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15 Predictions for the AI Future of Medicine You Need to See | The Shoggoth Will See You Now · The BlackVeil Files

• 0:00
  SPEAKER_18: Intelligence is rare.
• 0:01
  SPEAKER_18: You know, a great doctor, a great teacher.
• 0:04
  SPEAKER_18: With AI, uh, over the next decade, that will become free.
• 0:09
  SPEAKER_03: ChatGPT today, by the way, is like a better diagnostician than most doctors in the world.
• 0:13
  SPEAKER_09: The most powerful men in tech are predicting that AI is going to cure all disease, double your lifespan, and replace your doctor for free.
• 0:22
  SPEAKER_09: We track down the 15 biggest predictions Silicon Valley is making about the future of medicine.
• 0:29
  SPEAKER_09: To find out if any of it is actually true, I tagged up with Dr.
• 0:32
  SPEAKER_09: Sam Kohanzadot.
• 0:34
  SPEAKER_09: He's double board certified in both general surgery, plastic, and reconstructive surgery.
• 0:38
  SPEAKER_09: He's the director of plastic surgery at two different hospitals in Los Angeles and the director and founder of the wound center and Roberts Surgical Institute.
• 0:46
  SPEAKER_09: When extreme physical trauma requires rebuilding a patient, he is the architect they call.
• 0:52
  SPEAKER_19: The scary part is what if it becomes alive and starts giving you misinformation.
• 0:56
  SPEAKER_09: From AI algorithms deciding who gets surgery to custom drugs that have never been tested on a living person to the machine that can literally hear you think.
• 1:05
  SPEAKER_09: Here are 15 predictions for the future of your body, and we are starting with the one that is already happening right now.
• 1:14
  SPEAKER_09: The ghost signature.
• 1:53
  SPEAKER_09: The numbers are crazy.
• 1:54
  SPEAKER_09: In just three months, two of these AI companies denied nearly 6,000 medical requests.
• 2:00
  SPEAKER_09: One of them denied more procedures than it approved.
• 2:03
  SPEAKER_09: It got so bad, the U.S.
• 2:05
  SPEAKER_09: Senate tried to kill the entire program.
• 2:07
  SPEAKER_09: The vote failed, which means that this AI bounty system is locked in until 2031.
• 2:13
  SPEAKER_09: When confronted with this, Medicare always falls back on the same defense.
• 2:17
  SPEAKER_08: They claim a licensed human doctor signs every single denial.
• 2:21
  SPEAKER_08: The purpose of these is not to deny care, it's to make sure you get the care you need and deserve, not the care that some unscrupulous doctor wants to use on you.
• 2:30
  SPEAKER_08: That is the head of Medicare, defending AI.
• 2:33
  SPEAKER_09: I expected Dr.
• 2:34
  SPEAKER_09: Somm to hate it, but he actually thinks it could work as long as there is a human safety net.
• 2:39
  SPEAKER_09: I asked him, what happens when the machine says no?
• 2:42
  SPEAKER_19: And we can do something called a peer-to-peer, where I will say, hey, your reason for denial doesn't make any sense.
• 2:48
  SPEAKER_19: I have to speak to another physician, and the physician will come on, they'll review the case, and oftentimes they'll say, Well, it looks like they were missing this one criteria.
• 2:57
  SPEAKER_19: Their weight is supposed to be stable for six months, and you didn't say that in here.
• 3:01
  SPEAKER_19: And we'll say, Yes, it definitely was.
• 3:03
  SPEAKER_19: They've been stable for a year, they lost 100 pounds, they definitely should qualify.
• 3:07
  SPEAKER_19: Then they go and add it, and then you get an approval.
• 3:10
  SPEAKER_19: So as long as that balance does exist, this is not a terrible thing.
• 3:14
  SPEAKER_09: But the insurance companies know exactly how humans work.
• 3:18
  SPEAKER_09: In a massive lawsuit against United Healthcare, the complaint revealed exactly how many people actually fight back against the machine.
• 3:26
  SPEAKER_09: That number is 0.2%.
• 3:29
  SPEAKER_09: 0.2% of people appeal a denial.
• 3:32
  SPEAKER_09: All the machine has to do is to beat your patients.
• 3:36
  SPEAKER_09: You get tired, the machine doesn't.
