littafin tushen gwajin «Spiral Dynamics:
Mastering Values, Leadership, and
Change» (ISBN-13: 978-1405133562)
Tallafawa

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

ChartsHulda
?
Ga dangantakar da ke tsakanin martani na zaben da kuma launuka na gwaji
VUCA
?
Ga sabon salo game da daidaitawa a tebur ta matakan da volatility (V.U.C.A.), rikicewar launuka masu inganci
kasar
harshe
-
Mail
Sake tara
M darajar da hulda coefficient
Rarraba al'ada, ta William Gubetes (Dalibi) r = 0.0718
Rarraba al'ada, ta William Gubetes (Dalibi) r = 0.0718
Rarraba ba rarraba ba, da Spearman r = 0.0029
RarrabuwaDa
ba al'ada ba
Na al'adaDa
ba al'ada ba
Na al'adaNa al'adaNa al'adaNa al'adaNa 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
0.0708
Rauni kyau
0.0197
Rauni kyau
0.0942
Rauni korau
-0.1158
Rauni kyau
0.0007
Rauni korau
-0.0461
Rauni kyau
0.0163
Answer 2-
Rauni kyau
0.0170
Rauni korau
-0.0075
Rauni kyau
0.0441
Rauni korau
-0.0223
Rauni kyau
0.0348
Rauni kyau
0.0017
Rauni korau
-0.0533
Answer 3-
Rauni korau
-0.0306
Rauni korau
-0.0288
Rauni kyau
0.0092
Rauni kyau
0.0596
Rauni korau
-0.0264
Rauni korau
-0.0113
Rauni kyau
0.0030
Answer 4-
Rauni kyau
0.0348
Rauni korau
-0.0106
Rauni kyau
0.0164
Rauni korau
-0.0570
Rauni korau
-0.0332
Rauni kyau
0.0046
Rauni kyau
0.0562
Answer 5-
Rauni korau
-0.0137
Rauni korau
-0.0241
Rauni korau
-0.0239
Rauni kyau
0.0438
Rauni kyau
0.0320
Rauni kyau
0.0227
Rauni korau
-0.0554
Answer 2-
Rauni korau
-0.0138
Rauni korau
-0.0526
Rauni korau
-0.0740
Rauni kyau
0.0650
Rauni korau
-0.0071
Rauni kyau
0.0438
Rauni kyau
0.0148
Answer 6-
Rauni korau
-0.0554
Rauni kyau
0.1068
Rauni korau
-0.0652
Rauni kyau
0.0149
Rauni kyau
0.0042
Rauni korau
-0.0171
Rauni kyau
0.0168
2) Gudanarwa (nawa ne ka yarda ko ba da yarda ba?)
Answer 7-
Rauni kyau
0.0123
Rauni kyau
0.0023
Rauni kyau
0.0772
Rauni kyau
0.0566
Rauni korau
-0.0241
Rauni korau
-0.0754
Rauni korau
-0.0436
Answer 8-
Rauni kyau
0.0168
Rauni korau
-0.0315
Rauni korau
-0.0355
Rauni kyau
0.0207
Rauni kyau
0.0870
Rauni korau
-0.0030
Rauni korau
-0.0551
Answer 9-
Rauni kyau
0.0171
Rauni korau
-0.0270
Rauni korau
-0.0694
Rauni korau
-0.0079
Rauni korau
-0.0035
Rauni kyau
0.0573
Rauni kyau
0.0309
Answer 10-
Rauni kyau
0.0181
Rauni kyau
0.0007
Rauni kyau
0.0309
Rauni korau
-0.0588
Rauni korau
-0.0310
Rauni korau
-0.0125
Rauni kyau
0.0558
Answer 11-
Rauni korau
-0.0034
Rauni kyau
0.0263
Rauni kyau
0.0655
Rauni kyau
0.0322
Rauni korau
-0.0684
Rauni korau
-0.0152
Rauni korau
-0.0352
Answer 8-
Rauni korau
-0.0909
Rauni korau
-0.0336
Rauni korau
-0.0184
Rauni kyau
0.0087
Rauni kyau
0.0272
Rauni kyau
0.0750
Rauni korau
-0.0014
Answer 12-
Rauni kyau
0.0041
Rauni kyau
0.0892
Rauni korau
-0.0341
Rauni korau
-0.0676
Rauni korau
-0.0262
Rauni korau
-0.0098
Rauni kyau
0.0683


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


2023.11.27
FearpersonqualitiesprojectorganizationalstructureRACIresponsibilitymatrixCritical ChainProject Managementfocus factorJiraempathyleadersbossGermanyChinaPolicyUkraineRussiawarvolatilityuncertaintycomplexityambiguityVUCArelocatejobproblemcountryreasongive upobjectivekeyresultmathematicalpsychologyMBTIHR metricsstandardDEIcorrelationriskscoringmodelGame TheoryPrisoner's Dilemma
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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