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#434580 How Genome Sequencing and Senolytics Can ...

Posted on February 1, 2019 by Android

The causes of aging are extremely complex and unclear. With the dramatic demonetization of genome reading and editing over the past decade, and Big Pharma, startups, and the FDA starting to face aging as a disease, we are starting to find practical ways to extend our healthspan.

Here, in Part 2 of a series of blogs on longevity and vitality, I explore how genome sequencing and editing, along with new classes of anti-aging drugs, are augmenting our biology to further extend our healthy lives.

In this blog I’ll cover two classes of emerging technologies:

Genome Sequencing and Editing;
Senolytics, Nutraceuticals & Pharmaceuticals.

Let’s dive in.

Genome Sequencing & Editing
Your genome is the software that runs your body.

A sequence of 3.2 billion letters makes you “you.” These base pairs of A’s, T’s, C’s, and G’s determine your hair color, your height, your personality, your propensity to disease, your lifespan, and so on.

Until recently, it’s been very difficult to rapidly and cheaply “read” these letters—and even more difficult to understand what they mean.

Since 2001, the cost to sequence a whole human genome has plummeted exponentially, outpacing Moore’s Law threefold. From an initial cost of $3.7 billion, it dropped to $10 million in 2006, and to $5,000 in 2012.

Today, the cost of genome sequencing has dropped below $500, and according to Illumina, the world’s leading sequencing company, the process will soon cost about $100 and take about an hour to complete.

This represents one of the most powerful and transformative technology revolutions in healthcare.

When we understand your genome, we’ll be able to understand how to optimize “you.”

We’ll know the perfect foods, the perfect drugs, the perfect exercise regimen, and the perfect supplements, just for you.
We’ll understand what microbiome types, or gut flora, are ideal for you (more on this in a later blog).
We’ll accurately predict how specific sedatives and medicines will impact you.
We’ll learn which diseases and illnesses you’re most likely to develop and, more importantly, how to best prevent them from developing in the first place (rather than trying to cure them after the fact).

CRISPR Gene Editing
In addition to reading the human genome, scientists can now edit a genome using a naturally-occurring biological system discovered in 1987 called CRISPR/Cas9.

Short for Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9, the editing system was adapted from a naturally-occurring defense system found in bacteria.

Here’s how it works:

The bacteria capture snippets of DNA from invading viruses (or bacteriophage) and use them to create DNA segments known as CRISPR arrays.
The CRISPR arrays allow the bacteria to “remember” the viruses (or closely related ones), and defend against future invasions.
If the viruses attack again, the bacteria produce RNA segments from the CRISPR arrays to target the viruses’ DNA. The bacteria then use Cas9 to cut the DNA apart, which disables the virus.

Most importantly, CRISPR is cheap, quick, easy to use, and more accurate than all previous gene editing methods. As a result, CRISPR/Cas9 has swept through labs around the world as the way to edit a genome.

A short search in the literature will show an exponential rise in the number of CRISPR-related publications and patents.

2018: Filled With CRISPR Breakthroughs
Early results are impressive. Researchers from the University of Chicago recently used CRISPR to genetically engineer cocaine resistance into mice.

Researchers at the University of Texas Southwestern Medical Center used CRISPR to reverse the gene defect causing Duchenne muscular dystrophy (DMD) in dogs (DMD is the most common fatal genetic disease in children).

With great power comes great responsibility, and moral and ethical dilemmas.

In 2015, Chinese scientists sparked global controversy when they first edited human embryo cells in the lab with the goal of modifying genes that would make the child resistant to smallpox, HIV, and cholera.

Three years later, in November 2018, researcher He Jiankui informed the world that the first set of CRISPR-engineered female twins had been delivered.

To accomplish his goal, Jiankui deleted a region of a receptor on the surface of white blood cells known as CCR5, introducing a rare, natural genetic variation that makes it more difficult for HIV to infect its favorite target, white blood cells.

Setting aside the significant ethical conversations, CRISPR will soon provide us the tools to eliminate diseases, create hardier offspring, produce new environmentally resistant crops, and even wipe out pathogens.

