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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

siartiau Cydberthyniad

VUCA

Gwerth feirniadol o'r cyfernod cydberthyniad

Dosbarthiad Arferol, gan William Sealy Gosset (Myfyriwr) r = 0.0763

Dosbarthiad nad yw'n arferol, gan Spearman r = 0.0031

Dangos canlyniadau yn unig > r = 0.0763

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 0.0780	Negyddol gwan -0.0013	Gadarnhaol gwan 0.1092	Negyddol gwan -0.0965	Negyddol gwan -0.0082	Negyddol gwan -0.0554	Gadarnhaol gwan 0.0083
Answer 2	-	Gadarnhaol gwan 0.0290	Negyddol gwan -0.0016	Gadarnhaol gwan 0.0401	Negyddol gwan -0.0312	Gadarnhaol gwan 0.0451	Gadarnhaol gwan 0.0015	Negyddol gwan -0.0620
Answer 3	-	Negyddol gwan -0.0142	Negyddol gwan -0.0519	Negyddol gwan -0.0059	Gadarnhaol gwan 0.0485	Negyddol gwan -0.0108	Negyddol gwan -0.0076	Gadarnhaol gwan 0.0174
Answer 4	-	Gadarnhaol gwan 0.0204	Gadarnhaol gwan 0.0084	Gadarnhaol gwan 0.0182	Negyddol gwan -0.0414	Negyddol gwan -0.0314	Negyddol gwan -0.0132	Gadarnhaol gwan 0.0495
Answer 5	-	Negyddol gwan -0.0036	Negyddol gwan -0.0097	Negyddol gwan -0.0185	Gadarnhaol gwan 0.0477	Negyddol gwan -0.0030	Gadarnhaol gwan 0.0301	Negyddol gwan -0.0557
Answer 6	-	Negyddol gwan -0.0414	Negyddol gwan -0.0556	Negyddol gwan -0.0823	Gadarnhaol gwan 0.0795	Negyddol gwan -0.0012	Gadarnhaol gwan 0.0520	Gadarnhaol gwan 0.0146
Answer 7	-	Negyddol gwan -0.0600	Gadarnhaol gwan 0.1144	Negyddol gwan -0.0542	Negyddol gwan -0.0096	Gadarnhaol gwan 0.0012	Negyddol gwan -0.0080	Gadarnhaol gwan 0.0241
2) Rheoli (faint ydych chi'n cytuno neu'n anghytuno?)
Answer 8	-	Gadarnhaol gwan 0.0283	Gadarnhaol gwan 0.0174	Gadarnhaol gwan 0.0583	Gadarnhaol gwan 0.0581	Negyddol gwan -0.0182	Negyddol gwan -0.0745	Negyddol gwan -0.0550
Answer 9	-	Gadarnhaol gwan 0.0097	Negyddol gwan -0.0287	Negyddol gwan -0.0387	Gadarnhaol gwan 0.0305	Gadarnhaol gwan 0.0863	Negyddol gwan -0.0161	Negyddol gwan -0.0470
Answer 10	-	Gadarnhaol gwan 0.0190	Negyddol gwan -0.0334	Negyddol gwan -0.0417	Negyddol gwan -0.0013	Negyddol gwan -0.0142	Gadarnhaol gwan 0.0502	Gadarnhaol gwan 0.0176
Answer 11	-	Gadarnhaol gwan 0.0358	Gadarnhaol gwan 0.0118	Gadarnhaol gwan 0.0160	Negyddol gwan -0.0628	Negyddol gwan -0.0127	Negyddol gwan -0.0174	Gadarnhaol gwan 0.0434
Answer 12	-	Negyddol gwan -0.0211	Gadarnhaol gwan 0.0354	Gadarnhaol gwan 0.0631	Gadarnhaol gwan 0.0352	Negyddol gwan -0.0736	Gadarnhaol gwan 0.0029	Negyddol gwan -0.0414
Answer 13	-	Negyddol gwan -0.1112	Negyddol gwan -0.0452	Negyddol gwan -0.0103	Gadarnhaol gwan 0.0029	Gadarnhaol gwan 0.0144	Gadarnhaol gwan 0.0795	Gadarnhaol gwan 0.0259
Answer 14	-	Gadarnhaol gwan 0.0038	Gadarnhaol gwan 0.0641	Negyddol gwan -0.0297	Negyddol gwan -0.0850	Negyddol gwan -0.0222	Gadarnhaol gwan 0.0037	Gadarnhaol gwan 0.0820

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

Valerii Kosenko

Perchennog y Cynnyrch Saas Pet Project Sdtest®

Roedd Valerii yn gymwys fel addysgegydd cymdeithasol-seicolegydd ym 1993 ac ers hynny mae wedi cymhwyso ei wybodaeth mewn rheoli prosiect.
Cafodd Valerii radd meistr a chymhwyster y prosiect a rheolwr rhaglen yn 2013. Yn ystod rhaglen ei feistr, daeth yn gyfarwydd â Map Ffordd Project (GPM Deutsche Gesellschaft für Projektmanagement e. V.) a Spiral Dynamics.
Cipiodd Valerii amryw o brofion dynameg troellog a defnyddio ei wybodaeth a'i brofiad i addasu'r fersiwn gyfredol o SDTest.
Valerii yw awdur archwilio ansicrwydd y V.U.C.A. Cysyniad gan ddefnyddio dynameg troellog ac ystadegau mathemategol mewn seicoleg, mwy nag 20 o bolau rhyngwladol.

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