The Principles of a Modern Computer Scientist
What the practitioners who will shape the future of Artificial Intelligence could learn from the achievements and shortcomings of the current generation of computer scientists
Maybe like you, over the last years I have attended many events about the past, present and future of Artificial Intelligence. AI pioneer and DeepMind co-founder Demis Hassabis was a speaker in one of them in Oviedo, Spain. In that moment, little did I know about his brilliant career and fascinating experiments with AlphaFold.
I view Demis Hassabis as an archetype of a modern computer scientist. A professional that displays creativity and imagination in addition to logic, abstract thinking and engineering skills. Current predominant tech culture is driven by “deterministic thinking.” Visions are polarized. The future feels binary with serious utopian and dystopian thinking swirling simultaneously. In contrast, Demis talks about AI with nuances; he is aware of what other disciplines bring, and he can articulate how his work plays a role in the co-evolution between society and technology. I left the event inspired.
There might be a set of principles to draw from the achievements and shortcomings of my generation of computer scientists. The “Principles of a modern computer scientist” that the younger generation now at school could use as a blueprint for their future practice. Some of these principles might look like this.
A modern computer scientist values*:
Imagination over logic
Logic and abstract thinking are essential, but they can limit whatever challenge into a narrow, finite solution. Imagination is a differential ingredient of the modern computer scientist capable of exploring the broadest range of possibilities.
Responsibility over agility
With its “sprints,” “accelerators,” and “agile methodology,” the language in the tech world has sacralized optimization and fast execution. In contrast, modern computer scientists take pride in identifying the potential consequences of their work. And that takes time and patience.
Creativity over processes
The practice of computer science is not limited to following well structured iterative processes. Modern computer scientists look at challenges through multiple perspectives. They use creativity to think first. They build experiments and prototypes in safe environments to create multiple paths to choose from.
Nuances over convictions
Current world rewards being persuasive. Modern computer scientists are driven by doubt. They know how to listen to and challenge convictions. Their mission is to synthesize those convictions into nuanced conclusions.
* While there is value in the items on the right, the modern computer scientist values the items on the left more. Of course, there might be more and these principles should not be considered universal rules.
Thanks to Pelayo González Arbues for bringing me along to this event and congratulations to Irene Díaz for moderating the inspiring talks and conversation.