Senolytics, Nutraceuticals & Pharmaceuticals
Over the arc of your life, the cells in your body divide until they reach what is known as the Hayflick limit, or the number of times a normal human cell population will divide before cell division stops, which is typically about 50 divisions.

What normally follows next is programmed cell death or destruction by the immune system. A very small fraction of cells, however, become senescent cells and evade this fate to linger indefinitely.

These lingering cells secrete a potent mix of molecules that triggers chronic inflammation, damages the surrounding tissue structures, and changes the behavior of nearby cells for the worse.

Senescent cells appear to be one of the root causes of aging, causing everything from fibrosis and blood vessel calcification, to localized inflammatory conditions such as osteoarthritis, to diminished lung function.

Fortunately, both the scientific and entrepreneurial communities have begun to work on senolytic therapies, moving the technology for selectively destroying senescent cells out of the laboratory and into a half-dozen startup companies.

Prominent companies in the field include the following:

Unity Biotechnology is developing senolytic medicines to selectively eliminate senescent cells with an initial focus on delivering localized therapy in osteoarthritis, ophthalmology and pulmonary disease.
Oisin Biotechnologiesis pioneering a programmable gene therapy that can destroy cells based on their internal biochemistry.
SIWA Therapeuticsis working on an immunotherapy approach to the problem of senescent cells.

In recent years, researchers have identified or designed a handful of senolytic compounds that can curb aging by regulating senescent cells. Two of these drugs that have gained mainstay research traction are rapamycin and metformin.

Rapamycin
Originally extracted from bacteria found on Easter Island, Rapamycin acts on the m-TOR (mechanistic target of rapamycin) pathway to selectively block a key protein that facilitates cell division.

Currently, rapamycin derivatives are widely used as immunosuppression in organ and bone marrow transplants. Research now suggests that use results in prolonged lifespan and enhanced cognitive and immune function.

PureTech Health subsidiary resTORbio (which started 2018 by going public) is working on a rapamycin-based drug intended to enhance immunity and reduce infection. Their clinical-stage RTB101 drug works by inhibiting part of the mTOR pathway.

Results of the drug’s recent clinical trial include:

Decreased incidence of infection
Improved influenza vaccination response
A 30.6 percent decrease in respiratory tract infections

Impressive, to say the least.

Metformin
Metformin is a widely-used generic drug for mitigating liver sugar production in Type 2 diabetes patients.

Researchers have found that Metformin also reduces oxidative stress and inflammation, which otherwise increase as we age.

There is strong evidence that Metformin can augment cellular regeneration and dramatically mitigate cellular senescence by reducing both oxidative stress and inflammation.

Over 100 studies registered on ClinicalTrials.gov are currently following up on strong evidence of Metformin’s protective effect against cancer.

Nutraceuticals and NAD+
Beyond cellular senescence, certain critical nutrients and proteins tend to decline as a function of age. Nutraceuticals combat aging by supplementing and replenishing these declining nutrient levels.

NAD+ exists in every cell, participating in every process from DNA repair to creating the energy vital for cellular processes. It’s been shown that NAD+ levels decline as we age.

The Elysium Health Basis supplement aims to elevate NAD+ levels in the body to extend one’s lifespan. Elysium’s clinical study reports that Basis increases NAD+ levels consistently by a sustained 40 percent.

Conclusion
These are just a taste of the tremendous momentum that longevity and aging technology has right now. As artificial intelligence and quantum computing transform how we decode our DNA and how we discover drugs, genetics and pharmaceuticals will become truly personalized.

The next blog in this series will demonstrate how artificial intelligence is converging with genetics and pharmaceuticals to transform how we approach longevity, aging, and vitality.

We are edging closer to a dramatically extended healthspan—where 100 is the new 60. What will you create, where will you explore, and how will you spend your time if you are able to add an additional 40 healthy years to your life?

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Posted in Human Robots

#434508 The Top Biotech and Medicine Advances to ...

