The head of the BBVA Data & Analytics’ Edge team, José Antonio Rodríguez-Serrano, who coordinates the innovation area in BBVA's center of excellence in data science, shares his insights into five key questions to understand the implications of this exponential technology in different economical sectors and spheres of society.
What is this technology all about?
It is a field in computer science that focuses on the study and development of systems capable of performing tasks that are normally reserved to human intellect, such as translating documents or recognizing people by their face. Also systems that learn how to behave autonomously, such as driverless cars, robots or software capable of playing Go.
It is a booming field, in constant development. The most mature part and with a higher practical impact is the part known as (“machine learning"), which allows to program systems to make automatic decisions based on huge datasets.
However, and despite the mounting hype, automatic learning and its more advanced applications, such as ‘deep learning’, are still far from behaving as autonomous agents with an intelligence comparable to that of humans and taking over the most complex and creative human tasks. Although they are better extracting patterns and executing repetitive tasks, the capability of putting pieces of information in context, finding causality or improvising responses with fragmented data is something that, for the time being, machines can’t still do easily.
An example of automatic learning is a system to detect what language is a tweet written in. Instead of coding a program that applies certain rules (such as finding letter “ñ” to detect Spanish), developers have been able to implement mathematical models that analyze millions of tweets in different languages and deduct functions to calculate the probability of a new string of characters corresponds to a specific language.
How will this affect businesses?
Tech giants are already using artificial intelligence in products we use every day. For example, the most popular social networks (Twitter, Instagram, Facebook) choose the posts they show and also detect inappropriate content using artificial intelligence algorithms. Amazon or Netflix recommend new products or movies inferring user preferences. Recently Apple rolled out its face recognition technology to unlock devices.
At BBVA, we’ve also started offering AI-powered products already, which bring new functionalities to our customers and allow us distance ourselves from our competitors, for example for recommending discounts, detecting unauthorized transactions or help customers plan their expenses based on past transactions.
An interesting point for company sis not so much the progress in artificial intelligence itself, but also on the IT platforms that support the storage and processing of vast datasets, as well as the availability of specialized software. This is going to put machine learning within the reach of more and more businesses. Maybe in certain sectors we will see AI functionalities go from being a differentiating factor to a standard feature that consumers expect.
On which sectors will artificial intelligence have a bigger impact?
AI is already transforming sectors such as e-commerce, digital marketing, or logistics, which have been actively working on it for years. Currently, on TV, auto makers are already advertising models with pedestrian detection, automatic braking and even self-driving functionalities, (Tesla).
In general, AI offers opportunities in all sectors that are going digital and have large amounts of data that were not being leveraged before. For example, in the financial sector, we see how banks and insurance companies are focusing on data science and artificial intelligence to develop more effective tools for employees, as well as for enhancing customer services and interactions. For example, through the BBVA apps, we have started to release functionalities that deliver added value to customers, using their personal information (offering them an overview of their financial standing, or meaningful notifications or recommendations). Thanks to digitization and artificial intelligence, a bank can become an organization that helps customers make better financial decisions, not just an entity that keeps and manages their money.
Do you think that companies are applying it correctly or taking full advantage of it?
We know about companies in our country that have been using AI-enabled technologies for decades. Computer vision is used to detect defects in manufacturing processes. When we enter the parking lot of the airport, a system reads our car’s license plate, and when they ask us for our ID card when checking into a hotel, it is probably scanned using a character recognition system to extract our data.
These are examples of mature artificial intelligence algorithms being used in products in a specific market niche or for a very specific application. Now we have the opportunity to find more innovative and disruptive use cases, where artificial intelligence is used across entire organizations on a regular basis or revolutionizes large industries. Here we always take tech giants as references, but one could think that this is not an adequate comparison. I suggest that we turn this argument around and think that if a sector in our country, such as banking, can go fully digital, perhaps the day will come when a bank is not so different from a company like Google or Amazon.
What challenges do companies face in terms of artificial intelligence?
A challenge that is a bit overlooked has to do with talent and internal culture. Artificial intelligence is not a service that is bought, but a practice, a way of working. It requires professionals with the adequate skills, knowledge and experience and usually entails the need for certain changes within the company, from digitization and data gathering processes, to deploying the required computational infrastructure. Also a cultural shift, which involves applying a more quantitative, creative mindset that fosters exploration more than traditional computer projects, and with visionary employees across the organization as a whole.
Jose Antonio Rodríguez-Serrano
Lead Data Scientist and head of the BBVA Data & Analytics' Edge team.
Linkedin: Jose Antonio Rodríguez-Serrano