

http://www.economicmodeling.com/2014/10/31/low-skill-jobs-are-booming-but-theyre-at-

greater-risk-for-automation/


Susceptibility to the Impact of Automation

Source: McKinsey & Company

https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet


View at the Industry Level

Source: McKinsey & Company

https://www.mckinsey.com/business-functions/digital-mckinsey/our-insights/where-machines-could-replace-humans-and-where-they-cant-yet


It’s Ultimately About the Cost

“Technology can provide better efficiency and quality with menial tasks, as Webster noted. But employers are

less likely to invest in that technology if there aren’t a high volume of workers to replace, or if it’s more

expensive than really cheap labor.”

JOSHUA WRIGHT, EMSI, OCTOBER 31, 2014“Low-Skill Jobs Are Booming, But They’re at

Greatest Risk for Automation”


Evolving Curriculum

Curriculum Analysis Framework

Curriculum Development Considerations


Curriculum Analysis, Framework

Develop a framework that will analyze the curriculum

Consider subjectivity to automation

Adjust based on economic likelihood of automation

Adjust based on specific forecast of the technological development


Curriculum Analysis, Considerations

Rate each Career Path offered, not just the associated

industry

Understand how your existing key economic forecasting

models account for automation (or not) at the career

path level


Curriculum Development, Suggestions

Develop courses as you always have, but consider…

Developing curriculum for creating, managing, or supporting automation jobs, not just the jobs themselves

Acquiring (buy/partner/collaborate) content for extremely short cycle-time

Developing at least one hybrid model with industry partner extending the internship/apprenticeship model


Curriculum Development, Complicating Factors

Industrial / Corporate Education

Portable / Micro Credentials

Differentiation

Career Changers

Cycle-time


“On net…”

…some career pathways will disappear, some will be created,

but our primary goal will be learning to forecast the impact of

technological change on specific careers, drastically shorten

curricula development cycle-times, and evolve the structure

of our relationship with employers.


Questions?

Discussion?

How can we help?


Thank You!

Derrick Edwards, President & CTO

AGS Data Systems / G*STARS

[email protected]

Links to resource materials

Call, write, or connect with me on LinkedIn

mailto:[email protected]

https://www.gstars.com/nwpa2019.html

the future of work: technology and the workforce · 2019-04-22 · the future of work: technology...

Documents