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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.

Ujuzi wa bandia na mwisho wa maendeleo

chati Uwiano

VUCA

Muhimu thamani ya mgawo uwiano

Usambazaji wa kawaida, na William Sealy Gosset (Mwanafunzi) r = 0.0874

Usambazaji usio wa kawaida, na Spearman r = 0.0039

Onyesha matokeo tu > r = 0.0874

Usambazaji	Sio kawaida	Kawaida	Kawaida	Kawaida	Kawaida	Kawaida	Kawaida	Kawaida
Maswali yote Maswali yote 1) Usalama (unakubali au haukubaliani?) 2) Udhibiti (unakubali au haukubaliani?)
1) Usalama (unakubali au haukubaliani?)
Answer 1	-	Chanya dhaifu 0.0647	Hasi dhaifu -0.0402	Chanya dhaifu 0.1238	Hasi dhaifu -0.1305	Chanya dhaifu 0.0097	Hasi dhaifu -0.0535	Chanya dhaifu 0.0344
Answer 2	-	Chanya dhaifu 0.0497	Chanya dhaifu 0.0373	Chanya dhaifu 0.0295	Hasi dhaifu -0.0054	Hasi dhaifu -0.0046	Hasi dhaifu -0.0176	Hasi dhaifu -0.0596
Answer 3	-	Hasi dhaifu -0.0307	Hasi dhaifu -0.0330	Chanya dhaifu 0.0063	Chanya dhaifu 0.0822	Hasi dhaifu -0.0127	Hasi dhaifu -0.0159	Hasi dhaifu -0.0149
Answer 4	-	Hasi dhaifu -0.0069	Chanya dhaifu 0.0432	Chanya dhaifu 0.0293	Hasi dhaifu -0.0238	Hasi dhaifu -0.0470	Hasi dhaifu -0.0193	Chanya dhaifu 0.0315
Answer 5	-	Chanya dhaifu 0.0069	Hasi dhaifu -0.0237	Hasi dhaifu -0.0152	Chanya dhaifu 0.0131	Hasi dhaifu -0.0018	Chanya dhaifu 0.0608	Hasi dhaifu -0.0308
Answer 6	-	Hasi dhaifu -0.0388	Hasi dhaifu -0.0576	Hasi dhaifu -0.1067	Chanya dhaifu 0.0816	Chanya dhaifu 0.0191	Chanya dhaifu 0.0491	Chanya dhaifu 0.0162
Answer 7	-	Hasi dhaifu -0.0360	Chanya dhaifu 0.0619	Hasi dhaifu -0.0510	Hasi dhaifu -0.0486	Chanya dhaifu 0.0403	Chanya dhaifu 0.0061	Chanya dhaifu 0.0322
2) Udhibiti (unakubali au haukubaliani?)
Answer 8	-	Chanya dhaifu 0.0254	Chanya dhaifu 0.0424	Chanya dhaifu 0.1084	Chanya dhaifu 0.0601	Hasi dhaifu -0.0356	Hasi dhaifu -0.1149	Hasi dhaifu -0.0695
Answer 9	-	Chanya dhaifu 0.0118	Hasi dhaifu -0.0446	Hasi dhaifu -0.0559	Chanya dhaifu 0.0325	Chanya dhaifu 0.0961	Hasi dhaifu -0.0228	Hasi dhaifu -0.0252
Answer 10	-	Chanya dhaifu 0.0535	Hasi dhaifu -0.0376	Hasi dhaifu -0.0089	Hasi dhaifu -0.0281	Hasi dhaifu -0.0308	Chanya dhaifu 0.0262	Chanya dhaifu 0.0309
Answer 11	-	Chanya dhaifu 0.0157	Chanya dhaifu 0.0103	Hasi dhaifu -0.0089	Hasi dhaifu -0.0482	Chanya dhaifu 0.0039	Chanya dhaifu 0.0010	Chanya dhaifu 0.0318
Answer 12	-	Hasi dhaifu -0.0377	Chanya dhaifu 0.0444	Chanya dhaifu 0.0304	Chanya dhaifu 0.0435	Hasi dhaifu -0.0755	Chanya dhaifu 0.0475	Hasi dhaifu -0.0432
Answer 13	-	Hasi dhaifu -0.1232	Hasi dhaifu -0.0353	Hasi dhaifu -0.0230	Chanya dhaifu 0.0330	Hasi dhaifu -0.0105	Chanya dhaifu 0.0883	Chanya dhaifu 0.0191
Answer 14	-	Chanya dhaifu 0.0124	Chanya dhaifu 0.0425	Hasi dhaifu -0.0572	Hasi dhaifu -0.1125	Chanya dhaifu 0.0256	Chanya dhaifu 0.0326	Chanya dhaifu 0.0763

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

2023.11.27

Valerii Kosenko

Mmiliki wa bidhaa SaaS PET SDTEST ®

Valerii alihitimu kama mtaalam wa kisaikolojia wa kijamii mnamo 1993 na tangu sasa ametumia maarifa yake katika usimamizi wa mradi.
Valerii alipata digrii ya bwana na sifa ya meneja na sifa ya meneja wa programu mnamo 2013. Wakati wa mpango wa bwana wake, alifahamiana na Mradi wa barabara (GPM Deutsche Gesellschaft für Projektmanagement e. V.) na mienendo ya ond.
Valerii alichukua vipimo kadhaa vya mienendo ya ond na alitumia maarifa na uzoefu wake kurekebisha toleo la sasa la SDTest.
Valerii ndiye mwandishi wa kuchunguza kutokuwa na uhakika wa V.U.C.A. Dhana ya kutumia mienendo ya ond na takwimu za hisabati katika saikolojia, zaidi ya kura 20 za kimataifa.

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