كىتاب ئاساسىدا سىناق «Spiral Dynamics:
Mastering Values, Leadership, and
Change» (ISBN-13: 978-1405133562)
قوللىغۇچىلار

Future of Jobs and Generative AI

The advent of large language models (LLMs) like ChatGPT promises to transform the workplace by automating or augmenting a wide range of occupational tasks. However, a single perspective cannot fully grasp both the opportunities and risks these technologies represent across industries, workers, businesses and society. This article analyzes the World Economic Forum’s recent white paper [1] assessing the impact of LLMs on jobs through the lens of Spiral Dynamics. This integral framework reveals how different value systems perceive threats and opportunities differently. Administrative roles face disruption but efficiency gains (Blue). Innovative businesses are pressured to adopt but see new revenue potential (Orange). Vulnerable workers require support amidst job transformations (Green). Policymakers struggle to holistically analyze systemic impacts (Yellow). Realizing the benefits of LLMs requires honoring multiple worldviews, evolving processes, encouraging innovation, caring for people and conducting systems analysis. The analysis provides insights into LLMs’ multi-dimensional impacts and underscores the need for inclusive dialogue and initiatives to shape the AI-enabled future of work.


Here are the key points:

  1. LLMs could significantly impact many jobs due to their ability to automate or augment language-based tasks, which account for an estimated 62% of work time.
  2. The analysis assessed over 19,000 work tasks across 867 occupations to assess their LLM exposure. Tasks with high automation potential are routine and repetitive clerical/administrative tasks. Tasks with high augmentation potential require more abstract reasoning and problem-solving. Tasks with lower exposure potential emphasize interpersonal interaction.
  3. Occupations with the highest automation potential include credit authorizers, telemarketers, statistical assistants, and tellers. Occupations with the highest augmentation potential include insurance underwriters, bioengineers, mathematicians, and editors. Occupations with lower exposure include counselors, clergy, home health aides, and lawyers.
  4. Adopting LLMs will also likely create new roles like AI developers, content creators, interface designers, data curators, and AI ethics specialists.
  5. The financial services and information technology industries have the overall highest potential exposure. The finance and IT functional areas also have increased exposure.
  6. Significant alignment exists between occupations this analysis identifies as having high augmentation potential and those the Future of Jobs Report found to have high expected job growth. Similarly, occupations with high automation potential align with declining occupations.
  7. The report concludes LLMs will transform jobs and tasks, requiring strategies by businesses and government to prepare workforces for the change through training, transition support, and social safety nets. Overall, LLMs present opportunities to raise productivity and create new jobs, if managed responsibly.



Spiral Dynamics stages



What color are you Spiral Dynamics?


ColorBeigePurpleRedBlueOrangeGreenYellowTurquoise
In a lifeSurvivalFamily relationsThe rule of forceThe power of truthCompetitionInterpersonal relationsFlexible streamThe Global vision
In a businessOwn farmFamily businessStarting up a personal businessBusiness Process ManagementProject managementSocial networksWin-Win-Win behaviorSynthesis

Here is an analysis of the World Economic Forum white paper on large language models and jobs through the lens of Spiral Dynamics stages:


Spiral Dynamics StageQuotes from Document
 Beige No relevant quotes
 Purple No relevant quotes
 Red No relevant quotes
 Blue "With 62% of total work time involving language-based tasks, the widespread adoption of LLMs, such as ChatGPT, could significantly impact a broad spectrum of job roles." (p.4) This reflects the blue focus on structure, process and order.
 Orange "Adopting LLMs will transform business and the nature of work, displacing some existing jobs, enhancing others and ultimately creating many new roles." (p.19) This reflects the orange drive for innovation and progress.
 Green "Governments can also partner with and support employers and educational institutions to provide training programs that prepare workers for the jobs that will grow and benefit the most from LLMs. Additionally, social safety nets and assistance in transitioning to new roles will need to be reimagined and be more precisely targeted for those most likely to be affected." (p.19) This reflects the green concern for people and relationships.
 Yellow "To assess the impact of LLMs on jobs, this paper provides an analysis of over 19,000 individual tasks across 867 occupations, assessing the potential exposure of each task to LLM adoption, classifying them as tasks that have a high potential for automation, high potential for augmentation, low potential for either or are unaffected (non-language tasks). The paper also provides an overview of new roles that are emerging due to the adoption of LLMs." (p.4) This reflects yellow's emphasis on complex systems analysis.
 Turquoise No relevant quotes


