She is one of five women, compared to four men, who make up a female majority in the group of wise men that advises the Government on the preparation of a White Paper on artificial intelligence (AI). Elena Alfaro, CEO of BBVA Data Analytics, welcomes us at the Data Neuralgic Center where the financial institution creates its solutions and experiences in which artificial intelligence has something to say.
However, Elena does not like the term artificial intelligence. She prefers to talk about translation, navigation, search engines or voice recognition that use AI technologies such as machine learning or machine learning, deep learning or deep learning, and neural networks or neural networks. Calling something AI, it seems that we are talking about the Terminator, and nothing is further from the truth.
There are many references in AI for Elena Alfaro, but without a doubt, for her, the number one is Geoffrey Hinton, who is known as the father of Deep Learning, and who is giving positive results in some aspects such as image recognition, autonomous driving, or translation using natural language processing. Hinton works at Google and is a professor at the University of Toronto.
In what Elena Alfaro is also exhaustive is that we should be more afraid of how AI is being applied today , when a sufficient level of progress has not yet been reached, than of what it will bring us in 20 years. There are many decisions that are being made today through algorithms and machines that should concern us more than the fact that in the future machines have human capabilities.
That said, the CEO of Data and Analytics at BBVA believes that the evolution of AI involves complementing people. The combination of people and machines is what will allow us to advance in many economic and social areas, quality of life, and so on. “ And, honestly, I’m not afraid of this,” says Elena Alfaro.
Elena does not believe that it is necessary, or possible, for AI to replicate human intelligence . Consider that each of us contributes something that we are hardly going to be able to have from the other. “I will never be able to do the number of calculations that a machine does, or based on past data to identify patterns, and no machine will be able to give an innovative perspective to a problem when it is always trained with historical data.” Machines are very good at answering questions, but not asking them , and when it comes to identifying the problem we want to solve, people contribute and we will continue to contribute more than machines.