• 3:38
  SPEAKER_09: And the signature is just a human name rubber stamped on an algorithm's math.
• 3:43
  SPEAKER_09: Last year, ProPublica got inside one of the biggest health insurers in the country, and they found that an automated system flagged the claims.
• 3:51
  SPEAKER_09: Then the company doctors signed the denials in massive batches.
• 3:54
  SPEAKER_09: They signed more than 300,000 of them in two months.
• 3:58
  SPEAKER_09: So the math on that works out to this: the average time a human doctor spent looking at your medical fate was 1.2 seconds.
• 4:07
  SPEAKER_09: If you're wondering how that's physically possible, one of the doctors confessed.
• 4:16
  SPEAKER_09: That was a former medical director at Cigna.
• 4:18
  SPEAKER_09: The people building these algorithms know exactly what happens next.
• 4:22
  SPEAKER_09: The CEO behind ChatGPT sat down inside the Federal Reserve and he admitted it.
• 4:28
  SPEAKER_03: Like, maybe I'm a dinosaur here, but I really do not want to like entrust my medical fate to ChatGPT with no human doctor in the loop.
• 4:35
  SPEAKER_03: He built it and he wants a human in the loop.
• 4:38
  SPEAKER_09: So do I.
• 4:39
  SPEAKER_09: The listener in the exam room.
• 4:42
  SPEAKER_09: How much of our medical fate is decided by software before we even walk into the office?
• 4:47
  SPEAKER_19: Usually not before, but once they step in, we'll often have an AI scribe.
• 4:52
  SPEAKER_19: So as they tell us their story, the AI will put it all into a note format for us.
• 4:59
  SPEAKER_09: To a surgeon, it's just a glorified tape recorder.
• 5:02
  SPEAKER_09: It's an app taking notes, but taking notes is just how the machine gets its foot in the door.
• 5:07
  SPEAKER_07: It should say to me periodically, Doctor, it seems like you think this patient has pneumonia, but the patient still has a fever on day six, are you sure?
• 5:14
  SPEAKER_07: Because I've looked at the last 10 million patients like your patient, and 97% of them, their fever was gone.
• 5:20
  SPEAKER_09: That is the chair of medicine at UC San Francisco.
• 5:23
  SPEAKER_09: Three years ago, UCSF had a hundred human scribes taking notes.
• 5:28
  SPEAKER_09: Today, every single one has been replaced by the machine.
• 5:31
  SPEAKER_09: Dr.
• 5:32
  SPEAKER_09: Somm has this software in his exam room right now, and he can already see where this tech is heading.
• 5:37
  SPEAKER_19: We're not quite there yet, but at one point soon, AI is gonna start going through differential diagnosis and tell us treatment plans.
• 5:45
  SPEAKER_19: Not yet quite there yet.
• 5:47
  SPEAKER_19: They haven't put those two together.
• 5:48
  SPEAKER_19: That's definitely coming and will be the next step.
• 5:51
  SPEAKER_19: That next step is already here.
• 5:53
  SPEAKER_09: Epic software now suggests medical orders while the doctor writes the note.
• 5:57
  SPEAKER_09: Microsoft and a bridge both say their scribes make recommendations during the actual visit.
• 6:03
  SPEAKER_09: And it's already triggering lawsuits.
• 6:05
  SPEAKER_09: A patient sued Sharp Healthcare in San Diego, alleging that the hospital's AI scribe recorded more than 100,000 patients without everyone's consent.
• 6:14
  SPEAKER_09: The suit also alleges the AI automatically wrote a line into those patients' chart saying that they did consent.
• 6:20
  SPEAKER_09: The machine is putting words into your mouth validated by a ghost signature.
• 6:25
  SPEAKER_09: The doctor's doctor.
• 6:42
  SPEAKER_09: That was Daniel Nadler.
• 6:44
  SPEAKER_09: He's the CEO of a company called Open Evidence.
• 6:47
  SPEAKER_09: And he makes it sound like this hyper-tailored AI is still 10 years away.
• 6:51
  SPEAKER_09: But when I sat down with Dr.
• 6:53
  SPEAKER_09: Somm, he brought up open evidence unprompted, and he says they are already here.
• 6:58
  SPEAKER_19: There is actually an online platform where physicians and providers go and we can look up medical history and medical data.
