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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 = 0.0828

Dosbarthiad nad yw'n arferol, gan Spearman r = 0.0035

Dangos canlyniadau yn unig > r = 0.0828

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 0.0762	Negyddol gwan -0.0046	Gadarnhaol gwan 0.1086	Negyddol gwan -0.1228	Gadarnhaol gwan 0.0184	Negyddol gwan -0.0551	Gadarnhaol gwan 0.0148
Answer 2	-	Gadarnhaol gwan 0.0302	Gadarnhaol gwan 0.0072	Gadarnhaol gwan 0.0367	Negyddol gwan -0.0046	Gadarnhaol gwan 0.0238	Negyddol gwan -0.0124	Negyddol gwan -0.0587
Answer 3	-	Negyddol gwan -0.0182	Negyddol gwan -0.0500	Negyddol gwan -0.0009	Gadarnhaol gwan 0.0531	Negyddol gwan -0.0099	Gadarnhaol gwan 0.0009	Negyddol gwan -0.0011
Answer 4	-	Gadarnhaol gwan 0.0057	Gadarnhaol gwan 0.0166	Gadarnhaol gwan 0.0297	Negyddol gwan -0.0251	Negyddol gwan -0.0543	Negyddol gwan -0.0202	Gadarnhaol gwan 0.0538
Answer 5	-	Gadarnhaol gwan 0.0128	Negyddol gwan -0.0180	Negyddol gwan -0.0228	Gadarnhaol gwan 0.0229	Gadarnhaol gwan 0.0196	Gadarnhaol gwan 0.0167	Negyddol gwan -0.0444
Answer 6	-	Negyddol gwan -0.0435	Negyddol gwan -0.0554	Negyddol gwan -0.1053	Gadarnhaol gwan 0.0937	Gadarnhaol gwan 0.0049	Gadarnhaol gwan 0.0536	Gadarnhaol gwan 0.0151
Answer 7	-	Negyddol gwan -0.0509	Gadarnhaol gwan 0.1070	Negyddol gwan -0.0386	Negyddol gwan -0.0397	Gadarnhaol gwan 0.0022	Gadarnhaol gwan 0.0126	Gadarnhaol gwan 0.0224
2) Rheoli (faint ydych chi'n cytuno neu'n anghytuno?)
Answer 8	-	Gadarnhaol gwan 0.0236	Gadarnhaol gwan 0.0396	Gadarnhaol gwan 0.0723	Gadarnhaol gwan 0.0688	Negyddol gwan -0.0290	Negyddol gwan -0.0910	Negyddol gwan -0.0671
Answer 9	-	Gadarnhaol gwan 0.0314	Negyddol gwan -0.0439	Negyddol gwan -0.0372	Gadarnhaol gwan 0.0109	Gadarnhaol gwan 0.0894	Negyddol gwan -0.0354	Negyddol gwan -0.0199
Answer 10	-	Gadarnhaol gwan 0.0449	Negyddol gwan -0.0301	Negyddol gwan -0.0304	Negyddol gwan -0.0111	Negyddol gwan -0.0279	Gadarnhaol gwan 0.0391	Gadarnhaol gwan 0.0218
Answer 11	-	Gadarnhaol gwan 0.0152	Negyddol gwan -0.0074	Gadarnhaol gwan 0.0081	Negyddol gwan -0.0440	Gadarnhaol gwan 0.0039	Negyddol gwan -0.0051	Gadarnhaol gwan 0.0334
Answer 12	-	Negyddol gwan -0.0524	Gadarnhaol gwan 0.0334	Gadarnhaol gwan 0.0347	Gadarnhaol gwan 0.0537	Negyddol gwan -0.0655	Gadarnhaol gwan 0.0322	Negyddol gwan -0.0480
Answer 13	-	Negyddol gwan -0.1113	Negyddol gwan -0.0423	Negyddol gwan -0.0035	Gadarnhaol gwan 0.0030	Gadarnhaol gwan 0.0101	Gadarnhaol gwan 0.0817	Gadarnhaol gwan 0.0204
Answer 14	-	Negyddol gwan -0.0015	Gadarnhaol gwan 0.0730	Negyddol gwan -0.0472	Negyddol gwan -0.1012	Negyddol gwan -0.0108	Gadarnhaol gwan 0.0289	Gadarnhaol gwan 0.0804

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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