Posted on January 22, 2019 by Android

2018 was bonkers for science.

From a woman who gave birth using a transplanted uterus, to the infamous CRISPR baby scandal, to forensics adopting consumer-based genealogy test kits to track down criminals, last year was a factory churning out scientific “whoa” stories with consequences for years to come.

With CRISPR still in the headlines, Britain ready to bid Europe au revoir, and multiple scientific endeavors taking off, 2019 is shaping up to be just as tumultuous.

Here are the science and health stories that may blow up in the new year. But first, a note of caveat: predicting the future is tough. Forecasting is the lovechild between statistics and (a good deal of) intuition, and entire disciplines have been dedicated to the endeavor. But January is the perfect time to gaze into the crystal ball for wisps of insight into the year to come. Last year we predicted the widespread approval of gene therapy products—on the most part, we nailed it. This year we’re hedging our bets with multiple predictions.

Gene Drives Used in the Wild
The concept of gene drives scares many, for good reason. Gene drives are a step up in severity (and consequences) from CRISPR and other gene-editing tools. Even with germline editing, in which the sperm, egg, or embryos are altered, gene editing affects just one genetic line—one family—at least at the beginning, before they reproduce with the general population.

Gene drives, on the other hand, have the power to wipe out entire species.

In a nutshell, they’re little bits of DNA code that help a gene transfer from parent to child with almost 100 percent perfect probability. The “half of your DNA comes from dad, the other comes from mom” dogma? Gene drives smash that to bits.

In other words, the only time one would consider using a gene drive is to change the genetic makeup of an entire population. It sounds like the plot of a supervillain movie, but scientists have been toying around with the idea of deploying the technology—first in mosquitoes, then (potentially) in rodents.

By releasing just a handful of mutant mosquitoes that carry gene drives for infertility, for example, scientists could potentially wipe out entire populations that carry infectious scourges like malaria, dengue, or Zika. The technology is so potent—and dangerous—the US Defense Advances Research Projects Agency is shelling out $65 million to suss out how to deploy, control, counter, or even reverse the effects of tampering with ecology.

Last year, the U.N. gave a cautious go-ahead for the technology to be deployed in the wild in limited terms. Now, the first release of a genetically modified mosquito is set for testing in Burkina Faso in Africa—the first-ever field experiment involving gene drives.

The experiment will only release mosquitoes in the Anopheles genus, which are the main culprits transferring disease. As a first step, over 10,000 male mosquitoes are set for release into the wild. These dudes are genetically sterile but do not cause infertility, and will help scientists examine how they survive and disperse as a preparation for deploying gene-drive-carrying mosquitoes.

Hot on the project’s heels, the nonprofit consortium Target Malaria, backed by the Bill and Melinda Gates foundation, is engineering a gene drive called Mosq that will spread infertility across the population or kill out all female insects. Their attempt to hack the rules of inheritance—and save millions in the process—is slated for 2024.

A Universal Flu Vaccine
People often brush off flu as a mere annoyance, but the infection kills hundreds of thousands each year based on the CDC’s statistical estimates.

The flu virus is actually as difficult of a nemesis as HIV—it mutates at an extremely rapid rate, making effective vaccines almost impossible to engineer on time. Scientists currently use data to forecast the strains that will likely explode into an epidemic and urge the public to vaccinate against those predictions. That’s partly why, on average, flu vaccines only have a success rate of roughly 50 percent—not much better than a coin toss.

Tired of relying on educated guesses, scientists have been chipping away at a universal flu vaccine that targets all strains—perhaps even those we haven’t yet identified. Often referred to as the “holy grail” in epidemiology, these vaccines try to alert our immune systems to parts of a flu virus that are least variable from strain to strain.

Last November, a first universal flu vaccine developed by BiondVax entered Phase 3 clinical trials, which means it’s already been proven safe and effective in a small numbers and is now being tested in a broader population. The vaccine doesn’t rely on dead viruses, which is a common technique. Rather, it uses a small chain of amino acids—the chemical components that make up proteins—to stimulate the immune system into high alert.

