Daniel Samaan: ChatGPT and the Future of Work People Analytics Conference 2023 Summer Website: https://pacamp.org Youtube: https://www.youtube.com/channel/UCeHtPZ_ZLZ-nHFMUCXY81RQ FB: https://www.facebook.com/pacamporg

1. ChatGPT and the Future of Work
Daniel Samaan
Senior Economist and Future of Work Expert
International Labour Organization, Geneva, Switzerland
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2. Overview
My abstract for this talk:
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3. Overview
The only problem is...I did not write it!
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4. What’s ChatGPT?
ChatGPT - Background
I Recent advance in the development of Large Language Models
(LLMs) with Generative Pre-trained Transformer (GPT)
I ChatGPT writes essays by repeatedly "guessing" what the next
word in a sentence is.
I It "learnt" about the structure of human language by accessing the
about 5 million digitalized books, in particular the patterns of 40k
commonly used words in English, and by continued interaction
with humans
I See article by Stephen Wolfram (2023): What is ChatGPT
doing...and why does it work?1
...and what could be the consequences for the world of work?
1
https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/
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5. ChatGPT and the Future of Work
My short answer:
ChatGPT is another step in the digital transformation of our societies,
including our workplaces and the world of work. Over the next 10 - 25 years,
this transformation provides opportunities for entire economies as well as
individual enterprises to:
I Re-think all production processes
I deconstruct and regenerate "jobs" by new job designs
I re-think the division of labor between humans and machines
I raise productivity and create better and more satisfying working
conditions
...but this has less to do with Technology than it has with the "Political
Framework" (such as labor market regulations, HR policies, bargaining
power of workforce vs. management/shareholders)
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6. ChatGPT and the Future of Work
My long(er) answer:
I Automation and job replacement
I Transformation of jobs
I Productivity
I Ethical Considerations
I Implications for HRM
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7. Automation and Transformation
Automation and transformation of jobs
I Knowledge workers or "white collar workers" mostly affected.
I 80% of U.S. workforce could have 10% of their tasks affected.2
I 19% of workers may see at least 50% of their tasks impacted.
I And in other countries...?
2
see Eloundou et. al. (2023): "GPTs are GPTs: An early look at labor market impact potential of large language models.
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8. Automation and Transformation
Globally, there are about 644 and 944 million knowledge workers
(between 19.4 - 30.7% of global workforce3
3
see Berg and Gmyrek (2023): "Automation hits the knowledge worker: ChatGPT and the Future of Work."
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9. Automation and Transformation
...but are the jobs automated, i.e. destroyed, or transformed?
The implications in each case are different for:
I Types of labor market transitions (intra-organizational,
interorganizational, across sectors)
I Training and skills demand, and financing of training
I Income shifts (Between wages and profits or within the wage
distribution)
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10. Productivity
Experimental evidence about productivity hints at the
following:4
I Productivity of workers can be raised (for example for mid-level
professional writing tasks).
I ChatGTP restructures tasks towards idea-generation and editing
and away from rough-drafting.
I But quality of essays did not significantly improve for all workers:
Hence, it mostly substitutes for worker effort rather than
complementing worker skills.
I Inequality between workers decreased during the experiment, as
low-ability workers benefited more from the help provided by
ChatGPT.
4
see Noy and Zhang (2023): "Experimental Evidence on the Productivity Effects of Generative Artificial Intelligence."
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11. Productivity
More (anecdotical) evidence about working with ChatGPT:
I find it very useful for
I Programming (but I am not a strong programmer....)
I Looking up quickly how to do something related to computer work
I Producing a rough draft of something that I can work on.
I Is it basically a better search engine?
Can we generalize all this evidence somehow?
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12. Productivity
Many jobs require carrying out simple or more complex computations....
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13. Productivity
ChatGPT: The equivalent of the pocket calculator that released workers
from making these calculation with paper and pencil?
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14. Productivity
Some jobs might be lost...
Computers Manhattan Project 1944
Computers U.S. Veterans Bureau, 1924
Computers NASA, 1953
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15. Conclusions and Implications for HRM
Probably we will see more transformation than automation for
most jobs:
It’s not so easy to automate things on a large scale!
1 Technical feasibility
2 Economic viability
3 Re-organize production process so (1) ans (2) apply
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16. Conclusions and Implications for HRM
What would I do if I were in a People Analytics Unit?
I Focus on tasks of your workers and their job designs.
I In a big organization, it’s complicated...but let’s not do it adhoc we have
data science.
I Who are your knowledge workers and what are they actually doing?
I Identify the potential and then raise organizational efficiency
(productivity).
I Try to establish a fair process of transitions... that makes your workforce
better off in terms of working conditions and wages5
I ....and makes your workforce better off.
Thank you!
5
see Fossen, Samaan, and Sorgner (2022): "How Are Patented AI, Software and Robot Technologies Related to Wage
Changes in the United States?"
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17. Conclusions and Implications for HRM
StackOverflow bans ChatGPT:
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