Artificial Intelligence, or AI, is a topic that we hear much more frequently as time goes by, although the term was coined in the mid-twentieth century. We could say that it has only been a couple of decades since it has been creating roots in popular culture, where the accelerated integration processes of digital technology into our daily lives are due to the historical moment in which we find ourselves, this have led us to interact with it in a wide range of experiences that we perceive now as common and familiar that we are not always aware of this situation. We do not question it and we simply take it for granted.
If you are a curious enough person, questions may arise such as, what is artificial intelligence?, how did it come into our lives?, where is it?, how does it affect me?, how do I recognize it?, is it like in the movies?, am I in danger, will it take my job?, how does it benefit me?, is it already here?, how come we did not notice? and possibly many others.
This text is informative and introductory, for this reason we will approach the subject from a perspective in which you, as a reader, can observe it in your own life and how you have been interacting with AI for a long time.
What is AI? thanks to the same AI and the internet, you can find a fairly simple definition to assimilate that says something like this:
"In simple terms, Artificial Intelligence (AI) refers to systems or machines that mimic human intelligence to perform tasks and that have the ability to improve iteratively from the information they collect."
It is important to clarify that it is a discipline still in development stage, construction and constant evolution, where new developments and discoveries are happening almost every day, for this reason, trying to pigeonhole it into a single branch of application, we would be limiting the observation of everything that is happening, but it is already present in many industries.
Due to our cognitive biases and constant search for self-validation as the center of everything that happens in the world, we usually seek to associate Artificial Intelligence with Human Intelligence, hoping that the first is a mirror of the second, looking for a behavior like that of a human being, although there are branches in particular that seek to emulate a certain level of that interaction capacity, in reality its applications and therefore its mechanics are incredibly varied and different from how the human being works.
Currently we are still in the process of studying and understanding how human intelligence works, which has been the product of millions of years of evolution as living beings, and where other disciplines such as philosophy, psychology, and neuroscience among others, have allowed us to find some answers that previously eluded us about its mechanisms. So, we continue in the process of self-discovery and evolution in this area of knowledge, which is why, at this moment we aspire to create systems that emulate it, but in the background, we must recognize the completely different nature of AI, which is based on machines, on logical-mathematical systems and is where the importance of the verb "imitate" is emphasized. present in the current definition.
When we conceptualize, design and build computers, their systems and their processes, we start from a basic principle of manipulating electricity within a logical system based on mathematics, from which we could execute specific tasks expecting for a series of concrete results. That is, electric current passes or not, better known as 1's and 0's or binary system, this is the basis from which electrical, electronic, and computational systems start, very different from the electrochemical biological systems in our bodies.
Just as human beings and other living beings on this planet, we developed a communication mechanism to interact in our social and survival groups, we also did this with machines. No person in their daily life knows how to speak in binary, so new structures and layers of language were developed; an intermediate one from which machines communicate with other machines and another one from which human beings could interact with the computer, giving it instructions and programing it to execute a specific task that was useful to us (algorithms).
We required some easier way to communicate with them, operate them, manipulate them to perform a task efficiently, as we have been doing since humans began to use and develop primitive tools; one day we went from tying a stick to a stone to turning it into a hammer, these became the most advanced pieces of technology we had at that time. Today, we speak so naturally with a small speaker connected to the internet and ask it to play our favorite song.
The same thing happened with fire, writing, books, the steam engine, toilets, running water in bathrooms, electricity, the incandescent bulb, the switch, the telegraph, the radio, television, the internet, and many other things that we currently take for granted. We build them, we develop the most efficient ways to interact with them, and once assimilated by society, we stop recognizing them as the greatest piece of technology we had at the time, and we continue to build on the new layers of complexity that we have integrated into our lives.
Apparently, being exposed and familiar with something is the minimum required to normalize and integrate it into our lives, but unlike the way we used computers only about 10 years ago, we are at an intersection or a breaking point in the case of AI, we have taken it a step further, which has been significant for the combination of several elements, such as the versatility to program a current computer system, the expansion of the use of the internet, the hyperconnectivity in which we live today, how accessible digital technology has become for most people and the massive amount of data we produce and share online. We have fostered the conditions so that we not only program a specific task to be executed on a computer and it is repeated countless times, but also with each repetition, each iteration, as it is exposed to more tasks, circumstances and environments, it can learn from these improving exponentially, a situation that opens the possibilities unlike we had never experienced before.
But how do computers learn?
Machine Learning and Deep Learning are some of the processes by which a machine learns, which basically consist of feeding their systems massive amounts of data you want to learn, for example, if you want them to learn about how a cat looks, they are given a huge amount of photos and videos of cats, to be broken down and identify the elements and patterns of the images that identify the characteristics of a cat.
One of the best-known applications is image recognition, you can check this with every photograph you take with your smartphone, and it recognizes faces, when a social network suggests tagging a person in a photograph you just uploaded, when you use those cat and aging filters. These are ways in which AI has been applied and learned thanks to the massive amount of information we share online.
Another is application in robotics, and we are not referring only to those robots similar to humans or animals, but they are also present in warehouses, kitchens, domestic vacuum cleaners, drones, assembly plants and other industries with repetitive tasks that can be executed in less time and at a lower cost with robots that learn and improve the more times they perform a task.
