How often do we feel that society, and sometimes we ourselves, put an ‘expiry date’ on our abilities and our value?
We live in an age that demands from us to be the best boss, the best professional, father, mother, friend…. All at the same time! We are labelled and, when we don’t meet certain standards, it seems that we no longer ‘fit’ into the system and we are ‘expelled’. The film made me reflect on this, and reminded me of the importance of looking for our best version of ourselves, but not only to fulfil what is expected of us, but to ‘develop ourselves according to our own experiences’.
This is where I see that Artificial Intelligence can be that ‘substance’ that helps us in this journey of reinvention. Imagine an artificial intelligence that not only helps us to update our skills, the famous ‘reeskilling’, to make our work more efficient, but that allows us to enhance everything we have learned and experienced, making us stronger, more complete! Because reinventing ourselves is not just about adapting, but also about rediscovering what we have inside us and what we can still offer.
An honest self-analysis of our goals, achievements, dreams (and even those that have fallen by the wayside) allows us to build a map for the future. And with AI as an ally, we can empower this renewed version of ourselves without repeating the patterns of the past. As our beloved Einstein once said: ‘If you want different results, you have to do things differently’. It is not about looking for a ‘new’ version of ourselves that fits in, and makes the same mistakes again, but a version that moves forward, has purpose and continues to contribute with the same or more passion than before.
So, to all those who feel they no longer ‘fit in’ or have reached a so-called ‘finish line’… let’s remember that reinvention is a constant opportunity. AI is here to empower us, to bring out our best and show us that we still have a lot to give.
This is where both reinvention and our ability to turn biases around and recognise their importance come into play. It is about learning to unlearn and to find value even in what we call ‘biases’.
The role of biases
It is common to hear that AI has biases and that these should always be avoided. We rightly worry about the ethical and responsible use of algorithms, especially when they are trained on data that could compromise our privacy or our rights. Regulations such as the AI Act in Europe are necessary steps to address these concerns.
But what if a bias is just what an AI model needs to make a more accurate projection?
For example, how can an AI model predict how many units of a product we will sell at a price we have never used before? Conventional models are missing an essential ingredient: knowledge of the business.
Data engineers are adept at identifying growth trends or declines, but those numbers alone don’t tell the whole story. Did we get 5%? Great, but if we were supposed to grow 30%, then it’s not so positive. Did we lose 3 customers? That may not seem like much, but if one of those customers was the most important, the impact is much greater.
That nuance, that ‘bias’ based on experience, is invaluable for improving predictions. An AI model cannot predict what it does not know. That is why it is essential to inject knowledge of the business: knowing that in August in Spain there are not as many sales because everyone is on holiday, or that in Brazil, in February, Carnival is in February and paralyses contract closures.
So not all biases are bad. Some are just the touch AI needs to generate more robust and realistic scenarios. After all, how can the AI help you if you don’t give it the best information you have? Help the AI so the AI can help you.