• 7:06
  SPEAKER_19: It's called open evidence, and it has AI built into it where it goes and scours all of the medical journals, looks at all the internet and the data, and will give you diagnoses, recommendations for treatment, and a lot of people already rely on that.
• 7:20
  SPEAKER_09: Somewhere between half to two-thirds of all doctors in America are already using this software.
• 7:25
  SPEAKER_09: Wall Street just valued the company at$12 billion, but you're not allowed to see it.
• 7:30
  SPEAKER_09: You need a federal medical provider number just to log in.
• 7:33
  SPEAKER_09: But for your doctor, the app is completely free because pharmaceutical companies and medical device makers are buying ads inside the machine your doctor is using to diagnose you.
• 7:44
  SPEAKER_09: The algorithm recommends the treatment, and the people selling the treatment fund the algorithm, and they are doing it entirely behind our backs.
• 7:52
  SPEAKER_17: Most US doctors are quietly using this AI tool.
• 7:55
  SPEAKER_17: Few patients know about it.
• 7:56
  SPEAKER_09: That was NBC News, and you are the patient they're talking about.
• 7:59
  SPEAKER_09: The tech companies love to brag about how much smarter the software is.
• 8:04
  SPEAKER_09: Last year, Microsoft pitted an AI agent against 21 human doctors using the hardest diagnostic cases in the world.
• 8:12
  SPEAKER_09: The doctors got about 20% right compared to the machine, which scored in 85.
• 8:17
  SPEAKER_09: But there's a catch.
• 8:19
  SPEAKER_09: They did not let the doctors look anything up.
• 8:21
  SPEAKER_09: The machine had access to the entire internet.
• 8:24
  SPEAKER_09: The humans had to work from memory.
• 8:26
  SPEAKER_09: It was a rigged game designed to sell software.
• 8:30
  SPEAKER_09: I asked Dr.
• 8:31
  SPEAKER_09: Somb if he would actually trust his family's life to a tool like this.
• 8:35
  SPEAKER_19: I trust it to help give guidance and recommendations.
• 8:39
  SPEAKER_19: Obviously, as a medical professional, you need to evaluate and make sure what it's telling you is accurate.
• 8:44
  SPEAKER_19: Sometimes it'll tell you something weird, but most of the time, rather than it's very good for data gathering.
• 8:50
  SPEAKER_19: So finding out the data that we would look up on our own, it goes out and finds all that and brings us the data, and then you evaluate the data that it's given you, and it saves you a ton of time.
• 9:00
  SPEAKER_19: The scary part is what if it becomes alive and starts giving you misinformation.
• 9:04
  SPEAKER_09: One cardiology journal found an AI got more than half of its answers wrong on heart valve treatments.
• 9:10
  SPEAKER_09: A joint study between Stanford and Harvard proved that when these bots make harmful mistakes, it's because they randomly omit crucial facts about your health.
• 9:19
  SPEAKER_09: The scientist who just won a Nobel Prize for inventing this technology knows what happens next.
• 9:25
  SPEAKER_02: They're comparable with radiologists for many different kinds of medical scans.
• 9:29
  SPEAKER_02: And I believe that in 10 years they'll be routinely used as to give a second opinion.
• 9:35
  SPEAKER_02: And maybe in 15 years, they'll be so good at giving second opinions that the doctor's opinion will be the second one.
• 9:42
  SPEAKER_02: The doctor who forgets.
• 9:44
  SPEAKER_07: If we stop training young physicians in physicianship and learning how to make a diagnosis and and have judgment and diagnostic reasoning, essentially we'll turn them back into lay people.
• 9:57
  SPEAKER_09: The AI becomes the doctor.
• 9:59
  SPEAKER_09: The human just becomes the backup.
• 10:01
  SPEAKER_09: But today, the machine still needs a human to absorb the legal liability.
• 10:06
  SPEAKER_09: The algorithm writes the verdict, but the doctor has to sign the page.
• 10:10
  SPEAKER_09: Harvard Medical School is already forcing AI courses onto first-year students.
• 10:15
  SPEAKER_09: Mount Sinai gave its entire student body chat GPT, but the American Medical Association is sounding the alarm.
• 10:22
  SPEAKER_09: 70% of doctors warn this is going to gut the actual skills of doctors in training.
• 10:28
  SPEAKER_09: And it's already happening.
