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AI Assistants Boost Beginners More Than Experts, Study Shows Correlation

There once was an AI named Chat who was really good at repeating back information it already knew. One day, Chat was given to some office workers [1] to help them with their jobs. Some of the workers were experts at their jobs, while others were still learning.

At first, Chat helped all the workers get more work done faster - even the experts! But soon, the experts noticed something funny. The workers who were still learning got way MORE help from Chat. The new workers improved a lot using Chat, doing their work faster and better than ever before!

The experts wondered why Chat didn't help them as much. That's when they realized - that Chat is an expert at repeating back facts but can't come up with brand new ideas. So, for workers who already knew those facts, Chat didn't offer them that much new help. But for newer workers still learning those basics, Chat was able to teach them so much more!

This shows a correlation - as in, two things that relate to each other and change together. The more expert a worker already was, the less helpful Chat was for them. But for newer workers, Chat could help them almost as much as the experts! It's because of their different starting points. Chat has a limit to how expert it can be. So, the closer a worker already was to Chat's expertise, the less new stuff Chat offered them.

The experts and newbies improved at different rates thanks to Chat. Their own expertise compared to Chat's matters for how much more they can learn. That connection in how much they improve is the correlation!

The SDTEST^® gives clues to someone's motivational values. However, additional polls can provide more pieces of the puzzle.

Imagine also giving an "A.I. and the end of civilization" poll. It asks people to rate at the agree or disagree level.

Now imagine 100 people who took both tests. You could match up each person's SDTEST^® colors with their rated answers about the danger of AI.

Comparing tests gives an expanded picture of values in action. More puzzle pieces make the whole image more apparent!

Multiple tests can work together, like colors blending on a palette. Other polls reveal what engages your values, like what is the perception of the danger of AI. Combined, they paint a richer picture of what motivates our thoughts and deeds.

Below you can read an abridged version of the results of our VUCA poll “A.I. and the end of civilization“. The full results of the poll are available for free in the FAQ section after login or registration.

Hankali da kuma ƙarshen wayewar kai

Charts Hulda

VUCA

M darajar da hulda coefficient

Rarraba al'ada, ta William Gubetes (Dalibi) r = 0.0727

Rarraba ba rarraba ba, da Spearman r = 0.003

Nuna kawai sakamako > r = 0.0727

Rarrabuwa	Da ba al'ada ba	Na al'ada	Da ba al'ada ba	Na al'ada	Na al'ada	Na al'ada	Na al'ada	Na al'ada
Duk Tambayoyi Duk Tambayoyi 1) Aminci (nawa kuka yarda ko ba da yarda ba?) 2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
1) Aminci (nawa kuka yarda ko ba da yarda ba?)
Answer 1	-	Rauni kyau 0.0734	Rauni kyau 0.0222	Rauni kyau 0.0930	Rauni korau -0.1129	Rauni korau -0.0082	Rauni korau -0.0441	Rauni kyau 0.0172
Answer 2	-	Rauni kyau 0.0176	Rauni korau -0.0064	Rauni kyau 0.0439	Rauni korau -0.0235	Rauni kyau 0.0411	Rauni korau -0.0037	Rauni korau -0.0536
Answer 3	-	Rauni korau -0.0237	Rauni korau -0.0293	Rauni kyau 0.0041	Rauni kyau 0.0580	Rauni korau -0.0254	Rauni korau -0.0131	Rauni kyau 0.0056
Answer 4	-	Rauni kyau 0.0353	Rauni korau -0.0020	Rauni kyau 0.0147	Rauni korau -0.0434	Rauni korau -0.0329	Rauni korau -0.0045	Rauni kyau 0.0461
Answer 5	-	Rauni korau -0.0159	Rauni korau -0.0257	Rauni korau -0.0233	Rauni kyau 0.0425	Rauni kyau 0.0329	Rauni kyau 0.0241	Rauni korau -0.0546
Answer 2	-	Rauni korau -0.0137	Rauni korau -0.0525	Rauni korau -0.0709	Rauni kyau 0.0701	Rauni korau -0.0147	Rauni kyau 0.0443	Rauni kyau 0.0137
Answer 6	-	Rauni korau -0.0651	Rauni kyau 0.0972	Rauni korau -0.0603	Rauni korau -0.0026	Rauni kyau 0.0092	Rauni korau -0.0026	Rauni kyau 0.0252
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7	-	Rauni kyau 0.0139	Rauni kyau 0.0048	Rauni kyau 0.0805	Rauni kyau 0.0622	Rauni korau -0.0317	Rauni korau -0.0783	Rauni korau -0.0456
Answer 8	-	Rauni kyau 0.0230	Rauni korau -0.0258	Rauni korau -0.0352	Rauni kyau 0.0274	Rauni kyau 0.0832	Rauni korau -0.0126	Rauni korau -0.0582
Answer 9	-	Rauni kyau 0.0143	Rauni korau -0.0423	Rauni korau -0.0553	Rauni korau -0.0195	Rauni kyau 0.0021	Rauni kyau 0.0614	Rauni kyau 0.0320
Answer 10	-	Rauni kyau 0.0256	Rauni kyau 0.0035	Rauni kyau 0.0149	Rauni korau -0.0597	Rauni korau -0.0187	Rauni korau -0.0176	Rauni kyau 0.0573
Answer 11	-	Rauni korau -0.0173	Rauni kyau 0.0347	Rauni kyau 0.0531	Rauni kyau 0.0412	Rauni korau -0.0701	Rauni kyau 0.0068	Rauni korau -0.0464
Answer 8	-	Rauni korau -0.0930	Rauni korau -0.0342	Rauni korau -0.0141	Rauni kyau 0.0112	Rauni kyau 0.0211	Rauni kyau 0.0739	Rauni kyau 0.0020
Answer 12	-	Rauni kyau 0.0002	Rauni kyau 0.0882	Rauni korau -0.0341	Rauni korau -0.0785	Rauni korau -0.0241	Rauni korau -0.0070	Rauni kyau 0.0777

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Wannan aikin zai kasance a cikin zaben VUCA

[1] https://www.ft.com/content/b2928076-5c52-43e9-8872-08fda2aa2fcf

2023.11.27

Valerii Kosenko

Mai Samfurin SaaS SDTEST®

Valerii ya cancanta a matsayin masanin ilimin zamantakewar jama'a-psychologist a 1993 kuma tun daga lokacin ya yi amfani da iliminsa a cikin gudanar da ayyukan.
Valerii ya sami digiri na biyu da kuma cancantar aikin da mai sarrafa shirye-shirye a cikin 2013. A lokacin shirinsa na Jagora, ya saba da Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) da Spiral Dynamics.
Valerii shine marubucin binciken rashin tabbas na V.U.C.A. ra'ayi ta yin amfani da Ƙaƙwalwar Ƙarƙashin Ƙarƙashin Ƙarƙashin Ƙarƙashin Ƙarƙashin Ƙididdiga da Ƙididdiga na Lissafi a cikin ilimin halin dan Adam, da kuma 38 na kasa da kasa zabe.

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