With the government pouring $160 million into the research and several other universal candidates entering clinical trials, universal flu vaccines may finally experience a breakthrough this year.

In-Body Gene Editing Shows Further Promise
CRISPR and other gene editing tools headed the news last year, including both downers suggesting we already have immunity to the technology and hopeful news of it getting ready for treating inherited muscle-wasting diseases.

But what wasn’t widely broadcasted was the in-body gene editing experiments that have been rolling out with gusto. Last September, Sangamo Therapeutics in Richmond, California revealed that they had injected gene-editing enzymes into a patient in an effort to correct a genetic deficit that prevents him from breaking down complex sugars.

The effort is markedly different than the better-known CAR-T therapy, which extracts cells from the body for genetic engineering before returning them to the hosts. Rather, Sangamo’s treatment directly injects viruses carrying the edited genes into the body. So far, the procedure looks to be safe, though at the time of reporting it was too early to determine effectiveness.

This year the company hopes to finally answer whether it really worked.

If successful, it means that devastating genetic disorders could potentially be treated with just a few injections. With a gamut of new and more precise CRISPR and other gene-editing tools in the works, the list of treatable inherited diseases is likely to grow. And with the CRISPR baby scandal potentially dampening efforts at germline editing via regulations, in-body gene editing will likely receive more attention if Sangamo’s results return positive.

Neuralink and Other Brain-Machine Interfaces
Neuralink is the stuff of sci fi: tiny implanted particles into the brain could link up your biological wetware with silicon hardware and the internet.

But that’s exactly what Elon Musk’s company, founded in 2016, seeks to develop: brain-machine interfaces that could tinker with your neural circuits in an effort to treat diseases or even enhance your abilities.

Last November, Musk broke his silence on the secretive company, suggesting that he may announce something “interesting” in a few months, that’s “better than anyone thinks is possible.”

Musk’s aspiration for achieving symbiosis with artificial intelligence isn’t the driving force for all brain-machine interfaces (BMIs). In the clinics, the main push is to rehabilitate patients—those who suffer from paralysis, memory loss, or other nerve damage.

2019 may be the year that BMIs and neuromodulators cut the cord in the clinics. These devices may finally work autonomously within a malfunctioning brain, applying electrical stimulation only when necessary to reduce side effects without requiring external monitoring. Or they could allow scientists to control brains with light without needing bulky optical fibers.

Cutting the cord is just the first step to fine-tuning neurological treatments—or enhancements—to the tune of your own brain, and 2019 will keep on bringing the music.

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Posted in Human Robots

#434336 These Smart Seafaring Robots Have a ...

Posted on January 16, 2019 by Android

Drones. Self-driving cars. Flying robo taxis. If the headlines of the last few years are to be believed, terrestrial transportation in the future will someday be filled with robotic conveyances and contraptions that will require little input from a human other than to download an app.

But what about the other 70 percent of the planet’s surface—the part that’s made up of water?

Sure, there are underwater drones that can capture 4K video for the next BBC documentary. Remotely operated vehicles (ROVs) are capable of diving down thousands of meters to investigate ocean vents or repair industrial infrastructure.

Yet most of the robots on or below the water today still lean heavily on the human element to operate. That’s not surprising given the unstructured environment of the seas and the poor communication capabilities for anything moving below the waves. Autonomous underwater vehicles (AUVs) are probably the closest thing today to smart cars in the ocean, but they generally follow pre-programmed instructions.

A new generation of seafaring robots—leveraging artificial intelligence, machine vision, and advanced sensors, among other technologies—are beginning to plunge into the ocean depths. Here are some of the latest and most exciting ones.

The Transformer of the Sea
Nic Radford, chief technology officer of Houston Mechatronics Inc. (HMI), is hesitant about throwing around the word “autonomy” when talking about his startup’s star creation, Aquanaut. He prefers the term “shared control.”