• 10:29
  SPEAKER_09: A recent study out of Europe gave experienced doctors AI to help find precancerous growths.
• 10:35
  SPEAKER_09: When they took the AI away just three months later, the doctor's accuracy tanked.
• 10:40
  SPEAKER_09: The software actively made them worse at their jobs.
• 10:43
  SPEAKER_09: If you learn medicine from an algorithm from day one, do you become a better doctor or a worse one?
• 10:50
  SPEAKER_19: Both.
• 10:51
  SPEAKER_19: In some ways, better because they'll have a lot more data at their fingertips, but at the same time, the problem is they may lose a lot of that rudimentary knowledge of going through and doing the work of looking up the data, understanding, processing the data.
• 11:05
  SPEAKER_19: From that standpoint, they'll be lost a little bit and they'll lose that basic skill.
• 11:10
  SPEAKER_09: They lose the skill.
• 11:34
  SPEAKER_09: Eventually, the tech companies argue they don't even need a human at all.
• 11:40
  SPEAKER_09: The prescription with no doctor.
• 11:42
  SPEAKER_09: Utah just signed a contract creating a legal loophole so an algorithm can prescribe you drugs.
• 11:49
  SPEAKER_09: The software handles refills for blood pressure, birth control, and antidepressants.
• 11:53
  SPEAKER_09: They put a human chaperone in the loop just to watch the machine.
• 11:56
  SPEAKER_09: But the second the AI hits 250 successful refills for a specific drug, the human is cut out entirely.
• 12:04
  SPEAKER_09: The software bypasses the doctor and it goes straight to the pharmacy.
• 12:08
  SPEAKER_09: The CEO selling this tech told politicians the machine is infinitely safer than a real doctor.
• 12:14
  SPEAKER_09: Meanwhile, the state's actual medical licensing board is actively fighting to stop it.
• 12:19
  SPEAKER_09: The pilot program runs out this month and they are deciding right now if the machine keeps its job.
• 12:26
  SPEAKER_09: The therapist with no privilege.
• 12:39
  SPEAKER_03: What should I do?
• 12:40
  SPEAKER_03: And right now, if you talk to a therapist or a lawyer or a doctor about those problems, there's like a legal privilege for it.
• 12:47
  SPEAKER_03: You know, like it's there's doctor-patient confidentiality, there's legal confidentiality, whatever.
• 12:53
  SPEAKER_03: We don't we haven't figured that out yet for when you talk to ChatGPT.
• 12:56
  SPEAKER_09: People are confessing to the machine because the machine is always there.
• 13:00
  SPEAKER_09: Last year, Dartmouth ran a clinical trial.
• 13:03
  SPEAKER_09: They gave a therapy bot to adults with depression, and it worked.
• 13:07
  SPEAKER_09: Symptoms dropped by half.
• 13:09
  SPEAKER_09: But the control group was just people sitting on a waiting list.
• 13:13
  SPEAKER_09: All they really proved is that talking to a piece of code is better than waiting for a human that hasn't shown up yet.
• 13:20
  SPEAKER_09: The state sees the trap.
• 13:22
  SPEAKER_09: Illinois just banned AI therapy entirely, threatening$10,000 fines.
• 13:27
  SPEAKER_09: Nevada and five other states are trying to restrict it too, because the scale of this is staggering.
• 13:33
  SPEAKER_09: OpenAI published its own internal numbers based on their 800 million weekly users.
• 13:39
  SPEAKER_09: Every single week, 1.2 million people are typing out explicit suicidal plans to an algorithm.
• 13:46
  SPEAKER_09: And the man who built it just told you the truth.
• 13:48
  SPEAKER_09: None of it's legally protected.
• 13:50
  SPEAKER_09: There's no doctor-patient privilege with a server.
• 13:53
  SPEAKER_09: Families are already filing lawsuits and they are ongoing.
• 13:57
  SPEAKER_09: Up until now, we've been talking about your current medical care.
• 14:00
  SPEAKER_09: But the next two predictions can see your future and your children's future.
• 14:06
  SPEAKER_09: The forecast.
• 14:24
  SPEAKER_09: They fed it millions of patient files.
• 14:27
  SPEAKER_09: It can now look at your medical history and forecast your risk for more than a thousand different diseases up to two decades before you ever get sick.
