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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 = 0.085

Rarraba ba rarraba ba, da Spearman r = 0.0037

Nuna kawai sakamako > r = 0.085

Rarrabuwa	Da ba al'ada ba	Na al'ada	Na al'ada	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 0.0470	Rauni korau -0.0496	Rauni kyau 0.1038	Rauni korau -0.1084	Rauni kyau 0.0232	Rauni korau -0.0373	Rauni kyau 0.0296
Answer 2	-	Rauni kyau 0.0396	Rauni kyau 0.0285	Rauni kyau 0.0397	Rauni korau -0.0014	Rauni kyau 0.0089	Rauni korau -0.0157	Rauni korau -0.0672
Answer 3	-	Rauni korau -0.0198	Rauni korau -0.0355	Rauni kyau 0.0038	Rauni kyau 0.0600	Rauni korau -0.0108	Rauni korau -0.0072	Rauni korau -0.0144
Answer 4	-	Rauni kyau 0.0112	Rauni kyau 0.0303	Rauni kyau 0.0240	Rauni korau -0.0166	Rauni korau -0.0588	Rauni korau -0.0263	Rauni kyau 0.0474
Answer 5	-	Rauni kyau 0.0270	Rauni korau -0.0118	Rauni korau -0.0176	Rauni kyau 0.0059	Rauni kyau 0.0039	Rauni kyau 0.0337	Rauni korau -0.0448
Answer 2	-	Rauni korau -0.0429	Rauni korau -0.0493	Rauni korau -0.1035	Rauni kyau 0.0801	Rauni kyau 0.0191	Rauni kyau 0.0447	Rauni kyau 0.0184
Answer 6	-	Rauni korau -0.0522	Rauni kyau 0.0775	Rauni korau -0.0433	Rauni korau -0.0454	Rauni kyau 0.0195	Rauni kyau 0.0136	Rauni kyau 0.0372
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7	-	Rauni kyau 0.0080	Rauni kyau 0.0237	Rauni kyau 0.0777	Rauni kyau 0.0792	Rauni korau -0.0143	Rauni korau -0.0982	Rauni korau -0.0701
Answer 8	-	Rauni kyau 0.0274	Rauni korau -0.0395	Rauni korau -0.0420	Rauni korau -0.0025	Rauni kyau 0.0892	Rauni korau -0.0261	Rauni korau -0.0102
Answer 9	-	Rauni kyau 0.0553	Rauni korau -0.0271	Rauni korau -0.0175	Rauni korau -0.0221	Rauni korau -0.0351	Rauni kyau 0.0247	Rauni kyau 0.0318
Answer 10	-	Rauni kyau 0.0201	Rauni kyau 0.0084	Rauni kyau 0.0002	Rauni korau -0.0363	Rauni korau -0.0007	Rauni korau -0.0169	Rauni kyau 0.0337
Answer 11	-	Rauni korau -0.0453	Rauni kyau 0.0420	Rauni kyau 0.0373	Rauni kyau 0.0491	Rauni korau -0.0783	Rauni kyau 0.0450	Rauni korau -0.0559
Answer 8	-	Rauni korau -0.1090	Rauni korau -0.0396	Rauni korau -0.0078	Rauni kyau 0.0259	Rauni korau -0.0091	Rauni kyau 0.0900	Rauni kyau 0.0099
Answer 12	-	Rauni korau -0.0030	Rauni kyau 0.0569	Rauni korau -0.0541	Rauni korau -0.1104	Rauni kyau 0.0146	Rauni kyau 0.0416	Rauni kyau 0.0737

Aika zuwa MS Excel

Wannan aikin zai kasance a cikin zaben VUCA

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

2023.11.27

Valerii Kosenko

Samfurin Samfurin Saas Parfult Sdtest®

Valerii ya cancanci a matsayin mai ilimin halin dan Adam a 1993 kuma tun bayan da saninsa a aikin aikin.
Valeridi ya samu digiri na biyu da kuma aikin da kuma cancantar shirin Attap (a lokacin shirin maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne ga aikin ubangijinsa, ya zama sananne ga aikin ubangijinsa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne game da hanyar maigidansa, ya zama sananne ga aikin ubangijinsa, ya zama kamar yadda Fattifrschaft Für projechtmanageel e.
Valeridi ya dauki hanyoyi daban-daban na kifaye da kuma amfani da iliminsa da gogewa don daidaita da sigar SDTest.
Valeria shine marubucin binciken rashin tabbas game da V.U.C.C. Tunani na amfani da Kewaye na Kuranni da ƙididdiga na lissafi a cikin ilimin halin mutumci, sama da zaben ƙasa da ƙasa da ƙasa da ƙasa.

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