Understanding Artificial Intelligence in Everyday Life
People interact with AI daily, often without realizing how it works or how it shapes decisions, conversations, and work. AI has spread rapidly, yet many Canadians and Americans remain unfamiliar with its inner mechanics. Jordi Torres, a researcher at the Barcelona Supercomputing Center and a professor at the Universitat Politècnica de Catalunya, aims to bridge that gap.
After more than two decades of study, Torres has released Explaining Artificial Intelligence to Humans, published by Plataforma Editorial in 2023. The book examines the social, economic, political, and cultural implications of AI and how technology could influence everyday life. He also serves as a consultant for the Artificial Intelligence exhibition hosted by CCCB beginning October 18.
Artificial intelligence emerged in the mid-20th century, but its profile surged last year with the debut of conversational agents such as ChatGPT. Was this a surprise? The power of the technology was anticipated, since the underlying language models existed in academic circles, yet public participation and curiosity exceeded expectations.
When people hear AI, they often picture conscious robots. What is the simplest way to explain what AI really is?
AI is an evolving idea born in 1956. Its meaning has shifted as technology has advanced. At its core, AI reflects the progression of computing and data processing rather than a static entity.
Modern AI systems are trained on large language models, drawing from vast text datasets. They respond to user queries by pattern matching learned from those data. Some observers describe chatty AI as capable of mimicking conversation without true understanding or awareness of causality.
They answer plausibly but can also produce misinformation. The concern is real: synthetic data used to train AI can introduce or amplify inaccuracies if the data contain errors or falsehoods. Even when the data come from the internet at large, models can learn to treat mistaken information as valid, affecting future answers. This does not create new knowledge, but it can distort existing data and lead to unreliable outputs. Prior information on the web sometimes contained inaccuracies, and the rise of misinformation resembles past challenges with fake news.
Some supporters of AI point to ambitious goals, such as General Artificial Intelligence, while others caution about safety and ethics. The reality is that current technology has no conscience and is guided by human oversight. Experts argue we are not near achieving sentient machines, and a balanced approach should emphasize beneficial uses for science while mitigating negative effects, including misleading content or misuse in security contexts.
One claim often echoed is that AI could usher in a revolution comparable to steam, electricity, or the internet itself. The truth is that the world will change, but the extent of that change remains uncertain. Understanding AI helps communities decide the direction of this transformation and encourages collective awareness.
Despite concerns, major tech voices warn about risks to humanity. Notable figures raise questions about safety, conflict of interest, and accountability. It is important to scrutinize claims and recognize that AI is a powerful tool that requires careful management to curb misinformation and prevent harmful deployment, including military uses that should be restricted.
What does a supercomputer contribute to this landscape? Founded decades ago, Barcelona’s supercomputing facility demonstrates how massive computing power enables rapid processing of enormous data volumes and the execution of complex algorithms. Such power drives advances across disciplines, including health research, climate science, and materials discovery. A handful of European facilities lead this field, with Barcelona hosting one of the most capable systems. These machines push the boundaries of what is computationally possible, often delivering insights that would take far longer on regular computers.
As systems scale, so do data needs, computational speed, and energy usage. Balancing performance with sustainability becomes essential when AI research touches climate modeling and environmental monitoring. Even though training large models demands substantial energy, AI can help address pressing global challenges if developed with responsible practices and transparent methodologies.
What might the next decade hold for AI? Many industries have proposed potential impacts, though predictions vary widely. The field has advanced rapidly through larger datasets and faster hardware, but continued exponential growth may face practical limits, including chip availability and energy costs. The conversation now shifts toward responsible innovation that aligns with societal values and ecological considerations. In short, AI progress will likely be transformative, but exact outcomes remain uncertain, and deliberate planning matters.
In the broader North American context, researchers emphasize education, ethics, and governance to ensure AI serves public interest. Widespread adoption should be accompanied by clear explanations of how models work, what they can and cannot do, and how users can verify information. This approach helps communities navigate the AI era with confidence and accountability [Source: Jordi Torres, Barcelona Supercomputing Center].
Ultimately, the aim is to empower people to understand AI rather than fear it. By demystifying how these systems learn, respond, and sometimes err, readers can participate in shaping a future where technology enhances science, health, and daily life while safeguarding truth and trust [Source: Jordi Torres, Barcelona Supercomputing Center].
“Life before the internet is not the same as life after the internet, but we survived.”
Public debates about AI risk and opportunity continue to evolve. The focus remains on practical uses, ethical considerations, and the need for informed discourse that centers on human well-being rather than hype.
In sum, AI is an amplifier of computing power and data. It offers many benefits, but it also demands responsible stewardship to ensure accuracy, transparency, and fairness. As research advances, so does the imperative to educate people about what AI can and cannot do, enabling better decisions for communities across Canada, the United States, and beyond.