They are also present in the recognition of sounds and voices, apps such as Shazam or dictation taking apps are a clear example of AI. This goes even further because there are AIs that can generate music on their own learning from the enormous amounts of sounds, styles and songs online.
Language recognition is another of the most notorious, which we can appreciate in the already so common customer service bots from many companies, that although some are obvious, you would be surprised to know how many there are when interacting with them. It becomes indistinguishable if you communicated with a human or with a machine. Online translation services have already surpassed the average human being in terms of language usage accuracy, not to mention text self-add-on systems when writing an email or sending a text.
Or you can already write a few words and an AI can write a full text on the subject.
The challenges of applying artificial intelligence in the development of Latin American cities such as Guadalajara in Mexico or Lagos in Nigeria can no longer be ignored. For example, Asian megacities face the challenge of increasing traffic congestion, which has reached levels where autonomous driving could be a practical solution.
In fact, plans to create systems to collect and analyse real-time data on traffic congestionor air pollution have begun to take shape. The aim is to facilitate decision-making on how best to deal with situations such as traffic jams. The Lagos Smart Mobility Program has already started with projects such as Link, a pilot project for autonomous electric vehicles, and the Coastal Zone Traffic Management System, to monitor both traffic flow and pollution levels.
The challenge is not only about traffic congestion, but also about the design of integrated solutions to address congestion and pollution. As Suresh Narayanan, an associate professor in the Department of Computer Science at the University of Texas in Dallas, explains.
The three paragraphs above were written entirely with Artificial Intelligence, and I show the following screenshots as evidence:
No doubt the ability to fluidly simulate the writing of a human being is more than proven, although at the moment it seems to lack something fundamental compared to the human being; the intention to write with a merely subjective and selfish purpose, when giving the first sentences, it moved completely away from what it intended to write, instead, it wrote about what it had more information in its data sets that it had access to.
On the other hand, there is something that is very similar to the human being, because we are only able to express or create from what we know or have been exposed at some point in our lives. A fact that is already beginning to happen with new variables and neural networks, through which they are able to interpret an image, a video, or a context, from the perspective or field in which that particular AI has been trained. In humans we call those "cognitive biases" or "reality filters".
Another sector that in particular has taken a juicy benefit from the use of AI is that of online marketplaces, where the most impressively notorious example on this side of the world is Amazon and in the East is Alibaba with all its subsidiaries and diversification of services.
Streaming services transformed the way we consume entertainment, educational platforms opened up a world of possibilities to learn new things, and if you're old enough, have you wondered how many times you've gone to the bank and be in the waiting line within the last couple of years compared to 10 years ago?
Fintechs powered by AI systems are changing the way we relate to money and resources, where systems such as blockchain and cryptocurrencies are disrupting global economic systems, stock exchanges and deploying new paths in the economy we did not think were possible.
No doubt they have completely changed the way we consume goods and services, these have transformed situations so common in our lives, that our routines and habits in cities have also been modified, the way we move within travel platforms on demand, or delivery platforms, as it is almost already a habit when leaving a place, we review the time it will take to reach our destination through the maps platforms.
All this is potentiated, influenced, based or focused on some type of artificial intelligence system or process.
These are just some examples that we can observe in our day to day life, but the list can go on and it is possible to delve even deeper into the subject, but the purpose of this introductory text was to show you how we use AI without greater friction than what we have with a human being.
We are at an incredibly interesting time in humanity regarding AI and we are fast approaching a point where some aspects of our lives will be indistinguishable or inseparable from it. Of course, there is still a long way to go, and we try to focus on the most exposed and positive examples.
An important reminder is that evolution and technology are amoral, and whether they are good or bad for someone, depends on the use we give it and how present we have new ethical principles around these issues, since there will be situations so complex where it will be incredibly difficult to discern as to the applicable morality, standing in a gray and unknown territory, to which we can only appeal to the context and accept our limitations, of what we know, what we did with what we had at that time, the rest is to walk forward full of curiosity and try new experiences.
About the author:
Juan Ponce Briseño, is an architect graduated from ITESO in 2006, Founder and General Director of "Laboratorio de Tecnología Urbana S.C." (LTU), a company dedicated to projects for systemic change for the best cities to livein; specialized in projects of integral accessibility, urban mobility, public space, urban design and information analysis.
He has participated in projects such as the Non-Motorized Mobility Plan for the AMG, Zones 30, Zapopan Tramway, Macrobus, Urban Image Manual for Guadalajara, Metro Cable de Caracas, Urban Development Regulation for the AMG, Member of Com:Plot Forum, Consultant for UN HABITAT in the Prosperous Cities Program, Guest Lecturer at the FOVUS Networks for Mobility congress in Stuttgart, Germany, and for the IDB's "Transport Week 2018, Big Data and its application to transport infrastructure" in Miami. Se has exhibited his work at the Venice Biennale 2016. He is currently developing together with a multidisciplinary team "LTU - City Tools", a smartcities and open data project, and "Ruta eseOese", a project to connect migrants with opportunities through Big Data.