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FeatheryBallOfFluff t1_j0kwtol wrote

Oh no, another non-expert thinking it knows exactly how things will work out. Most people would be pretty bored doing nothing at all with their lives. As long as people are curious, people will work on science, volunteer, build stuff and create stuff. That's why you see businessmen, rockstars, designers and other artists still work even if they have enough money to never work a day in their life again. People like to feel useful.

Also don't underestimate social pressure (what society thinks being "succesful" means)

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anglesideside1 t1_j0l8x34 wrote

You’d think we would have learned that lesson during the pandemic. The vast majority of people did things you mentioned while we were forced to be isolated from one another. Sure, some people probably stayed home and played video games all day by themselves, but the vast majority of us were bored and did whatever we could to feel useful.

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StanielBlorch t1_j0lrgdy wrote

>the vast majority of us were bored and did whatever we could to feel useful.

I learned to knit. Made my own scarves for winter and my god am I happy with the results. Went way overboard. The extras? Given away to friends and family and the stuff that was still left over went to Goodwill.

I tutored my step-brother's son with algebra and his daughter with chemistry.

OP's outlook is just sad.. I hope they get help.

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giantsteps92 t1_j0lhfy0 wrote

This. A big difference would be the ability to socialize. So if you learned music, you could go and play with your friends (unlike lockdowns).

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Gubekochi t1_j0ljv9f wrote

To be honest being an adult with time to maintain my friendships sounds like heaven on earth.

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passwordsarehard_3 t1_j0m58wd wrote

The only thing stopping it is greed.

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Gubekochi t1_j0m6tks wrote

Not mine, nor theirs. For years I worked 4 days a week because my employer would allow it and I valued my free time more than actual money. But at the same time, I'd like to be able to save for retirement and nice things like 1.6 children or something...

The greed of the capitalist/owner/bourgeois class though... now we're talking!

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DeckardPain t1_j0mdx5t wrote

For real. Another doomer thread that totally misses the entire psychology of society in 2022.

You will get bored with no job for longer than 6-12 months. Jobs aren’t just about earning money. They keep you busy, engaged, and feel like you’re contributing in some way. Obviously shitty work environments can degrade this, but the point still stands.

I also work with AI somewhat regularly as a software engineer. This shit isn’t replacing any jobs in the near future. The art ones especially. They just steal and combine. Mega copyright issues that nobody is going to touch.

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DCSMU t1_j0npa9i wrote

Yeah, what's up with all the angsty AI doom and gloom on here today?

Also, why can't I see this guy's recent post history, am I making some noob mistake? I dont usually check such things, but given the frequency of posts like these hitting my feed today, I figured I should start looking.

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SCP-Agent-Arad t1_j0ou4y7 wrote

I feel like all these dystopia fetishists think we’re going to do a time jump 100 years into the future, and simply don’t consider anything in the intervening time.

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Surur t1_j0kxgbp wrote

No, he is right. If UBI is enabled by AGI/ASI, then "people will work on science, volunteer, build stuff and create stuff" will be unnecessary.

Whatever you can do, could be done more easily and better by an AGI.

Ironically the best thing the ASI could do was put everyone in the matrix, where they pretend to live meaningful lives.

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FeatheryBallOfFluff t1_j0kykz1 wrote

Highly unlikely. A scientist still needs to guide AI to make it search in the right direction. You can tell AI "Find me the best binding proteins with this protein of interest, binding epitope X", and AI may find you the best one, but someone still has to do something with that information and how to apply it.

Then there is research on things that are hard for a robot to understand. A lot of research in ecology is barely significant, but biologically relevant. A human may understand why something is biologically relevant, AI as it stands now is uncapable of doing so.

What AI can do though, is optimize plant growth parameters, so energy requirements go down, while food security increases. So essentially, it would be possible to eventually feed the population with very little labour, and so we can focus on other tasks that further improve our lives (hint: science).

AGI as it stands, is decades, if not centuries away. But let's for a second assume it is, why wouldn't humans collaborate with AGI to find new scientific results?

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Surur t1_j0l3xsp wrote

If AIs can understand protein folding better than humans, I think it is pretty obvious those higher level abstractions are also tractible, especially complex things like ecology. I would bet AI would be much better at understanding ecology than us.

There is very little sign AGI is centuries away, and decades go past pretty fast.

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FeatheryBallOfFluff t1_j0l6723 wrote

AIs can predict, but that isn't equal to understanding why or how it works. It's like being able to apply a very complex formula. You may know how to apply the formula, but may not understand why the formula is like that. Computers are good at finding correlations, but in an environment with little correlations, AI may have difficulty, as there is no number that indicates biological relevance.

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Surur t1_j0l6tj8 wrote

Finding the relationship between items is exactly what AI is good at. You sound like the people who said AI would never beat Go because the number of combinations were more than the atoms in the universe.

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breaditbans t1_j0l9qc4 wrote

I work in medical research. We are already seeing cool image based analysis, but it’s supervised machine learning that is only as good as the training set. This will apply to any machine learning algos. And that’s where we are going to run into issues. What I’d like to see in ML algos that can read 50 high impact papers in a field and put together a summary of the data. The problems arise when people have bad data. It might be fabricated, poorly designed expts or just bad statistics. The ML algos are going to assume that data is as real as the most well-performed experiments. The bad data will contaminate the good data and corrupt the conclusions drawn from the algos.

Will that problem get alleviated? Probably, but it’s going to take some time and it’s going to require a lot of bright people to curate the dataset to actually be able to draw better conclusions than we can arrive at alone. But in 15 years? God only knows. Maybe I’ll just submit whatever grant ChatGPT13 writes for me.

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Surur t1_j0ld4s8 wrote

Dealing with dirty data is exactly the strength of neural networks. It is just a matter of time.

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Yokono666 t1_j0wtrvs wrote

You're missing the point of human creativity. There doesn't have to be a purpose. The purpose is the process. AI can't replicate the experience of learning a skill over years and deriving pleasure from engaging in it.

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