pukapuka whakamātautau hāngai «Spiral
Dynamics: Mastering Values, Leadership,
and Change» (ISBN-13: 978-1405133562)
Kaitautoko

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.


Te mohio mohio me te mutunga o te ao

Ngā tūtohiIne
?
Anei te hononga i waenga i nga urupare a te pooti me nga tae whakamatautau a Siaril Shonamics
VUCA
?
Anei he tirohanga atanga hou mo te Whakakotahitanga i roto i te ripanga ma nga taumata o te Spiral Dynamics e whakaatuhia ana te pähekeheke, te rangirua, te whïwhiwhi, me te rangirua (V.U.C.A.) na roto i nga hononga pai me te kino i waenga i nga whakautu o te pooti me nga tae Spiral Dynamics.
whenua
reo
-
Mail
Whakatara
uara Critical o te whakarea te faatanoraa
Tohatoha noa, na William Sealy Gospes (akonga) r = 0.0718
Tohatoha noa, na William Sealy Gospes (akonga) r = 0.0718
Ko te tohatoha noa, na te taote r = 0.0029
WhakaratongaKore
noa
TonuKore
noa
TonuTonuTonuTonuTonu
Nga paatai ​​katoa
Nga paatai ​​katoa
1) Haumaru (E hia tau e whakaae ana, e whakaae ana ranei?)
2) Mana (pehea te whakaae ki a koe, kaore ranei?)
1) Haumaru (E hia tau e whakaae ana, e whakaae ana ranei?)
Answer 1-
Pai ngoikore
0.0708
Pai ngoikore
0.0197
Pai ngoikore
0.0942
Negative ngoikore
-0.1158
Pai ngoikore
0.0007
Negative ngoikore
-0.0461
Pai ngoikore
0.0163
Answer 2-
Pai ngoikore
0.0170
Negative ngoikore
-0.0075
Pai ngoikore
0.0441
Negative ngoikore
-0.0223
Pai ngoikore
0.0348
Pai ngoikore
0.0017
Negative ngoikore
-0.0533
Answer 3-
Negative ngoikore
-0.0306
Negative ngoikore
-0.0288
Pai ngoikore
0.0092
Pai ngoikore
0.0596
Negative ngoikore
-0.0264
Negative ngoikore
-0.0113
Pai ngoikore
0.0030
Answer 4-
Pai ngoikore
0.0348
Negative ngoikore
-0.0106
Pai ngoikore
0.0164
Negative ngoikore
-0.0570
Negative ngoikore
-0.0332
Pai ngoikore
0.0046
Pai ngoikore
0.0562
Answer 5-
Negative ngoikore
-0.0137
Negative ngoikore
-0.0241
Negative ngoikore
-0.0239
Pai ngoikore
0.0438
Pai ngoikore
0.0320
Pai ngoikore
0.0227
Negative ngoikore
-0.0554
Answer 6-
Negative ngoikore
-0.0138
Negative ngoikore
-0.0526
Negative ngoikore
-0.0740
Pai ngoikore
0.0650
Negative ngoikore
-0.0071
Pai ngoikore
0.0438
Pai ngoikore
0.0148
Answer 7-
Negative ngoikore
-0.0554
Pai ngoikore
0.1068
Negative ngoikore
-0.0652
Pai ngoikore
0.0149
Pai ngoikore
0.0042
Negative ngoikore
-0.0171
Pai ngoikore
0.0168
2) Mana (pehea te whakaae ki a koe, kaore ranei?)
Answer 8-
Pai ngoikore
0.0123
Pai ngoikore
0.0023
Pai ngoikore
0.0772
Pai ngoikore
0.0566
Negative ngoikore
-0.0241
Negative ngoikore
-0.0754
Negative ngoikore
-0.0436
Answer 9-
Pai ngoikore
0.0168
Negative ngoikore
-0.0315
Negative ngoikore
-0.0355
Pai ngoikore
0.0207
Pai ngoikore
0.0870
Negative ngoikore
-0.0030
Negative ngoikore
-0.0551
Answer 10-
Pai ngoikore
0.0171
Negative ngoikore
-0.0270
Negative ngoikore
-0.0694
Negative ngoikore
-0.0079
Negative ngoikore
-0.0035
Pai ngoikore
0.0573
Pai ngoikore
0.0309
Answer 11-
Pai ngoikore
0.0181
Pai ngoikore
0.0007
Pai ngoikore
0.0309
Negative ngoikore
-0.0588
Negative ngoikore
-0.0310
Negative ngoikore
-0.0125
Pai ngoikore
0.0558
Answer 12-
Negative ngoikore
-0.0034
Pai ngoikore
0.0263
Pai ngoikore
0.0655
Pai ngoikore
0.0322
Negative ngoikore
-0.0684
Negative ngoikore
-0.0152
Negative ngoikore
-0.0352
Answer 13-
Negative ngoikore
-0.0909
Negative ngoikore
-0.0336
Negative ngoikore
-0.0184
Pai ngoikore
0.0087
Pai ngoikore
0.0272
Pai ngoikore
0.0750
Negative ngoikore
-0.0014
Answer 14-
Pai ngoikore
0.0041
Pai ngoikore
0.0892
Negative ngoikore
-0.0341
Negative ngoikore
-0.0676
Negative ngoikore
-0.0262
Negative ngoikore
-0.0098
Pai ngoikore
0.0683


Kaweake ki MS Excel
Ka waatea tenei mahinga i roto i o ake ake pooti VUCA
Ok



[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
Kaipupuri Hua SaaS SDTEST®

I whai tohu a Valerii hei kai-whakaako-a-hinengaro i te tau 1993, a, mai i tera wa kua whakamahia e ia ona matauranga ki te whakahaere kaupapa.
I whiwhi a Valerii i te tohu Kaiwhakaako me te tohu kaiwhakahaere kaupapa me te kaupapa i te tau 2013. I te wa o te kaupapa a tona Kaiwhakaako, i mohio ia ki te Mahere Arataki Kaupapa (GPM Deutsche Gesellschaft für Projektmanagement e. V.) me Spiral Dynamics.
Ko Valerii te kaituhi o te tirotiro i te koretake o te V.U.C.A. ariā e whakamahi ana i te Spiral Dynamics me te tatauranga pāngarau i roto i te hinengaro hinengaro, me te 38 pooti o te ao.
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