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.


Kunsmatige intelligensie en die einde van die beskawing

Land
Taal
-
Mail
Herbereken
Kritieke waarde van die korrelasiekoëffisiënt
Normale verspreiding, deur William Sealy Gosset (student) r = 0.0874
Normale verspreiding, deur William Sealy Gosset (student) r = 0.0874
Nie normale verspreiding, deur Spearman r = 0.0039
VerspreidingNie
normaal nie
NormaalNormaalNormaalNormaalNormaalNormaalNormaal
Alle vrae
Alle vrae
1) Veiligheid (hoeveel stem u saam of stem u nie saam nie?)
2) Beheer (hoeveel stem u saam of stem u nie saam nie?)
1) Veiligheid (hoeveel stem u saam of stem u nie saam nie?)
Answer 1-
Swak positief
0.0647
Swak negatief
-0.0402
Swak positief
0.1238
Swak negatief
-0.1305
Swak positief
0.0097
Swak negatief
-0.0535
Swak positief
0.0344
Answer 2-
Swak positief
0.0497
Swak positief
0.0373
Swak positief
0.0295
Swak negatief
-0.0054
Swak negatief
-0.0046
Swak negatief
-0.0176
Swak negatief
-0.0596
Answer 3-
Swak negatief
-0.0307
Swak negatief
-0.0330
Swak positief
0.0063
Swak positief
0.0822
Swak negatief
-0.0127
Swak negatief
-0.0159
Swak negatief
-0.0149
Answer 4-
Swak negatief
-0.0069
Swak positief
0.0432
Swak positief
0.0293
Swak negatief
-0.0238
Swak negatief
-0.0470
Swak negatief
-0.0193
Swak positief
0.0315
Answer 5-
Swak positief
0.0069
Swak negatief
-0.0237
Swak negatief
-0.0152
Swak positief
0.0131
Swak negatief
-0.0018
Swak positief
0.0608
Swak negatief
-0.0308
Answer 6-
Swak negatief
-0.0388
Swak negatief
-0.0576
Swak negatief
-0.1067
Swak positief
0.0816
Swak positief
0.0191
Swak positief
0.0491
Swak positief
0.0162
Answer 7-
Swak negatief
-0.0360
Swak positief
0.0619
Swak negatief
-0.0510
Swak negatief
-0.0486
Swak positief
0.0403
Swak positief
0.0061
Swak positief
0.0322
2) Beheer (hoeveel stem u saam of stem u nie saam nie?)
Answer 8-
Swak positief
0.0254
Swak positief
0.0424
Swak positief
0.1084
Swak positief
0.0601
Swak negatief
-0.0356
Swak negatief
-0.1149
Swak negatief
-0.0695
Answer 9-
Swak positief
0.0118
Swak negatief
-0.0446
Swak negatief
-0.0559
Swak positief
0.0325
Swak positief
0.0961
Swak negatief
-0.0228
Swak negatief
-0.0252
Answer 10-
Swak positief
0.0535
Swak negatief
-0.0376
Swak negatief
-0.0089
Swak negatief
-0.0281
Swak negatief
-0.0308
Swak positief
0.0262
Swak positief
0.0309
Answer 11-
Swak positief
0.0157
Swak positief
0.0103
Swak negatief
-0.0089
Swak negatief
-0.0482
Swak positief
0.0039
Swak positief
0.0010
Swak positief
0.0318
Answer 12-
Swak negatief
-0.0377
Swak positief
0.0444
Swak positief
0.0304
Swak positief
0.0435
Swak negatief
-0.0755
Swak positief
0.0475
Swak negatief
-0.0432
Answer 13-
Swak negatief
-0.1232
Swak negatief
-0.0353
Swak negatief
-0.0230
Swak positief
0.0330
Swak negatief
-0.0105
Swak positief
0.0883
Swak positief
0.0191
Answer 14-
Swak positief
0.0124
Swak positief
0.0425
Swak negatief
-0.0572
Swak negatief
-0.1125
Swak positief
0.0256
Swak positief
0.0326
Swak positief
0.0763


Uitvoer na MS Excel
Hierdie funksionaliteit sal beskikbaar wees in u eie VUCA-stembusse
Ok



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


2023.11.27
Valerii Kosenko
Produk -eienaar SaaS Pet Project SdTest®

Valerii is in 1993 as 'n maatskaplike pedagoge-sielkundige gekwalifiseer en het sedertdien sy kennis in projekbestuur toegepas.
Valerii het in 2013 'n meestersgraad en die kwalifikasie van die projek- en programbestuurder verwerf. Tydens sy meestersprogram het hy vertroud geraak met Project Roadmap (GPM Deutsche Gesellschaft Für Projektmanagement e. V.) en Spiral Dynamics.
Valerii het verskillende spiraaldinamika -toetse afgelê en sy kennis en ervaring gebruik om die huidige weergawe van SDTest aan te pas.
Valerii is die skrywer van die verkenning van die onsekerheid van die V.U.C.A. Konsep met behulp van spiraaldinamika en wiskundige statistieke in sielkunde, meer as 20 internasionale peilings.
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