PhD in Education, MA in Business Process Management, and MA in Governance and Organizational Culture from the University of Navarra. He currently serves as Corporate Director of Development and Graduate Programs at Universidad Autónoma de Chile, where he has also held roles as Director of Community Engagement, Director of Admissions, lecturer, and researcher.

The emergence of artificial intelligence (AI) in the workplace has raised numerous questions. On the one hand, its ability to increase efficiency and relieve people of routine tasks is widely celebrated. On the other hand, there is growing concern about the role humans will play when machines not only execute tasks but also create, respond, and decide. In this new scenario, soft skills are often proposed as a possible answer—but not without significant challenges.

In an environment where algorithms can already write texts, generate images, serve customers, and solve operational problems, it is inevitable to ask what a human worker can offer that a machine cannot. The most common—and perhaps most hopeful—answer is that human values such as empathy, creativity, and ethical judgment will remain irreplaceable. These so-called soft skills are now gaining unprecedented relevance (Niklander, 2023a).

However, relying on these qualities as a safeguard against automation is naïve if we fail to address the profound structural inequalities that hinder their development. In many Latin American countries, and particularly in Chile, the educational system remains focused on the transmission of rigid knowledge, neglecting the integral formation of the student. Skills such as collaboration, critical thinking, or ethical leadership are rarely among pedagogical priorities.

To this historical debt must be added a structural issue: the low participation of women in STEM fields (Science, Technology, Engineering, and Mathematics). This exclusion—prevalent both in Latin America and the United States—limits women’s access to sectors with the greatest labor prospects and highest wages. Moreover, it prevents the development of more inclusive technologies, those capable of incorporating diverse perspectives from their very design and application.

AI is neither neutral nor equitable by default. Without democratizing access to its use and understanding, technology risks becoming yet another factor of exclusion. According to recent reports by the World Bank, up to half of the jobs that could benefit from AI are currently constrained by a lack of access to digital technologies, connectivity, and adequate infrastructure. And, as is often the case, the most vulnerable sectors are the ones left behind (World Bank & ILO, 2023).

The digital divide, therefore, is not only a technical challenge but also a social barrier. Family conditions, the availability of devices, and teacher support are just as important as internet connectivity. Educational inequality inevitably translates into labor inequality. And if AI is implemented only in privileged contexts, it will merely deepen the divide between those who can innovate and those who struggle to survive within a system that excludes them.

The labor market, already undergoing profound transformation, is now being accelerated by generative AI. According to the World Economic Forum, nearly 50% of companies plan to automate part of their tasks in the coming years. Goldman Sachs estimates that more than 300 million jobs could be affected worldwide. Although global productivity may rise by 7% according to recent estimates, the distribution of this growth will not be equitable (Goldman Sachs, 2023).

In this context, the role of higher education institutions is essential. It is not enough to teach programming or technical skills. It is imperative to foster critical thinking, nurture creativity, strengthen professional ethics, and promote lifelong learning. AI demands new ways of teaching—but, more importantly, new reasons for learning. As UNESCO has pointed out, the development of digital competencies must be incorporated transversally, from school education to university training.

Amidst this debate, we must not forget what is essential: technology must serve people. AI can be a powerful ally if guided by humanistic values. But if it becomes an end in itself, we risk sacrificing our capacity for discernment, dialogue, and reflection. We have already seen how technological immediacy suppresses critical pause. The growing reliance on applications such as ChatGPT or virtual assistants may facilitate many tasks, but it also risks atrophying our ability to question, reason, and debate.

Beyond automation, the real question is whether our decisions will remain truly human. Will we be able to teach future generations how to live alongside AI without losing what makes us unique? Can we form citizens, not just users? Are we willing to question the kind of society we wish to build in this new landscape?

Ultimately, soft skills should not be seen as a desirable complement, but as the core of what makes us human in an increasingly automated environment. Only by articulating technology with equity, knowledge with critical thinking, and progress with inclusion, can we ensure that the future of work is truly a future for all.

Within this framework, it is essential to recall the warning of philosopher Alasdair MacIntyre, who argued that without a philosophical vision, any other area of knowledge remains incomplete. His proposition is clear: philosophy must reclaim its privileged place—not to impose answers, but to offer a critical and reflective framework from which to understand scientific and technological advances.

In a world where artificial intelligence redefines our cognitive and organizational capacities, philosophical thinking becomes more necessary than ever. Philosophy can help us integrate the multiple dimensions of knowledge, make ethical judgments about technology’s uses, and preserve the human essence amid algorithmic advancement. It is not only about adapting to the future but about reflecting on the kind of future we want to build.

The university, in its fullest sense, cannot forgo its mission to educate individuals capable of reflection, dialogue, and ethically grounded decision-making. AI challenges us all—but it is through critical education and humanistic reflection that we can respond with responsibility and depth.

References

• World Bank & International Labour Organization. (2023). The Impact of Artificial Intelligence on Labor Markets in Latin America. https://www.worldbank.org/
• CADEM. (2023). National Survey on Digital Access, Use, and Habits in Chile. https://www.cadem.cl/
• Goldman Sachs. (2023). Generative AI Could Raise Global GDP by 7%. https://www.goldmansachs.com/
• Niklander, G. (2023a). Replaced by AI? El Austral de La Araucanía. https://www.australtemuco.cl/
• Niklander, G. (2023b). Digital Divide and Educational Equality. Cooperativa Opinión. https://opinion.cooperativa.cl/
• Niklander, G. (2024). The Future of Work in Chile and AI: Challenges and Opportunities. Cooperativa Opinión. https://opinion.cooperativa.cl/
• Giménez, J., & Sánchez-Migallón, S. (2011). Diagnosis of the University in Alasdair MacIntyre: Genesis and Development of an Anthropological Project.