اختبار على أساس كتاب «Spiral Dynamics:
Mastering Values, Leadership, and
Change» (ISBN-13: 978-1405133562)
الرعاة

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.

الذكاء الاصطناعي ونهاية الحضارة

بلد
لغة
-
Mail
إعادة حساب
القيمة الحرجة معامل الارتباط
التوزيع الطبيعي ، بقلم ويليام سيلي جوسريت (طالب) r = 0.0763
التوزيع الطبيعي ، بقلم ويليام سيلي جوسريت (طالب) r = 0.0763
التوزيع غير الطبيعي ، بواسطة سبيرمان r = 0.0031
توزيعغير
طبيعي
طبيعيغير
طبيعي
طبيعيطبيعيطبيعيطبيعيطبيعي
كل الأسئلة
كل الأسئلة
1) السلامة (كم توافق أو لا توافق؟)
2) السيطرة (كم توافق أو لا توافق؟)
1) السلامة (كم توافق أو لا توافق؟)
Answer 1-
ضعيفة إيجابية
0.0777
سلبية ضعيفة
-0.0017
ضعيفة إيجابية
0.1092
سلبية ضعيفة
-0.0962
سلبية ضعيفة
-0.0080
سلبية ضعيفة
-0.0552
ضعيفة إيجابية
0.0081
Answer 2-
ضعيفة إيجابية
0.0284
سلبية ضعيفة
-0.0021
ضعيفة إيجابية
0.0401
سلبية ضعيفة
-0.0306
ضعيفة إيجابية
0.0454
ضعيفة إيجابية
0.0019
سلبية ضعيفة
-0.0624
Answer 3-
سلبية ضعيفة
-0.0148
سلبية ضعيفة
-0.0525
سلبية ضعيفة
-0.0058
ضعيفة إيجابية
0.0491
سلبية ضعيفة
-0.0105
سلبية ضعيفة
-0.0073
ضعيفة إيجابية
0.0170
Answer 4-
ضعيفة إيجابية
0.0200
ضعيفة إيجابية
0.0079
ضعيفة إيجابية
0.0182
سلبية ضعيفة
-0.0410
سلبية ضعيفة
-0.0312
سلبية ضعيفة
-0.0129
ضعيفة إيجابية
0.0492
Answer 5-
سلبية ضعيفة
-0.0039
سلبية ضعيفة
-0.0100
سلبية ضعيفة
-0.0185
ضعيفة إيجابية
0.0480
سلبية ضعيفة
-0.0029
ضعيفة إيجابية
0.0303
سلبية ضعيفة
-0.0560
Answer 6-
سلبية ضعيفة
-0.0419
سلبية ضعيفة
-0.0561
سلبية ضعيفة
-0.0823
ضعيفة إيجابية
0.0800
سلبية ضعيفة
-0.0010
ضعيفة إيجابية
0.0522
ضعيفة إيجابية
0.0143
Answer 7-
سلبية ضعيفة
-0.0573
ضعيفة إيجابية
0.1175
سلبية ضعيفة
-0.0547
سلبية ضعيفة
-0.0125
سلبية ضعيفة
-6.21E-5
سلبية ضعيفة
-0.0097
ضعيفة إيجابية
0.0262
2) السيطرة (كم توافق أو لا توافق؟)
Answer 8-
ضعيفة إيجابية
0.0276
ضعيفة إيجابية
0.0169
ضعيفة إيجابية
0.0584
ضعيفة إيجابية
0.0588
سلبية ضعيفة
-0.0179
سلبية ضعيفة
-0.0742
سلبية ضعيفة
-0.0555
Answer 9-
ضعيفة إيجابية
0.0091
سلبية ضعيفة
-0.0293
سلبية ضعيفة
-0.0387
ضعيفة إيجابية
0.0311
ضعيفة إيجابية
0.0866
سلبية ضعيفة
-0.0157
سلبية ضعيفة
-0.0475
Answer 10-
ضعيفة إيجابية
0.0185
سلبية ضعيفة
-0.0339
سلبية ضعيفة
-0.0417
سلبية ضعيفة
-0.0008
سلبية ضعيفة
-0.0139
ضعيفة إيجابية
0.0505
ضعيفة إيجابية
0.0172
Answer 11-
ضعيفة إيجابية
0.0354
ضعيفة إيجابية
0.0114
ضعيفة إيجابية
0.0160
سلبية ضعيفة
-0.0624
سلبية ضعيفة
-0.0125
سلبية ضعيفة
-0.0172
ضعيفة إيجابية
0.0431
Answer 12-
سلبية ضعيفة
-0.0214
ضعيفة إيجابية
0.0351
ضعيفة إيجابية
0.0631
ضعيفة إيجابية
0.0355
سلبية ضعيفة
-0.0734
ضعيفة إيجابية
0.0030
سلبية ضعيفة
-0.0416
Answer 13-
سلبية ضعيفة
-0.1083
سلبية ضعيفة
-0.0422
سلبية ضعيفة
-0.0106
سلبية ضعيفة
-0.0007
ضعيفة إيجابية
0.0128
ضعيفة إيجابية
0.0780
ضعيفة إيجابية
0.0287
Answer 14-
ضعيفة إيجابية
0.0034
ضعيفة إيجابية
0.0638
سلبية ضعيفة
-0.0297
سلبية ضعيفة
-0.0846
سلبية ضعيفة
-0.0220
ضعيفة إيجابية
0.0039
ضعيفة إيجابية
0.0817


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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
فاليري كوسنكو
مالك المنتج SaaS مشروع الحيوانات الأليفة SDTEST®

تم تأهيل فاليري كأخصائي في علم النفس التربوي الاجتماعي في عام 1993، ومنذ ذلك الحين طبق معرفته في إدارة المشاريع.
حصل فاليري على درجة الماجستير ومؤهل مدير المشروع والبرامج في عام 2013. وخلال برنامج الماجستير، أصبح على دراية بخريطة طريق المشروع (GPM Deutsche Gesellschaft für Projektmanagement e. V.) والديناميكيات الحلزونية.
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