>> Support for "AI: Unpacking the Black Box" comes from viewers like you and from Goodwill Keystone Area.

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>> Imagine yourself as a father three centuries ago, pacing anxiously outside a dimly lit room.

Now, the muffled sounds of your wife's labor pierce the air, a stark reminder of the precarious journey of childbirth.

Your heart races -- not just with anticipation, but with fear.

This is your fifth child, yet the shadow of loss looms large.

Two of your children never even drew their first breath, claimed by the perils of childbirth.

Another, a bright-eyed toddler of 3, succumbed to the relentless grip of tuberculosis.

Now, many in the future may look back at this time as the good old days.

But in this era, life hangs by a thread so fragile, it might snap at any moment.

Medicine, in many ways, intertwines with superstition.

Midwives whisper ancient charms as they work, and herbs of dubious efficacy are administered with fervent hope.

The line between science and folklore blurs, leaving families at the mercy of fate and faith.

Now let's leap forward to the 21st century.

It's 2010, and you're sitting in a sterile doctor's office, your husband's hand clasped tightly in yours.

The word "cancer" hangs in the air, heavy and suffocating.

As the doctor outlines your options, a whirlwind of emotions engulf you.

Fear grips your heart.

Questions flood your mind.

Will you see your children grow up?

"How much time do I have?"

The future, once a canvas of possibilities, now seems uncertain and daunting.

But here we are today, standing on the precipice of a new era.

Welcome to "AI:" Unpacking the Black Box."

I'm your host, John McElligott.

In this episode, we're diving into the future of healthcare and longevity in the age of artificial intelligence, quantum computing, and gene editing.

We're about to embark on a journey that will challenge our understanding of what it means to be a human.

We'll explore how artificial intelligence is revolutionizing healthcare, potentially eradicating diseases that have plagued humanity for millennia.

We'll dive into the realm of quantum computing, where the impossible becomes possible and the boundaries of scientific discovery are pushed beyond our wildest dreams.

And what about the human genome itself?

We'll explore how gene-editing techniques, like CRISPR, are opening doors to designer babies and the eradication of genetic diseases.

But perhaps the most tantalizing prospect of all is the quest for longevity and even immortality.

We'll be joined by world-renowned experts who are at the forefront of this research, pushing the boundaries of human life-span and challenging our very concept of mortality.

Stay tuned as we embark on this fascinating journey into the future.

>> How do we find new medicines for diseases?

Do we do it systematically?

Do we do it on a computer?

No.

For the most part, it's trial and error.

We get thousands of Petri dishes, put a little bit of chemicals in it, plus the medicine that we want to try, and simply wait to see whether that chemical can kill the germ.

That's primitive, but that's how we do it.

That's how penicillin was discovered -- by accident.

Most drugs are found by accident or something similar to accident.

We want a way to systematically cure cancer, systematically cure the aging process.

And quantum computers -- that's where they come in, because quantum computers work at the atomic level.

You realize that germs do not operate at the microscopic level that you can see.

Germs operate at the molecular level, where you can't see them.

That's the realm, that's the home of quantum computers.

So quantum computers will, from first principles, crack the nature of disease and also the aging process.

Why do we age?

We age because errors build up.

And when errors build up, that causes the body to become less and less efficient, and, eventually, we die.

But that mechanism, we don't know how that works.

That's where quantum comes in, because one of the computers may begin to unravel the aging process.

So watch out.

When quantum computers hits the market, that'll be the next really big thing.

We'll be able to perhaps tackle the aging process, tackle the question of life and death, calculate the question of the origin of the universe itself.

All the things that are beyond our reach will be within the reach of quantum computers, because Mother Nature is quantum.

But I think, within the next 5 to 10 years, we'll have multipurpose quantum computers that can handle a series of problems simultaneously and then be able to solve practical problems -- like I mentioned, the aging process.

We're now beginning to understand why we get old, why we die.

So the whole question of eternal life is now on the table, especially because quantum computers allow you to understand, at the molecular level, where aging damages DNA, where aging takes place.

And so things that were way beyond our capabilities, these technologies are now within the realm of solvability.

>> How do we use AI to design drugs or to increase the efficiency of building drugs or the likelihood of getting through a clinical trial?

And, so, there was already people that understood biology and understood machine learning and building these AI models, and there was kind of that convergence already happening.

So it wasn't like we were just taking, you know, technologies like AI and machine learning and taking it to biology and being like, "Look, guys, let's try this."

And where I think it's going for our field is, I think you're already starting to see drugs that are gonna come to market faster.

They're going to come to market cheaper.

You're going to have higher levels of efficacy.

