Jan 23, 2020
What will it take to solve many of the world’s most difficult
and complex challenges?
Rebecca D. Costa is an American sociobiologist and futurist. She
is the preeminent global expert on the subject of "fast adaptation"
and recipient of the prestigious Edward O. Wilson Biodiversity
Technology Award. Her career spans four decades of working with
founders, executives and leading venture capitalists in Silicon
Valley. Costa's work has been featured in the New York Times,
Washington Post, USA Today, The Guardian, and other leading
publications. She presently serves on the Advisory Committee for
the Lifeboat Foundation along with futurist Ray Kurzweil and Nobel
Laureates Daniel Kahneman, Eric S. Maskin, Richard J. Roberts and
Costa was the founder and CEO of one of the largest technology
marketing firms in California, where she developed an extensive
track record of launching game-changing technologies. Her clients
included industry innovators such as Hewlett-Packard, Apple
Computer, Oracle, Siebel Systems, General Electric, 3M and others.
She has been on the forefront of technological and scientific
innovation, assisting venture capitalists and large corporations to
identify, fund and launch disruptive new trends.
Retiring at the zenith of her career in Silicon Valley, Costa
spent six years researching and writing the international
The Watchman's Rattle: A Radical New Theory of Collapse. Her
follow-on book, titled On
the Verge was introduced in 2017 to critical acclaim, shooting
to the top of Amazon's #1 New Business Releases.
In today’s conversation with us, Rebecca Costa explains how
climate change and other world problems remain unresolved because
they are similar in nature. The real culprit is our lack of
distinction between empirical fact and our beliefs and opinions,
leaving us at the mercy of competing interests.
Rebecca shows how artificial intelligence-powered predictive
models can help us solve these issues, and help us predict future
events with unprecedented accuracy, paving the way for leaders to
act before-the-fact. Using real world examples, she
demonstrates how the certainty of future outcomes is changing the
way business and governments solve problems and preempt
- As a society loses a grip on the difference between an unproven
belief and an empirical provable fact, it loses its way. Social and
public policy quickly becomes based on opinion.
- The distinction between what is a scientific and empirical fact
and what is your opinion or belief is probably the most important
distinction to make in any transformation.
- There are billions of temperature recordings of the Earth’s
surface temperature. Like it or don’t like it, believe it or don’t
believe it, it doesn’t matter. The empirical data says that the
oceans are warming and the land is warming. We are beginning to see
some of the symptoms of that. Record floods, super storms, and
other signs that scientists predicted would happen.
- The predictions on the timeline have been wrong, so it’s easy
to dismiss the empirical facts, but that doesn’t change the fact
that the climate is changing and it is warming.
- The political question is now, how much if any has human
activity contributed to it? Causation in science is extremely
difficult to prove, particularly with something as complex as
global climate change.
- Even if human activity contributed all, part or none, do we
have the ability to reverse that climate change? That’s the
question to focus on.
- When it comes to complex problems, the danger people have is
they overstate what the empirical data indicates and that will
eventually bite you in the behind.
- Rather than saying something is causal, say it’s correlated. We
have to be careful about telling the truth about what we know and
what we surmise.
- If there is any threat that could wipe out the entire species
then better safe than sorry comes to mind. We owe it to ourselves
to do everything we can, knowing that it may not do anything. But
at least we’re doing everything we can.
- If I have worry right now, it’s that we’re not an
empirical-driven world. If I have optimism, it’s that we’re relying
more on machines to make decisions on our behalf. And machines do
not have beliefs, only data.
- There can be no social change of any importance without
recruitment. When you get into someone’s face and alienate them,
call them names, and treat them as they are stupid and their
opinions are invalid, you’re doing exactly the reverse of what you
intend to do.
- In order to create social change, you must leverage the media
to do that recruitment, to bring the reason you seeking social
change into the livingroom of every human being.
- Make your message compelling and relevant to them. Without
critical mass you have nothing.
- The polarization we see right now between the Republicans and
the Democrats is the reason that nothing gets done. They don’t
understand that they have to recruit people from the other
- There are many things in life where you may not know that the
outcome is certain. So you place really good bets. The bigger the
upside and downside the more important it is to place those
- Unlike previous civilizations we have this tremendous
opportunity to allow computers and artificial intelligence to guide
our decisions on an empirical and factual basis, in spite of our
opinions and theories.
- The billions of data points that artificial intelligence can
observe and analyze data in real time in a dynamic way, is going to
overshadow human capability, and is already doing so.
- What AI and quantum computing has allowed us to do is take
millions of facts and very precisely predict whether a future event
is going to occur.
- In many respects, we’re moving into an era where we can avoid
many problems – like mass shootings – because we can work backwards
to see the data that showed that the mass shooter was moving toward
criticality. That data is actually in the public domain. They’re
posting their manifestos on social media.
- Opioid addiction is rampant around the world. Companies like
Fuzzy Logix can administer a written questionnaire and look at your
health records and determine within 85-90% whether you are
genetically predisposed to become an opioid addict before the
doctor gives you your first prescription.
- We’re getting to a point where AI algorithms can do everything
from inform judges at arraignment hearings whether the person
should be released on their own recognizance, what the bail should
be, and whether they should not be released into society.
- So predictive algorithms can inform us of the likelihood of a
future event so we can make better decisions today.
- But there is a problem with knowing what the future is. In
99.999% of the cases, we can predict what you’re going to do,
however there is that small chance that you could intervene through
free will. There’s always a chance that you could override, make a
different decision and change course. But are we going to bet on
free will or are we going to play the percentages?
- When you know what the future is, you can reverse engineer the
decision to avoid a failure or danger. So there really shouldn’t
ever be a product launch that doesn’t make it because we have tools
that will say, how many will sell, at what price, and when your
product needs refreshing or be dead in the water.
- Where it gets tricky is where computers don’t have any
information. Innovation for example.
- The challenge right now is that the tools to do this are very
expensive. In some ways that digital divide is creating a social
divide. For those who know what’s going to happen, there couldn’t
be a bigger advantage.
- There are some very fundamental building blocks you have to
have in order to experience happiness. 50-60% of your aptitude to
be happy and enjoy life is genetically inherited.
- Approximately one-third is your decisions in life, which makes
that one-third extra important because it’s the only part that you
- Unemployment numbers should not be looked at as an economic
barometer anymore. It’s actually tied to people’s ability to be
optimistic and happy in life. When you have massive unemployment
you are actually building a depressed society.
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