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Augmented Machines and Augmented Humans are converging VI

Human augmentation can be pursued either by changing the genome (with effect on the phenotype) or by changing the phenotype (with effect on the extended phenotype) or by changing the extended phenotype.

Human Augmentation

There are basically three ways to augment humans:

  • Modifying the genotype
  • Modifying the phenotype
  • Modifying the extended phenotype

As individual we inherit the genotype (the set of our genes contained in our chromosomes, each of us has 22 pairs of chromosomes –autosomes- plus the sex chromosomes, either X-X, or X-Y, female or male respectively). So far scientists do not agree on the exact number of genes, the estimate is between 19,000 and 20,000. Each gene is composed by a number of base-pairs (A:T –Adenine, Thymine- and C:G–Cytosine, Guanine-).

Range of genome size in organisms of the three domains of life. Image credit: Metode

The number of base pairs per gene varies significantly and it is not, generally speaking, an indication of the sophistication of the living being (at least in the perception we have of “sophistication”). As an example compare the 20,000 genes (probably less than that) in a human genome with the 164,000-334,000 genes estimated in wheat!

In general scientists tend to look at the number of base-pairs, rather that at the number of genes. In the figure an overview of the number of base pairs in different life forms (expressed in millions of base-pairs).

In the figure an overview of the number of base pairs in different life forms (expressed in millions of base-pairs). As you can see mammals are not the ones having the highest number of pairs and humans are an “average” mammal 😉 in this sense.

So, having many genes, or having many pairs, does not necessarily match our perception of “smartness”.

What is sure is that by changing a gene there is the potential of changing the phenotype (change includes also deleting as well as adding a gene).

The problem is that we do not know in general how a change in a gene affects the phenotype, so in spite of having the technology for changing genes (CRISPR/Cas 9 and more recent, more precise ones, like CRISPR/Cas 12a) we cannot start from a desirable phenotype and reverse-engineered it into a change in the genotype. Someone noticed that today’s gene modification technology is comparable to have an extremely precise gun and being blindfold when using it.

Some researchers are planning to use AI to create this link between the genotype and the phenotype. This is becoming more and more a possibility given the growing number of sequenced genomes onto which machine learning can be applied.

There are already some clear correlation between genes and their expression in the phenotype and companies like Genomic Predictions are exploiting them to steer in-vitro fertilisation towards higher probability of avoiding disorders like diabetes, osteoporosis, schizophrenia and dwarfism.

Among these correlations are the colours of the eyes and this is being exploited by companies like The Fertility Institute that are offering future parents the possibility to “design” some aspects of their future child, including the sex and the colour of the eye.

Augmenting human intelligence through gene modification is still a big question mark, although there is a feeling that this should be “technically” possible (leaving aside the big ethical issues –that, of course, should not be left aside!). Recently, in February 2019, there was a report of a gene deletion performed in China to create HIV immunity that may have as an unexpected side effect the increase of learning capability.

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 Industry Advisory Board within the Future Directions Committee and co-chairs the Digital Reality Initiative. 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.

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