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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 = 0.0874

Rarraba ba rarraba ba, da Spearman r = 0.0039

Nuna kawai sakamako > r = 0.0874

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 0.0647	Rauni korau -0.0402	Rauni kyau 0.1238	Rauni korau -0.1305	Rauni kyau 0.0097	Rauni korau -0.0535	Rauni kyau 0.0344
Answer 2	-	Rauni kyau 0.0497	Rauni kyau 0.0373	Rauni kyau 0.0295	Rauni korau -0.0054	Rauni korau -0.0046	Rauni korau -0.0176	Rauni korau -0.0596
Answer 3	-	Rauni korau -0.0307	Rauni korau -0.0330	Rauni kyau 0.0063	Rauni kyau 0.0822	Rauni korau -0.0127	Rauni korau -0.0159	Rauni korau -0.0149
Answer 4	-	Rauni korau -0.0069	Rauni kyau 0.0432	Rauni kyau 0.0293	Rauni korau -0.0238	Rauni korau -0.0470	Rauni korau -0.0193	Rauni kyau 0.0315
Answer 5	-	Rauni kyau 0.0069	Rauni korau -0.0237	Rauni korau -0.0152	Rauni kyau 0.0131	Rauni korau -0.0018	Rauni kyau 0.0608	Rauni korau -0.0308
Answer 2	-	Rauni korau -0.0388	Rauni korau -0.0576	Rauni korau -0.1067	Rauni kyau 0.0816	Rauni kyau 0.0191	Rauni kyau 0.0491	Rauni kyau 0.0162
Answer 6	-	Rauni korau -0.0360	Rauni kyau 0.0619	Rauni korau -0.0510	Rauni korau -0.0486	Rauni kyau 0.0403	Rauni kyau 0.0061	Rauni kyau 0.0322
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7	-	Rauni kyau 0.0254	Rauni kyau 0.0424	Rauni kyau 0.1084	Rauni kyau 0.0601	Rauni korau -0.0356	Rauni korau -0.1149	Rauni korau -0.0695
Answer 8	-	Rauni kyau 0.0118	Rauni korau -0.0446	Rauni korau -0.0559	Rauni kyau 0.0325	Rauni kyau 0.0961	Rauni korau -0.0228	Rauni korau -0.0252
Answer 9	-	Rauni kyau 0.0535	Rauni korau -0.0376	Rauni korau -0.0089	Rauni korau -0.0281	Rauni korau -0.0308	Rauni kyau 0.0262	Rauni kyau 0.0309
Answer 10	-	Rauni kyau 0.0157	Rauni kyau 0.0103	Rauni korau -0.0089	Rauni korau -0.0482	Rauni kyau 0.0039	Rauni kyau 0.0010	Rauni kyau 0.0318
Answer 11	-	Rauni korau -0.0377	Rauni kyau 0.0444	Rauni kyau 0.0304	Rauni kyau 0.0435	Rauni korau -0.0755	Rauni kyau 0.0475	Rauni korau -0.0432
Answer 8	-	Rauni korau -0.1232	Rauni korau -0.0353	Rauni korau -0.0230	Rauni kyau 0.0330	Rauni korau -0.0105	Rauni kyau 0.0883	Rauni kyau 0.0191
Answer 12	-	Rauni kyau 0.0124	Rauni kyau 0.0425	Rauni korau -0.0572	Rauni korau -0.1125	Rauni kyau 0.0256	Rauni kyau 0.0326	Rauni kyau 0.0763

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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