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#434753 Top Takeaways From The Economist ...

Over the past few years, the word ‘innovation’ has degenerated into something of a buzzword. In fact, according to Vijay Vaitheeswaran, US business editor at The Economist, it’s one of the most abused words in the English language.

The word is over-used precisely because we’re living in a great age of invention. But the pace at which those inventions are changing our lives is fast, new, and scary.

So what strategies do companies need to adopt to make sure technology leads to growth that’s not only profitable, but positive? How can business and government best collaborate? Can policymakers regulate the market without suppressing innovation? Which technologies will impact us most, and how soon?

At The Economist Innovation Summit in Chicago last week, entrepreneurs, thought leaders, policymakers, and academics shared their insights on the current state of exponential technologies, and the steps companies and individuals should be taking to ensure a tech-positive future. Here’s their expert take on the tech and trends shaping the future.

Blockchain
There’s been a lot of hype around blockchain; apparently it can be used for everything from distributing aid to refugees to voting. However, it’s too often conflated with cryptocurrencies like Bitcoin, and we haven’t heard of many use cases. Where does the technology currently stand?

Julie Sweet, chief executive of Accenture North America, emphasized that the technology is still in its infancy. “Everything we see today are pilots,” she said. The most promising of these pilots are taking place across three different areas: supply chain, identity, and financial services.

When you buy something from outside the US, Sweet explained, it goes through about 80 different parties. 70 percent of the relevant data is replicated and is prone to error, with paper-based documents often to blame. Blockchain is providing a secure way to eliminate paper in supply chains, upping accuracy and cutting costs in the process.

One of the most prominent use cases in the US is Walmart—the company has mandated that all suppliers in its leafy greens segment be on a blockchain, and its food safety has improved as a result.

Beth Devin, head of Citi Ventures’ innovation network, added “Blockchain is an infrastructure technology. It can be leveraged in a lot of ways. There’s so much opportunity to create new types of assets and securities that aren’t accessible to people today. But there’s a lot to figure out around governance.”

Open Source Technology
Are the days of proprietary technology numbered? More and more companies and individuals are making their source code publicly available, and its benefits are thus more widespread than ever before. But what are the limitations and challenges of open source tech, and where might it go in the near future?

Bob Lord, senior VP of cognitive applications at IBM, is a believer. “Open-sourcing technology helps innovation occur, and it’s a fundamental basis for creating great technology solutions for the world,” he said. However, the biggest challenge for open source right now is that companies are taking out more than they’re contributing back to the open-source world. Lord pointed out that IBM has a rule about how many lines of code employees take out relative to how many lines they put in.

Another challenge area is open governance; blockchain by its very nature should be transparent and decentralized, with multiple parties making decisions and being held accountable. “We have to embrace open governance at the same time that we’re contributing,” Lord said. He advocated for a hybrid-cloud environment where people can access public and private data and bring it together.

Augmented and Virtual Reality
Augmented and virtual reality aren’t just for fun and games anymore, and they’ll be even less so in the near future. According to Pearly Chen, vice president at HTC, they’ll also go from being two different things to being one and the same. “AR overlays digital information on top of the real world, and VR transports you to a different world,” she said. “In the near future we will not need to delineate between these two activities; AR and VR will come together naturally, and will change everything we do as we know it today.”

For that to happen, we’ll need a more ergonomically friendly device than we have today for interacting with this technology. “Whenever we use tech today, we’re multitasking,” said product designer and futurist Jody Medich. “When you’re using GPS, you’re trying to navigate in the real world and also manage this screen. Constant task-switching is killing our brain’s ability to think.” Augmented and virtual reality, she believes, will allow us to adapt technology to match our brain’s functionality.

This all sounds like a lot of fun for uses like gaming and entertainment, but what about practical applications? “Ultimately what we care about is how this technology will improve lives,” Chen said.

A few ways that could happen? Extended reality will be used to simulate hazardous real-life scenarios, reduce the time and resources needed to bring a product to market, train healthcare professionals (such as surgeons), or provide therapies for patients—not to mention education. “Think about the possibilities for children to learn about history, science, or math in ways they can’t today,” Chen said.

Quantum Computing
If there’s one technology that’s truly baffling, it’s quantum computing. Qubits, entanglement, quantum states—it’s hard to wrap our heads around these concepts, but they hold great promise. Where is the tech right now?

Mandy Birch, head of engineering strategy at Rigetti Computing, thinks quantum development is starting slowly but will accelerate quickly. “We’re at the innovation stage right now, trying to match this capability to useful applications,” she said. “Can we solve problems cheaper, better, and faster than classical computers can do?” She believes quantum’s first breakthrough will happen in two to five years, and that is highest potential is in applications like routing, supply chain, and risk optimization, followed by quantum chemistry (for materials science and medicine) and machine learning.

