¿Qué es la IA?

What is Artificial Intelligence?

Artificial Intelligence (AI) is a type of technology that enables computers and machines that seem to mimic human thinking and learning. It analyzes massive amounts of data and then, using the existing data's language, makes a prediction, writes text, or produces an image.

What can AI do?

AI systems can help solve problems, make decisions, and perform tasks, often improving over time as they "learn" or are corrected / guided from the data they are given. In short, AI helps machines act smart and do things like recognize speech, understand text, or even suggest creative ideas, much like how humans would.

If you use a mobile phone, it is likely that you interact with AI every day. Virtual assistants like Siri or Google Assistant use AI to answer questions and perform tasks. AI powers your camera to enhance photos, recognizes your voice commands, and suggests replies in messaging apps. It also curates personalized content on social media, recommends music or videos, and helps detect spam emails. When you use Google Maps for directions or perform internet searches, AI is working behind the scenes to provide accurate location results and route suggestions, making your phone more helpful to you in daily life.

Background understanding of AI

According to Professor John Lennox, Christian Mathematician and Philosopher, the term artificial intelligence, was coined in a summer school held at the mathematics department of Dartmouth University in 1956. The conference was organized by John McCarthy, who said, “AI is the science and engineering of making intelligent machines.” [John C. Lennox, 2084: Artificial Intelligence and the Future of Humanity. Zondervan Reflective, 2020, USA].

Two forms of AI

Lennox helpfully identifies two categories of AI: "narrow AI" and "Artificial General Intelligence" (AGI). Narrow AI refers to the current state of AI, where machines can perform specific tasks better or faster than humans. On the other hand, AGI would involve AI developing to a level where it could completely replace human capabilities. Although science fiction often focuses on AGI, research is not yet close to achieving this form of intelligence. Earlier attempts at machine learning include the Enigma machine used to code break during WWII, and machines developed to win chess games against humans. The new development, reflected in current AI, is the employment of algorithms to ‘learn’ to solve not just one problem but a whole class of problems.

Current AI, or narrow AI, operates through an algorithm embedded in software. An algorithm (derived from the name of a famous Persian mathematician, Muhammad ibn Musa alKhwarizmi, 780 to 850) is, “a precisely defined set of mathematical or logical operations for the performance of a particular task," (Oxford English Dictionary). The key feature of an algorithm is that once you know how it works, you can solve not only one problem, but a whole class of problems.

Wide Uses of AI

AI is a versatile technology and can enhance activity in a wide variety of areas including healthcare, finance, entertainment, transportation, and education. AI applications can be categorized into several main types, each serving different purposes. Here are some of the key categories:

Type	Description
Natural Language Processing (NLP)	This includes applications like chatbots, language translation, and sentiment analysis. NLP enables machines to understand and generate human language.
Computer Vision	Applications in this category involve image and video analysis, such as facial recognition, object detection, and autonomous vehicles.
Machine Learning	This encompasses predictive analytics, recommendation systems, and anomaly detection. It involves training models on vast amounts of data to make predictions or decisions.
Robotics	AI is used in robotics for tasks like automation in manufacturing, drones, and robotic assistants in healthcare.
Expert Systems	These are AI programs that mimic human decision-making in specific domains, such as medical diagnosis or financial forecasting.
Speech Recognition	Applications like virtual assistants (e.g., Siri, Alexa) and voice-to-text systems fall under this category.
Game AI	This includes AI used in video games for non-player character behaviour and strategic planning.
Reinforcement Learning	Used in applications where an agent learns to make decisions by receiving rewards or penalties, like in game playing or robotic control.
Predictive Maintenance	AI is applied in industries to predict equipment failures and schedule maintenance proactively.
Personalization	AI helps tailor content and experiences to individual users, such as in e-commerce and media streaming services.

Difference between Human Intelligence and AI

Artificial Intelligence is different from Human Intelligence in several main ways.

Type	Description
Processing Speed	AI can process data and perform calculations much faster than the human brain, especially for large datasets and complex computations.
Learning Methods	AI typically relies on enormous amounts of correctly labelled data for training (supervised learning) or learns through trial and error (reinforcement learning). In contrast, humans learn through a combination of experiences, social interactions, and intuitive understanding, often with minimal data.
Generalization vs. Specialization	Humans excel at generalizing knowledge across different domains, allowing for flexible thinking and creativity. AI tends to be specialized, performing well in specific tasks for which it has been trained but struggling to adapt to new, unrelated tasks without additional training.
Understanding and Context	The human brain has a rich understanding of context, emotions, and nuances in communication. AI may struggle with ambiguous situations and often lacks true understanding, relying instead on patterns learned from data.
Consciousness and Intuition	Humans have consciousness, self-awareness, and intuition, allowing for complex emotional responses and moral reasoning. AI operates without consciousness or emotions, making decisions based solely on algorithms and data.
Creativity	While AI can generate creative outputs (like art or music), human creativity involves emotions, experiences, and the ability to think abstractly, often leading to innovative ideas that AI cannot replicate in the same way.

The complementary strengths and weaknesses of AI and human intelligence point us towards the benefits of collaborating rather than competing.