Context:

• In the past, waves of innovation, such as assembly lines or steam engines, have mostly affected low-skilled, blue-collar jobs.
• Later, the digital revolution affected white-collar jobs through software and outsourcing.
• The AI era, however, is distinct. India is facing a multidimensional employment crisis - one that is both visible and invisible.

A Dual Employment Crisis:

• Visible crisis:
  • Youth unemployment: Over 80% of unemployed Indians are youth, many with secondary or higher education.
  • Disengagement: 1 in 3 young Indians is disengaged from both work and learning.
  • Job creation needs: India must create over 90 million new jobs by 2030, many in yet-to-emerge fields.
• Invisible crisis:
  • Changing nature of work: Rise of AI, automation, and data-driven systems is reshaping work across sectors.
  • Key concern: Every worker must ask - “How replaceable is my job with technology?”

AI Era - A Paradigm Shift in Job Disruption:

• The AI age disrupts all levels - from low-wage laborers to high-skill professionals (e.g., programmers, designers, artists).
• Creative and analytical jobs are increasingly at risk due to generative AI.

The Core Competency - Adaptability through Learning:

• Job security matrix:
  • Low-skill, low-replaceability jobs may survive
  • High-skill or low-skill but high-replaceability roles are most vulnerable.
  • Reskilling and lifelong learning emerge as the only durable edge.
• Essential skills:
  • Tech literacy: Understanding digital systems, AI, automation.
  • Data literacy: Ability to interpret and act on large volumes of information.

Education for the Future - A Humanistic Approach:

• Joseph Aoun’s “Humanics” framework:
  • Technical ability: Skills to work with machines and augment productivity.
  • Data discipline: Strategic thinking using algorithmic and analytical tools.
  • Human discipline: Creativity, empathy, contextual reasoning — uniquely human capabilities.
• Shift required: Move from rote learning to experiential, interdisciplinary, and lifelong learning models.

Micro-Credentials - Modular Learning for a Modular Future:

• Definition and importance:
  • Micro-credentials are short, focused certifications offering stackable learning experiences.
  • Already being embedded in global universities across disciplines.
• Application in India:
  • Could reform India’s rigid, degree-centric higher education system.
  • Encourage interdisciplinary learning - e.g., data visualisation for political science or AI tools in historical research.

Strategic Imperatives for India:

• Embed literacy in education:
  • Integrate tech and data literacy from school to college.
  • Train educators to become facilitators of future-ready skills.
• Promote lifelong learning:
  • Encourage accessible, modular upskilling over traditional degree paths.
  • Support micro-credential ecosystems aligned with evolving job markets.
• Foster cross-sectoral tech integration:
  • Apply AI and data tools across arts, agriculture, healthcare, and policy-making.
  • Enable personalised learning pathways to prepare for jobs that don't yet exist.

Conclusion - Shaping the Future of Work:

• The future of work is uncertain but within control.
• India must cultivate problem-solvers, creators, and adaptive thinkers.
• Focus should not just be on AI engineers, but on empowered individuals across sectors who can lead in a tech-driven global economy.