David Awschalom, director of the Chicago Quantum Exchange and senior scientist at Argonne National Laboratory, believes quantum communication and quantum sensing will become a reality in three to seven years. “We’ll use states of matter to encrypt information in ways that are completely secure,” he said. A quantum voting system, currently being prototyped, is one application.

Who should be driving quantum tech development? The panelists emphasized that no one entity will get very far alone. “Advancing quantum tech will require collaboration not only between business, academia, and government, but between nations,” said Linda Sapochak, division director of materials research at the National Science Foundation. She added that this doesn’t just go for the technology itself—setting up the infrastructure for quantum will be a big challenge as well.

Space
Space has always been the final frontier, and it still is—but it’s not quite as far-removed from our daily lives now as it was when Neil Armstrong walked on the moon in 1969.

The space industry has always been funded by governments and private defense contractors. But in 2009, SpaceX launched its first commercial satellite, and in subsequent years have drastically cut the cost of spaceflight. More importantly, they published their pricing, which brought transparency to a market that hadn’t seen it before.

Entrepreneurs around the world started putting together business plans, and there are now over 400 privately-funded space companies, many with consumer applications.

Chad Anderson, CEO of Space Angels and managing partner of Space Capital, pointed out that the technology floating around in space was, until recently, archaic. “A few NASA engineers saw they had more computing power in their phone than there was in satellites,” he said. “So they thought, ‘why don’t we just fly an iPhone?’” They did—and it worked.

Now companies have networks of satellites monitoring the whole planet, producing a huge amount of data that’s valuable for countless applications like agriculture, shipping, and observation. “A lot of people underestimate space,” Anderson said. “It’s already enabling our modern global marketplace.”

Next up in the space realm, he predicts, are mining and tourism.

Artificial Intelligence and the Future of Work
From the US to Europe to Asia, alarms are sounding about AI taking our jobs. What will be left for humans to do once machines can do everything—and do it better?

These fears may be unfounded, though, and are certainly exaggerated. It’s undeniable that AI and automation are changing the employment landscape (not to mention the way companies do business and the way we live our lives), but if we build these tools the right way, they’ll bring more good than harm, and more productivity than obsolescence.

Accenture’s Julie Sweet emphasized that AI alone is not what’s disrupting business and employment. Rather, it’s what she called the “triple A”: automation, analytics, and artificial intelligence. But even this fear-inducing trifecta of terms doesn’t spell doom, for workers or for companies. Accenture has automated 40,000 jobs—and hasn’t fired anyone in the process. Instead, they’ve trained and up-skilled people. The most important drivers to scale this, Sweet said, are a commitment by companies and government support (such as tax credits).

Imbuing AI with the best of human values will also be critical to its impact on our future. Tracy Frey, Google Cloud AI’s director of strategy, cited the company’s set of seven AI principles. “What’s important is the governance process that’s put in place to support those principles,” she said. “You can’t make macro decisions when you have technology that can be applied in many different ways.”

High Risks, High Stakes
This year, Vaitheeswaran said, 50 percent of the world’s population will have internet access (he added that he’s disappointed that percentage isn’t higher given the proliferation of smartphones). As technology becomes more widely available to people around the world and its influence grows even more, what are the biggest risks we should be monitoring and controlling?

Information integrity—being able to tell what’s real from what’s fake—is a crucial one. “We’re increasingly operating in siloed realities,” said Renee DiResta, director of research at New Knowledge and head of policy at Data for Democracy. “Inadvertent algorithmic amplification on social media elevates certain perspectives—what does that do to us as a society?”

Algorithms have also already been proven to perpetuate the bias of the people who create it—and those people are often wealthy, white, and male. Ensuring that technology doesn’t propagate unfair bias will be crucial to its ability to serve a diverse population, and to keep societies from becoming further polarized and inequitable. The polarization of experience that results from pronounced inequalities within countries, Vaitheeswaran pointed out, can end up undermining democracy.

We’ll also need to walk the line between privacy and utility very carefully. As Dan Wagner, founder of Civis Analytics put it, “We want to ensure privacy as much as possible, but open access to information helps us achieve important social good.” Medicine in the US has been hampered by privacy laws; if, for example, we had more data about biomarkers around cancer, we could provide more accurate predictions and ultimately better healthcare.

But going the Chinese way—a total lack of privacy—is likely not the answer, either. “We have to be very careful about the way we bake rights and freedom into our technology,” said Alex Gladstein, chief strategy officer at Human Rights Foundation.