And we are actually seeing biotechs and pharma groups that had a drug.

Maybe it didn't pass clinical trials.

They didn't really know why.

And now they're using -- We're using our AI system to do an analysis of it to understand, if you made these tweaks, would it would have passed?

So we think there's a lot of, like, incredible drugs that are on the back burner or on the cutting-room floor, if you will, from, like a Hollywood perspective, that just -- that never made it to market because they failed, but no one really knows why they failed.

They just know that they failed, right?

And so I think that we will be able to not only design drugs, I think that we will be able to synthesize full genomes and even full chromosomes, right?

CRISPR is one of the many tools in our tool belt.

So, you need to think about CRISPR as -- think of it as like DNA scissors.

But, like, when the average person, including myself, thinks about DNA, they think about a ladder, and it's twisted.

Well, imagine each one of those rungs of the ladder are individual what's called nucleotides.

But what if you could, like, change those to a different type of color?

What if you could cut out pieces of that ladder?

What if you could cut out pieces of that ladder, put it somewhere else?

That's essentially what CRISPR does, right?

It's a combination of tools that you can use to modify that twisted ladder that is that DNA helix, right?

>> What I got very fascinated with was this idea, with this emergence of new technology, that we could start to detect disease early and put people on a path that maybe, in the future, they never succumb to heart disease or neurodegenerative disease or certainly metabolic disease, which we know we can reverse today, or even early-stage cancer, right?

And so the ability now with advanced genomic sequencing, with whole-body and brain MRI, with advanced cardiac scans, with looking at everything from advanced blood biomarkers, metabolomics, proteomics, an explosion of medical data that right now really doesn't have a very effective home for that data, because physicians today are still trained very traditionally, like I was 30 years ago, at matching symptoms with diseases.

And as long as we're focused on late-stage findings, we're never going to get to the front of the train.

And then the other nice thing that we're doing with the AI right now is, once we get your symptom complex and we find out what we may think is wrong with you, then if there is -- You know, you may be totally asymptomatic, and, yet, we want the and you may want to try a new drug.

There's certainly a lot of drugs that are being repurposed.

And those trials are out there today.

And we can now, with the AI, search the world's literature.

I think one of the important things that doctors will have to remember going forward and have to get very comfortable with is that there are about 4,000 to 7,000 medical articles published every single day, 365 days, worldwide.

So it is an impossibility for any physician to think they're going to keep up with the latest and greatest technology, much less the latest and greatest clinical trial.

I think when it comes to the human body, I don't think AI is there, okay?

I think human body is far too complicated for any AI at this stage.

What people need to know is that the AI will be their best copilot in the future.

It will be the one thing they can turn to day in, day out, any time of day, any time of night, and have your data embedded in that AI so that that AI can make recommendations for you or just to answer questions about you, things that you may otherwise want to go to the doctor for in the middle of the night.

The AI will be there to answer those questions for you or escalate it to your physician if it's not the appropriate answer that you may want, but, more importantly, it will give you agency as a patient.

And what you don't have in the system is, you have no control today, and the best way for you to have control is to have your own health data and your own doc -- your pocket doc, if you will, and, at the same time, have an engine that knows more about you and you know more than your doctor that can help you guide your health.

And so I wouldn't be afraid of it.

If anything, I would embrace it, because it may be the one thing that keeps you from having a catastrophic event.

>> The big shift in medicine -- big, huge shift, and it's occurring now and I'm so excited for it -- is from reactive to proactive, from action and response to prevention and personalization.

Because we all have unique characteristics.

Personalization is changing everything.

It's changing how we shop.

We're going to live in a bespoke world.

And so my personal health record and my personal doctor that is in my alter ego, in my AI avatar, will help me watch my health.

And that's going to be the biggest change is because it will coach us, and then we'll be able to plan ahead better for what we're going to need to do.

And science is going to be rocking, doing things that we can't even imagine yet.

One of the real hopes is that we're going to really take a -- make a serious dent into dementia with mRNA technology and with DNA technology.

The biggest thing we have to overcome, the number-one biggest thing is our ego and the fear and the pessimism it puts inside of us, because that's where this comes from.

If you are really looking at life in its totality, my gosh, what a fabulous time to live in.

>> So, healthcare needs to innovate, and particularly here in the U.S.

So, one of the things that Digital Humans help with is, they can take a lot of the human-resource load that might be highly repeatable or maybe not as valuable focus of time for human resources, right?

So if nurses are driving around to many, many locations and having to do visits 12 visits a day, and of those visits, actually only one really needed their time, the rest was check-in, conversational, looking at the metrics, you know, from the different, you know, whether it's diabetes, other things that, you know, that nurse could go to one and then the next one that matters.

