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

negara
bahasa
-
Mail
Mengira semula
Nilai kritikal pekali korelasi
Pengagihan Normal, oleh William Sealy Gosset (Pelajar) r = 0.0874
Pengagihan Normal, oleh William Sealy Gosset (Pelajar) r = 0.0874
Pengedaran tidak normal, oleh Spearman r = 0.0039
PengedaranTidak
normal
BiasaBiasaBiasaBiasaBiasaBiasaBiasa
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
0.0647
Lemah negatif
-0.0402
Lemah positif
0.1238
Lemah negatif
-0.1305
Lemah positif
0.0097
Lemah negatif
-0.0535
Lemah positif
0.0344
Answer 2-
Lemah positif
0.0497
Lemah positif
0.0373
Lemah positif
0.0295
Lemah negatif
-0.0054
Lemah negatif
-0.0046
Lemah negatif
-0.0176
Lemah negatif
-0.0596
Answer 3-
Lemah negatif
-0.0307
Lemah negatif
-0.0330
Lemah positif
0.0063
Lemah positif
0.0822
Lemah negatif
-0.0127
Lemah negatif
-0.0159
Lemah negatif
-0.0149
Answer 4-
Lemah negatif
-0.0069
Lemah positif
0.0432
Lemah positif
0.0293
Lemah negatif
-0.0238
Lemah negatif
-0.0470
Lemah negatif
-0.0193
Lemah positif
0.0315
Answer 5-
Lemah positif
0.0069
Lemah negatif
-0.0237
Lemah negatif
-0.0152
Lemah positif
0.0131
Lemah negatif
-0.0018
Lemah positif
0.0608
Lemah negatif
-0.0308
Answer 6-
Lemah negatif
-0.0388
Lemah negatif
-0.0576
Lemah negatif
-0.1067
Lemah positif
0.0816
Lemah positif
0.0191
Lemah positif
0.0491
Lemah positif
0.0162
Answer 7-
Lemah negatif
-0.0360
Lemah positif
0.0619
Lemah negatif
-0.0510
Lemah negatif
-0.0486
Lemah positif
0.0403
Lemah positif
0.0061
Lemah positif
0.0322
2) Mengawal (berapa yang anda setuju atau tidak setuju?)
Answer 8-
Lemah positif
0.0254
Lemah positif
0.0424
Lemah positif
0.1084
Lemah positif
0.0601
Lemah negatif
-0.0356
Lemah negatif
-0.1149
Lemah negatif
-0.0695
Answer 9-
Lemah positif
0.0118
Lemah negatif
-0.0446
Lemah negatif
-0.0559
Lemah positif
0.0325
Lemah positif
0.0961
Lemah negatif
-0.0228
Lemah negatif
-0.0252
Answer 10-
Lemah positif
0.0535
Lemah negatif
-0.0376
Lemah negatif
-0.0089
Lemah negatif
-0.0281
Lemah negatif
-0.0308
Lemah positif
0.0262
Lemah positif
0.0309
Answer 11-
Lemah positif
0.0157
Lemah positif
0.0103
Lemah negatif
-0.0089
Lemah negatif
-0.0482
Lemah positif
0.0039
Lemah positif
0.0010
Lemah positif
0.0318
Answer 12-
Lemah negatif
-0.0377
Lemah positif
0.0444
Lemah positif
0.0304
Lemah positif
0.0435
Lemah negatif
-0.0755
Lemah positif
0.0475
Lemah negatif
-0.0432
Answer 13-
Lemah negatif
-0.1232
Lemah negatif
-0.0353
Lemah negatif
-0.0230
Lemah positif
0.0330
Lemah negatif
-0.0105
Lemah positif
0.0883
Lemah positif
0.0191
Answer 14-
Lemah positif
0.0124
Lemah positif
0.0425
Lemah negatif
-0.0572
Lemah negatif
-0.1125
Lemah positif
0.0256
Lemah positif
0.0326
Lemah positif
0.0763


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
Valerii Kosenko
Pemilik Produk SaaS Pet Project SDTest®

Valerii layak sebagai ahli pedagogi sosial-psikologi 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 tuannya, beliau menjadi akrab dengan Roadmap Project (GPM Deutsche Gesellschaft für Projektmanagement e. V.) dan Spiral Dynamics.
Valerii mengambil pelbagai ujian dinamik lingkaran dan menggunakan pengetahuan dan pengalamannya untuk menyesuaikan versi semasa SDTest.
Valerii adalah pengarang meneroka ketidakpastian V.U.C.A. Konsep menggunakan dinamik lingkaran dan statistik matematik dalam psikologi, lebih daripada 20 pemilihan antarabangsa.
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