AARYAN RAGHUNATHAN – 2024
Amid rampant fear that AI will exacerbate income inequality and polarization in the job market that has been proliferated by all technological change since 19801, a WEF report showed 133 million new job roles would replace 75 million jobs2. Projected to undergo an annual compounded growth of 37.3% between 2023 to 20303, AI is expected to contribute $15.7 trillion to the world economy by 2030– more than India and China’s current combined output4.
A study which analyzed the effect of industrial robot usage on labor markets from 1990-2007 demonstrated that while robot usage led to job loss, it also had a positive price-productivity effect– market expansion and increased labor demand5. With AI replacing jobs and the market expanding, AI transformation partially mirrors this trend, although augmented job types and composition. AI has created offshooting opportunities in human-computer interaction, emotional intelligence and ethics across tech and non-tech domains where AI applications can exist (medtech, legal tech, etc.).
AI’s predominant focus on automating mental tasks-related to ‘visual perception, speech, sentiment and decision making,6-over physical ones, is poised to have an unprecedented impact on the labor market. Beyond core AI skill development, the right policy frameworks like supportive regulations and tax concessions to encourage new job proliferation, will also nudge workers to build muscle in tangential professions that could complement AI and continue to be unique to human abilities.
MIT research identifies a silver lining to the inevitable job displacement of traditional roles– the emergence of novel job categories. These roles transcend traditional job paradigms, requiring unprecedented skills to rapidly teach nuanced aspects of human communication like sarcasm to AI systems (Trainers), bridge the gap between sophisticated algorithms and non-technical
business leaders (Explainers), and ensure the ethical operation of AI systems (Sustainers)7. This shift underscores the imperative for innovative training/development strategies in organizations. Public-private partnerships can prove extremely useful to drive this change– a collaboration Singapore has exemplified.
Gleaning inspiration from Singapore, economies can be made fertile with AI-friendly policy and strong digital infrastructure. Additionally, targeted AI investment to strengthen employability, career satisfaction, adaptability to evolving trends, and access to education/training can turn the tide favorably. Singaporean tech firm JobKred leverages Big Data to scrutinize global labor market trends, empowering its AI engine for comprehensive insights into job and skills dynamics8. Individuals can leverage this to acquire industry-relevant skills for an evolving job landscape using the AI integrated into JobKred’s workforce platform to access digital career guidance, skills gap analysis, and training recommendations.
To actually deliver the tool’s benefits, SkillsFuture Credit, a government initiative, further bolsters and creates a strong push for accessibility and adoption by allocating S$500 to Singapore citizens aged 25 and above for personal growth, which was utilized by 285,000 citizens in the first two years since its launch9. JobKred’s AI also supports Singapore’s national skills portal, MySkillsFuture.sg, aiding citizens in understanding their current skills, identifying gaps, and receiving targeted training recommendations to align with evolving skills demands9, thus creating an ‘ikigai’ intersection for citizens to leverage AI transformation.
Extrapolating the Singapore model globally could mitigate the frequency of ‘boom and bust cycles’ by bridging the job hunter-seeker gap across diverse skills, and foster an integrated, unified and stable job market for enhanced job security.
Similar initiatives that leverage AI can effect sustained improved worker prosperity. For instance, higher returns on personal savings may be accumulated by using AI-powered investment/saving platforms like Wealthfront10 or Digit11, and predictive analytics platforms like Kensho12. Moreover, since AI is furthering the OECD trend- where productivity grew at a faster pace than median wages1- AI policy can focus on building income security and bolstering wages by directing taxpayer money to Universal Base Income models. The UBI schemes in Alaska since 1982, and Finland have increased feelings of health, wellbeing, psychological security, and the freedom to delve into education/upskilling13 – cultivating enough security for people to start businesses.
Coupled with UBI security, AI can catalyze entrepreneurship and innovation. Descartes Labs is an example– its founders metamorphosed a government research unit’s work, Manhattan Project, into a sprawling company14. Descartes has created 150+ jobs15 through entrepreneurial usage of AI to give intelligent insights on disaster management and agricultural development
using computer vision and satellite imagery16.
While AI may have displaced traditional jobs, it has created space for many new roles. Through innovation, governments, markets and individuals can leverage AI to create opportunities, mitigate job market gaps, develop ethical AI and build income security to enhance personal income.
Figure 117
– AI generated image.
This image exemplifies my discussion – groups of people who can pioneer it will see prosperity and those who cannot, will see unemployment.
References
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