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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 = 0.0719

Rarraba ba rarraba ba, da Spearman r = 0.0029

Nuna kawai sakamako > r = 0.0719

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 0.0717	Rauni kyau 0.0194	Rauni kyau 0.0951	Rauni korau -0.1167	Rauni kyau 0.0005	Rauni korau -0.0468	Rauni kyau 0.0167
Answer 2	-	Rauni kyau 0.0182	Rauni korau -0.0080	Rauni kyau 0.0453	Rauni korau -0.0234	Rauni kyau 0.0345	Rauni kyau 0.0008	Rauni korau -0.0527
Answer 3	-	Rauni korau -0.0296	Rauni korau -0.0292	Rauni kyau 0.0103	Rauni kyau 0.0587	Rauni korau -0.0267	Rauni korau -0.0122	Rauni kyau 0.0036
Answer 4	-	Rauni kyau 0.0297	Rauni korau -0.0085	Rauni kyau 0.0111	Rauni korau -0.0523	Rauni korau -0.0318	Rauni kyau 0.0089	Rauni kyau 0.0535
Answer 5	-	Rauni korau -0.0130	Rauni korau -0.0244	Rauni korau -0.0233	Rauni kyau 0.0432	Rauni kyau 0.0319	Rauni kyau 0.0222	Rauni korau -0.0550
Answer 2	-	Rauni korau -0.0129	Rauni korau -0.0530	Rauni korau -0.0732	Rauni kyau 0.0643	Rauni korau -0.0074	Rauni kyau 0.0432	Rauni kyau 0.0153
Answer 6	-	Rauni korau -0.0546	Rauni kyau 0.1065	Rauni korau -0.0644	Rauni kyau 0.0141	Rauni kyau 0.0040	Rauni korau -0.0178	Rauni kyau 0.0173
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7	-	Rauni kyau 0.0135	Rauni kyau 0.0019	Rauni kyau 0.0785	Rauni kyau 0.0556	Rauni korau -0.0244	Rauni korau -0.0765	Rauni korau -0.0430
Answer 8	-	Rauni kyau 0.0181	Rauni korau -0.0321	Rauni korau -0.0343	Rauni kyau 0.0195	Rauni kyau 0.0867	Rauni korau -0.0040	Rauni korau -0.0545
Answer 9	-	Rauni kyau 0.0181	Rauni korau -0.0274	Rauni korau -0.0685	Rauni korau -0.0090	Rauni korau -0.0038	Rauni kyau 0.0565	Rauni kyau 0.0315
Answer 10	-	Rauni kyau 0.0189	Rauni kyau 0.0003	Rauni kyau 0.0318	Rauni korau -0.0597	Rauni korau -0.0312	Rauni korau -0.0132	Rauni kyau 0.0563
Answer 11	-	Rauni korau -0.0127	Rauni kyau 0.0304	Rauni kyau 0.0570	Rauni kyau 0.0415	Rauni korau -0.0665	Rauni korau -0.0080	Rauni korau -0.0408
Answer 8	-	Rauni korau -0.0904	Rauni korau -0.0338	Rauni korau -0.0178	Rauni kyau 0.0081	Rauni kyau 0.0270	Rauni kyau 0.0746	Rauni korau -0.0010
Answer 12	-	Rauni kyau 0.0048	Rauni kyau 0.0890	Rauni korau -0.0335	Rauni korau -0.0684	Rauni korau -0.0264	Rauni korau -0.0104	Rauni kyau 0.0688

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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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