Whatever you want to call it, Aquanaut seems like something out of the script of a Transformers movie. The underwater robot begins each mission in a submarine-like shape, capable of autonomously traveling up to 200 kilometers on battery power, depending on the assignment.

When Aquanaut reaches its destination—oil and gas is the primary industry HMI hopes to disrupt to start—its four specially-designed and built linear actuators go to work. Aquanaut then unfolds into a robot with a head, upper torso, and two manipulator arms, all while maintaining proper buoyancy to get its job done.

The lightbulb moment of how to engineer this transformation from submarine to robot came one day while Aquanaut’s engineers were watching the office’s stand-up desks bob up and down. The answer to the engineering challenge of the hull suddenly seemed obvious.

“We’re just gonna build a big, gigantic, underwater stand-up desk,” Radford told Singularity Hub.

Hardware wasn’t the only problem the team, comprised of veteran NASA roboticists like Radford, had to solve. In order to ditch the expensive support vessels and large teams of humans required to operate traditional ROVs, Aquanaut would have to be able to sense its environment in great detail and relay that information back to headquarters using an underwater acoustics communications system that harkens back to the days of dial-up internet connections.

To tackle that problem of low bandwidth, HMI equipped Aquanaut with a machine vision system comprised of acoustic, optical, and laser-based sensors. All of that dense data is compressed using in-house designed technology and transmitted to a single human operator who controls Aquanaut with a few clicks of a mouse. In other words, no joystick required.

“I don’t know of anyone trying to do this level of autonomy as it relates to interacting with the environment,” Radford said.

HMI got $20 million earlier this year in Series B funding co-led by Transocean, one of the world’s largest offshore drilling contractors. That should be enough money to finish the Aquanaut prototype, which Radford said is about 99.8 percent complete. Some “high-profile” demonstrations are planned for early next year, with commercial deployments as early as 2020.

“What just gives us an incredible advantage here is that we have been born and bred on doing robotic systems for remote locations,” Radford noted. “This is my life, and I’ve bet the farm on it, and it takes this kind of fortitude and passion to see these things through, because these are not easy problems to solve.”

On Cruise Control
Meanwhile, a Boston-based startup is trying to solve the problem of making ships at sea autonomous. Sea Machines is backed by about $12.5 million in capital venture funding, with Toyota AI joining the list of investors in a $10 million Series A earlier this month.

Sea Machines is looking to the self-driving industry for inspiration, developing what it calls “vessel intelligence” systems that can be retrofitted on existing commercial vessels or installed on newly-built working ships.

For instance, the startup announced a deal earlier this year with Maersk, the world’s largest container shipping company, to deploy a system of artificial intelligence, computer vision, and LiDAR on the Danish company’s new ice-class container ship. The technology works similar to advanced driver-assistance systems found in automobiles to avoid hazards. The proof of concept will lay the foundation for a future autonomous collision avoidance system.

It’s not just startups making a splash in autonomous shipping. Radford noted that Rolls Royce—yes, that Rolls Royce—is leading the way in the development of autonomous ships. Its Intelligence Awareness system pulls in nearly every type of hyped technology on the market today: neural networks, augmented reality, virtual reality, and LiDAR.

In augmented reality mode, for example, a live feed video from the ship’s sensors can detect both static and moving objects, overlaying the scene with details about the types of vessels in the area, as well as their distance, heading, and other pertinent data.

While safety is a primary motivation for vessel automation—more than 1,100 ships have been lost over the past decade—these new technologies could make ships more efficient and less expensive to operate, according to a story in Wired about the Rolls Royce Intelligence Awareness system.

Sea Hunt Meets Science
As Singularity Hub noted in a previous article, ocean robots can also play a critical role in saving the seas from environmental threats. One poster child that has emerged—or, invaded—is the spindly lionfish.

A venomous critter endemic to the Indo-Pacific region, the lionfish is now found up and down the east coast of North America and beyond. And it is voracious, eating up to 30 times its own stomach volume and reducing juvenile reef fish populations by nearly 90 percent in as little as five weeks, according to the Ocean Support Foundation.

