物理学家

自动化风险
计算出的
0.0%
风险等级
投票
19.2%
根据 932 票的投票结果
劳动力需求
增长
8.2%
到2032年
工资
$142,850
或每小时 $68.67
体积
18,840
截至 2022
摘要
工作评分
8.3/10

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自动化风险

0.0% (最小风险)

最小风险(0-20%):这一类别的职业被自动化的可能性较低,因为它们通常需要复杂的问题解决能力,创造力,强大的人际交往能力和高度的手动灵巧。这些工作通常涉及复杂的手部动作和精确的协调,使得机器难以复制所需的任务。

有关这个分数是什么以及如何计算的更多信息可在这里找到。

工作中的一些非常重要的品质很难实现自动化:

  • 原创性

工作中的一些相当重要的品质难以自动化:

  • 社会洞察力

  • 说服

用户投票

在接下来的二十年内,实现全自动化的可能性为19.2%

我们的访客投票表示,这个职业被自动化的可能性极小。 这个评估进一步得到了通过计算得出的自动化风险等级的支持,该等级预计有0.0%的机会实现自动化。

你认为自动化的风险是什么?

物理学家在未来20年内被机器人或人工智能取代的可能性有多大?






情感

以下图表会在有大量投票数据可以呈现有意义的数据时包含在内。这些视觉表示显示了用户投票结果随时间的变化,提供了对情绪趋势的重要指示。

随着时间(每年)的情绪变化

增长

相对于其他职业的快速增长

预计"Physicists"的工作空缺数量将在2032内增长8.2%

总就业人数和预计的职位空缺

* 根据劳工统计局的数据,该数据涵盖了从2021到2031的期间。
更新的预测将在09-2023到期.

工资

相对于其他职业,薪酬非常高

在2022,'Physicists'的年度中位数工资为$142,850,或每小时$68。

'Physicists'的薪资比全国中位工资高208.5%,全国中位工资为$46,310。

随着时间推移的工资

* 来自美国劳工统计局的数据

体积

与其他职业相比,就业机会的下限范围较低。

截至2022,在美国有18,840人被雇佣为'Physicists'。

这代表了全国就业劳动力的大约< 0.001%

换句话说,大约每7 千人中就有1人被雇佣为“Physicists”。

工作描述

进行物理现象的研究,基于观察和实验发展理论,并设计方法来应用物理定律和理论。

SOC Code: 19-2012.00

资源

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评论

留下评论

9 (没有机会)说
We teach AI. That's how it understands. Although it can learn, it can't accumulate pure factual knowledge by itself.
Nov 14, 2023 at 08:02 上午
Jamie (极有可能)说
Hard science fields will be the easiest fields for AI to take-over.
Jun 18, 2023 at 12:03 下午
MainEditor说
But if AI can do hard science why it wouldn't as easy do soft science?
Mar 14, 2024 at 06:20 下午
Zuzia (适度)说
AI can already teach itself new things and it escalates very quickly, it probably will be able to analyze all the knowledge we have on Earth and come to some important conclusions.
Jun 07, 2023 at 02:40 下午
Samuel (没有机会)说
It requires thinking outside the box, solving new problems, writing new programs. It has already implemented computers for calculations.
May 25, 2023 at 09:40 下午
Toast (没有机会)说
Being a physicist requires, at least to a certain degree, being able to come up with purely original ideas, rather than interpolating the existing body of knowledge.
Feb 24, 2023 at 02:04 上午
Quarked_Out (低)说
Hmm, a lot of areas in physics do incorporate ML techniques and AI to some degree. However, people with physics training play an undisputedly dominant role in research.

If anything, I can see some simulation aspects or redundant experimental procedures being automated in the near term. But parts that incorporate creative problem solving or the physical intuition needed in determining directions to take research are things that are pretty safeguarded to humans for a bit.

I think those "intuitions" are very difficult to map to general problem-solving algorithms.
Feb 02, 2023 at 12:42 上午
Brian (No Chance)说
Many other experimental physicists and I already automate every measurement we can, but there is still plenty of work to do.
Oct 25, 2022 at 05:51 下午
David (没有机会)说
I wonder what all those people were thinking when they said there was a realistic possibility that physicists will be obsolete in 20 years. That's absurd on its face and every physicist I have ever met would agree.

We can have a discussion on whether it is possible in the next 200 years, sure, but 20 years? That's laughable. Given that only physicists are qualified to write, train, and optimize the algorithms that would be used to replace them, it will take a long, long, long time.

I suspect that we would need true machine sentience before we could actually start to talk about replacing theoretical and mathematical physicists.
May 29, 2022 at 05:30 上午
Bimsara Bodaragama (没有机会)说
It's more about intuition and innovativeness. Of course, we will use more tools, but with Physics, since we interpret as we observe (there is a little problem with that conclusion, though), AI may not be able to take it over.
Mar 29, 2022 at 06:37 下午
Wesley I (没有机会)说
I believe that it will be possible but not for a very long time, the process of positing new questions and then solving them is rather complex and I'm guessing that it will be at least 100 years before the jobs of theoretical physicists start to become threatened.
Aug 30, 2021 at 01:48 下午
just bored (没有机会)说
Even though computers may get more intelligent than us humans, there is still a very small chance because computers don't have the basic questioning ability which we humans have
Jun 23, 2021 at 08:02 上午
Rowan (不确定)说
The development of AI is rapidly improving, AI maybe 10 years in the future being able to predict or understand the universe better through random generation or pure knowledge is very probable. However I doubt they will replace Physicists in the near decade it should be very increasingly possible.
Mar 23, 2021 at 03:36 下午
rafel说
We are users of AI to improve some calculations and we need robots and AI for experimental precision and performance. Until the singularity, we will be in charge.
Mar 18, 2021 at 08:36 下午
Pinaki Patra说
A huge section of theoretical physicists do algorithm based research, which can easily be replaced by automation.
However, Philosophy based theoretical research is difficult to be replaced.
Feb 08, 2021 at 07:08 下午
Physics Boi (低)说
Doubt it, anyway we need physicists to understand what the AI is discovering anyway
Jan 06, 2021 at 08:16 上午
Anonymous (没有机会)说
It is scientifically proven that the human brain is MUCH more complicated than any AI, and it is very hard for AI to ask a question and solve it on their own, so I think AI stands no chance on taking over the complex job of science.
Dec 28, 2020 at 01:45 下午
Tom (没有机会)说
Whilst experimental physics can be automated, I doubt theoretical physics will be automated
Aug 07, 2020 at 12:20 下午
Mark (没有机会)说
Most physicists I know are already good with experimental automation and AI and there's still plenty of work for everyone.
Jul 20, 2020 at 04:55 下午
Nine说
Scientific discovery can be easily automated. It has a rather rigorous process. And if not, then the computer can use randomness like humans do.
Feb 26, 2020 at 10:24 下午
No Nine说
Computers use "seeds" as a way to "randomize" events. As soon as the seed is known, randomness is no more useful. The randomness of computers is limited, is false.
Jan 18, 2021 at 03:39 上午
Me (低)说
Too chaotic
Dec 07, 2019 at 01:08 上午

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