Premise
What follows is my personal opinion on what I consider plausible to happen in the not too distant future, it is not a prediction, much less a certainty, and as an opinion it must be taken and evaluated.
As a techno-optimist, I consider technological advancement as a whole to be a positive factor, and as such it must be encouraged and supported, but at the same time, like everything, it must be managed with attention, responsibility and above all: ethics.
Where deemed possible I have indicated a year in which I consider it likely that that specific aspect can be achieved or in any case take a form similar to that described.
Introduction
In the vortex of technological evolution, we are getting ever closer to a future that will radically redefine our perception of work, creativity and even the very concept of intelligence. The evolutions of artificial intelligence (AI) are laying the foundations for an epochal change, where every aspect of our daily lives will be intertwined with the omnipresent presence of algorithms and intelligent machines.
Large Language Models: The first piece.
The advent of Large Language Models (LLM) undoubtedly marks a turning point in the research and development of artificial intelligence, but it is only the first step in a race that promises to be intense and full of developments in the coming years. These models, such as the modern (November 2023) GPT-4, Claude, etc., have demonstrated the extraordinary ability to understand and generate human language at scale, paving the way for multiple applications in areas such as virtual assistance, creation of content, automatic translation and much more.
However, the race to the cutting edge of AI is set to evolve in increasingly ambitious directions. Developers are aiming for even larger and more complex models, capable of learning from more diverse data and understanding increasingly rich contexts. This implies not only an increase in the necessary computing power but also greater attention to training and the quality of the data used to train the models.
A crucial next step will be honing your contextual understanding and continuous learning ability. More sophisticated models will need to be able to understand not only the immediate meaning of words, but also the broader context in which they are used. This will require significant progress in understanding the semantics, irony, and cultural and social nuances that make human language so rich and complex.
The race to the cutting edge will not only be about the size of the models, but also their ability to adapt to specific industries and domains. Customizing and adapting the capabilities of an LLM to specific contexts will become a crucial focus, enabling more specialized and refined applications, such as advanced medical care, personalized scientific research and much more.
At the same time, the research will go beyond language alone. Vision, listening, understanding the environmental context and more complex interactions with users will become key objectives. AI will aim to become increasingly multimodal, integrating different input and output modalities to offer a more complete and natural experience.
In conclusion, Large Language Models represent an excellent starting point, but the race in artificial intelligence is destined to expand, embracing increasingly ambitious challenges and paving the way for a future in which machines will be able to understand and interact with the world more and more like humans.
I believe it is likely that Large Language Models will become less and less impactful and that instead the focus will be oriented towards AGI around 2030–2035.
My prediction is that the Turing Test will become obsolete by 2030 and will be replaced by a more sophisticated test that takes into account what, when the Turing was designed, was considered the limit to overcome.
AGI
AGI, or General Artificial Intelligence, represents the final goal in the field of artificial intelligence as we know it today, characterized by the ability to perform any human intellectual task. AGI is expected to not only reach, but radically surpass the capabilities of current Large Language Models (LLM), bringing artificial intelligence to an unprecedented level of understanding and adaptability.
LLMs are known for their exceptional ability to understand and generate natural language, but they are limited to specific contexts and do not have a deep understanding of the physical world or human interactions beyond text. AGI, in contrast, aims to overcome these limitations, demonstrating intelligence that can be generalized across a wide range of tasks and situations.
One of the key challenges in the transition to AGI will be acquiring a broader and deeper understanding of the context. The AGI should be able to extract knowledge from various sources, understand complex relationships between concepts, and apply their learning to new situations in a flexible way. While LLMs excel at manipulating language, AGI will extend to a wide range of sensory input and complex information from different sources.
Furthermore, AGI will feature an advanced form of machine learning and self-improvement. This ability to continuously learn and improve its performance over time is a key element in building general AI. LLMs are powerful in their ability to learn from large datasets, but AGI will need to go further, actively adapting to new information and improving their understanding and performance on their own.
Another crucial aspect is the ability to interact in a more sophisticated way with the physical environment and with humans. AGI should demonstrate social intelligence, understanding emotions, responding to nonverbal cues, and adapting to the nuances of human interactions. This represents a significant challenge compared to current language-focused models.
In conclusion, while the current Large Language Models represent a significant step in the evolution of artificial intelligence, AGI is destined to radically surpass them, bringing AI to a level of complexity and understanding that will radically transform our conception of artificial intelligence and its applications. The road to AGI will be characterized by technical, ethical and social challenges that will require prudent management to ensure sustainable and responsible benefits.
My prediction is that we will reach AGI by 2040, but that it will still not be able to surpass human intelligence, although it will come very close. This will happen, in my opinion, not before 2045.
Work
The traditional concept of work may gradually give way to an era in which employment is more like a paid hobby than a monotonous duty.
The automation of repetitive tasks and the efficiency of machines in performing specific tasks will free individuals from a tiring routine, allowing them to focus on more meaningful and personally rewarding activities. The evolution of AI could transform the very nature of work, pushing society towards a model in which creativity and innovation are key values.
My prediction is that work as we know it today will be obsolete by 2050, and that by 2100 no one will be working the traditional way anymore. The period is deliberately broad as the cultural change will be so drastic that it will require a generational change or two to assimilate.
Creativity
The future of creativity stands out as an evolving landscape, in which humans continue to hold the helm, despite witnessing a radical transformation that recalls, in a singular way, the roots of the past. While artificial intelligence and advanced technologies will profoundly influence the creative process, we are likely to see a rebirth of the fundamental principles of human inspiration.
