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Transhumanism: Increasing Human Thought Capabilities II

An interesting mapping showing the inter-relations of Big Data with Digital Health and Precision Health (personalised monitoring and cure). Brain Machine Interface technology connects to implantable sensors, optogenetics, VR, Lab-on-a-Chip, and clusters with Natural Language Processing, Artificial Intelligence and Machine Learning. Image Credit: 2017 Roadmap for Innovation. ACC Health Policy Statement on Healthcare Transformation in the Era of Digital Health, Big Data, and Precision Health

The increase of thinking capabilities can be pursued by:

  1. “engineering” a better “brain” (pretty though, since we do not know yet how it works nor how the genome is shaping it …)
  2. Improving processing capabilities through focused stimulation
  3. better exploiting its capabilities, including establishing better connection with it, feeding more pertinent data and getting the output from its processing faster
  4. using it as a co-processor flanking external processors and calling “thinking” the symbiotic processing (although processing does not mean exactly the same thing in a brain and in a computer)
  5. providing more resilience to the thinking activity (including more focus)

Engineering a better brain

Our brains, as those of alla animal life, have evolved through natural selection to make their “host” more effective in the life game. They have not been “designed”. David Linden, professor of Neuroscience at John Hopkins University said:

“no engineer ever would have designed it like this”.

On the other hand one could easily claim that no engineer, today and for the foreseeable future, would be able to design a brain as good as our (meaning with the thinking, emotional, size and energy requirements of our brain, or a fly brain…).

However, the fact that there is no design at the core of our brain makes any attempt to improve its design an almost impossible task. You cannot, say, take a fe neuronal circuits are re-wire them to increase the brain performance. Likewise, we are getting close to understand that some brain pathologies derive from some faulty wiring (like in depression cases) but we don’t know how to re-wire that brain in a proper way (even assuming we get the technology for re-wiring the brain).

In addition consider that the growing understanding of the genome is just making the idea of tinkering with the genome to improve the brain ever more daunting. Our genome contains some 20,000 genes (not as many as scientists assumed just a decade ago but still a big number) and it is now understood that about one third of them, close to 7,000, have their saying in how our brain develops and “works”. Notice that in most cases the development of the brain and its operation is related to the interworking of these genes and their expression (so there is also a time relationship). This is clearly making the idea of designing a better brain by modifying the genome an impossible dream (at least for the foreseeable future).

A different matter would be to recognise some mutation in the genome associated a specific disorder and attempting to fix it by modifying the genome. That would be much easier and it is almost within out technology capability. In this case what is needed is to compare a genome resulting in a brain without that specific disorder with a genome of persons having that disorder. If, by pure luck, it turns out that only a few genes are involved one might hope that restoring them would get rid of the disorder. Beware, however, that the situation is not that linear. There may be more genes that have mutated in parallel with those that result in a brain disorder but that all together lead to a living person. The risk is that by fixing “only” the genes involved in the disorder one would alter the equilibrium hampering life.

There is also a further way: on planet Earth there are 7 billion humans that have evolved in slightly different ways to better adapt to local conditions, like Tibetan being more apt to live in an atmosphere having less oxygen. NASA scientists are looking at these diversities with the goal of identifying specific genes that are providing better adaptation to conditions that astronauts will have to face in long space travel, like going to Mars. They have already identified genes that provide better resistance to radiation, other that increase memory… And, they have also started to wonder if by manipulating the genome to create the “perfect” astronaut they are creating a new species…

This is clearly an area that we can only hope to address with the help of computer processing power, to analyse the big data resulting from the genome and gene expression and through deep learning (artificial intelligence) to understand both what it means and more importantly what a modification would imply (basically understand how a genotype modification impact the phenotype). The graphics accompanying this post makes visually clear the many relations existing in this area.

The idea of creating transhumans by designing their brain both from scratch and by modifying existing genome seems too far fetched at least for this century. However, there are other approaches to improve our thinking capabilities that seem more feasible. I’ll look at them in the coming posts.

About Roberto Saracco

Roberto Saracco fell in love with technology and its implications long time ago. His background is in math and computer science. Until April 2017 he led the EIT Digital Italian Node and then was head of the Industrial Doctoral School of EIT Digital up to September 2018. Previously, up to December 2011 he was the Director of the Telecom Italia Future Centre in Venice, looking at the interplay of technology evolution, economics and society. At the turn of the century he led a World Bank-Infodev project to stimulate entrepreneurship in Latin America. He is a senior member of IEEE where he leads the New Initiative Committee and co-chairs the Digital Reality Initiative. He is a member of the IEEE in 2050 Ad Hoc Committee. He teaches a Master course on Technology Forecasting and Market impact at the University of Trento. He has published over 100 papers in journals and magazines and 14 books.