The document overall reflects blue, orange, and green worldviews, with some elements of yellow systems thinking. There are no clear expressions of the beige, purple, red or turquoise value systems. This analysis illustrates how technology impacts different aspects of society and values.



Threats



Here is an analysis of threats and affected stakeholders through the lens of Spiral Dynamics stages:


Spiral Dynamics StageThreatsAffected Stakeholders
 Beige No major threats identified N/A
 Purple No major threats identified N/A
 Red No major threats identified N/A
 Blue Disruption of administrative processes and routines Organizations, administrative staff
 Orange Pressure to rapidly adopt new technologies Businesses, managers
 Green Job losses, inequality, lack of support during transition Individual workers, marginalized groups, society
 Yellow Complexity of analyzing and managing impacts Policy-makers, business leaders
 Turquoise No major threats identified N/A


In summary, the blue stage is threatened by disruption of established administrative processes, the orange faces pressure to innovate, the green risks job losses and inequality, and the yellow struggles with complex systems analysis. This highlights how different worldviews perceive threats and opportunities from the same technology trend. A holistic perspective is needed to understand the range of stakeholders and design responsible policies.


Elon Musk said about the danger of artificial intelligence (A.I.) in an interview with Tucker Carlson in April 2023. Below you can read an abridged version of the results of our VUCA poll "A.I. and the end of civilization". The full version of the results is available for free in the FAQ section after login or registration.