That has made the colorful but deadly fish Public Enemy No. 1 for many marine conservationists. Both researchers and startups are developing autonomous robots to hunt down the invasive predator.

At the Worcester Polytechnic Institute, for example, students are building a spear-carrying robot that uses machine learning and computer vision to distinguish lionfish from other aquatic species. The students trained the algorithms on thousands of different images of lionfish. The result: a lionfish-killing machine that boasts an accuracy of greater than 95 percent.

Meanwhile, a small startup called the American Marine Research Corporation out of Pensacola, Florida is applying similar technology to seek and destroy lionfish. Rather than spearfishing, the AMRC drone would stun and capture the lionfish, turning a profit by selling the creatures to local seafood restaurants.

Lionfish: It’s what’s for dinner.

Water Bots
A new wave of smart, independent robots are diving, swimming, and cruising across the ocean and its deepest depths. These autonomous systems aren’t necessarily designed to replace humans, but to venture where we can’t go or to improve safety at sea. And, perhaps, these latest innovations may inspire the robots that will someday plumb the depths of watery planets far from Earth.

Image Credit: Houston Mechatronics, Inc. Continue reading →

Posted in Human Robots

#434311 Understanding the Hidden Bias in ...

Posted on January 11, 2019 by Android

Facial recognition technology has progressed to point where it now interprets emotions in facial expressions. This type of analysis is increasingly used in daily life. For example, companies can use facial recognition software to help with hiring decisions. Other programs scan the faces in crowds to identify threats to public safety.

Unfortunately, this technology struggles to interpret the emotions of black faces. My new study, published last month, shows that emotional analysis technology assigns more negative emotions to black men’s faces than white men’s faces.

This isn’t the first time that facial recognition programs have been shown to be biased. Google labeled black faces as gorillas. Cameras identified Asian faces as blinking. Facial recognition programs struggled to correctly identify gender for people with darker skin.

My work contributes to a growing call to better understand the hidden bias in artificial intelligence software.

Measuring Bias
To examine the bias in the facial recognition systems that analyze people’s emotions, I used a data set of 400 NBA player photos from the 2016 to 2017 season, because players are similar in their clothing, athleticism, age and gender. Also, since these are professional portraits, the players look at the camera in the picture.

I ran the images through two well-known types of emotional recognition software. Both assigned black players more negative emotional scores on average, no matter how much they smiled.

For example, consider the official NBA pictures of Darren Collison and Gordon Hayward. Both players are smiling, and, according to the facial recognition and analysis program Face++, Darren Collison and Gordon Hayward have similar smile scores—48.7 and 48.1 out of 100, respectively.

Basketball players Darren Collision (left) and Gordon Hayward (right). basketball-reference.com

However, Face++ rates Hayward’s expression as 59.7 percent happy and 0.13 percent angry and Collison’s expression as 39.2 percent happy and 27 percent angry. Collison is viewed as nearly as angry as he is happy and far angrier than Hayward—despite the facial recognition program itself recognizing that both players are smiling.

In contrast, Microsoft’s Face API viewed both men as happy. Still, Collison is viewed as less happy than Hayward, with 98 and 93 percent happiness scores, respectively. Despite his smile, Collison is even scored with a small amount of contempt, whereas Hayward has none.

Across all the NBA pictures, the same pattern emerges. On average, Face++ rates black faces as twice as angry as white faces. Face API scores black faces as three times more contemptuous than white faces. After matching players based on their smiles, both facial analysis programs are still more likely to assign the negative emotions of anger or contempt to black faces.

Stereotyped by AI
My study shows that facial recognition programs exhibit two distinct types of bias.

First, black faces were consistently scored as angrier than white faces for every smile. Face++ showed this type of bias. Second, black faces were always scored as angrier if there was any ambiguity about their facial expression. Face API displayed this type of disparity. Even if black faces are partially smiling, my analysis showed that the systems assumed more negative emotions as compared to their white counterparts with similar expressions. The average emotional scores were much closer across races, but there were still noticeable differences for black and white faces.

