Effects of AI on Supply Chain Jobs - Supply Chain in 3 minutes

Conor Doherty of Lokad scrutinizes a Harvard study on AI's impact on white-collar jobs, revealing nuanced effects. The research, involving 758 consultants, assesses AI's role in enhancing productivity, particularly in supply chain management. It finds that AI boosts performance in certain tasks, especially with training, but may falter in complex scenarios. Doherty critiques the study's narrow view of AI as an adjunct to human labor, arguing for its potential to fully automate tasks, thus revolutionizing productivity and redefining white-collar work. He warns of overconfidence in job security, as AI's full capabilities could dramatically alter the employment landscape.
Full transcript available: www.lokad.com/...
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Timestamps:
00:00:00: Brief summary of research paper by Harvard
00:00:32: ChatGPT-4 study with BCG consultants
00:01:31: Exploring AI's impact on productivity
00:02:31: AI's displacement potential and critique
00:03:47: AI's broader effects on employment
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[@jaypatidar8482]

what is frontier though...i didn't get???

[@Lokad]

Hi! It simply means a line/border separating two (or more) things. It is the same term used to describe borders ("frontiers") that separate countries - e.g., the Pyrenees form a natural frontier between France and Spain.
In this context, Harvard Business School suggests there is a digital frontier between the things gen-AI (ChatGPT-4) can do well and the things it cannot do well. We disagree.
See this essay for a greater explanation of our position: www.lokad.com/blog/2024/4/8/a-nuanced-perspective-on-jagged-technological-frontier/

[@hiratiomasterson4009]

What we need to keep in mind is that LLMs are not the ideal solution for analytical tasks - though of course they excel in descriptive outputs. We are still waiting to see what Q Star will be in terms of quantitative skills and capabilities - that may be truly transformative...and not in a good way for long term professional employment opportunities for large numbers of people...
GPT-4 is still a bit limited in many respects, but future iterations of it, Claude et al will be displaying true leaps in capability. Just hope the travelling salesman/routing problem can finally be easily solved.

[@Lokad]

It is certainly unfair to use an LLM for complex quantitative tasks and then say "hey, look at how badly it did!"
In case you are interested, we expanded our critique of the paper here: www.lokad.com/blog/2024/4/8/a-nuanced-perspective-on-jagged-technological-frontier/