سۈنئىي ئىدراك ۋە مەدەنىيەت ئاخىرلاشقان

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تىل
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قايتا ھېسابلاش
مۇناسىۋەتلىك كوئېففىتسېنتى ھالقىلىق قىممىتى
نورمال تەقسىملەش, ۋىليام دېڭىز قىرغىقىدا (ئوقۇغۇچى) r = 0.0849
نورمال تەقسىملەش, ۋىليام دېڭىز قىرغىقىدا (ئوقۇغۇچى) r = 0.0849
نەيزە بىلەن نورمال تەقسىمات ئەمەس r = 0.0037
تەقسىملەشنورمال
ئەمەس
نورمالنورمالنورمالنورمالنورمالنورمالنورمال
بارلىق سوئاللار
بارلىق سوئاللار
1) بىخەتەرلىك (قانچىلىك قوشۇلىسىز ياكى قوشۇلىسىز?)
2) كونترول (قانچىلىك قوشۇلىسىز ياكى قوشۇلۇۋاتىسىز?)
1) بىخەتەرلىك (قانچىلىك قوشۇلىسىز ياكى قوشۇلىسىز?)
Answer 1-
ئاجىز مۇسبەت
0.0479
ئاجىز مەنپىي
-0.0487
ئاجىز مۇسبەت
0.1036
ئاجىز مەنپىي
-0.1091
ئاجىز مۇسبەت
0.0228
ئاجىز مەنپىي
-0.0373
ئاجىز مۇسبەت
0.0298
Answer 2-
ئاجىز مۇسبەت
0.0411
ئاجىز مۇسبەت
0.0298
ئاجىز مۇسبەت
0.0395
ئاجىز مەنپىي
-0.0029
ئاجىز مۇسبەت
0.0082
ئاجىز مەنپىي
-0.0157
ئاجىز مەنپىي
-0.0668
Answer 3-
ئاجىز مەنپىي
-0.0183
ئاجىز مەنپىي
-0.0342
ئاجىز مۇسبەت
0.0037
ئاجىز مۇسبەت
0.0586
ئاجىز مەنپىي
-0.0114
ئاجىز مەنپىي
-0.0072
ئاجىز مەنپىي
-0.0141
Answer 4-
ئاجىز مۇسبەت
0.0124
ئاجىز مۇسبەت
0.0313
ئاجىز مۇسبەت
0.0239
ئاجىز مەنپىي
-0.0178
ئاجىز مەنپىي
-0.0593
ئاجىز مەنپىي
-0.0263
ئاجىز مۇسبەت
0.0476
Answer 5-
ئاجىز مۇسبەت
0.0216
ئاجىز مەنپىي
-0.0160
ئاجىز مەنپىي
-0.0235
ئاجىز مۇسبەت
0.0106
ئاجىز مۇسبەت
0.0119
ئاجىز مۇسبەت
0.0306
ئاجىز مەنپىي
-0.0424
Answer 6-
ئاجىز مەنپىي
-0.0455
ئاجىز مەنپىي
-0.0515
ئاجىز مەنپىي
-0.0981
ئاجىز مۇسبەت
0.0823
ئاجىز مۇسبەت
0.0161
ئاجىز مۇسبەت
0.0466
ئاجىز مۇسبەت
0.0156
Answer 7-
ئاجىز مەنپىي
-0.0510
ئاجىز مۇسبەت
0.0785
ئاجىز مەنپىي
-0.0433
ئاجىز مەنپىي
-0.0464
ئاجىز مۇسبەت
0.0190
ئاجىز مۇسبەت
0.0135
ئاجىز مۇسبەت
0.0374
2) كونترول (قانچىلىك قوشۇلىسىز ياكى قوشۇلۇۋاتىسىز?)
Answer 8-
ئاجىز مۇسبەت
0.0097
ئاجىز مۇسبەت
0.0251
ئاجىز مۇسبەت
0.0774
ئاجىز مۇسبەت
0.0775
ئاجىز مەنپىي
-0.0150
ئاجىز مەنپىي
-0.0982
ئاجىز مەنپىي
-0.0697
Answer 9-
ئاجىز مۇسبەت
0.0252
ئاجىز مەنپىي
-0.0411
ئاجىز مەنپىي
-0.0377
ئاجىز مەنپىي
-0.0006
ئاجىز مۇسبەت
0.0860
ئاجىز مەنپىي
-0.0241
ئاجىز مەنپىي
-0.0123
Answer 10-
ئاجىز مۇسبەت
0.0566
ئاجىز مەنپىي
-0.0258
ئاجىز مەنپىي
-0.0175
ئاجىز مەنپىي
-0.0234
ئاجىز مەنپىي
-0.0356
ئاجىز مۇسبەت
0.0246
ئاجىز مۇسبەت
0.0320
Answer 11-
ئاجىز مۇسبەت
0.0212
ئاجىز مۇسبەت
0.0094
ئاجىز مۇسبەت
0.0001
ئاجىز مەنپىي
-0.0374
ئاجىز مەنپىي
-0.0012
ئاجىز مەنپىي
-0.0169
ئاجىز مۇسبەت
0.0340
Answer 12-
ئاجىز مەنپىي
-0.0502
ئاجىز مۇسبەت
0.0366
ئاجىز مۇسبەت
0.0301
ئاجىز مۇسبەت
0.0536
ئاجىز مەنپىي
-0.0683
ئاجىز مۇسبەت
0.0413
ئاجىز مەنپىي
-0.0532
Answer 13-
ئاجىز مەنپىي
-0.1079
ئاجىز مەنپىي
-0.0387
ئاجىز مەنپىي
-0.0079
ئاجىز مۇسبەت
0.0250
ئاجىز مەنپىي
-0.0095
ئاجىز مۇسبەت
0.0899
ئاجىز مۇسبەت
0.0101
Answer 14-
ئاجىز مەنپىي
-0.0020
ئاجىز مۇسبەت
0.0576
ئاجىز مەنپىي
-0.0541
ئاجىز مەنپىي
-0.1112
ئاجىز مۇسبەت
0.0142
ئاجىز مۇسبەت
0.0416
ئاجىز مۇسبەت
0.0739


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Opportunities



Here is an analysis of opportunities and affected stakeholders through the lens of Spiral Dynamics stages:


