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.

人工智能和文明的終結

Country
Lang
-
Mail
重新計算
Critical_value_of_the_correlation_coefficient
正態分佈,威廉·西莉·格塞特(William Sealy Gosset)(學生) r = 0.0759
正態分佈,威廉·西莉·格塞特(William Sealy Gosset)(學生) r = 0.0759
非正態分佈,Spearman r = 0.0031
分配非正常普通的非正常普通的普通的普通的普通的普通的
所有問題
所有問題
1) 安全(您同意或不同意多少?)
2) 控制(您同意或不同意多少?)
1) 安全(您同意或不同意多少?)
Answer 1-
Weak_positive
0.0750
Weak_negative
-0.0021
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0.1009
Weak_negative
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Weak_negative
-0.0026
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Answer 2-
Weak_positive
0.0270
Weak_negative
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Weak_positive
0.0397
Weak_negative
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Weak_positive
0.0488
Weak_negative
-0.0019
Weak_negative
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Answer 2-
Weak_negative
-0.0132
Weak_negative
-0.0503
Weak_negative
-0.0031
Weak_positive
0.0486
Weak_negative
-0.0081
Weak_negative
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Weak_positive
0.0121
Answer 3-
Weak_positive
0.0226
Weak_positive
0.0067
Weak_positive
0.0137
Weak_negative
-0.0404
Weak_negative
-0.0345
Weak_negative
-0.0090
Weak_positive
0.0515
Answer 4-
Weak_negative
-0.0029
Weak_negative
-0.0088
Weak_negative
-0.0168
Weak_positive
0.0477
Weak_negative
-0.0014
Weak_positive
0.0289
Weak_negative
-0.0583
Answer 5-
Weak_negative
-0.0388
Weak_negative
-0.0525
Weak_negative
-0.0750
Weak_positive
0.0793
Weak_negative
-0.0080
Weak_positive
0.0518
Weak_positive
0.0112
Answer 6-
Weak_negative
-0.0621
Weak_positive
0.1119
Weak_negative
-0.0549
Weak_negative
-0.0059
Weak_negative
-0.0022
Weak_negative
-0.0078
Weak_positive
0.0266
2) 控制(您同意或不同意多少?)
Answer 7-
Weak_positive
0.0275
Weak_positive
0.0215
Weak_positive
0.0643
Weak_positive
0.0500
Weak_negative
-0.0212
Weak_negative
-0.0730
Weak_negative
-0.0530
Answer 8-
Weak_positive
0.0120
Weak_negative
-0.0293
Weak_negative
-0.0408
Weak_positive
0.0309
Weak_positive
0.0898
Weak_negative
-0.0167
Weak_negative
-0.0492
Answer 8-
Weak_positive
0.0199
Weak_negative
-0.0318
Weak_negative
-0.0387
Weak_negative
-0.0009
Weak_negative
-0.0115
Weak_positive
0.0481
Weak_positive
0.0123
Answer 9-
Weak_positive
0.0328
Weak_positive
0.0098
Weak_positive
0.0143
Weak_negative
-0.0584
Weak_negative
-0.0088
Weak_negative
-0.0205
Weak_positive
0.0429
Answer 10-
Weak_negative
-0.0181
Weak_positive
0.0311
Weak_positive
0.0531
Weak_positive
0.0352
Weak_negative
-0.0795
Weak_positive
0.0107
Weak_negative
-0.0321
Answer 11-
Weak_negative
-0.1104
Weak_negative
-0.0442
Weak_negative
-0.0084
Weak_positive
0.0032
Weak_positive
0.0160
Weak_positive
0.0780
Weak_positive
0.0223
Answer 12-
Weak_positive
0.0003
Weak_positive
0.0609
Weak_negative
-0.0318
Weak_negative
-0.0797
Weak_negative
-0.0271
Weak_positive
0.0046
Weak_positive
0.0860


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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
Valerii Kosenko
產品負責人 SaaS SDTEST®

Valerii 於 1993 年獲得社會教育心理學家資格,此後將他的知識應用於專案管理。
Valerii 於 2013 年獲得碩士學位以及專案和專案經理資格。
Valerii 是探討 V.U.C.A. 不確定性的作者。使用螺旋動力學和心理學數理統計的概念,以及 38 個國際民意調查。
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