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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 = 0.0874

Dosbarthiad nad yw'n arferol, gan Spearman r = 0.0039

Dangos canlyniadau yn unig > r = 0.0874

Nosbarthiadau	Nad yw'n normal	Normal	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 0.0647	Negyddol gwan -0.0402	Gadarnhaol gwan 0.1238	Negyddol gwan -0.1305	Gadarnhaol gwan 0.0097	Negyddol gwan -0.0535	Gadarnhaol gwan 0.0344
Answer 2	-	Gadarnhaol gwan 0.0497	Gadarnhaol gwan 0.0373	Gadarnhaol gwan 0.0295	Negyddol gwan -0.0054	Negyddol gwan -0.0046	Negyddol gwan -0.0176	Negyddol gwan -0.0596
Answer 3	-	Negyddol gwan -0.0307	Negyddol gwan -0.0330	Gadarnhaol gwan 0.0063	Gadarnhaol gwan 0.0822	Negyddol gwan -0.0127	Negyddol gwan -0.0159	Negyddol gwan -0.0149
Answer 4	-	Negyddol gwan -0.0069	Gadarnhaol gwan 0.0432	Gadarnhaol gwan 0.0293	Negyddol gwan -0.0238	Negyddol gwan -0.0470	Negyddol gwan -0.0193	Gadarnhaol gwan 0.0315
Answer 5	-	Gadarnhaol gwan 0.0069	Negyddol gwan -0.0237	Negyddol gwan -0.0152	Gadarnhaol gwan 0.0131	Negyddol gwan -0.0018	Gadarnhaol gwan 0.0608	Negyddol gwan -0.0308
Answer 6	-	Negyddol gwan -0.0388	Negyddol gwan -0.0576	Negyddol gwan -0.1067	Gadarnhaol gwan 0.0816	Gadarnhaol gwan 0.0191	Gadarnhaol gwan 0.0491	Gadarnhaol gwan 0.0162
Answer 7	-	Negyddol gwan -0.0360	Gadarnhaol gwan 0.0619	Negyddol gwan -0.0510	Negyddol gwan -0.0486	Gadarnhaol gwan 0.0403	Gadarnhaol gwan 0.0061	Gadarnhaol gwan 0.0322
2) Rheoli (faint ydych chi'n cytuno neu'n anghytuno?)
Answer 8	-	Gadarnhaol gwan 0.0254	Gadarnhaol gwan 0.0424	Gadarnhaol gwan 0.1084	Gadarnhaol gwan 0.0601	Negyddol gwan -0.0356	Negyddol gwan -0.1149	Negyddol gwan -0.0695
Answer 9	-	Gadarnhaol gwan 0.0118	Negyddol gwan -0.0446	Negyddol gwan -0.0559	Gadarnhaol gwan 0.0325	Gadarnhaol gwan 0.0961	Negyddol gwan -0.0228	Negyddol gwan -0.0252
Answer 10	-	Gadarnhaol gwan 0.0535	Negyddol gwan -0.0376	Negyddol gwan -0.0089	Negyddol gwan -0.0281	Negyddol gwan -0.0308	Gadarnhaol gwan 0.0262	Gadarnhaol gwan 0.0309
Answer 11	-	Gadarnhaol gwan 0.0157	Gadarnhaol gwan 0.0103	Negyddol gwan -0.0089	Negyddol gwan -0.0482	Gadarnhaol gwan 0.0039	Gadarnhaol gwan 0.0010	Gadarnhaol gwan 0.0318
Answer 12	-	Negyddol gwan -0.0377	Gadarnhaol gwan 0.0444	Gadarnhaol gwan 0.0304	Gadarnhaol gwan 0.0435	Negyddol gwan -0.0755	Gadarnhaol gwan 0.0475	Negyddol gwan -0.0432
Answer 13	-	Negyddol gwan -0.1232	Negyddol gwan -0.0353	Negyddol gwan -0.0230	Gadarnhaol gwan 0.0330	Negyddol gwan -0.0105	Gadarnhaol gwan 0.0883	Gadarnhaol gwan 0.0191
Answer 14	-	Gadarnhaol gwan 0.0124	Gadarnhaol gwan 0.0425	Negyddol gwan -0.0572	Negyddol gwan -0.1125	Gadarnhaol gwan 0.0256	Gadarnhaol gwan 0.0326	Gadarnhaol gwan 0.0763

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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