(highlight:: The Impact of Job Automation Is A Product of Automatibility and Skill Transferability
Summary:
Job automatibility is not a direct indicator of job security as people are not just their occupations, but also their skills.
While some occupations are likely to be automated, individuals in those roles often possess transferable skills that allow them to transition to other growing occupations. Conversely, occupations that are not likely to be automated may still face challenges due to oversupply and may not offer the same opportunities for skill transfer.
The impact of job automation is complex and cannot be determined solely based on the likelihood of automatibility.
The network analysis reveals that the situation is not as straightforward as assuming automatable occupations will suffer and non-automatable occupations will grow; rather, it lies somewhere in between and requires a comprehensive understanding of the network to fully grasp.
Transcript:
Speaker 1
And what we saw in this model was that, for example, we take the example of childcare workers and statistical assistants. And I like to say, if your nephew asks you, I either want to become a childcare worker or a statistical assistant. You look at those automation probabilities. Child care worker, not likely to be automated. Statistical assistant, likely to be automated. And you might think, well, of course, you should be a childcare worker, then you're not gonna be automated. Your job is not gonna be automated. And our results tend to hint otherwise. Why? The thing is, people are not only their occupations. They're their skills. And with their skills, they can't transition. They can't transition in this network. And the thing is, the statistical assistant might be automated, but they have skills that allow them to transition to other occupations that are growing in demand. Well, childcare workers might not be automated, but they're easy to reach. In a way, childcare work is something intrinsic to humans. So other people that may be automated might go for that occupation. And again, talking about demand and supply, that's why. And this is something the network reveals. It's not straightforward to say, automation, automatable occupations are bad. Well, sorry, are gonna suffer, non-autobiotiable occupations are gonna grow, but it's somewhere in between. And to see that completely, we have to go to the network.)
- Time 0:30:24
- artificial_intelligence_ai, automation, labor_markets, 1social/dont-post,

(highlight:: Will Automation Just Exacerbate Polarization of Professional Skill Level Across Society?
Summary:
The potential impact of automation on society could lead to a scenario where a significant portion of the population lacks the necessary skills for high-demand fields such as health and science, resulting in a division between high-skill and low-skill individuals.
This could lead to a dystopian future where only a privileged few can access enhancements and advancements, creating a divide between the affluent and the less privileged. However, the key to avoiding this scenario is through retraining and providing the right education and motivation to enable everyone to pursue high-skill jobs.
The focus should be on job transitions and ensuring that individuals have the opportunity for dignified and meaningful work through appropriate education and training.
Transcript:
Speaker 1
So I think that's the good scenario, where we educate people and everyone, those interesting jobs, does health, does science, and understands the world ultimately. The bad scenario is where it actually, we have so many unemployed people. Well, as I said, it's not gonna hit like massive levels, but we have a lot of people that, whose skills is not compatible with the health, and science, and all of that. And then we say, well, you know, it costs energy to pay it to have a robot, but there's people willing to do it. So let's just pay a low wage to those people. And that is actually a bit this topic, is that means we're gonna split people into the ones that can do high skill, the ones that can do low skill. And this is actually a bit related to what Harari says. So Harari puts this dystopia, right? That maybe some people are the ones that are gonna be able to buy goods that will amplify our capability. So I don't know, we're gonna expand our memory. But some people, and for example, talked about blood transfusions, that might enable you to live longer. So there's the people that are gonna be able to afford it, and the people that cannot. And that's gonna create, you know, two types of humans in a way, and that's scary. I really hope we don't go that way, and I hope the way to ensure that is through retraining. Because I think everyone can do high skill jobs if they receive the right education, and the right motivation. And I think that's the core of what this work is about. It's about job transitions. It's about what retraining do we need to get into, let's say, the steady state we want, the attractor we want. Well, in a way we're in the same attractor, yeah. And to the fixed pointers, or around the fixed point we want instead of the other. We have a choice. Well, I think we have, I like to think we have a choice. And where are we gonna push the system? Is it the one where everyone can go to every job, because we have education? Well, not every job, but like, to a job with dignity that is important to them, or is it the other? And I think that's where we need to really push for the science.)
- Time 0:36:17
- artificial_intelligence_ai, economic inequality, inequality, labor_markets, polarization, unemployment, 1social/dont-post,

