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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.

Ka naʻauao a me ka hopena o ke kīwī

nńnńMea hoʻopili

VUCA

Pilikia waiwai o ka mea hoʻopili kaʻi lau waiwai

ʻO ka hoʻokaʻawale maʻamau, e William Sealy Gosset (haumāna) r = 0.0718

ʻO ka māhele maʻamauʻole, e ka'ōlelo r = 0.0029

Hōʻike i nā hopena wale nō > r = 0.0718

Ka Hoʻohanohano	Non maʻamau	Maʻamau	Non maʻamau	Maʻamau	Maʻamau	Maʻamau	Maʻamau	Maʻamau
Nā nīnau āpau Nā nīnau āpau 1) Palekana (pehea kāu eʻae ai aʻaeʻole paha?) 2) E kāohi (pehea kāu eʻae ai aʻaeʻole paha?)
1) Palekana (pehea kāu eʻae ai aʻaeʻole paha?)
Answer 1	-	Nawaliwali maikaʻi 0.0708	Nawaliwali maikaʻi 0.0197	Nawaliwali maikaʻi 0.0942	Nawaliwali hopena maikaʻi -0.1158	Nawaliwali maikaʻi 0.0007	Nawaliwali hopena maikaʻi -0.0461	Nawaliwali maikaʻi 0.0163
Answer 2	-	Nawaliwali maikaʻi 0.0170	Nawaliwali hopena maikaʻi -0.0075	Nawaliwali maikaʻi 0.0441	Nawaliwali hopena maikaʻi -0.0223	Nawaliwali maikaʻi 0.0348	Nawaliwali maikaʻi 0.0017	Nawaliwali hopena maikaʻi -0.0533
Answer 3	-	Nawaliwali hopena maikaʻi -0.0306	Nawaliwali hopena maikaʻi -0.0288	Nawaliwali maikaʻi 0.0092	Nawaliwali maikaʻi 0.0596	Nawaliwali hopena maikaʻi -0.0264	Nawaliwali hopena maikaʻi -0.0113	Nawaliwali maikaʻi 0.0030
Answer 4	-	Nawaliwali maikaʻi 0.0348	Nawaliwali hopena maikaʻi -0.0106	Nawaliwali maikaʻi 0.0164	Nawaliwali hopena maikaʻi -0.0570	Nawaliwali hopena maikaʻi -0.0332	Nawaliwali maikaʻi 0.0046	Nawaliwali maikaʻi 0.0562
Answer 5	-	Nawaliwali hopena maikaʻi -0.0137	Nawaliwali hopena maikaʻi -0.0241	Nawaliwali hopena maikaʻi -0.0239	Nawaliwali maikaʻi 0.0438	Nawaliwali maikaʻi 0.0320	Nawaliwali maikaʻi 0.0227	Nawaliwali hopena maikaʻi -0.0554
Answer 6	-	Nawaliwali hopena maikaʻi -0.0138	Nawaliwali hopena maikaʻi -0.0526	Nawaliwali hopena maikaʻi -0.0740	Nawaliwali maikaʻi 0.0650	Nawaliwali hopena maikaʻi -0.0071	Nawaliwali maikaʻi 0.0438	Nawaliwali maikaʻi 0.0148
Answer 7	-	Nawaliwali hopena maikaʻi -0.0554	Nawaliwali maikaʻi 0.1068	Nawaliwali hopena maikaʻi -0.0652	Nawaliwali maikaʻi 0.0149	Nawaliwali maikaʻi 0.0042	Nawaliwali hopena maikaʻi -0.0171	Nawaliwali maikaʻi 0.0168
2) E kāohi (pehea kāu eʻae ai aʻaeʻole paha?)
Answer 8	-	Nawaliwali maikaʻi 0.0123	Nawaliwali maikaʻi 0.0023	Nawaliwali maikaʻi 0.0772	Nawaliwali maikaʻi 0.0566	Nawaliwali hopena maikaʻi -0.0241	Nawaliwali hopena maikaʻi -0.0754	Nawaliwali hopena maikaʻi -0.0436
Answer 9	-	Nawaliwali maikaʻi 0.0168	Nawaliwali hopena maikaʻi -0.0315	Nawaliwali hopena maikaʻi -0.0355	Nawaliwali maikaʻi 0.0207	Nawaliwali maikaʻi 0.0870	Nawaliwali hopena maikaʻi -0.0030	Nawaliwali hopena maikaʻi -0.0551
Answer 10	-	Nawaliwali maikaʻi 0.0171	Nawaliwali hopena maikaʻi -0.0270	Nawaliwali hopena maikaʻi -0.0694	Nawaliwali hopena maikaʻi -0.0079	Nawaliwali hopena maikaʻi -0.0035	Nawaliwali maikaʻi 0.0573	Nawaliwali maikaʻi 0.0309
Answer 11	-	Nawaliwali maikaʻi 0.0181	Nawaliwali maikaʻi 0.0007	Nawaliwali maikaʻi 0.0309	Nawaliwali hopena maikaʻi -0.0588	Nawaliwali hopena maikaʻi -0.0310	Nawaliwali hopena maikaʻi -0.0125	Nawaliwali maikaʻi 0.0558
Answer 12	-	Nawaliwali hopena maikaʻi -0.0034	Nawaliwali maikaʻi 0.0263	Nawaliwali maikaʻi 0.0655	Nawaliwali maikaʻi 0.0322	Nawaliwali hopena maikaʻi -0.0684	Nawaliwali hopena maikaʻi -0.0152	Nawaliwali hopena maikaʻi -0.0352
Answer 13	-	Nawaliwali hopena maikaʻi -0.0909	Nawaliwali hopena maikaʻi -0.0336	Nawaliwali hopena maikaʻi -0.0184	Nawaliwali maikaʻi 0.0087	Nawaliwali maikaʻi 0.0272	Nawaliwali maikaʻi 0.0750	Nawaliwali hopena maikaʻi -0.0014
Answer 14	-	Nawaliwali maikaʻi 0.0041	Nawaliwali maikaʻi 0.0892	Nawaliwali hopena maikaʻi -0.0341	Nawaliwali hopena maikaʻi -0.0676	Nawaliwali hopena maikaʻi -0.0262	Nawaliwali hopena maikaʻi -0.0098	Nawaliwali maikaʻi 0.0683

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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

Mea nona ka huahana SaaS SDTEST®

Ua kūpono ʻo Valerii ma ke ʻano he kanaka aʻoaʻo-psychologist ma 1993 a ua hoʻohana ʻo ia i kona ʻike i ka hoʻokele papahana.
Ua loaʻa iā Valerii ke kēkelē laeoʻo a me ka hōʻailona papahana a me ka manakia papahana ma 2013. I ka wā o kāna papahana Master, ua kamaʻāina ʻo ia me Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) a me Spiral Dynamics.
ʻO Valerii ka mea kākau o ka ʻimi ʻana i ka maopopo ʻole o ka V.U.C.A. manaʻo e hoʻohana ana i ka Spiral Dynamics a me ka helu makemakika i loko o ka psychology, a me 38 mau koho balota.

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