5/2/2024 - Technology and Innovation

AI and employment: great language models, a predator 2.0?

By Ian Cristian Ariel Yané

AI and employment: great language models, a predator 2.0?

Well yes... you must have said "why does that note start with that title?", and I don't blame you, I would be thinking the same thing, what a title I made up... but hey... stop there! stop there!!!, you can keep reading (there is no terminator here), first of all I chose that title because in a way, that's how we all feel ("he is going to leave us without a job car**o!!"), and secondly you guessed it, it was for you to come in, read it and now that you are here... it will only take you a few minutes and I hope in that time to give you some close brush strokes regarding all this and a fresh opinion of what is going on with this predator android that is out there (who knows who from what dark corner is stalking us), I mean... this new breed of Artificial Intelligence that seems to stalk our jobs (the great language models or LLM's).

Enough of killer androids, let's get serious. First of all highlight that for this brief analysis, I considered the reports of OpenAI, GatesNotes, the World Economic Forum and of course my experience and knowledge and good faith to clarify some points and nuances, which may be creating unnecessary dissonances and tensions.

Unlike an initial approach with little information, artificial intelligence (according to OpenAI and Bill Gates reports) seems to affect mainly office and computerized jobs but which paradoxically have a large part of lateral or analytical thinking, such as lawyers, administrative assistants, graphic designers, content creators, and among other professions, there is one even more paradoxical and it has to do with the one responsible for its creation, programming.

Manual jobs, such as electricians, plumbers, bricklayers, among others, are less affected. This makes sense considering that large language models operate at the software level and are not currently directly linked to the hardware and robotics needed to perform manual jobs that have a wide range of nuances. It is important to keep in mind that the GPT-4 are trained with information from the web, so linking this information with specific hardware would require considering the real situations in which these professionals work, a lot of training data, a lot of testing time and money (although the latter is never a problem for corporations that put their eye on this type of technology we already know, I think it was over), let's say that the work, the more similar to a recipe the more replaceable it will be.. that's why the more nuances, the more innovative and the less data collected about the task, the more value human work has and the less the big language models have.

By the way, with the above, I have in mind that since 2023, several proposals for autonomous cars, robots that cook, among others, have been coming to market. and although from time to time we hear some terrifying news, in general they work very well and continue to be perfected, but as I said, although a car on wheels is more dangerous than a robot electrician, the reality that compiling the amount of nuances and contextual variables that can have this last work and the amount of different tasks so different make it difficult to implement this in a viable and convenient way in the short term, think about how it would detect the different patterns, how that robot would pass the cable ducts, how much it would cost to repair a socket or even more bizarre, how big would such a robot occupy and how much would it cost?.

Now on the other hand, if we leave Bill Gates and the Open-Ai engineers to continue with their work and we go to see what the World Economic Forum proposes and we take into account the information about the most demanded skills and the current deficiencies of GPT-4 (context of approximately 4500 words, difficulty to understand too long entries and lack of subjective and nuanced experience), a higher demand for technical skills in the field of Big Data is expected by 2027, such as artificial intelligence and handling of large volumes of data mainly in the areas that most require soft skills such as critical and analytical thinking, leadership, influence, continuous learning, automation, resilience, adaptability and curiosity to adapt to these changes. Again, this may seem contradictory; won't professions such as mathematics, software, management, among others, be as necessary at the same time that great critical and analytical thinking will be required? well, as I commented in the previous paragraphs, although GPT-4 can already perform many tasks that follow established patterns and for which information is available, such as data analysis and graphic design, or yes... post like this (in case you were thinking about it), it is expected that for a long time it will be only in a percentage of the tasks (yes, that thing we talked about a while ago about context and nuances), and people with strategic, analytical and systematic thinking will be needed, for the adaptation of the different pieces to the particular system. A sort of AI-powered 2.0 versions of the above disciplines and careers are expected to develop, as the Innovation and Artificial Intelligence Lab of the UBA (University of Buenos Aires) has been anticipating for years. In addition, new jobs will be created as notoriously happened with "prompts engineering", and in areas of innovation or creation, such as research, talent with strong mathematical skills will be required more than ever, despite what we might think when reading OpenAI or Note Gates reports.

After reading this brief opinion piece, you now know which professions have the greatest future and an idea of what to do about it, but you may still have two questions... How do I adapt to change? What professions or specializations can I take to keep my career competent? Although I mentioned a new emerging profession, prompt engineering, next time I will investigate about the different emerging professions and those trainings that pretend to articulate to the current professions as the Innovation and Artificial Intelligence Lab of the UBA does.

If this blog helped you in any way, don't forget to hit share, you help me a lot to gain visibility and bring some clarity to people like you, reader.

Bibliography:

Clarín - For Bill Gates, these are the jobs most threatened by ChatGPT and artificial intelligence: https://www.clarin.com/internacional/bill-gates-trabajos-amenazados-chatgpt-inteligencia-artificial_0_hL123JE5IC.html

El Confidencial - The 10 jobs that artificial intelligence will eliminate first - and the ones that are safe: https://www.elconfidencial.com/tecnologia/novaceno/2023-03-24/chatgpt4-openai-trabajo_3599085/

GatesNotes - The Age of AI has begun: https://www.gatesnotes.com/The-Age-of-AI-Has-Begun#ALChapter3

GatesNotes - The risks of AI are real but manageable: https://www.gatesnotes.com/The-risks-of-AI-are-real-but-manageable

arxiv - GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models: https://arxiv.org/abs/2303.10130

World Economic Forum - Future of jobs 2023: These are the most in-demand skills now - and beyond: https://www.notion.so/Recording-from-22-1-2024-12-26-05-d11c8d26e6554adaa4622190e0f4f017?pvs=4

Codemotion: Devin - a new end-to-end artificial intelligence programming tool: https://www.codemotion.com/magazine/es/inteligencia-artificial/devin-una-nueva-herramienta-de-programacion-de-ia-de-extremo-a-extremo/

Wikipedia - Tesla Autopilot: https://es.wikipedia.org/wiki/Tesla_Autopilot

YouTube, channel - "The Future Is Exciting from Vodafone": https://www.youtube.com/watch?v=7PR5-3xZXsM&ab_channel=ElFuturoEsApasionantedeVodafone

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ian yane

Ian Cristian Ariel Yané

After exploring Psychology, Business Administration and Web Programming, I found my true passion in Data Science. I think data is the key to making informed decisions and approaching the truth when it is not evident. I am currently in third year of higher technicality in data science and artificial and living intelligence learning in a self-taught way various platforms to then do research and projects on my own.

As Blogger of **FinGurú**, my goal is to share the best of me by bringing clarity to a topic that is spoken a lot. I want to provide the general public with fundamental knowledge about Data Science as clearly as possible, including my analysis of essential technical aspects, latest developments and emerging conspiracy, employability in this field, prospects for the future and more.

My mission is that, as a society, we can make more informed decisions, based on understanding rather than fear or ignorance, in order to advance and improve.

**This is my journey, and I am excited to share it with you!**

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