This observation aligns with other research, which suggests that black professionals must amplify positive emotions to receive parity in their workplace performance evaluations. Studies show that people perceive black men as more physically threatening than white men, even when they are the same size.

Some researchers argue that facial recognition technology is more objective than humans. But my study suggests that facial recognition reflects the same biases that people have. Black men’s facial expressions are scored with emotions associated with threatening behaviors more often than white men, even when they are smiling. There is good reason to believe that the use of facial recognition could formalize preexisting stereotypes into algorithms, automatically embedding them into everyday life.

Until facial recognition assesses black and white faces similarly, black people may need to exaggerate their positive facial expressions—essentially smile more—to reduce ambiguity and potentially negative interpretations by the technology.

Although innovative, artificial intelligence can perpetrate and exacerbate existing power dynamics, leading to disparate impact across racial/ethnic groups. Some societal accountability is necessary to ensure fairness to all groups because facial recognition, like most artificial intelligence, is often invisible to the people most affected by its decisions.

Lauren Rhue, Assistant Professor of Information Systems and Analytics, Wake Forest University

This article is republished from The Conversation under a Creative Commons license. Read the original article.

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Posted in Human Robots

#434297 How Can Leaders Ensure Humanity in a ...

Posted on January 9, 2019 by Android

It’s hard to avoid the prominence of AI in our lives, and there is a plethora of predictions about how it will influence our future. In their new book Solomon’s Code: Humanity in a World of Thinking Machines, co-authors Olaf Groth, Professor of Strategy, Innovation and Economics at HULT International Business School and CEO of advisory network Cambrian.ai, and Mark Nitzberg, Executive Director of UC Berkeley’s Center for Human-Compatible AI, believe that the shift in balance of power between intelligent machines and humans is already here.

I caught up with the authors about how the continued integration between technology and humans, and their call for a “Digital Magna Carta,” a broadly-accepted charter developed by a multi-stakeholder congress that would help guide the development of advanced technologies to harness their power for the benefit of all humanity.

Lisa Kay Solomon: Your new book, Solomon’s Code, explores artificial intelligence and its broader human, ethical, and societal implications that all leaders need to consider. AI is a technology that’s been in development for decades. Why is it so urgent to focus on these topics now?

Olaf Groth and Mark Nitzberg: Popular perception always thinks of AI in terms of game-changing narratives—for instance, Deep Blue beating Gary Kasparov at chess. But it’s the way these AI applications are “getting into our heads” and making decisions for us that really influences our lives. That’s not to say the big, headline-grabbing breakthroughs aren’t important; they are.

But it’s the proliferation of prosaic apps and bots that changes our lives the most, by either empowering or counteracting who we are and what we do. Today, we turn a rapidly growing number of our decisions over to these machines, often without knowing it—and even more often without understanding the second- and third-order effects of both the technologies and our decisions to rely on them.

There is genuine power in what we call a “symbio-intelligent” partnership between human, machine, and natural intelligences. These relationships can optimize not just economic interests, but help improve human well-being, create a more purposeful workplace, and bring more fulfillment to our lives.

However, mitigating the risks while taking advantage of the opportunities will require a serious, multidisciplinary consideration of how AI influences human values, trust, and power relationships. Whether or not we acknowledge their existence in our everyday life, these questions are no longer just thought exercises or fodder for science fiction.

In many ways, these technologies can challenge what it means to be human, and their ramifications already affect us in real and often subtle ways. We need to understand how

LKS: There is a lot of hype and misconceptions about AI. In your book, you provide a useful distinction between the cognitive capability that we often associate with AI processes, and the more human elements of consciousness and conscience. Why are these distinctions so important to understand?

OG & MN: Could machines take over consciousness some day as they become more powerful and complex? It’s hard to say. But there’s little doubt that, as machines become more capable, humans will start to think of them as something conscious—if for no other reason than our natural inclination to anthropomorphize.