Spiral Dynamics StageOpportunitiesAffected Stakeholders
 Beige No major opportunities identified N/A
 Purple No major opportunities identified N/A
 Red No major opportunities identified N/A
 Blue Increased efficiency of administrative processes Organizations, administrative staff
 Orange Creation of new business models and revenue streams Businesses, entrepreneurs
 Green Upskilling workers, maintaining an inclusive workforce Individual workers, marginalized groups, society
 Yellow Holistic analysis of technology's impact on work Policy-makers, business leaders
 Turquoise No major opportunities identified N/A


In summary, blue sees opportunities for improved efficiency, orange in innovation and profit, green in supporting workers, and yellow in systems analysis. This highlights how different worldviews perceive opportunities from the same technology trend. An integral perspective is required to balance opportunities for organizations and individuals.


GAP Analysis



Here is a GAP analysis from a Spiral Dynamics perspective:


Spiral Dynamics StageGAP Analysis
 Beige No major gap identified
 Purple No major gap identified
 Red No major gap identified
 Blue GAP: Lacks discussion of how to evolve administrative processes rather than just making existing ones more efficient
 Orange GAP: Could provide more examples of how new business models and industries could arise from LLMs
 Green GAP: More detail is needed on programs to support workers through transitions and ensure opportunities are inclusive
 Yellow GAP: Deeper analysis required on technological impacts across education, business, and government domains
 Turquoise GAP: Holistic vision absent - how could LLMs improve society and actualization beyond business impacts?


In summary, blue could be used more on process evolution, orange on business model innovation, green on worker support, yellow on cross-domain impacts, and turquoise on realizing higher human potential. This reflects common gaps faced when new technologies are viewed primarily through one worldview lens rather than holistically. An integral perspective is needed to fully understand impacts and opportunities.


Overcome Gaps



Here are some suggested measures to overcome the gaps through the lens of Spiral Dynamics perspective:


Spiral Dynamics StageSuggested Measures to Overcome GAPs
 Beige N/A
 Purple N/A
 Red N/A
 Blue Conduct process redesign workshops to evolve administrative workflows
 Orange Research case studies and build scenarios describing new LLMs-enabled business models
 Green Profile reskilling programs and multi-stakeholder partnerships to support workers
 Yellow Model impacts of LLMs on education, healthcare, government, and other complex systems
 Turquoise Envision how LLMs could advance human potential and consciousness evolution


In summary, suggested measures include:
  • Blue: Process redesign workshops
  • Orange: New business model research
  • Green: Reskilling program profiles
  • Yellow: Modelling systemic impacts
  • Turquoise: Envisioning advancing human potential

This highlights the value of taking a holistic perspective and utilizing tools and ways of thinking from multiple stages and worldviews to fully understand and act upon the opportunities presented by emerging technologies like large language models.


Conclusion



The Spiral Dynamics framework reveals that the opportunities and threats presented by large language models are perceived differently across value systems. Blue sees potential efficiency gains but disruption of administrative routines. Orange focuses on innovation possibilities but feels pressured to rapidly adopt. Green emphasizes supporting impacted workers but risks exacerbating inequalities. Yellow provides systems analysis but grapples with complexity.

Fully realizing the benefits of large language models in the workplace and society requires transcending any worldview. An integral approach that honors multiple perspectives is needed. This includes evolving processes, encouraging innovation, caring for people, and systemic analysis. Further, a holistic vision looks beyond business impacts to how emerging technologies can advance human potential and social actualization.

By understanding these different value perspectives, businesses, policymakers, and workers can collaboratively shape the future of work in the age of artificial intelligence. A shared vision arises when stakeholders cooperate across stages of psychological and social development. This white paper provides insights into the multi-dimensional impacts of large language models across industries, occupations, and societal roles. Yet more inclusive dialogue and initiatives are needed to proactively guide this technology for the benefit of all.


[1] https://www3.weforum.org/docs/WEF_Jobs_of_Tomorrow_Generative_AI_2023.pdf

2023.10.12
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