G20 Policy Implications for the Future of Work

Emerging technologies such as Artificial Intelligence, Chabots, and Robotics will change the world of work as we know it. Scholars predict that the emergence of AI will result in the loss of repetitive and routine jobs. Chatbots in various sectors may result in the automation of several jobs. AI-led art may restrict design-specific roles and employment. This will also affect women more, considering they are more likely to occupy entry-level positions which risk automation. While there are risks, technology disruptions bring opportunities for young people - dangerous occupations may be automated and possibilities for greater equity for all. It is, therefore, crucial that government interventions and policy pathways reimagine the future of work while working to make the gains of technology equitable and fair for all while responding to and employing emergent technologies in innovative ways. For the skilling sector, based on our experience

1. Increase focus on self-learning and 21st-century skills in the TVET ecosystem - Research suggests that a young person changes multiple jobs in her lifetime against the fast paced changing world of work. This will require skilling institutes to respond by teaching critical skills and dispositions such as self-learning, adaptability, and cognitive flexibility, among others. Also, emphasize lifelong learning and Futures literacy as a crucial skill set for young people.?
2. Focus on the creation of learning environments in the TVET ecosystem for self-learning: Our work with the youth shows that learning environments may be nurtured in ways that self-learning can be inculcated, which is crucial against the advances of AI in the fast-changing world of work. This is possible by prioritizing a learner-centric learning process, prioritizing a learning climate where there is safety and dignity for all learners, and trust in a flexible environment for learners.
3. Recognition of informal learning - Several youths can now self-learn skills online and utilize technologies in innovative ways. Extending credits to informally learned skills online in their respective courses will bring greater flexibility for youth and formalize learning.??
4. Address digital poverty and harness emerging technologies to create blended learning programs - While there is an advance in technology, there is still a digital divide that persists in the country. Policy directions must address digital poverty. When relevant, students must be allowed options for a blended delivery format to allow flexibility in online and in-person designs.? Quest Alliance’s experience introducing offline models such as the Quest app has shown considerable uptake and increased completion of employability skills modules in the online format providing flexibility and greater autonomy for students.?
5. Innovate Curriculum and delivery responsive to Future of Work trends - Revisiting Curriculum and including cutting-edge technology-based trades holds great potential to make the skilling sector more aspirational for youth.

• Considering that digital skills are required in sectors not traditionally in the digital industry. The TVET ecosystem must prioritize these skills.
• Make allowances in the Curriculum to take preferred online courses, which can be given formal credits.

1. Prioritize Digital Empowerment: It is also crucial to move beyond digital skills provided for digital literacy to move beyond it to digital empowerment. Trends in the Future of Work suggest that the Online platforms economy is trending and booming in India today, with online platform work replacing traditional income sources - institutions must have a Curriculum on accessing and benefiting from it, including introducing skills to access popular platforms to enlist on, individual brand building and moving beyond digital skills and fluency to digital empowerment where AI biases and an understanding of how AI may influence youth choices.
2. Prioritize diversity and inclusion: Policymakers should prioritize diversity and inclusion by creating programs that support underrepresented groups, including women, people with disabilities, and minority groups. This includes providing access to learning opportunities, mentorship, and support networks. Technology models may also be utilized to overcome some of the existing? information bias. For instance, our experience suggests that women choose traditional trades because of how information on trades and vocational programs reaches them - mainly through word of mouth and close contacts such as relatives and family. Therefore it is more likely that they are recommended courses that society deems fit for women.?
3. While AI may be utilized to counter some of the existing biases, it is also true that it may worsen or amplify biases. For instance, AI based hiring has shown to bring discriminatory practices. Therefore regulations against such practices and sensitizing industries to carry audits of their hiring practices is crucial.?
4. Build a robust social security system that can support workers in case of job loss or other unforeseen circumstances. With the increasing prevalence of automation and AI, many sectors are witnessing job losses. Therefore, creating a safety net that can protect workers from financial distress.?

Additionally, AI advances can depress wages more. While there is a declining share of total income to labour and with emerging technologies, it is likely to worsen. Policy measures must consider increasing entry level wages for skilling sector graduates, which may also contribute to making skilling sector trades aspirations.