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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.

Deallusrwydd artiffisial a diwedd gwareiddiad

siartiauCydberthyniad

VUCA

Math Cydberthynas	llinellol (Pearson) llinellol (Pearson) Aflinol (Spearman)
Gwerth feirniadol o'r cyfernod cydberthyniad	Dosbarthiad Arferol, gan William Sealy Gosset (Myfyriwr) Dosbarthiad Arferol, gan William Sealy Gosset (Myfyriwr) Dosbarthiad nad yw'n arferol, gan Spearman	Dangos canlyniadau yn unig > r = 0.0671

Nosbarthiadau	Nad yw'n normal	Normal	Nad yw'n normal	Normal	Normal	Normal	Normal	Normal
Pob cwestiwn Pob cwestiwn 1) Diogelwch (faint ydych chi'n cytuno neu'n anghytuno?) 2) Rheoli (faint ydych chi'n cytuno neu'n anghytuno?)
1) Diogelwch (faint ydych chi'n cytuno neu'n anghytuno?)
Answer 1	-	Gadarnhaol gwan 0.0771	Gadarnhaol gwan 0.0276	Gadarnhaol gwan 0.0839	Negyddol gwan -0.1222	Negyddol gwan -0.0128	Negyddol gwan -0.0428	Gadarnhaol gwan 0.0245
Answer 2	-	Gadarnhaol gwan 0.0215	Negyddol gwan -0.0262	Gadarnhaol gwan 0.0704	Negyddol gwan -0.0404	Gadarnhaol gwan 0.0280	Negyddol gwan -0.0018	Negyddol gwan -0.0420
Answer 3	-	Negyddol gwan -0.0320	Negyddol gwan -0.0060	Negyddol gwan -0.0094	Gadarnhaol gwan 0.0601	Negyddol gwan -0.0079	Negyddol gwan -0.0262	Gadarnhaol gwan 0.0050
Answer 4	-	Gadarnhaol gwan 0.0273	Negyddol gwan -0.0227	Gadarnhaol gwan 0.0161	Negyddol gwan -0.0538	Negyddol gwan -0.0264	Gadarnhaol gwan 0.0036	Gadarnhaol gwan 0.0569
Answer 5	-	Negyddol gwan -0.0043	Negyddol gwan -0.0101	Negyddol gwan -0.0377	Gadarnhaol gwan 0.0377	Gadarnhaol gwan 0.0312	Gadarnhaol gwan 0.0169	Negyddol gwan -0.0339
Answer 6	-	Negyddol gwan -0.0057	Negyddol gwan -0.0599	Negyddol gwan -0.0707	Gadarnhaol gwan 0.0711	Negyddol gwan -0.0165	Gadarnhaol gwan 0.0670	Negyddol gwan -0.0047
Answer 7	-	Negyddol gwan -0.0717	Gadarnhaol gwan 0.1053	Negyddol gwan -0.0619	Gadarnhaol gwan 0.0368	Gadarnhaol gwan 0.0047	Negyddol gwan -0.0143	Negyddol gwan -0.0018
2) Rheoli (faint ydych chi'n cytuno neu'n anghytuno?)
Answer 8	-	Gadarnhaol gwan 0.0189	Negyddol gwan -0.0068	Gadarnhaol gwan 0.0836	Gadarnhaol gwan 0.0573	Negyddol gwan -0.0349	Negyddol gwan -0.0836	Negyddol gwan -0.0320
Answer 9	-	Gadarnhaol gwan 0.0239	Negyddol gwan -0.0186	Negyddol gwan -0.0265	Gadarnhaol gwan 0.0116	Gadarnhaol gwan 0.0676	Gadarnhaol gwan 0.0068	Negyddol gwan -0.0589
Answer 10	-	Gadarnhaol gwan 0.0030	Negyddol gwan -0.0301	Negyddol gwan -0.0699	Negyddol gwan -0.0067	Gadarnhaol gwan 0.0087	Gadarnhaol gwan 0.0575	Gadarnhaol gwan 0.0277
Answer 11	-	Gadarnhaol gwan 0.0105	Negyddol gwan -0.0051	Gadarnhaol gwan 0.0296	Negyddol gwan -0.0648	Negyddol gwan -0.0179	Negyddol gwan -0.0080	Gadarnhaol gwan 0.0570
Answer 12	-	Negyddol gwan -0.0047	Gadarnhaol gwan 0.0278	Gadarnhaol gwan 0.0563	Gadarnhaol gwan 0.0317	Negyddol gwan -0.0421	Negyddol gwan -0.0152	Negyddol gwan -0.0393
Answer 13	-	Negyddol gwan -0.0772	Negyddol gwan -0.0316	Negyddol gwan -0.0310	Gadarnhaol gwan 0.0136	Gadarnhaol gwan 0.0169	Gadarnhaol gwan 0.0793	Negyddol gwan -0.0005
Answer 14	-	Negyddol gwan -0.0017	Gadarnhaol gwan 0.0933	Negyddol gwan -0.0357	Negyddol gwan -0.0593	Negyddol gwan -0.0257	Negyddol gwan -0.0220	Gadarnhaol gwan 0.0680

Allforio i MS Excel

Bydd y swyddogaeth hon ar gael yn eich polau VUCA eich hun

Iawn

[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

Perchennog Cynnyrch SaaS SDTEST®

Cymhwyswyd Valerii fel pedagog-seicolegydd cymdeithasol yn 1993 ac ers hynny mae wedi cymhwyso ei wybodaeth mewn rheoli prosiectau.
Enillodd Valerii radd Meistr a chymhwyster rheolwr prosiect a rhaglen yn 2013. Yn ystod ei raglen Meistr, daeth yn gyfarwydd â Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) a Spiral Dynamics.
Mae Valerii yn awdur ar archwilio ansicrwydd y V.U.C.A. cysyniad defnyddio Spiral Dynamics ac ystadegau mathemategol mewn seicoleg, a 38 polau rhyngwladol.

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