home/Blog/AI Assistants Boost Beginners More Than Experts, Study Shows Correlation

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.

Intelliġenza artifiċjali u t-tmiem taċ-ċiviltà

mapep nawtiċi Korrelazzjoni

VUCA

Hemm korrelazzjoni statistikament sinifikanti

Distribuzzjoni Normali, minn William Sealy Gosset (student) r = 7.63

Distribuzzjoni mhux normali, minn Spearman r = 0.31

Juru biss ir-riżultati > r = 7.63

Mistoqsijiet dwar l-istħarriġ

Il-mistoqsijiet kollha

1) Sigurtà (kemm taqbel jew ma taqbilx?)

2) Kontroll (Kemm taqbel jew ma taqbilx?)

Distribuzzjoni

Korrelazzjoni pożittiva,%

Korrelazzjoni negattiva,%

Normali

0.8 Answer 1 1.7 Answer 2 5 Answer 3 1.5 Answer 4 2.4 Answer 5 #1	-6.2 Answer 10 -5.6 Answer 11 #1
1.8 Answer 6 4.3 Answer 7 2.6 Answer 8 8.2 Answer 9 #2	-5.5 Answer 12 -4.7 Answer 13 -4.1 Answer 14 #2

Normali

0.2 Answer 10 3 Answer 11 5.2 Answer 4 #1	-5.5 Answer 1 -0.8 Answer 2 -1.3 Answer 3 -0.8 Answer 5 #1
5 Answer 6 0.3 Answer 14 8 Answer 8 0.4 Answer 9 #2	-7.5 Answer 12 -1.6 Answer 13 -1.7 Answer 7 #2

Normali

4.5 Answer 10 0.1 Answer 5 #1	-0.8 Answer 1 -1.1 Answer 2 -3.2 Answer 3 -0.3 Answer 11 -0.1 Answer 4 #1
8.6 Answer 13 1.4 Answer 8 #2	-1.8 Answer 12 -1.4 Answer 6 -1.3 Answer 7 -7.4 Answer 14 -2.2 Answer 9 #2

Normali

4.9 Answer 2 4.8 Answer 11 8 Answer 4 #1	-9.7 Answer 1 -3.1 Answer 10 -4.2 Answer 3 -1 Answer 5 #1
5.8 Answer 12 3.1 Answer 13 3.5 Answer 14 0.3 Answer 8 #2	-0.1 Answer 6 -6.3 Answer 7 -8.5 Answer 9 #2

Normali

10.9 Answer 1 4 Answer 10 1.8 Answer 3 #1	-0.6 Answer 2 -1.9 Answer 11 -8.2 Answer 4 -5.4 Answer 5 #1
5.8 Answer 12 1.6 Answer 7 6.3 Answer 14 #2	-3.9 Answer 13 -4.2 Answer 6 -1 Answer 8 -3 Answer 9 #2

Mhux
normali

0.8 Answer 3 11.4 Answer 5 #1	-0.1 Answer 1 -0.2 Answer 10 -5.2 Answer 2 -1 Answer 11 -5.6 Answer 4 #1
1.7 Answer 12 1.2 Answer 7 3.5 Answer 14 6.4 Answer 9 #2	-2.9 Answer 13 -3.3 Answer 6 -4.5 Answer 8 #2

Normali

7.8 Answer 1 2.9 Answer 10 2.1 Answer 3 #1	-1.4 Answer 2 -0.4 Answer 11 -4.1 Answer 4 -6 Answer 5 #1
2.8 Answer 12 1 Answer 13 1.9 Answer 6 3.6 Answer 7 0.4 Answer 9 #2	-2.1 Answer 14 -11.1 Answer 8 #2

Esportazzjoni lejn MS Excel

Din il-funzjonalità se tkun disponibbli fl-istħarriġ tal-VUCA tiegħek

Kollox sew

[1] https://www.ft.com/content/b2928076-5c52-43e9-8872-08fda2aa2fcf

2023.11.27

Valerii Kosenko

Sid tal-Prodott SaaS Pet Project SDTest®

Valerii kien ikkwalifikat bħala pedagoga soċjali-psikologu fl-1993 u minn dakinhar applika l-għarfien tiegħu fil-ġestjoni tal-proġett.
Valerii kiseb il-grad ta 'master u l-kwalifika tal-Proġett u l-Maniġer tal-Programm fl-2013. Matul il-programm tal-kaptan tiegħu, sar familjari mal-pjan direzzjonali tal-proġett (GPM Deutsche Gesellschaft Für Projektmanagement e. V.) u Spiral Dynamics.
Valerii ħa diversi testijiet ta 'dinamika spirali u uża l-għarfien u l-esperjenza tiegħu biex jadatta l-verżjoni attwali ta' SDTest.
Valerii huwa l-awtur tal-esplorazzjoni tal-inċertezza tal-V.U.C.A. Kunċett bl-użu ta 'dinamika spirali u statistika matematika fil-psikoloġija, aktar minn 20 stħarriġ internazzjonali.

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