• 14:36
  SPEAKER_09: If you put two people in front of it, it can accurately predict which one will get a disease 76% of the time.
• 14:43
  SPEAKER_09: The scientists who built it swear it's for research only, but the biggest corporations on earth are already moving on it.
• 14:50
  SPEAKER_09: Epic is the company that probably runs your hospital software right now.
• 14:54
  SPEAKER_09: They recently published a paper with Microsoft on their own prediction model, which was trained on 118 million Americans.
• 15:01
  SPEAKER_09: There's a federal law from 2008 that makes it illegal for your health insurer or your employer to discriminate against you based on your DNA.
• 15:10
  SPEAKER_09: But this AI isn't looking at your genes.
• 15:12
  SPEAKER_09: It's forecasting your future from your chart history, which means it just bypassed your legal protection entirely.
• 15:19
  SPEAKER_09: Soon you will have the equivalent of a weather report for your own body, but nobody has decided who else gets to see that forecast.
• 15:28
  SPEAKER_09: The child you choose.
• 15:38
  SPEAKER_09: A company called Nucleus Genomics bought out advertisements in a Manhattan subway station.
• 15:44
  SPEAKER_09: The ads told parents, have your best baby, and it claimed that IQ is 50% genetic.
• 15:50
  SPEAKER_09: The transit authority actually had to reject two of their other ads, which said, have a girl and have a boy.
• 15:56
  SPEAKER_09: This is polygenetic embryo screening.
• 15:59
  SPEAKER_09: You make embryos through IBF, and a tech company assigns a score to each one based on its disease risk and its intelligence.
• 16:07
  SPEAKER_09: The problem is the science doesn't match the billboard.
• 16:09
  SPEAKER_09: The actual AI tools screening these embryos can only predict a small fraction of a person's cognitive ability.
• 16:16
  SPEAKER_09: The American Society for Reproductive Medicine states that this tech is unproven and should not be used on patients.
• 16:24
  SPEAKER_09: But because there's no federal agency regulating it, it reaches American parents anyway.
• 16:29
  SPEAKER_09: The prediction is that parents will stop rolling the dice.
• 16:33
  SPEAKER_09: Instead, they'll pick their child based on a corporate algorithm's ranking.
• 16:36
  SPEAKER_09: Every drug you've ever taken had to follow the exact same rules.
• 16:40
  SPEAKER_09: It was tested on a lab and then on people, usually twice so nobody could claim that the first result was a fluke.
• 16:47
  SPEAKER_09: The next two predictions are about what happens when the tech industry decides that those rules are just slowing them down.
• 16:55
  SPEAKER_09: Built for one.
• 17:07
  SPEAKER_11: I mean, now that we have shown the way, we fully expect many metabolic physicians around the world to be, you know, excited about trying to do this for themselves.
• 17:15
  SPEAKER_11: And so I think this is the start of something.
• 17:18
  SPEAKER_11: There is a baby named KJ.
• 17:20
  SPEAKER_09: He was born with a genetic disease that was so rare it hits fewer than one in a million children.
• 17:25
  SPEAKER_09: His body can't process ammonia.
• 17:28
  SPEAKER_09: Half the babies born with it don't survive infancy.
• 17:31
  SPEAKER_09: So a hospital in Philadelphia built a custom gene editor just for him.
• 17:36
  SPEAKER_09: One baby with one small mistake in his DNA and a cure written for his exact code.
• 17:42
  SPEAKER_09: It took them six months to build.
• 17:44
  SPEAKER_09: They gave him the dose and he survived.
• 17:47
  SPEAKER_09: It was an absolute miracle, and the tech industry used that miracle to rewrite the rules.
• 17:52
  SPEAKER_16: The FDA's default position is that one adequate and well-controlled study, combined with confirmatory evidence, will serve as the basis of marketing authorization.
• 18:00
  SPEAKER_09: For 60 years, the gold standard for safety was two complete clinical trials.
• 18:05
  SPEAKER_09: Now the government says one is enough.
• 18:07
  SPEAKER_09: They built that miracle for a single trial, but they used it to lower the bar for every drug you will ever take for the rest of your life.
• 18:16
  SPEAKER_06: The 48-hour vaccine.
• 18:57
  SPEAKER_09: In early trials, it cut the risk of death or relapse by almost half.
