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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 = 0.0828

Rarraba ba rarraba ba, da Spearman r = 0.0035

Nuna kawai sakamako > r = 0.0828

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 0.0762	Rauni korau -0.0046	Rauni kyau 0.1086	Rauni korau -0.1228	Rauni kyau 0.0184	Rauni korau -0.0551	Rauni kyau 0.0148
Answer 2	-	Rauni kyau 0.0302	Rauni kyau 0.0072	Rauni kyau 0.0367	Rauni korau -0.0046	Rauni kyau 0.0238	Rauni korau -0.0124	Rauni korau -0.0587
Answer 3	-	Rauni korau -0.0182	Rauni korau -0.0500	Rauni korau -0.0009	Rauni kyau 0.0531	Rauni korau -0.0099	Rauni kyau 0.0009	Rauni korau -0.0011
Answer 4	-	Rauni kyau 0.0057	Rauni kyau 0.0166	Rauni kyau 0.0297	Rauni korau -0.0251	Rauni korau -0.0543	Rauni korau -0.0202	Rauni kyau 0.0538
Answer 5	-	Rauni kyau 0.0128	Rauni korau -0.0180	Rauni korau -0.0228	Rauni kyau 0.0229	Rauni kyau 0.0196	Rauni kyau 0.0167	Rauni korau -0.0444
Answer 2	-	Rauni korau -0.0435	Rauni korau -0.0554	Rauni korau -0.1053	Rauni kyau 0.0937	Rauni kyau 0.0049	Rauni kyau 0.0536	Rauni kyau 0.0151
Answer 6	-	Rauni korau -0.0509	Rauni kyau 0.1070	Rauni korau -0.0386	Rauni korau -0.0397	Rauni kyau 0.0022	Rauni kyau 0.0126	Rauni kyau 0.0224
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7	-	Rauni kyau 0.0236	Rauni kyau 0.0396	Rauni kyau 0.0723	Rauni kyau 0.0688	Rauni korau -0.0290	Rauni korau -0.0910	Rauni korau -0.0671
Answer 8	-	Rauni kyau 0.0314	Rauni korau -0.0439	Rauni korau -0.0372	Rauni kyau 0.0109	Rauni kyau 0.0894	Rauni korau -0.0354	Rauni korau -0.0199
Answer 9	-	Rauni kyau 0.0449	Rauni korau -0.0301	Rauni korau -0.0304	Rauni korau -0.0111	Rauni korau -0.0279	Rauni kyau 0.0391	Rauni kyau 0.0218
Answer 10	-	Rauni kyau 0.0152	Rauni korau -0.0074	Rauni kyau 0.0081	Rauni korau -0.0440	Rauni kyau 0.0039	Rauni korau -0.0051	Rauni kyau 0.0334
Answer 11	-	Rauni korau -0.0524	Rauni kyau 0.0334	Rauni kyau 0.0347	Rauni kyau 0.0537	Rauni korau -0.0655	Rauni kyau 0.0322	Rauni korau -0.0480
Answer 8	-	Rauni korau -0.1113	Rauni korau -0.0423	Rauni korau -0.0035	Rauni kyau 0.0030	Rauni kyau 0.0101	Rauni kyau 0.0817	Rauni kyau 0.0204
Answer 12	-	Rauni korau -0.0015	Rauni kyau 0.0730	Rauni korau -0.0472	Rauni korau -0.1012	Rauni korau -0.0108	Rauni kyau 0.0289	Rauni kyau 0.0804

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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