Matthew Griffin, described as “The Adviser behind the Advisers” and a “Young Kurzweil,” is the founder and CEO of the World Futures Forum and the 311 Institute, a global Futures and Deep Futures consultancy working between the dates of 2020 to 2070, and is an award winning futurist, and author of “Codex of the Future” series. Regularly featured in the global media, including AP, BBC, Bloomberg, CNBC, Discovery, RT, Viacom, and WIRED, Matthew’s ability to identify, track, and explain the impacts of hundreds of revolutionary emerging technologies on global culture, industry and society, is unparalleled. Recognised for the past six years as one of the world’s foremost futurists, innovation and strategy experts Matthew is an international speaker who helps governments, investors, multi-nationals and regulators around the world envision, build and lead an inclusive, sustainable future. A rare talent Matthew’s recent work includes mentoring Lunar XPrize teams, re-envisioning global education and training with the G20, and helping the world’s largest organisations envision and ideate the future of their products and services, industries, and countries. Matthew's clients include three Prime Ministers and several governments, including the G7, Accenture, Aon, Bain & Co, BCG, Credit Suisse, Dell EMC, Dentons, Deloitte, E&Y, GEMS, Huawei, JPMorgan Chase, KPMG, Lego, McKinsey, PWC, Qualcomm, SAP, Samsung, Sopra Steria, T-Mobile, and many more.
WHY THIS MATTERS IN BRIEF
What happens when AI can design its own humans? And then breed them ex vivo? The future is weirder than you could ever imagine …
Have you ever wondered what will happen when Artificial Intelligence (AI) can design a human? And what happens when you can use 3D Bio-printing to manufacture an artificial human genome that can then be implanted into an artificial human egg and grown in an artificial womb ex vivo? I have, one the one hand it’s part of the futurists’ job spec to think about weird stuff, but on the other AI has been designing synthetic genomes for some time now, just not human ones, and researchers at Harvard, MIT, and UCL believe they can create a fully artificial, synthetic human by 2036.
We’ve seen AI algorithms create art, movies, music, and beat humans at their own games, but now a team of scientists is taking things a step further, with an algorithm to generate the entire genetic code of non-existent people.
Using a type of AI called a Generative Adversarial Network (GAN), in which two algorithms rapidly generate some sort of output, check their work against real-world examples, and refine things as they go, the team has managed to replicate realistic human genomes that they say are indistinguishable from the real thing, according to research first spotted by The Next Web.
Unlike other GAN projects, like the funny look art projects mentioned above, the team of researchers from Estonia’s University of Tartu and France’s Paris-Saclay University who developed the artificial genome project say that their fake genetic sequences have real value as a tool for research geneticists.
They argue in their paper, which was published Thursday in the journal PLOS Genetics, that these DNA codes could help further genetic experimentation — without compromising the privacy of actual people who would need to give up their genetic data.
But it may not be all it’s cracked up to be, says a geneticist unaffiliated with the paper. To explain why, consider the other examples of what a GAN can create. We know what the human face, famous works of art, and Pokémon look like. So for AI, learning from those examples and building its own is no problem. But in terms of the human genome, there are still so many questions about what the different parts do and mean that it’s not really feasible to plug it into an algorithm as training data.
“My initial take is that it is interesting, but I’m not sure I see real practical implications for research right now,” said Deanna Church, vice president of the Mammalian Business Area and Software Strategy at the biotech company Inscripta. “A lot of the scientific community is still trying to figure out how the non-coding (most) of the genome ‘works.’ Just because you can’t computationally distinguish these generated genomes from real genomes doesn’t mean they’ve really preserved functional motifs and domains that are important — there is much of this we still don’t understand.”
The real question on our minds is whether these GAN-generated genomes would actually compile, so to speak, into a real, functional human genetic sequence, and while the authors didn’t comment Church says she’s not too optimistic.
“As far as ‘compiling’ this into a human — I definitely don’t see the path to that,” she said. “There is a long way from computationally generating genome sequences to converting that to a human cell, much less a human.”
“I definitely think the work is interesting, but I don’t see practical applications of it right now,” Church added. “Of course, I could be missing something.”
And while she’s likely right right now look around you at the sci-fi like technology advances we’ve made as a civilisation in just the past decade, then think what we might be able to achieve given another decade – never say never.