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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.

Hankali da kuma ƙarshen wayewar kai

Charts Hulda

VUCA

M darajar da hulda coefficient

Rarraba al'ada, ta William Gubetes (Dalibi) r = 0.0723

Rarraba ba rarraba ba, da Spearman r = 0.0029

Nuna kawai sakamako > r = 0.0723

Rarrabuwa	Da ba al'ada ba	Na al'ada	Da ba al'ada ba	Na al'ada	Na al'ada	Na al'ada	Na al'ada	Na al'ada
Duk Tambayoyi Duk Tambayoyi 1) Aminci (nawa kuka yarda ko ba da yarda ba?) 2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
1) Aminci (nawa kuka yarda ko ba da yarda ba?)
Answer 1	-	Rauni kyau 0.0643	Rauni kyau 0.0187	Rauni kyau 0.0956	Rauni korau -0.1202	Rauni korau -0.0005	Rauni korau -0.0499	Rauni kyau 0.0193
Answer 2	-	Rauni kyau 0.0151	Rauni korau -0.0051	Rauni kyau 0.0441	Rauni korau -0.0253	Rauni kyau 0.0350	Rauni korau -0.0038	Rauni korau -0.0503
Answer 3	-	Rauni korau -0.0220	Rauni korau -0.0216	Rauni kyau 0.0115	Rauni kyau 0.0603	Rauni korau -0.0284	Rauni korau -0.0143	Rauni kyau 0.0013
Answer 4	-	Rauni kyau 0.0293	Rauni korau -0.0083	Rauni kyau 0.0101	Rauni korau -0.0467	Rauni korau -0.0320	Rauni kyau 0.0006	Rauni kyau 0.0502
Answer 5	-	Rauni korau -0.0072	Rauni korau -0.0246	Rauni korau -0.0240	Rauni kyau 0.0477	Rauni kyau 0.0335	Rauni kyau 0.0284	Rauni korau -0.0527
Answer 2	-	Rauni korau -0.0121	Rauni korau -0.0537	Rauni korau -0.0769	Rauni kyau 0.0657	Rauni korau -0.0086	Rauni kyau 0.0466	Rauni kyau 0.0152
Answer 6	-	Rauni korau -0.0591	Rauni kyau 0.0965	Rauni korau -0.0600	Rauni kyau 0.0071	Rauni kyau 0.0060	Rauni korau -0.0071	Rauni kyau 0.0168
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7	-	Rauni kyau 0.0132	Rauni kyau 0.0035	Rauni kyau 0.0801	Rauni kyau 0.0543	Rauni korau -0.0260	Rauni korau -0.0781	Rauni korau -0.0439
Answer 8	-	Rauni kyau 0.0242	Rauni korau -0.0234	Rauni korau -0.0420	Rauni kyau 0.0280	Rauni kyau 0.0824	Rauni korau -0.0099	Rauni korau -0.0551
Answer 9	-	Rauni kyau 0.0165	Rauni korau -0.0378	Rauni korau -0.0547	Rauni korau -0.0176	Rauni kyau 0.0019	Rauni kyau 0.0566	Rauni kyau 0.0289
Answer 10	-	Rauni kyau 0.0146	Rauni kyau 3.46E-5	Rauni kyau 0.0290	Rauni korau -0.0583	Rauni korau -0.0296	Rauni korau -0.0094	Rauni kyau 0.0558
Answer 11	-	Rauni korau -0.0069	Rauni kyau 0.0343	Rauni kyau 0.0508	Rauni kyau 0.0414	Rauni korau -0.0658	Rauni kyau 0.0075	Rauni korau -0.0442
Answer 8	-	Rauni korau -0.0955	Rauni korau -0.0364	Rauni korau -0.0180	Rauni kyau 0.0054	Rauni kyau 0.0261	Rauni kyau 0.0732	Rauni kyau 0.0073
Answer 12	-	Rauni kyau 0.0035	Rauni kyau 0.0867	Rauni korau -0.0352	Rauni korau -0.0661	Rauni korau -0.0264	Rauni korau -0.0137	Rauni kyau 0.0689

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Wannan aikin zai kasance a cikin zaben VUCA

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

2023.11.27

Valerii Kosenko

Mai Samfurin SaaS SDTEST®

Valerii ya cancanta a matsayin masanin ilimin zamantakewar jama'a-psychologist a 1993 kuma tun daga lokacin ya yi amfani da iliminsa a cikin gudanar da ayyukan.
Valerii ya sami digiri na biyu da kuma cancantar aikin da mai sarrafa shirye-shirye a cikin 2013. A lokacin shirinsa na Jagora, ya saba da Project Roadmap (GPM Deutsche Gesellschaft für Projektmanagement e. V.) da Spiral Dynamics.
Valerii shine marubucin binciken rashin tabbas na V.U.C.A. ra'ayi ta yin amfani da Ƙaƙwalwar Ƙarƙashin Ƙarƙashin Ƙarƙashin Ƙarƙashin Ƙarƙashin Ƙididdiga da Ƙididdiga na Lissafi a cikin ilimin halin dan Adam, da kuma 38 na kasa da kasa zabe.

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