The subtitle of our book is Finding Cassandras to Stop Catastrophes.
Cassandra in Greek mythology was someone cursed by the gods, who could accurately see the
future but would never be believed.
When we say “Cassandras” throughout the book, we’re talking about people who can
accurately see the future.
People who are right—Cassandra was right—people who are right about the future but are being
Having derived what we think are the lessons learned from past Cassandra events, we then
looked at people today who were predicting things and being ignored.
And we looked at issues first and then tried to see if there was someone warning about them.
So the book is about people, 14 people: Seven who we known were Cassandras, and seven who
we are examining to find out if they are.
Usually Cassandras are people who are not directly involved in the thing that they worry about.
There are people who observe it.
Then there are people who study it.
But in the case of Jennifer Doudna at the University of California Berkeley, she’s
the person who created it and she’s also our Cassandra.
The “it” in this case is CRISPR-Cas9, a method that she invented—and I’m sure
someday will get a Nobel prize for—a method of doing gene editing that allows for removal
of genetic defects in the strain or addition into a strain of new capabilities.
Now this is going to revolutionize human life.
It’s already beginning.
It’s going to mean that all of the genetic defects that have caused so much pain and
suffering for people for millions of years, all of that could potentially be removed.
So why does the great woman who invented this wake up in the middle of the night worrying
What she told us was she’s afraid that she might have become Dr. Frankenstein.
That the technique that she developed could be misused in horrible ways.
It could be misused, for example, to create biological weapons, to create new forms of
threat to human beings, threats for which we don’t have any known antidote.
Or it could simply be used to create human beings of far superior capability.
Not just taking genes and removing defects but adding new super capabilities.
And so one scenario we discussed with her was what if the North Koreans or the Chinese
decided that they would create super soldiers?
Physically large people with great athletic ability designed to be soldiers, designed
to be aggressive, designed to be able to fight for long periods of time.
Or what if they simply created people who were brilliant at computer programming and
had IQs off the charts?
What if in the process of that kind of gene editing we created a caste society where some
people were genetically designed to do menial tasks and didn’t have the capability of
doing anything else?
And other people were designed to be the rulers with huge IQs and the capability of understanding
things beyond the pale for lesser humans.
That’s something that scared the creator of CRISPR-Cas9 and it scared us.
When we heard Jennifer’s story, we asked ourselves, “does she fit the template of a Cassandra
that we developed in the first half of the book looking at the first seven?”
Is she an expert?
She is the expert.
She created it.
Is she data-driven?
She has a wealth of data on CRISPR-Cas9 and what it can do.
Is she predicting something that is first-occurrence syndrome?
Something that’s never happened before?
And the answer to that is “yes.”
Is it kind of outlandish?
Is the stuff of Hollywood fiction?
Yes it is.
What about the audience—the decisions maker?
One of the things we saw with the earlier Cassandras was it wasn’t always clear there
was a decision maker.
People always pointed at each other saying “that’s your job, or at least it’s not my job.”
And in this case, making decisions about what gene editing can happen, and can’t happen,
and enforcing that is a matter of law, and international law, and it’s not at all clear
whose job that is.
One of those issues we looked at was artificial intelligence.
Now frankly my co-author R.P. Eddy and I disagreed about whether or not to do artificial intelligence.
I said, “I don’t think this is a problem.”
After all if a computer acts up, you can unplug it.
Obviously I didn’t understand the issue.
And the way that my co-author, R.P. Eddy, convinced me that we should look for someone
on this issue was by saying, “who are the people who are talking about this today?”
Not the experts in AI but the people who are generally concerned about it.
And who are they?
Bill Gates, the founder of Microsoft.
Elon Musk, the founder of Tesla.
Stephen Hawking, the great physicist from Oxford.
And when I heard that I said “Okay, fine.
Maybe if those guys think this is a problem, maybe we should look for the expert who is
predicting that this could be a future disaster.”
And we found Eliezer Yudkowsky, who not only thinks this could become a disaster, he’s
dedicated his life and all of his work to dealing with the future threat of artificial intelligence.
Because he doesn’t think it’s inevitable that artificial intelligence should be a problem.
But he does have a scenario whereby it could be if we don’t do some of the things he has in mind.
What’s the problem?
The problem could be that artificial intelligence starts writing software.
Maybe even encrypted software that human beings do not understand.
And can’t deal with.
That future is just around the corner.
Already we have software writing software.
Already at Google we have artificial intelligence writing software for further artificial intelligence.
And the Google program is getting to the point where they’re afraid they don’t fully
understand how it’s doing what it’s doing.
What Eliezer Yudkowsky fears most is that superintelligence will come into existence.
That means artificial intelligence programs that are significantly smarter than human
intelligence, and even human intelligence today augmented by computers.
And what he sees as possible, looking at the rate of advance in technology, is that this
will not be a linear growth in the capabilities of software.
But it could be overnight.
One day, artificial intelligence might be under the control of humans beings, and the
next day it might have jumped into superintelligence—far more capable than anything we could possibly
If you then put artificial intelligence onto networks that are running critical infrastructure—the
Internet of Things, another subject we look at in the book—it’s possible in the worst
case scenario that human beings will lose control of the infrastructure of society.
In even worse case scenarios than that, artificial intelligence will decide it doesn’t need humans at all.
And it is that fear that causes him to agree now as a planet, as a number of different
countries and societies, to put limits on the development of artificial intelligence,
and to do that by international treaty and to have observation to make sure artificial
intelligence doesn’t break out of pre-determined limits agreed by human beings and their governments.
Now you’ve seen that plot before.
You’ve seen that in a Hollywood movie.
And that’s part of the problem.
With so many of the possible Cassandras that we looked at today.
That humans have seen these threats before, they saw them in science fiction.
So whether it’s the possibility of an asteroid hitting the Earth or human beings being genetically
engineered or artificial intelligence taking over, part of the reason we don’t take these
Cassandras seriously is we’ve seen it in the movies, we’ve seen it in science fiction.
A corollary issue to artificial intelligence is the rise of robotics.
And already in this country we’re hearing debates about the possibility that the next
wave in automation rather than just shifting jobs from one function to another which has
happened in the past with automation maybe the next wave of automation would be far more
advanced and complex and actually throw humans out of work.
It’s a debate that’s going on and we don’t know who’s right.
Some people say, “people will be thrown out of work and there’ll be less need for humans
to do work and we’ll have to pay humans for doing nothing.”
Tax computers is one proposal—tax robots is a proposal.
And the other theory is that just as in the past when technology advances it may displace
certain jobs but it will create new ones.
We don’t know who’s right there, but we do know and all of our future Cassandras,
or our present day Cassandras predicting things about the future, that they need to be listened
to, and there needs to be examination of the theories that they’re putting forward and
the data that they’re putting forward, even if they are an outlier—a minority view among