• 19:01
  SPEAKER_09: But Ellison's timeline is fiction.
• 19:03
  SPEAKER_09: The fastest they can build it right now is about six weeks.
• 19:06
  SPEAKER_09: Some patients in trial waited for over three months.
• 19:09
  SPEAKER_09: The breakthrough is real, but the tech billionaires are already selling a version of the machine that doesn't exist yet.
• 19:16
  SPEAKER_09: Before our surgeon meets the robot that's supposed to replace him, one thing.
• 19:21
  SPEAKER_09: This channel is independent, and the people who are watching it, you keep it that way.
• 19:25
  SPEAKER_09: There's a blackvail hoodie, a shirt, a hardcover journal that I use to write the questions for my guests in.
• 19:31
  SPEAKER_09: Since this video is 15 predictions, the code is BBF15 for 15% off, and that link is under the video.
• 19:38
  SPEAKER_09: Up until now, the machine has stayed in the background.
• 19:42
  SPEAKER_09: It was reading your chart or approving your medication, but the next three predictions go after the body itself.
• 19:50
  SPEAKER_09: The surgeon with no hands.
• 19:53
  SPEAKER_10: When do you think optimists will be a better surgeon than the best surgeons?
• 19:59
  SPEAKER_10: How long for that?
• 20:00
  SPEAKER_10: Three years.
• 20:01
  SPEAKER_10: Three years.
• 20:02
  SPEAKER_10: Okay.
• 20:03
  unknown: Yeah.
• 20:03
  SPEAKER_13: And by the way, there's a lot of things.
• 20:04
  SPEAKER_13: I say three years.
• 20:05
  SPEAKER_13: Three years at scale.
• 20:06
  SPEAKER_13: Yes.
• 20:08
  SPEAKER_13: There's probably more optimist robots that are great surgeons than there are all surgeons on Earth.
• 20:14
  SPEAKER_09: Elon just put a four-year expiration date on my guest's career.
• 20:18
  SPEAKER_09: So I put the billionaire's bet to the doctor who actually operates for a living.
• 20:22
  SPEAKER_19: There's no way in three years that we'll be there.
• 20:25
  SPEAKER_19: Maybe at some point, 10, 20 years down the line, possibly.
• 20:29
  SPEAKER_19: But I wouldn't say the best surgeon.
• 20:31
  SPEAKER_19: They may be able to perform routine procedures with supervision, but there are always things that can happen where the AI robot can't anticipate, and it's the problems that's where the medical training and knowledge and technical skills of a surgeon come in handy.
• 20:47
  SPEAKER_09: The tech industry wants you to picture an autonomous droid running the operating room.
• 20:52
  SPEAKER_09: Dr.
• 20:52
  SPEAKER_09: Somm described what is actually in the room with you right now.
• 20:56
  SPEAKER_19: So let's talk about a robotic gallbladder, for example.
• 20:59
  SPEAKER_19: They'll make the holes, they insert everything, and then this giant, like spider-looking robot comes on and attaches and controls everything.
• 21:06
  SPEAKER_19: The robot is not doing the surgery.
• 21:08
  SPEAKER_19: The surgeon is sitting in the corner on a computer screen controlling the hands of the robot.
• 21:13
  SPEAKER_19: There's a human being controlling every single movement that the robot's making.
• 21:18
  SPEAKER_19: That's the difference versus AI taking over the robot and controlling the actual movements.
• 21:24
  SPEAKER_19: We're not anywhere near that yet.
• 21:26
  SPEAKER_09: It is an incredible tool.
• 21:27
  SPEAKER_09: A third of all gallbladder removals are now done this way.
• 21:31
  SPEAKER_09: But it's just a puppet.
• 21:33
  SPEAKER_09: A human drives every single movement.
• 21:35
  SPEAKER_09: The closest a robot has ever come to operating by itself was a study at Johns Hopkins.
• 21:41
  SPEAKER_09: It successfully cut out a gallbladder, but it was on a dead pig with no blood flowing to it.
• 21:46
  SPEAKER_09: Even the engineer who built it was quick to clarify what that means.
• 21:50
  SPEAKER_03: With more data now, we showed that we can already, you know, do other procedures.
• 21:55
  SPEAKER_03: Also, what is great that it's a lot of self correcting ability.
• 22:00
  SPEAKER_09: I asked Dr.