(highlight:: The Impact of Job Automation Is A Product of Automatibility and Skill Transferability
Summary:
Job automatibility is not a direct indicator of job security as people are not just their occupations, but also their skills.
While some occupations are likely to be automated, individuals in those roles often possess transferable skills that allow them to transition to other growing occupations. Conversely, occupations that are not likely to be automated may still face challenges due to oversupply and may not offer the same opportunities for skill transfer.
The impact of job automation is complex and cannot be determined solely based on the likelihood of automatibility.
The network analysis reveals that the situation is not as straightforward as assuming automatable occupations will suffer and non-automatable occupations will grow; rather, it lies somewhere in between and requires a comprehensive understanding of the network to fully grasp.
Transcript:
Speaker 1
And what we saw in this model was that, for example, we take the example of childcare workers and statistical assistants. And I like to say, if your nephew asks you, I either want to become a childcare worker or a statistical assistant. You look at those automation probabilities. Child care worker, not likely to be automated. Statistical assistant, likely to be automated. And you might think, well, of course, you should be a childcare worker, then you're not gonna be automated. Your job is not gonna be automated. And our results tend to hint otherwise. Why? The thing is, people are not only their occupations. They're their skills. And with their skills, they can't transition. They can't transition in this network. And the thing is, the statistical assistant might be automated, but they have skills that allow them to transition to other occupations that are growing in demand. Well, childcare workers might not be automated, but they're easy to reach. In a way, childcare work is something intrinsic to humans. So other people that may be automated might go for that occupation. And again, talking about demand and supply, that's why. And this is something the network reveals. It's not straightforward to say, automation, automatable occupations are bad. Well, sorry, are gonna suffer, non-autobiotiable occupations are gonna grow, but it's somewhere in between. And to see that completely, we have to go to the network.)
- Time 0:30:24
- artificial_intelligence_ai, automation, labor_markets, 1social/dont-post,

(highlight:: Will Automation Just Exacerbate Polarization of Professional Skill Level Across Society?
Summary:
The potential impact of automation on society could lead to a scenario where a significant portion of the population lacks the necessary skills for high-demand fields such as health and science, resulting in a division between high-skill and low-skill individuals.
This could lead to a dystopian future where only a privileged few can access enhancements and advancements, creating a divide between the affluent and the less privileged. However, the key to avoiding this scenario is through retraining and providing the right education and motivation to enable everyone to pursue high-skill jobs.
The focus should be on job transitions and ensuring that individuals have the opportunity for dignified and meaningful work through appropriate education and training.
Transcript:
Speaker 1
So I think that's the good scenario, where we educate people and everyone, those interesting jobs, does health, does science, and understands the world ultimately. The bad scenario is where it actually, we have so many unemployed people. Well, as I said, it's not gonna hit like massive levels, but we have a lot of people that, whose skills is not compatible with the health, and science, and all of that. And then we say, well, you know, it costs energy to pay it to have a robot, but there's people willing to do it. So let's just pay a low wage to those people. And that is actually a bit this topic, is that means we're gonna split people into the ones that can do high skill, the ones that can do low skill. And this is actually a bit related to what Harari says. So Harari puts this dystopia, right? That maybe some people are the ones that are gonna be able to buy goods that will amplify our capability. So I don't know, we're gonna expand our memory. But some people, and for example, talked about blood transfusions, that might enable you to live longer. So there's the people that are gonna be able to afford it, and the people that cannot. And that's gonna create, you know, two types of humans in a way, and that's scary. I really hope we don't go that way, and I hope the way to ensure that is through retraining. Because I think everyone can do high skill jobs if they receive the right education, and the right motivation. And I think that's the core of what this work is about. It's about job transitions. It's about what retraining do we need to get into, let's say, the steady state we want, the attractor we want. Well, in a way we're in the same attractor, yeah. And to the fixed pointers, or around the fixed point we want instead of the other. We have a choice. Well, I think we have, I like to think we have a choice. And where are we gonna push the system? Is it the one where everyone can go to every job, because we have education? Well, not every job, but like, to a job with dignity that is important to them, or is it the other? And I think that's where we need to really push for the science.)
- Time 0:36:17
- artificial_intelligence_ai, economic inequality, inequality, labor_markets, polarization, unemployment, 1social/dont-post,