And so the people that need that nurse are actually getting that nurse, and those that just need check-ins are working with their Digital Human each day, having conversations, talking about how they feel.

"I'm feeling a little bit off.

These meds make me feel just a bit funny, like I'm faint all the time, you know?"

And then that flows through.

It gets analyzed by a core centralized team.

All those things get a lot, lot better.

And so we need that technology in healthcare.

It's also, as we've talked about, a great equalizer.

Not everyone can afford great healthcare, but when you've got AI behind some of the really cool tech, like diagnostics and things like that, if you can create an interface, anyone can have a conversation and talk about what they're going through, instead of Googling and getting "cancer" for every diagnostics, you know, now you've got a trusted source that tells you where you could possibly go, how they can support you.

We've even been talking about, like, helping people with Medicare, Medicaid.

Like, filling out forms for people who can't afford healthcare is hard.

So even helping people fill out the form so they can get support.

So lots of areas in health, which I'm really excited about.

>> How could we use forms of automation, algorithms, anything we could throw at it, basically being able to see disease or harm earlier, to diagnose early disease.

And at the time, I was seeing that radiologists -- both radiologists in level-one trauma centers, you know, where things are happening super-fast, but also just normally with the proliferation of, you know, 600 or 700 slides, which means images, for a single test, that you have this incredible high throughput and stress to actually get an accurate diagnosis.

So I started really focusing using neural nets.

A neural net basically is an algorithm that is structured around certain aspects of the way the brain operates with nodes and being able to sort of take information apart and reassemble it, very similar to how the brain functions.

When I was doing the technical work, I was also studying on the ground, you know, community health centers and clinics and outside radiology departments.

Like, what was the diagnostic workflow like?

You know, what were the optimal environments in which you got a really good predictive result where a radiologist was right on the money?

And when were the environments themselves not conducive to good diagnostics?

So it was very technical, but it was also social.

I always look for the social-human impact, and I learned that it's increasingly important as we go forward with AI.

I was one of the founding members of a company early called Enlitic, and we were the first in the world to actually use deep learning, outside of what I was doing locally, to identify lung nodules and then potentially adenocarcinoma.

And, so, that company -- no one was doing that.

No one was using deep learning to look at any organ at the time.

So, anyway, we, Enlitic, really paved the way in radiology, both in terms of workflow, in terms of accuracy and prediction of adenocarcinoma and a range of others.

But it was kind of a whole wave of, "How can we help radiologists really look into the human body with more precision and more speed?"

We have some bold ambitions, but they're all possible, and we're already moving in those directions.

As we go forward, in terms of privacy and trust and all of that, those things will continue to get worked out, and we're very much on top of that.

But in terms of the actual tech itself and the AI behind it, it might sound like Marvel, but we are already there.

We're at Marvel.

>> My focus over the last 5, 10 years really has been sort of in two areas -- AI and longevity.

I think they're the two biggest markets on the planet.

When you're born, you get 3.2 billion letters from your mom and 3.2 billion letters from your dad.

That's your genome.

That genome is your software that runs your body, and it's present in all 30 trillion or 40 trillion cells.

You have the same genome when you're 20, when you're 40, when you're 60, when you're 80, when you're 100.

So why don't you look the same?

Why do you look different?

Why don't you have a six-pack at 100 that you had when you were 18?

Why aren't you disease-free, like you were at a younger age?

Well, it turns out it's not the genes you have.

It's which genes are on and which genes are off.

It's called your epigenome.

"Epi-" from the Greek word for "above."

It's your control system that says, "Okay, we're going to make these cells' - skin cells, these cells' neurons -- we're going to age these cells.

And the hottest area of research today is a topic called epigenetic reprogramming.

And epigenetic reprogramming involves the idea of being able to turn back the control system to an earlier state of youth.

And therein lies one of the big areas.

We also have companies working on regrowing a heart, liver, lung, or kidney to give us a spare set of organs, right?

And there's a multitude of strategies and approaches.

But here's the facts.

The body is a very complicated system.

You know, in your 30 trillion to 40 trillion cells, there's 1 billion to 2 billion chemical reactions per second.

And it's not possible for any physician or scientist to really understand what's going on, but AI will and can.

And so we're going to begin to understand, fundamentally, why we age, how to slow it, stop it, and hopefully reverse it.

And I think it's the breakthroughs of this decade.

And it's going to be one of the most important results of the AI revolution.

You know, I think about those who have had a genetic disease in their family passed on generation to generation to generation can now say, "No more.

