In today’s interconnected world of innovation, the traditional CV falls woefully short in capturing the true essence of engineers, scientists, and technologists. These professionals thrive on collaboration, cross-pollination of ideas, and the ability to tackle complex, multidisciplinary challenges.
A Graph Neural Network (GNN)
The GNN approach to representing their skills and connections offers a far more powerful and nuanced alternative. GNNs excel at modeling complex relationships and can capture the intricate web of collaborations, shared projects, and knowledge transfer that define the careers of technical professionals. By representing each individual as a node and their interactions as edges, a GNN can reveal patterns and potential synergies that a static CV could never hope to convey.
Predictive and prescriptive
This network-based approach aligns perfectly with the nature of scientific and technological work. It can highlight not just an individual’s skills, but also their role within larger ecosystems of innovation. A GNN could easily identify key connectors, bridge-builders between disciplines, and those with complementary skill sets for specific projects. Most importantly, the GNN could predict likelihood of future yet unknown outcomes.
Moreover, the dynamic nature of GNNs allows for real-time updates as professionals acquire new skills, complete projects, or forge new collaborations. This adaptability is crucial in rapidly evolving fields where traditional CVs quickly become outdated.
For hiring managers and project leaders, a GNN-based system would be transformative. It could suggest optimal team compositions, identify potential mentors, or flag rising stars in emerging fields. The ability to visualize and query this network would provide unprecedented insights into the collective capabilities of an organization or industry.
Ecosystem of talent
By embracing a GNN approach, we move beyond the limitations of two-dimensional representations. We create a living, breathing ecosystem of talent that truly reflects the collaborative and interconnected nature of modern scientific and technological endeavors. This shift isn’t just an improvement – it’s a necessary evolution to unlock the full potential of our collective mind and drive innovation forward.
Transcript:
The Resumé must Die – The Ingenesist Project
Knowledge is stored, transferred and applied by unique people with unique experiences in dimensions of space, time, context… and the 6 known natural senses.
The resumé attempts to convey this complex asset by reducing it down to 2 dimensions to fit on a PDF file.
A computer reduces the resumé to imperfect keywords before passing it through filters for upload to the hiring team.
This isn’t how people are found, this is how they are lost.
The problems of the future can only be solved by diverse and strategic combinations of knowledge assets.
The Ingenesist Project uses game theory, blockchain, and artificial intelligence to convert intangible assets to a more tangible form. So that people can find each other.