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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 = 0.0839

Usambazaji usio wa kawaida, na Spearman r = 0.0036

Onyesha matokeo tu > r = 0.0839

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 0.0780	Hasi dhaifu -0.0196	Chanya dhaifu 0.1061	Hasi dhaifu -0.1241	Chanya dhaifu 0.0204	Hasi dhaifu -0.0550	Chanya dhaifu 0.0223
Answer 2	-	Chanya dhaifu 0.0293	Chanya dhaifu 0.0227	Chanya dhaifu 0.0391	Hasi dhaifu -0.0020	Chanya dhaifu 0.0121	Hasi dhaifu -0.0040	Hasi dhaifu -0.0689
Answer 3	-	Hasi dhaifu -0.0078	Hasi dhaifu -0.0333	Hasi dhaifu -0.0043	Chanya dhaifu 0.0543	Hasi dhaifu -0.0064	Hasi dhaifu -0.0133	Hasi dhaifu -0.0090
Answer 4	-	Chanya dhaifu 0.0043	Chanya dhaifu 0.0256	Chanya dhaifu 0.0316	Hasi dhaifu -0.0209	Hasi dhaifu -0.0609	Hasi dhaifu -0.0195	Chanya dhaifu 0.0486
Answer 5	-	Chanya dhaifu 0.0089	Hasi dhaifu -0.0157	Hasi dhaifu -0.0219	Chanya dhaifu 0.0212	Chanya dhaifu 0.0235	Chanya dhaifu 0.0167	Hasi dhaifu -0.0464
Answer 6	-	Hasi dhaifu -0.0459	Hasi dhaifu -0.0555	Hasi dhaifu -0.1010	Chanya dhaifu 0.0890	Chanya dhaifu 0.0083	Chanya dhaifu 0.0476	Chanya dhaifu 0.0205
Answer 7	-	Hasi dhaifu -0.0568	Chanya dhaifu 0.0716	Hasi dhaifu -0.0427	Hasi dhaifu -0.0410	Chanya dhaifu 0.0108	Chanya dhaifu 0.0242	Chanya dhaifu 0.0385
2) Udhibiti (unakubali au haukubaliani?)
Answer 8	-	Chanya dhaifu 0.0258	Chanya dhaifu 0.0443	Chanya dhaifu 0.0756	Chanya dhaifu 0.0698	Hasi dhaifu -0.0220	Hasi dhaifu -0.1038	Hasi dhaifu -0.0717
Answer 9	-	Chanya dhaifu 0.0266	Hasi dhaifu -0.0445	Hasi dhaifu -0.0361	Hasi dhaifu -0.0030	Chanya dhaifu 0.0995	Hasi dhaifu -0.0335	Hasi dhaifu -0.0148
Answer 10	-	Chanya dhaifu 0.0468	Hasi dhaifu -0.0251	Hasi dhaifu -0.0253	Hasi dhaifu -0.0189	Hasi dhaifu -0.0301	Chanya dhaifu 0.0267	Chanya dhaifu 0.0332
Answer 11	-	Chanya dhaifu 0.0189	Chanya dhaifu 0.0040	Chanya dhaifu 0.0047	Hasi dhaifu -0.0403	Chanya dhaifu 0.0004	Hasi dhaifu -0.0106	Chanya dhaifu 0.0308
Answer 12	-	Hasi dhaifu -0.0509	Chanya dhaifu 0.0352	Chanya dhaifu 0.0295	Chanya dhaifu 0.0531	Hasi dhaifu -0.0676	Chanya dhaifu 0.0430	Hasi dhaifu -0.0524
Answer 13	-	Hasi dhaifu -0.1115	Hasi dhaifu -0.0433	Chanya dhaifu 0.0025	Chanya dhaifu 0.0200	Hasi dhaifu -0.0127	Chanya dhaifu 0.0931	Chanya dhaifu 0.0118
Answer 14	-	Hasi dhaifu -0.0077	Chanya dhaifu 0.0453	Hasi dhaifu -0.0579	Hasi dhaifu -0.0917	Hasi dhaifu -0.0042	Chanya dhaifu 0.0493	Chanya dhaifu 0.0797

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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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