• 22:01
  SPEAKER_09: Som how many times a fully autonomous machine has successfully performed surgery on a living person.
• 22:07
  SPEAKER_19: Someone's doing some stuff in a lab, they could be doing whatever they want.
• 22:10
  SPEAKER_19: But in human beings, not one.
• 22:12
  SPEAKER_09: For life or death operations, he's right.
• 22:14
  SPEAKER_09: The human is still in control.
• 22:16
  SPEAKER_09: But there is a footnote.
• 22:17
  SPEAKER_09: The FDA has already cleared a handful of surgical robots that map out part of an operation completely on their own.
• 22:24
  SPEAKER_09: The machine writes the surgical plan, the human doctor just hits approve.
• 22:30
  SPEAKER_09: The kidney from a pig.
• 22:33
  SPEAKER_20: So you really believe that within what a decade that this shortage of transplantable lungs may be cured?
• 22:40
  SPEAKER_20: Absolutely.
• 22:41
  SPEAKER_20: Uh Chris, I'm as certain as that as I was of the uh success that we've had with uh direct television broadcasting series XM.
• 22:49
  SPEAKER_09: She made that promise a decade ago.
• 22:51
  SPEAKER_09: There are more than 100,000 Americans on the national transplant waiting list.
• 22:56
  SPEAKER_09: A dozen of them die every single day, most of them waiting for a kidney.
• 23:00
  SPEAKER_09: Rothblatt's company is one of the frontrunners racing to solve this by growing human organs inside pigs.
• 23:06
  SPEAKER_09: And it's already happening.
• 23:08
  SPEAKER_09: Surgeons at Mass General recently gave a man named Tim Andrews a kidney from a gene-edited pig.
• 23:14
  SPEAKER_09: It kept him alive and off dialysis for nearly nine months, bridging the gap until he finally got a human organ.
• 23:21
  SPEAKER_09: I asked Dr.
• 23:22
  SPEAKER_09: Somm what it means if AI can finally close that gap.
• 23:26
  SPEAKER_19: If the AI is doing something to make the organ a more viable match for a human being, then that's a fantastic, wonderful thing.
• 23:35
  SPEAKER_19: There's a significant shortage of organs for transplantation.
• 23:38
  SPEAKER_19: Like kidney transplants have long waiting lists.
• 23:41
  SPEAKER_19: If we could create or grow them in a lab, it would change the world completely.
• 23:47
  SPEAKER_19: Dialysis would not exist anymore, and people, medical costs would go way down, people would live longer, live healthier.
• 23:53
  SPEAKER_09: That is the ultimate goal.
• 23:55
  SPEAKER_09: But right now, AI is just managing the shortage.
• 23:58
  SPEAKER_09: Stanford researchers built an AI that predicts if a dying donor's organs will survive extraction.
• 24:04
  SPEAKER_09: It cuts wasted surgeries by 60%, and we need every single one because the math is against us.
• 24:11
  SPEAKER_09: No lab-grown kidney has ever gone into a living person.
• 24:14
  SPEAKER_09: The pigs are our only option right now.
• 24:16
  SPEAKER_09: But the geneticists admit their next facility will only produce 6,000 organs a year, which is less than 10% of the demand.
• 24:25
  SPEAKER_13: The machine that hears you think.
• 24:28
  SPEAKER_13: Then our next product is blind sight, which will enable those who have total loss of vision, including if they've lost their eyes or the optic nerve, or maybe have never seen, were blind, even blind from birth, to be able to see again.
• 24:42
  SPEAKER_13: Initially low resolution, but ultimately very high resolution, and then in multiple wavelengths.
• 24:48
  SPEAKER_13: So you could be like Geordie LaForge in Star Trek, and you can see in radar, you can see in infrared, ultraviolet, superhuman capabilities.
• 24:55
  SPEAKER_09: He's selling superhuman vision.
• 24:57
  SPEAKER_09: But the real breakthrough in brain implants is already here.
• 25:01
  SPEAKER_09: Stanford researchers put chips into paralyzed patients who couldn't speak.
• 25:05
  SPEAKER_09: When those patients imagined saying a sentence, the machine decoded their inner speech perfectly.
• 25:11
  SPEAKER_09: When the patients silently counted shapes on a screen, the machine intercepted those numbers too.