Machines are already learning to recognize our emotional states and our physical health. Once they start talking that back to us and adjusting their behavior accordingly, we will be tempted to develop a certain rapport with them, potentially more trusting or more intimate because the machine recognizes us in our various states.

Consciousness is hard to define and may well be an emergent property, rather than something you can easily create or—in turn—deduce to its parts. So, could it happen as we put more and more elements together, from the realms of AI, quantum computing, or brain-computer interfaces? We can’t exclude that possibility.

Either way, we need to make sure we’re charting out a clear path and guardrails for this development through the Three Cs in machines: cognition (where AI is today); consciousness (where AI could go); and conscience (what we need to instill in AI before we get there). The real concern is that we reach machine consciousness—or what humans decide to grant as consciousness—without a conscience. If that happens, we will have created an artificial sociopath.

LKS: We have been seeing major developments in how AI is influencing product development and industry shifts. How is the rise of AI changing power at the global level?

OG & MN: Both in the public and private sectors, the data holder has the power. We’ve already seen the ascendance of about 10 “digital barons” in the US and China who sit on huge troves of data, massive computing power, and the resources and money to attract the world’s top AI talent. With these gaps already open between the haves and the have-nots on the technological and corporate side, we’re becoming increasingly aware that similar inequalities are forming at a societal level as well.

Economic power flows with data, leaving few options for socio-economically underprivileged populations and their corrupt, biased, or sparse digital footprints. By concentrating power and overlooking values, we fracture trust.

We can already see this tension emerging between the two dominant geopolitical models of AI. China and the US have emerged as the most powerful in both technological and economic terms, and both remain eager to drive that influence around the world. The EU countries are more contained on these economic and geopolitical measures, but they’ve leaped ahead on privacy and social concerns.

The problem is, no one has yet combined leadership on all three critical elements of values, trust, and power. The nations and organizations that foster all three of these elements in their AI systems and strategies will lead the future. Some are starting to recognize the need for the combination, but we found just 13 countries that have created significant AI strategies. Countries that wait too long to join them risk subjecting themselves to a new “data colonialism” that could change their economies and societies from the outside.

LKS: Solomon’s Code looks at AI from a variety of perspectives, considering both positive and potentially dangerous effects. You caution against the rising global threat and weaponization of AI and data, suggesting that “biased or dirty data is more threatening than nuclear arms or a pandemic.” For global leaders, entrepreneurs, technologists, policy makers and social change agents reading this, what specific strategies do you recommend to ensure ethical development and application of AI?

OG & MN: We’ve surrendered many of our most critical decisions to the Cult of Data. In most cases, that’s a great thing, as we rely more on scientific evidence to understand our world and our way through it. But we swing too far in other instances, assuming that datasets and algorithms produce a complete story that’s unsullied by human biases or intellectual shortcomings. We might choose to ignore it, but no one is blind to the dangers of nuclear war or pandemic disease. Yet, we willfully blind ourselves to the threat of dirty data, instead believing it to be pristine.

So, what do we do about it? On an individual level, it’s a matter of awareness, knowing who controls your data and how outsourcing of decisions to thinking machines can present opportunities and threats alike.

For business, government, and political leaders, we need to see a much broader expansion of ethics committees with transparent criteria with which to evaluate new products and services. We might consider something akin to clinical trials for pharmaceuticals—a sort of testing scheme that can transparently and independently measure the effects on humans of algorithms, bots, and the like. All of this needs to be multidisciplinary, bringing in expertise from across technology, social systems, ethics, anthropology, psychology, and so on.

Finally, on a global level, we need a new charter of rights—a Digital Magna Carta—that formalizes these protections and guides the development of new AI technologies toward all of humanity’s benefit. We’ve suggested the creation of a multi-stakeholder Cambrian Congress (harkening back to the explosion of life during the Cambrian period) that can not only begin to frame benefits for humanity, but build the global consensus around principles for a basic code-of-conduct, and ideas for evaluation and enforcement mechanisms, so we can get there without any large-scale failures or backlash in society. So, it’s not one or the other—it’s both.

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