vN – The AI Book That Should Be Turned Into A Movie

If you are a movie producer and you want to actually make an AI movie that helps people really understand one of the paths we could find ourselves going down in the next decade, read vN: The First Machine Dynasty by Madeline Ashby.

I’ve read a lot of sci-fi in the past few years that involves AI. William Hertling is my favorite writer in this domain right now (Ramez Naam is an extremely close second) although his newest book – Kill Process (which is about to be released) is a departure from AI for him (even though it’s not AI it’s amazing, so you should read it also).

I can’t remember who recommended Madeline Ashby and vN to me but I’ve been enjoying it on Audible over the past month while I’ve been running. I finished it today and had the “yup – this was great” reaction.

It’s an extremely uncomfortable book. I’ve been pondering the massive challenge we are going to have as a mixed society (non-augmented humans, augmented humans, and machines) for a while and this is the first book that I’ve read that feels like it could take place today. Ashby wrote this book in 2012 before the phrase AI got trendy again and I love that she refers to the machines as vNs (named after Von Neumann, with a delicious twist on the idea of a version number.)

I found the human / vN (organic / synthetic) sex dynamic to be overwhelming at times but a critically important underpinning of one of the major threads of the book. The mixed human / vN relationships, including those involved parenting vN children, had similar qualities to some of what I’ve read around racially mixed, religiously mixed, and same-sex parents.

I’ve hypothesized that the greatest human rights issue our species will face in the next 30 years is what it actually means to be human, and whether that means you should be treated differently, which traces back to Asimov’s three laws of robotics. Ashley’s concept of a Fail Safe, and the failure of the Fail Safe is a key part of this as it marks the moment when human control over the machines’ behavior fails. This happens through a variety of methods, including reprogramming, iterating (self-replication), and absorption of code through consuming other synthetic material (e.g. vN body parts, or even the entire vN.)

And then it starts to get complicated.

I’m going for a two hour run this morning so I’ll definitely get into the sequel, iD: The Second Machine Dynasty.


Also published on Medium.

  • “I’m going for a two hour run this morning so I’ll definitely get into the sequel”

    Are you doing Audible then? I was under the impression you consumed book visually only.

    • I do Audible when I run. That’s the only time I ever use it.

      • DnlCRG

        Do you read while you are driven ? I like to use my time behind the wheel to listen to books, “Ready Player One” currently.

        • I listen to podcasts when I’m driving.

  • On these themes:
    “Meaning and the Moral Sciences” Hilary Putnam (1978 !!!!)

  • Very cool, just added to my list.

  • ErlendK

    I just wanted to thank you sooooo much for your wonderful near-sci-fi recommendations. I adore the Ramez Naan books. Am close to finishing book 3 of the Hertling Tetralogy. Adding this to the reading list! Keep ’em coming!

  • Raju Chiluvuri

    Dear Mr. Fled,

    Can we see real AI (Artificial Intelligence) in next 30 years? There was so much talk of AI in mid 1980s. I don’t believe we made any real progress to get closer to real AI now (compared to mid-1980s). Major disciplines (e.g. CBSD/CBSE or AI) of Computer science in mid-1980s were rooted in untested beliefs, rather than demonstrable and repeatable facts. Even today these fields still rooted in same flawed beliefs.

    In history of science, I could find only one example where a major scientific discipline was rooted in such untested belief (i.e. the Earth is static), and the paradigm was known as geocentric paradigm. I have been struggling for past few years to expose flawed beliefs at the root of exiting CBSD paradigm: https://www.researchgate.net/publication/303756285_HowWhere_Real_Scientists_can_be_found_who_earned_PhD_due_to_real_merit_or_doing_real_research_in_Computer_Science_or_Software_Engineering

    Perhaps you could help me expose this error that could put computer science in right path, which eventually could leads to real AI. I provided all the information openly in my websites for anyone to prove me wrong. I greatly appreciate your guidance in my effort.

    It is a violation of basic scientific processes and principles to rely on such untested beliefs. Any scientific research in any scientific field end up on a wrong path, as soon as it start relying on beliefs, if the belief is flawed. There is no exception to this rule. Only way to put the scientific research on right path is by exposing the flawed belief.

    Best Regards,
    Raju