• 25:17
  SPEAKER_09: It was reading thoughts they never intended to share.
• 25:20
  SPEAKER_09: So the scientists built a mental lock.
• 25:23
  SPEAKER_09: The patient has to think a specific password, chitty chitty bang bang, to turn the microphone on.
• 25:29
  SPEAKER_09: For a paralyzed person, this technology is an absolute miracle.
• 25:34
  SPEAKER_09: But it's also the first machine ever built that requires a password to stop listening to your thoughts.
• 25:39
  SPEAKER_09: The final two predictions aren't science fiction.
• 25:42
  SPEAKER_09: They come from the most credentialed doctors on earth, and they are the biggest promises anyone has ever made about the human body.
• 25:50
  SPEAKER_00: The end of disease.
• 25:52
  SPEAKER_00: So on average, it takes, you know, 10 years and billions of dollars to design just one drug.
• 25:58
  SPEAKER_00: We can maybe reduce that down from years to maybe months or maybe even weeks.
• 26:02
  SPEAKER_00: Which sounds incredible today, but that's also what people used to think about protein structures.
• 26:06
  SPEAKER_00: It would revolutionize human health.
• 26:08
  SPEAKER_00: And I think one day, maybe we can cure all disease with the help of AI.
• 26:12
  SPEAKER_00: The end of disease?
• 26:14
  SPEAKER_00: I think that's within reach.
• 26:16
  SPEAKER_00: Maybe within the next decade or so.
• 26:18
  SPEAKER_00: I don't see why not.
• 26:19
  SPEAKER_00: He won the Nobel Prize for AlphaFold.
• 26:22
  SPEAKER_09: AlphaFold predicted the shapes of more than 200 million proteins.
• 26:26
  SPEAKER_09: If anyone on Earth has earned the right to say the end of disease, it's him.
• 26:31
  SPEAKER_09: His drug company, Isomorphic Labs, originally stated their AI design drugs would be in human trials within the year.
• 26:38
  SPEAKER_09: That timeline was pushed back, and they recently raised$2 billion and they frequently post about patient impact, but it's always in present tense.
• 26:46
  SPEAKER_09: As of this recording, no human being has ever been given one of its molecules.
• 26:50
  SPEAKER_09: Nearly a hundred new drugs were approved over the last 24 months, and none of them came from AI drug discovery.
• 26:56
  SPEAKER_09: I asked Dr.
• 26:57
  SPEAKER_09: Somm about the promise that AI will cure all diseases.
• 27:02
  SPEAKER_19: That would be wonderful if it were possible.
• 27:04
  SPEAKER_19: I would love for there to be no more disease and for us to all live longer, but that's that's a tall tale.
• 27:09
  SPEAKER_19: If there was a way for the AI to be able to do that, I'm all in.
• 27:13
  SPEAKER_19: That would be wonderful and fully supportive.
• 27:16
  SPEAKER_19: I just, that is a big statement to make.
• 28:52
  SPEAKER_09: One eye in a safety study.
• 28:54
  SPEAKER_09: Those are the 15 predictions for the future of your body, but there is one final reality check that nobody in Silicon Valley wants to talk about.
• 29:02
  SPEAKER_09: A machine cannot go to jail.
• 29:04
  SPEAKER_19: I think at least for the foreseeable future, anything AI does needs to be overseen by a surgeon or physician to test it and edge and make sure that it's a real, viable answer.
• 29:16
  SPEAKER_09: The AI designs the drug, it reads the scan, and it writes the prescription.
• 29:20
  SPEAKER_09: But the human doctor takes 100% of the legal risk if the machine is wrong.
• 29:26
  SPEAKER_09: The tech billionaires are selling us the Star Trek future, but the doctors actually working in the hospitals know exactly what happens if the system loses its mind.
• 29:35
  SPEAKER_19: Worst case scenario, look at Terminator.
• 29:38
  SPEAKER_19: We're gonna have AI take over and Skynet's gonna come out, and we're all gonna become slaves living in a robot-driven environment.
• 29:47
  SPEAKER_09: Where are the hospitals and surgeons in that world?
• 29:49
  SPEAKER_19: I I think they're all dead.
• 29:52
  SPEAKER_09: Are you going to trust the machine with your life?
• 29:55
  SPEAKER_09: Let me know below