In this scenario, human creativity will be more than ever a deliberate choice, a manifestation of our intrinsic capacity to imagine, innovate and express emotion. While machines can generate creative content based on models and data, the essence of human inspiration will remain irreducible to an algorithm. Art, literature, music and all forms of creative expression will retain the distinctive touch of human individuality, a signature that no algorithm can fully replicate.
We may witness a return to more traditional creative practices, inspired by manual skills and craftsmanship. Nostalgia for manual workmanship and craftsmanship could become a source of inspiration, causing people to seek a return to concreteness and authenticity in an increasingly digital world. Creativity could be shaped by a fusion of ancient and modern, incorporating age-old techniques with the possibilities offered by advanced technology.
However, as humans rediscover the roots of creativity, technology can still serve as a catalyst and amplifier of their ideas. Advanced tools can be used as a means to explore new creative frontiers, experiment with new media and take art to levels never seen before.
Ultimately, creativity in the future will remain a deliberate act of human beings, an articulation of our uniqueness and our ability to adapt to evolving challenges. The synthesis of ancient and modern could shape a creative landscape that celebrates human diversity, recognizing that creativity is, and will continue to be, an intrinsic trait of our species.
Education
The future of education promises to be a field of radical change, a place where the focus will shift from technical skills to an education more focused on humanistic, philosophical and artistic disciplines. In an era in which artificial intelligence and advanced technology will assume a predominant role in technical skills, the human essence will be increasingly reflected in subjects that challenge creativity, critical reflection and self-understanding.
The humanities will become key pillars of education, encouraging students to explore history, philosophy, literature and the arts. These subjects not only offer a critical perspective on past and present human experiences, but develop analytical, communication and critical thinking skills that are fundamental to tackling the complex challenges that the future will face us.
Philosophy, in particular, could emerge as a focus of education, stimulating critical and ethical thinking. In a world where decisions are increasingly influenced by algorithms and machines, philosophy will be able to offer a framework for addressing ethical and moral issues related to the use of artificial intelligence and advanced technology.
Artistic disciplines, including music, painting, theater and other creative expressions, will be integrated into the fabric of education to cultivate aesthetic sensitivity and stimulate individual creativity. Culture and the arts will become vehicles for exploring human diversity, promoting understanding and empathy between individuals of different origins and perspectives.
In this scenario, education will not only be a vehicle for acquiring specific knowledge, but also and above all an opportunity to develop a deep understanding of oneself and the surrounding world. The radical transformation of education will be a response to the needs of an evolving world, where distinctive human skills will be valued above simple technical knowledge, the domain of machines.
My prediction is that education will never do without technical subjects, but that they will no longer be compulsory by 2060. This ample time arises from the need for a generational change to assimilate such a radical change.
Politics
The future of politics will emerge as a context in which decisions and solutions to problems will be almost totally replaced by an ethical approach and conscious control of technological evolution.
While politics has traditionally focused on solving immediate challenges, the emergence of advanced technologies and artificial intelligence will lead society to reflect on fundamental ethical questions and the long-term implications of using certain technologies.
Controlling technological evolution will become a key responsibility for political leaders. While technological innovation offers extraordinary opportunities, it will be essential to mitigate the risks associated with it. Regulations and policies will need to be proactive in guiding technological development in an ethical way, ensuring transparency, security and accountability regarding new technologies.
The politics of the future will be characterized by greater international collaboration in managing global technology-related challenges, such as cybersecurity, the regulation of new technological initiatives and the management of ethical implications. Joint efforts to establish ethical international standards will help shape a future where technology serves the common good.
In this context, public participation and transparency will be crucial. Policy will no longer be an isolated process but will actively involve civil society, technology experts and affected communities in the decision-making process. The formation of informed and conscious policies will be essential to manage the complex challenges of an increasingly connected and technologically advanced world.
In conclusion, the politics of the future will be characterized by an ethical perspective and the awareness of the need to guide technological evolution in a responsible way. In this way, political leaders will be able to face emerging challenges with a vision oriented towards the common good and long-term sustainability.
My prediction is that in a political context the application of decentralized technologies, not necessarily via blockchain but similar, will first be strongly recommended and then made mandatory with a view to transparency by 2040.
Global Issues
Technological progress, driven by artificial intelligence and its ability to analyze data on a large scale, promises to be the bulwark that will transform our most serious daily problems into distant memories.
Global warming, a phenomenon that has threatened and continues to threaten the stability of our planet, could see a solution through the implementation of advanced technologies to monitor and mitigate greenhouse gas emissions. Intelligent systems could anticipate and manage climate fluctuations, offering preventive strategies that reduce environmental impact.
World hunger, one of the most complex challenges humanity faces today, could be overcome with the help of cutting-edge agricultural technologies. Artificial intelligence could optimize food production, improve distribution and ensure sustainable management of agricultural resources. Advanced monitoring systems, based on real-time data, could predict famines and coordinate timely responses to ensure that no individual goes hungry.
However, as we approach this potentially utopian future, it is crucial to address the ethical and social challenges that accompany the dominance of technology. We will need to ensure that access to these solutions is equitable and that decision-making power is not concentrated in limited hands. Furthermore, we will need to carefully consider the environmental impact of the very technologies we intend to use to solve environmental problems.
In summary, the future in which technology proactively prevents global problems may be on the horizon, but it is essential to adopt a holistic approach that balances technological effectiveness with an ethical and sustainable perspective. Only through a collective commitment to drive technological development responsibly can we hope to overcome the most pressing challenges of our time.
The use of the conditional is intentional in this section because although technology could allow such resolutions, politics and people will have to implement them, sometimes even giving up profits. The abandonment of unbridled capitalism is a prerequisite for the resolution of these problems but given today’s society it would be presumptuous of me to assume a plausible date of event.
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