Ethics, AI and Computational Design

It has been an honor to be nominated Forbes 30 under 30 Europe, even if I didn’t achieve the final recognition, due to my visa status here in the Silicon Valley, I would like to thank who nominated me.

However, I was able to obtain the Deep Learning Scholarship provided by Fast.Ai in order to access this amazing course. This allows me to go a step further, to make my dream come true. Before starting the course I would like to pause and make a reflection about some important concepts to keep in mind before starting the course.

“How to think about ethical implications of your work, to help ensure that you’re making the world a better place, and that your work isn’t misused for harm “

“Removing barriers: deep learning has, until now, been a very exclusive game. We’re breaking it open, and ensuring that everyone can play”

Jeremy Howard in his Fastbook

It is extremely hard to find someone who shares your same values and stress that important in one of the most important courses in deep learning. (Something that I didn’t find in Andrew Ng’s course). Thanks, Jeremy and Team.

I was so happy to be invited to the Ethics and AI talk in Rome: ReinAIssance but unfortunately, I could not leave the USA at that time. Furthermore, I was able to share my point of view with some participants and provide a small contribution.
I deeply care about those values that I hope will be embedded in my future development. Rachel Thomas from CADE (Center of Applied Data Ethics) is also a strong advocate about these principles and I strongly recommend following her.
Exactly, for this reason, the application that I am developing aims to establish Unity in the design process.

“Data scientists need to be part of a cross-disciplinary team. And researchers need to work closely with the kinds of people who will end up using their research. Better still is if the domain experts themselves have learned enough to be able to train and debug some models themselves”

Rachel Thomas, Data Ethics

In order to be a tool to achieve the empowerment for creativity as Genevieve Bell recommended at the Intel AI Summit in 2018.

 “We have entered the age of automation overconfident yet underprepared. If we fail to make ethical and inclusive artificial intelligence, we risk losing gains made in civil rights and gender equity under the guise of machine neutrality”.

Joy Buolamwini MIT


The nature of order by Christopher Alexander
Timeless Way Building by Christopher Alexander
Architecture of Happiness by Alain De Botton
Cortex Twitter by Luca Belli
Algorithms Of Oppression by Safiya Umoja Noble
Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy by Cathy O’Neil

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