We're going to not just, you know, treat this disease, we're going to cure it so it is gone from our gene line, it's gone from my kids."

I mean, what greater health would you want than being able to do that?

And I think that we are on the verge of exploring the universe in a fashion that has never been imagined before.

Whatever we evolve into 100,000 years from now, 10,000, 1,000 years from now, we're going to remember this next decade as the moment in time where we, as humans, moved irreversibly off the planet into the cosmos.

>> The basic goal is to be able to extend or have some type of version of individual that's authentic to them, authentic to their cognitive capabilities, authentic to the languages they were able to speak, authentic to, you know, their educational background.

And what became obvious to me was, like, the perspective, and how do you encapsulate that perspective -- not in a journal, but in an iterative or a dynamic way where an individual can communicate with that, and be able to pass that on?

And that was like, "Oh, that is the greatest inheritance," and that's where the name of the company came from was being able to build the greatest thing that someone can inherit and pass on to future generations.

So, we're a cybernetic company.

Like, it's just -- I've had to take small parts of what we're doing and, like, let people know, but, eventually, we will have models that will be able to figure out how to prevent the telomeres at the end of your DNA from degradation, which causes aging.

Once you're able to put those into some type of suspended animation, you do have uncontrolled cell growth, which is cancer, right?

But once -- There's a two-step problem.

It's one, getting telomere to stop degrading, right?

Which stops aging.

And then having an inhibitor within that process to stop the undivided cell growth, which kind of puts you, like, at a certain age for an indefinite amount of time until you stop doing that process.

So, we don't know how to do that as humans.

My hypothesis is that machines will give us the way to be able to do that.

And we are building, slowly building, iterations of those machines or models that are going to help us solve that problem.

So, I have two kids.

Kennedy is 8.

She's my daughter.

And Caden is 6.

He's my son.

I've been making digital versions of my kids since they could talk, but the real intent of it is to build -- that they live a long and healthy life.

And when Kennedy's daughter is 4, she can talk to a 4-year-old version of Kennedy that was recorded in a very forward-leaning and progressive-thinking way.

Or when Caden -- When we started with him, he was 2.

His kids can go back to when he was 2 and have conversations, and all he can say was Baby Shark was his favorite song, right?

So, yeah, I'm absolutely eating my own dog food on this initiative.

And I don't think I would want my kids to persist beyond their actual existence here on Earth, but, I mean, that's just me with incomplete information at this point in time.

>> As we conclude our journey through the landscape of AI and its profound impact on healthcare and longevity, let's take one final leap into the future.

The year is 2035, and you've decided it's time for you to start a family.

The process is far from what we know today.

You find yourself in a sleek, futuristic clinic, face-to-face with an AI that's conducting your pre-parenthood interview.

The question it poses seems surreal -- "Would you like any upgrades for your future children?"

The concept of designer babies is no longer an ethical dilemma, but more of a routine choice.

Thanks to the marvels of AI and gene editing, traditional conception is optional.

Your own cells can be reprogrammed to create a child.

No donor needed.

It's a brave new world of reproduction where the lines between natural and artificial blur.

As you ponder this decision, the AI delivers another piece of news.

During your pre-screening, it's detected cancer in your body.

But have no fear.

It can be cured that very afternoon.

The days of grueling treatments and uncertain outcomes are long gone.

And for a small additional fee, they offer to edit out the cancer-causing gene from your future children's DNA.

This scenario, once the stuff of science fiction, is now a tangible and financial possibility.

It raises profound questions about the nature of humanity, the ethics of genetic manipulation, and the role of AI in shaping our future as a species.

As we've explored through this series, the potential of AI and related technologies is vast and awe-inspiring.

Yet, with great power comes great responsibility.

As we stand on the brink of this new era, it's crucial that we approach these advancements with wisdom, foresight, and deep consideration for their long-term implications.

The choices we make today will shape the world of tomorrow, affecting not just our lives, but the lives of generations to come.

As we move forward into this brave new world, let's carry with us the knowledge we've gained, the questions we've raised, and the wonders we've experienced.

The future is not set in stone.

It's ours to shape with wisdom, compassion, and a deep respect for the incredible potential of human ingenuity.

Again, I'm your host, John McElligott, signing off for tonight from "AI: Unpacking the Black Box."

Thank you and good night.

>> Support for "AI: Unpacking the Black Box" comes from viewers like you and from Goodwill Keystone Area.

It's the last tea party for Krista with Miss Marshmallow and Sarah's first day of management training at Goodwill.

When you donate to Goodwill, you help provide skills, training, and career placement, and the things you loved start a new life, too.