Technology’s risks are clearly as fraught as its potential is promising. As Gary Shapiro, chief executive of the Consumer Technology Association, put it, “Everything we’ve talked about today is simply a tool, and can be used for good or bad.”

The decisions we’re making now, at every level—from the engineers writing algorithms, to the legislators writing laws, to the teenagers writing clever Instagram captions—will determine where on the spectrum we end up.

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Posted in Human Robots

#434655 Purposeful Evolution: Creating an ...

More often than not, we fall into the trap of trying to predict and anticipate the future, forgetting that the future is up to us to envision and create. In the words of Buckminster Fuller, “We are called to be architects of the future, not its victims.”

But how, exactly, do we create a “good” future? What does such a future look like to begin with?

In Future Consciousness: The Path to Purposeful Evolution, Tom Lombardo analytically deconstructs how we can flourish in the flow of evolution and create a prosperous future for humanity. Scientifically informed, the books taps into themes that are constructive and profound, from both eastern and western philosophies.

As the executive director of the Center for Future Consciousness and an executive board member and fellow of the World Futures Studies Federation, Lombardo has dedicated his life and career to studying how we can create a “realistic, constructive, and ethical future.”

In a conversation with Singularity Hub, Lombardo discussed purposeful evolution, ethical use of technology, and the power of optimism.

Raya Bidshahri: Tell me more about the title of your book. What is future consciousness and what role does it play in what you call purposeful evolution?

Tom Lombardo: Humans have the unique capacity to purposefully evolve themselves because they possess future consciousness. Future consciousness contains all of the cognitive, motivational, and emotional aspects of the human mind that pertain to the future. It’s because we can imagine and think about the future that we can manipulate and direct our future evolution purposefully. Future consciousness empowers us to become self-responsible in our own evolutionary future. This is a jump in the process of evolution itself.

RB: In several places in the book, you discuss the importance of various eastern philosophies. What can we learn from the east that is often missing from western models?

TL: The key idea in the east that I have been intrigued by for decades is the Taoist Yin Yang, which is the idea that reality should be conceptualized as interdependent reciprocities.

In the west we think dualistically, or we attempt to think in terms of one end of the duality to the exclusion of the other, such as whole versus parts or consciousness versus physical matter. Yin Yang thinking is seeing how both sides of a “duality,” even though they appear to be opposites, are interdependent; you can’t have one without the other. You can’t have order without chaos, consciousness without the physical world, individuals without the whole, humanity without technology, and vice versa for all these complementary pairs.

RB: You talk about the importance of chaos and destruction in the trajectory of human progress. In your own words, “Creativity frequently involves destruction as a prelude to the emergence of some new reality.” Why is this an important principle for readers to keep in mind, especially in the context of today’s world?

TL: In order for there to be progress, there often has to be a disintegration of aspects of the old. Although progress and evolution involve a process of building up, growth isn’t entirely cumulative; it’s also transformative. Things fall apart and come back together again.

Throughout history, we have seen a transformation of what are the most dominant human professions or vocations. At some point, almost everybody worked in agriculture, but most of those agricultural activities were replaced by machines, and a lot of people moved over to industry. Now we’re seeing that jobs and functions are increasingly automated in industry, and humans are being pushed into vocations that involve higher cognitive and artistic skills, services, information technology, and so on.

RB: You raise valid concerns about the dark side of technological progress, especially when it’s combined with mass consumerism, materialism, and anti-intellectualism. How do we counter these destructive forces as we shape the future of humanity?

TL: We can counter such forces by always thoughtfully considering how our technologies are affecting the ongoing purposeful evolution of our conscious minds, bodies, and societies. We should ask ourselves what are the ethical values that are being served by the development of various technologies.

For example, we often hear the criticism that technologies that are driven by pure capitalism degrade human life and only benefit the few people who invented and market them. So we need to also think about what good these new technologies can serve. It’s what I mean when I talk about the “wise cyborg.” A wise cyborg is somebody who uses technology to serve wisdom, or values connected with wisdom.

RB: Creating an ideal future isn’t just about progress in technology, but also progress in morality. How we do decide what a “good” future is? What are some philosophical tools we can use to determine a code of ethics that is as objective as possible?

TL: Let’s keep in mind that ethics will always have some level of subjectivity. That being said, the way to determine a good future is to base it on the best theory of reality that we have, which is that we are evolutionary beings in an evolutionary universe and we are interdependent with everything else in that universe. Our ethics should acknowledge that we are fluid and interactive.

Hence, the “good” can’t be something static, and it can’t be something that pertains to me and not everybody else. It can’t be something that only applies to humans and ignores all other life on Earth, and it must be a mode of change rather than something stable.

