Grazie, Antonio!
jc
On 20/03/23 13:36, Antonio Casilli wrote:
Grazie JC,
l'avevo visto e mi promettevo di commentarlo... La lista delle limitazioni di
questo articolo è lunga quanto la somma di tutte le braccia rubate
all'agricoltura dei suoi autori (tranne Daniel Rock, che qualche anno fa aveva
posizioni molto meno oltranziste sulla questione, cf.
https://www.nber.org/papers/w24001).
Questo documento è un ennesimo caso di LaTeX-driven advertising, nel senso che
un paper con parvenza di scientificità viene usato per fare pubblicità o
assecondare le operazioni di marketing di un'azienda. Un po' come il caso
storico di Eytan Bakshy, Solomon Messing, Lada Adamic, “Exposure to
ideologically diverse news and opinion on Facebook [archive]”, Science, 7,
2015, che scagionava l'algoritmo di NewsFeed di Facebook e dava la colpa agli
utilizzatori per la creazione di “echo chambers”.
Da accogliere, come tutte le analisi task-based, con un sonoro "meh".
Cheers,
---a
----- Original Message -----
From: "J.C. DE MARTIN" <[email protected]>
To: "Nexa" <[email protected]>
Sent: Monday, March 20, 2023 12:41:41 PM
Subject: [nexa] "GPTs are GPTs: An Early Look at the Labor Market Impact Potential
of Large Language Models"
[Submitted on 17 Mar 2023]
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large
Language Models
[ https://arxiv.org/search/econ?searchtype=author&query=Eloundou%2C+T | Tyna
Eloundou ] , [
https://arxiv.org/search/econ?searchtype=author&query=Manning%2C+S | Sam
Manning ] , [
https://arxiv.org/search/econ?searchtype=author&query=Mishkin%2C+P | Pamela
Mishkin ] , [
https://arxiv.org/search/econ?searchtype=author&query=Rock%2C+D | Daniel
Rock ]
We investigate the potential implications of Generative Pre-trained Transformer
(GPT) models and related technologies on the U.S. labor market. Using a new
rubric, we assess occupations based on their correspondence with GPT
capabilities, incorporating both human expertise and classifications from
GPT-4. Our findings indicate that approximately 80% of the U.S. workforce could
have at least 10% of their work tasks affected by the introduction of GPTs,
while around 19% of workers may see at least 50% of their tasks impacted. The
influence spans all wage levels, with higher-income jobs potentially facing
greater exposure. Notably, the impact is not limited to industries with higher
recent productivity growth. We conclude that Generative Pre-trained
Transformers exhibit characteristics of general-purpose technologies (GPTs),
suggesting that as these models could have notable economic, social, and policy
implications.
Subjects: General Economics (econ.GN) ; Artificial Intelligence
(cs.AI); Computers and Society (cs.CY)
Cite as: [ https://arxiv.org/abs/2303.10130 | arXiv:2303.10130 ]
[econ.GN]
(or [ https://arxiv.org/abs/2303.10130v1 | arXiv:2303.10130v1 ]
[econ.GN] for this version)
[ https://doi.org/10.48550/arXiv.2303.10130 |
https://doi.org/10.48550/arXiv.2303.10130 ]
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