Reference Message Network reported on May 9 that the website of The Indian Express published an article on April 21 with the title "What Should We Humans Do in the Era When Machines Can Do Everything?" The author is Aditya Vishwanath. Compiled as follows:

In history, waves of innovation - such as the steam engine or the factory assembly line - mainly disrupted low-skill blue-collar jobs. Later, the digital revolution disrupted white-collar jobs through software and outsourcing. However, the era of artificial intelligence will be different. Nowadays, technology affects everyone, from low-paid workers to high-skilled programmers, architects, designers, and even artists. This influence covers everyone from top to bottom. With the development of generative artificial intelligence and automation, even highly creative and analytical professions are being reshaped.

This means that everyone must be able to continuously evaluate: what relevant skills do I have in a task? How easy are these skills to be replicated or replaced by technology?

The ability to learn new skills

Low-skill, low-replaceable jobs may still be safe - at least for now. But regardless of the type of job, it faces increasing risks. The only long-term advantage a person can master is the ability to quickly and continuously learn new skills.

When we talk about the role of artificial intelligence in future work, we actually refer to a series of basic capabilities - technical literacy and data literacy, which enable people to understand, use, and adapt intelligent systems. In the workplace, these are the real and clear abilities that constitute "artificial intelligence literacy".

Having technical literacy means a person knows how to operate machines, how digital systems work, and how automation tools are deployed across industries. Having data literacy means a person can interpret and analyze the vast amount of information increasingly influencing every decision-making process and take action accordingly.

These literacies must begin to be cultivated early - starting from primary and secondary schools and universities - not only to cultivate future engineers but also to prepare future artists, educators, policymakers, scientists, and frontline workers so they can adapt to a technology-driven world and play leadership roles within it.

In envisioning how education should respond to current realities, Joseph Aoun, president of Northeastern University, proposed a powerful framework called "Humanics." He posed this question: What should we humans do in the age when machines can do everything?

Building Education for the Future

Aoun believes that education for the future must be built on three pillars.

First, technical competence, which is the ability to understand how machines work and how to work with them. As artificial intelligence and robotics take over more tasks, workers who can interact with and enhance these systems will be more efficient and indispensable.

Second, data disciplines, which are about understanding, analyzing, and processing data. In a world that relies on algorithmic decision-making, the ability to navigate massive streams of information is crucial for strategic thinking and problem-solving.

Third, humanities, which include skills that machines (currently) cannot replicate: empathy, creativity, cross-cultural adaptability, and contextual reasoning. Because of these skills, humans can draw analogies, meaningfully innovate, and purposefully lead.

In practice, this means moving away from rote learning to promoting experiential, interdisciplinary, and lifelong education.

Valuing Short-Term Targeted Training

To achieve this transformation, a powerful tool is the evolving "microcredential" model: qualifications obtained through brief, focused training, allowing learners to acquire more and more skills over time. Overall, universities are incorporating these certificates into undergraduate and graduate programs - not just in computer science, but also in liberal arts, business, and sciences.

For example, a political science major can obtain a certificate in public policy data visualization. A historian can earn a certificate in AI-assisted archival research.

Importantly, these credentials align with the concept of lifelong learning. As job roles evolve rapidly, employees must constantly acquire new skills - not through expensive new degree certificates, but through easily accessible, flexible, and optional credentials. To prepare the next generation for future jobs that don't yet exist, an education system based on agency, adaptability, and equity must be established.

This means incorporating content to develop technical and data literacy in primary, secondary, and university curricula; training educators to impart future-focused skills rather than merely teaching knowledge; promoting the "microcredential" model to drive personalized, stackable learning; and encouraging interdisciplinary applications of technology across all fields, from art to healthcare to agriculture.

The future of work is uncertain, but not uncontrollable. By broadly developing students' technical and data literacy, teaching human-centered skills, and enabling lifelong learning, we can give every student the opportunity to carve out their own path in the world of intelligent machines.

This is not just about cultivating artificial intelligence engineers; it's about fostering large numbers of creators, problem solvers, and adaptable thinkers who should already be prepared to play leadership roles in the rapidly evolving global economy. (Translated/By Hu Xue)

Original source: https://www.toutiao.com/article/7502314169807536692/

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