Manu Abuín is a member of Nova, the global top-talent network, and, as Lead Product Designer at Roche & TaxDown, incorporates AI into groundbreaking product and design strategies. In an interview with PANTA RHAI he shares his industry specific insights.
What are some interesting use cases for AI in your industry that you have already come across?
I have worked on AI applications that optimize user experience and personalize products in sectors such as fintech and healthcare. A prominent case is the use of AI to anticipate needs in banking products, such as loans and mortgages, by analyzing behavioral patterns. In healthcare, AI helps to personalize patient follow-up and predict necessary interventions, improving the impact on users' lives.
In what ways do you integrate AI tools into your personal daily routine either in a work environment or in your private life?
In my work, I not only use generative AI to be more optimal in my work, but also to locate repetitive patterns that may escape my interpretation and help me understand a problem better. In that way, I am able to solve problems more effectively and directly. Also, I use it to innovate in the different products I am involved in, creating a river feedback on user comments that can nurture us about possible new integrations or functionalities.
Personally, I also use AI quite a bit to not only optimize my household chores, but also to learn languages, improve language fluency and even to learn new professions, technologies or practices. And, of course, to satisfy my curiosity in a more efficient way than Google.
Which changes -by the influence of artificial intelligence - could you identify in your field of work? What development would you wish for?
One of the most relevant changes is how AI has made it possible to personalize the user experience on a large scale. A concrete example is in fintech, where AI helps to automatically adjust investment or savings options according to the user's risk profile. I have worked on solutions that employ AI models to analyze user interaction in real time, identifying abandonment patterns and adjusting content to improve retention.
In terms of desired evolution, I would like to see even more ethical and explanatory AI. One area that could improve is user transparency about how their data is used to personalize their experience. The evolution to an AI that allows users to visualize and understand the “why” behind each recommendation would go a long way toward improving trust and the relationship with the product.
What are eventual risks and/or threats that you see that come with the technological development?
One of the clearest risks is over-reliance on AI models without human supervision. In a recent project in the healthcare sector, we saw how AI recommendations for improving health habits could vary based on not entirely accurate data. This reliance can lead to errors of judgment in critical areas if expert review is not included. Another risk is the erosion of privacy, especially in applications that rely on large volumes of personal data.
There are also risks of bias in AI models, especially in processes such as personnel selection or financial recommendations. One case I observed was in a financial product recommendation system that, by relying on historical data, started to replicate socioeconomic biases. The solution was to manually intervene in the training of the models to ensure fairness and avoid decisions based on bias.
What would be a specific piece of information that you gained through working closely with AI and that you believe most people do not know?
One of the most surprising facts is how small variations in user data can greatly impact results. I have seen cases where minimal adjustments to personalization algorithms multiplied the effectiveness of product recommendations, something that might seem insignificant but has a huge impact on user satisfaction.Another and perhaps more interesting aspect of innovation is that currently, professionals who want to use this technology to build products and services are obsessed with doing so by solving problems of the past and are unable to move forward looking ahead, so we ignore the great capacity for innovation that AI can bring us.
Manu Abuín is a product and design leader specializing in AI, focused on building scalable, data-driven solutions with a user-centered approach. With his experience as lead product designer at Roche and TaxDown he leverages his deep AI expertise to not only drive impactful product strategies in fintech, healthcare, and tech but also to educate and empower non-technical teams—including Product Managers, business leaders, designers, and researchers—on the transformative potential of AI. ”
This interview is part of PANTA Experts where we interview diverse experts in the media industry and beyond. Interviewer: Jan Kersling (PANTA RHAI).
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