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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.


Kecerdasan buatan dan akhir tamadun

cartaKorelasi
?
Inilah hubungan antara jawapan pengundian dan warna ujian dinamik lingkaran
VUCA
?
Berikut adalah pandangan antara muka baru mengenai korelasi dalam jadual dengan tahap dinamik lingkaran di mana turun naik, ketidakpastian, kerumitan, dan kekaburan (V.U.C.A.) ditunjukkan melalui ketergantungan korelasi positif dan negatif antara tindak balas tinjauan dan warna dinamik lingkaran warna
negara
bahasa
-
Mail
Mengira semula
Nilai kritikal pekali korelasi
Pengagihan Normal, oleh William Sealy Gosset (Pelajar) r = 0.0718
Pengagihan Normal, oleh William Sealy Gosset (Pelajar) r = 0.0718
Pengedaran tidak normal, oleh Spearman r = 0.0029
PengedaranTidak
normal
BiasaTidak
normal
BiasaBiasaBiasaBiasaBiasa
Semua soalan
Semua soalan
1) Keselamatan (berapa yang anda setuju atau tidak setuju?)
2) Mengawal (berapa yang anda setuju atau tidak setuju?)
1) Keselamatan (berapa yang anda setuju atau tidak setuju?)
Answer 1-
Lemah positif
0.0708
Lemah positif
0.0197
Lemah positif
0.0942
Lemah negatif
-0.1158
Lemah positif
0.0007
Lemah negatif
-0.0461
Lemah positif
0.0163
Answer 2-
Lemah positif
0.0170
Lemah negatif
-0.0075
Lemah positif
0.0441
Lemah negatif
-0.0223
Lemah positif
0.0348
Lemah positif
0.0017
Lemah negatif
-0.0533
Answer 3-
Lemah negatif
-0.0306
Lemah negatif
-0.0288
Lemah positif
0.0092
Lemah positif
0.0596
Lemah negatif
-0.0264
Lemah negatif
-0.0113
Lemah positif
0.0030
Answer 4-
Lemah positif
0.0348
Lemah negatif
-0.0106
Lemah positif
0.0164
Lemah negatif
-0.0570
Lemah negatif
-0.0332
Lemah positif
0.0046
Lemah positif
0.0562
Answer 5-
Lemah negatif
-0.0137
Lemah negatif
-0.0241
Lemah negatif
-0.0239
Lemah positif
0.0438
Lemah positif
0.0320
Lemah positif
0.0227
Lemah negatif
-0.0554
Answer 6-
Lemah negatif
-0.0138
Lemah negatif
-0.0526
Lemah negatif
-0.0740
Lemah positif
0.0650
Lemah negatif
-0.0071
Lemah positif
0.0438
Lemah positif
0.0148
Answer 7-
Lemah negatif
-0.0554
Lemah positif
0.1068
Lemah negatif
-0.0652
Lemah positif
0.0149
Lemah positif
0.0042
Lemah negatif
-0.0171
Lemah positif
0.0168
2) Mengawal (berapa yang anda setuju atau tidak setuju?)
Answer 8-
Lemah positif
0.0123
Lemah positif
0.0023
Lemah positif
0.0772
Lemah positif
0.0566
Lemah negatif
-0.0241
Lemah negatif
-0.0754
Lemah negatif
-0.0436
Answer 9-
Lemah positif
0.0168
Lemah negatif
-0.0315
Lemah negatif
-0.0355
Lemah positif
0.0207
Lemah positif
0.0870
Lemah negatif
-0.0030
Lemah negatif
-0.0551
Answer 10-
Lemah positif
0.0171
Lemah negatif
-0.0270
Lemah negatif
-0.0694
Lemah negatif
-0.0079
Lemah negatif
-0.0035
Lemah positif
0.0573
Lemah positif
0.0309
Answer 11-
Lemah positif
0.0181
Lemah positif
0.0007
Lemah positif
0.0309
Lemah negatif
-0.0588
Lemah negatif
-0.0310
Lemah negatif
-0.0125
Lemah positif
0.0558
Answer 12-
Lemah negatif
-0.0034
Lemah positif
0.0263
Lemah positif
0.0655
Lemah positif
0.0322
Lemah negatif
-0.0684
Lemah negatif
-0.0152
Lemah negatif
-0.0352
Answer 13-
Lemah negatif
-0.0909
Lemah negatif
-0.0336
Lemah negatif
-0.0184
Lemah positif
0.0087
Lemah positif
0.0272
Lemah positif
0.0750
Lemah negatif
-0.0014
Answer 14-
Lemah positif
0.0041
Lemah positif
0.0892
Lemah negatif
-0.0341
Lemah negatif
-0.0676
Lemah negatif
-0.0262
Lemah negatif
-0.0098
Lemah positif
0.0683


Eksport ke MS Excel
Fungsi ini akan tersedia dalam pemilihan VUCA anda sendiri
Okey



[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
Pemilik Produk SaaS SDTEST®

Valerii telah layak sebagai pedagogue-psikologi sosial pada tahun 1993 dan sejak itu telah menggunakan pengetahuannya dalam pengurusan projek.
Valerii memperoleh ijazah Sarjana dan kelayakan pengurus projek dan program pada tahun 2013. Semasa program Sarjananya, beliau mengenali Pelan Hala Tuju Projek (GPM Deutsche Gesellschaft für Projektmanagement e. V.) dan Spiral Dynamics.
Valerii ialah pengarang meneroka ketidakpastian V.U.C.A. konsep menggunakan Spiral Dynamics dan statistik matematik dalam psikologi, dan 38 tinjauan antarabangsa.
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