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.

Зеҳнии сунъӣ ва охири тамаддун

кишвар
забон
-
Mail
Такрор мекунад
Арзиши интиқодии коэффитсиенти коррелятсионӣ
Тақсимоти муқаррарӣ, ки аз ҷониби Вилям Веллети баҳрӣ (донишҷӯ) r = 0.0874
Тақсимоти муқаррарӣ, ки аз ҷониби Вилям Веллети баҳрӣ (донишҷӯ) r = 0.0874
Тақсимоти муқаррарӣ, аз ҷониби Spearman r = 0.0039
ТащсимотНачандонМуқаррарӣМуқаррарӣМуқаррарӣМуқаррарӣМуқаррарӣМуқаррарӣМуқаррарӣ
Ҳама саволҳо
Ҳама саволҳо
1) Бехатарӣ (чӣ қадар розӣ ҳастед ё розӣ нестед?)
2) Назорат (чӣ қадар розӣ ҳастед ё розӣ нестед?)
1) Бехатарӣ (чӣ қадар розӣ ҳастед ё розӣ нестед?)
Answer 1-
Заифи мусбат
0.0647
Заифи манфӣ
-0.0402
Заифи мусбат
0.1238
Заифи манфӣ
-0.1305
Заифи мусбат
0.0097
Заифи манфӣ
-0.0535
Заифи мусбат
0.0344
Answer 2-
Заифи мусбат
0.0497
Заифи мусбат
0.0373
Заифи мусбат
0.0295
Заифи манфӣ
-0.0054
Заифи манфӣ
-0.0046
Заифи манфӣ
-0.0176
Заифи манфӣ
-0.0596
Answer 3-
Заифи манфӣ
-0.0307
Заифи манфӣ
-0.0330
Заифи мусбат
0.0063
Заифи мусбат
0.0822
Заифи манфӣ
-0.0127
Заифи манфӣ
-0.0159
Заифи манфӣ
-0.0149
Answer 4-
Заифи манфӣ
-0.0069
Заифи мусбат
0.0432
Заифи мусбат
0.0293
Заифи манфӣ
-0.0238
Заифи манфӣ
-0.0470
Заифи манфӣ
-0.0193
Заифи мусбат
0.0315
Answer 5-
Заифи мусбат
0.0069
Заифи манфӣ
-0.0237
Заифи манфӣ
-0.0152
Заифи мусбат
0.0131
Заифи манфӣ
-0.0018
Заифи мусбат
0.0608
Заифи манфӣ
-0.0308
Answer 6-
Заифи манфӣ
-0.0388
Заифи манфӣ
-0.0576
Заифи манфӣ
-0.1067
Заифи мусбат
0.0816
Заифи мусбат
0.0191
Заифи мусбат
0.0491
Заифи мусбат
0.0162
Answer 7-
Заифи манфӣ
-0.0360
Заифи мусбат
0.0619
Заифи манфӣ
-0.0510
Заифи манфӣ
-0.0486
Заифи мусбат
0.0403
Заифи мусбат
0.0061
Заифи мусбат
0.0322
2) Назорат (чӣ қадар розӣ ҳастед ё розӣ нестед?)
Answer 8-
Заифи мусбат
0.0254
Заифи мусбат
0.0424
Заифи мусбат
0.1084
Заифи мусбат
0.0601
Заифи манфӣ
-0.0356
Заифи манфӣ
-0.1149
Заифи манфӣ
-0.0695
Answer 9-
Заифи мусбат
0.0118
Заифи манфӣ
-0.0446
Заифи манфӣ
-0.0559
Заифи мусбат
0.0325
Заифи мусбат
0.0961
Заифи манфӣ
-0.0228
Заифи манфӣ
-0.0252
Answer 10-
Заифи мусбат
0.0535
Заифи манфӣ
-0.0376
Заифи манфӣ
-0.0089
Заифи манфӣ
-0.0281
Заифи манфӣ
-0.0308
Заифи мусбат
0.0262
Заифи мусбат
0.0309
Answer 11-
Заифи мусбат
0.0157
Заифи мусбат
0.0103
Заифи манфӣ
-0.0089
Заифи манфӣ
-0.0482
Заифи мусбат
0.0039
Заифи мусбат
0.0010
Заифи мусбат
0.0318
Answer 12-
Заифи манфӣ
-0.0377
Заифи мусбат
0.0444
Заифи мусбат
0.0304
Заифи мусбат
0.0435
Заифи манфӣ
-0.0755
Заифи мусбат
0.0475
Заифи манфӣ
-0.0432
Answer 13-
Заифи манфӣ
-0.1232
Заифи манфӣ
-0.0353
Заифи манфӣ
-0.0230
Заифи мусбат
0.0330
Заифи манфӣ
-0.0105
Заифи мусбат
0.0883
Заифи мусбат
0.0191
Answer 14-
Заифи мусбат
0.0124
Заифи мусбат
0.0425
Заифи манфӣ
-0.0572
Заифи манфӣ
-0.1125
Заифи мусбат
0.0256
Заифи мусбат
0.0326
Заифи мусбат
0.0763


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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
Валерий Косенко
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