Hasiera/Bloga/AI Assistants Boost Beginners More Than Experts, Study Shows Correlation

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.

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ChartsKorrelazioa

VUCA

Korrelazio Mota	Lineala (Pearson) Lineala (Pearson) Ez-lineala (Spearman)
Korrelazio koefizientea balioa kritikoa	Banaketa normala, William Seally Gosset-en (Ikaslea) Banaketa normala, William Seally Gosset-en (Ikaslea) Banaketa normala ez da, Spearman-ek eginda	Erakutsi emaitzak soilik > r = 0.0671

Banaketa	Normala ez	Ohiko	Normala ez	Ohiko	Ohiko	Ohiko	Ohiko	Ohiko
Galdera guztiak Galdera guztiak 1) Segurtasuna (zenbat ados edo ados zaude?) 2) Kontrola (zenbat ados edo ados zaude?)
1) Segurtasuna (zenbat ados edo ados zaude?)
Answer 1	-	Positibo ahula 0.0771	Positibo ahula 0.0276	Positibo ahula 0.0839	Negatiboa ahula -0.1222	Negatiboa ahula -0.0128	Negatiboa ahula -0.0428	Positibo ahula 0.0245
Answer 2	-	Positibo ahula 0.0215	Negatiboa ahula -0.0262	Positibo ahula 0.0704	Negatiboa ahula -0.0404	Positibo ahula 0.0280	Negatiboa ahula -0.0018	Negatiboa ahula -0.0420
Answer 3	-	Negatiboa ahula -0.0320	Negatiboa ahula -0.0060	Negatiboa ahula -0.0094	Positibo ahula 0.0601	Negatiboa ahula -0.0079	Negatiboa ahula -0.0262	Positibo ahula 0.0050
Answer 4	-	Positibo ahula 0.0273	Negatiboa ahula -0.0227	Positibo ahula 0.0161	Negatiboa ahula -0.0538	Negatiboa ahula -0.0264	Positibo ahula 0.0036	Positibo ahula 0.0569
Answer 5	-	Negatiboa ahula -0.0043	Negatiboa ahula -0.0101	Negatiboa ahula -0.0377	Positibo ahula 0.0377	Positibo ahula 0.0312	Positibo ahula 0.0169	Negatiboa ahula -0.0339
Answer 2	-	Negatiboa ahula -0.0057	Negatiboa ahula -0.0599	Negatiboa ahula -0.0707	Positibo ahula 0.0711	Negatiboa ahula -0.0165	Positibo ahula 0.0670	Negatiboa ahula -0.0047
Answer 6	-	Negatiboa ahula -0.0717	Positibo ahula 0.1053	Negatiboa ahula -0.0619	Positibo ahula 0.0368	Positibo ahula 0.0047	Negatiboa ahula -0.0143	Negatiboa ahula -0.0018
2) Kontrola (zenbat ados edo ados zaude?)
Answer 7	-	Positibo ahula 0.0189	Negatiboa ahula -0.0068	Positibo ahula 0.0836	Positibo ahula 0.0573	Negatiboa ahula -0.0349	Negatiboa ahula -0.0836	Negatiboa ahula -0.0320
Answer 8	-	Positibo ahula 0.0239	Negatiboa ahula -0.0186	Negatiboa ahula -0.0265	Positibo ahula 0.0116	Positibo ahula 0.0676	Positibo ahula 0.0068	Negatiboa ahula -0.0589
Answer 9	-	Positibo ahula 0.0030	Negatiboa ahula -0.0301	Negatiboa ahula -0.0699	Negatiboa ahula -0.0067	Positibo ahula 0.0087	Positibo ahula 0.0575	Positibo ahula 0.0277
Answer 10	-	Positibo ahula 0.0105	Negatiboa ahula -0.0051	Positibo ahula 0.0296	Negatiboa ahula -0.0648	Negatiboa ahula -0.0179	Negatiboa ahula -0.0080	Positibo ahula 0.0570
Answer 11	-	Negatiboa ahula -0.0047	Positibo ahula 0.0278	Positibo ahula 0.0563	Positibo ahula 0.0317	Negatiboa ahula -0.0421	Negatiboa ahula -0.0152	Negatiboa ahula -0.0393
Answer 8	-	Negatiboa ahula -0.0772	Negatiboa ahula -0.0316	Negatiboa ahula -0.0310	Positibo ahula 0.0136	Positibo ahula 0.0169	Positibo ahula 0.0793	Negatiboa ahula -0.0005
Answer 12	-	Negatiboa ahula -0.0017	Positibo ahula 0.0933	Negatiboa ahula -0.0357	Negatiboa ahula -0.0593	Negatiboa ahula -0.0257	Negatiboa ahula -0.0220	Positibo ahula 0.0680

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

2023.11.27

FearpersonqualitiesprojectorganizationalstructureRACIresponsibilitymatrixCritical ChainProject Managementfocus factorJiraempathyleadersbossGermanyChinaPolicyUkraineRussiawarvolatilityuncertaintycomplexityambiguityVUCArelocatejobproblemcountryreasongive upobjectivekeyresultmathematicalpsychologyMBTIHR metricsstandardDEIcorrelationriskscoringmodelGame TheoryPrisoner's Dilemma

Valerii Kosenko

SaaS SDTEST® produktuaren jabea

Valerii 1993an gizarte pedagogo-psikologo titulua lortu zuen eta ordutik proiektuen kudeaketan aplikatu ditu bere ezagutzak.
Valerii-k masterra eta proiektu eta programa kudeatzaile titulua lortu zituen 2013an. Masterreko programan zehar, Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) eta Spiral Dynamics ezagutu zituen.
Valerii V.U.C.A.ren ziurgabetasuna aztertzeko egilea da. kontzeptua Spiral Dynamics eta matematika-estatistika erabiliz psikologian, eta nazioarteko 38 inkesta.

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