RB: You present a consciousness-centered approach to creating a good future for humanity. What are some of the values we should develop in order to create a prosperous future?

TL: A sense of self-responsibility for the future is critical. This means realizing that the “good future” is something we have to take upon ourselves to create; we can’t let something or somebody else do that. We need to feel responsible both for our own futures and for the future around us.

Another one is going to be an informed and hopeful optimism about the future, because both optimism and pessimism have self-fulfilling prophecy effects. If you hope for the best, you are more likely to look deeply into your reality and increase the chance of it coming out that way. In fact, all of the positive emotions that have to do with future consciousness actually make people more intelligent and creative.

Some other important character virtues are discipline and tenacity, deep purpose, the love of learning and thinking, and creativity.

RB: Are you optimistic about the future? If so, what informs your optimism?

I justify my optimism the same way that I have seen Ray Kurzweil, Peter Diamandis, Kevin Kelly, and Steven Pinker justify theirs. If we look at the history of human civilization and even the history of nature, we see a progressive motion forward toward greater complexity and even greater intelligence. There’s lots of ups and downs, and catastrophes along the way, but the facts of nature and human history support the long-term expectation of continued evolution into the future.

You don’t have to be unrealistic to be optimistic. It’s also, psychologically, the more empowering position. That’s the position we should take if we want to maximize the chances of our individual or collective reality turning out better.

A lot of pessimists are pessimistic because they’re afraid of the future. There are lots of reasons to be afraid, but all in all, fear disempowers, whereas hope empowers.

Image Credit: Quick Shot / Shutterstock.com

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Posted in Human Robots

#434643 Sensors and Machine Learning Are Giving ...

According to some scientists, humans really do have a sixth sense. There’s nothing supernatural about it: the sense of proprioception tells you about the relative positions of your limbs and the rest of your body. Close your eyes, block out all sound, and you can still use this internal “map” of your external body to locate your muscles and body parts – you have an innate sense of the distances between them, and the perception of how they’re moving, above and beyond your sense of touch.

This sense is invaluable for allowing us to coordinate our movements. In humans, the brain integrates senses including touch, heat, and the tension in muscle spindles to allow us to build up this map.

Replicating this complex sense has posed a great challenge for roboticists. We can imagine simulating the sense of sight with cameras, sound with microphones, or touch with pressure-pads. Robots with chemical sensors could be far more accurate than us in smell and taste, but building in proprioception, the robot’s sense of itself and its body, is far more difficult, and is a large part of why humanoid robots are so tricky to get right.

Simultaneous localization and mapping (SLAM) software allows robots to use their own senses to build up a picture of their surroundings and environment, but they’d need a keen sense of the position of their own bodies to interact with it. If something unexpected happens, or in dark environments where primary senses are not available, robots can struggle to keep track of their own position and orientation. For human-robot interaction, wearable robotics, and delicate applications like surgery, tiny differences can be extremely important.

Piecemeal Solutions
In the case of hard robotics, this is generally solved by using a series of strain and pressure sensors in each joint, which allow the robot to determine how its limbs are positioned. That works fine for rigid robots with a limited number of joints, but for softer, more flexible robots, this information is limited. Roboticists are faced with a dilemma: a vast, complex array of sensors for every degree of freedom in the robot’s movement, or limited skill in proprioception?

New techniques, often involving new arrays of sensory material and machine-learning algorithms to fill in the gaps, are starting to tackle this problem. Take the work of Thomas George Thuruthel and colleagues in Pisa and San Diego, who draw inspiration from the proprioception of humans. In a new paper in Science Robotics, they describe the use of soft sensors distributed through a robotic finger at random. This placement is much like the constant adaptation of sensors in humans and animals, rather than relying on feedback from a limited number of positions.

The sensors allow the soft robot to react to touch and pressure in many different locations, forming a map of itself as it contorts into complicated positions. The machine-learning algorithm serves to interpret the signals from the randomly-distributed sensors: as the finger moves around, it’s observed by a motion capture system. After training the robot’s neural network, it can associate the feedback from the sensors with the position of the finger detected in the motion-capture system, which can then be discarded. The robot observes its own motions to understand the shapes that its soft body can take, and translate them into the language of these soft sensors.

“The advantages of our approach are the ability to predict complex motions and forces that the soft robot experiences (which is difficult with traditional methods) and the fact that it can be applied to multiple types of actuators and sensors,” said Michael Tolley of the University of California San Diego. “Our method also includes redundant sensors, which improves the overall robustness of our predictions.”

The use of machine learning lets the roboticists come up with a reliable model for this complex, non-linear system of motions for the actuators, something difficult to do by directly calculating the expected motion of the soft-bot. It also resembles the human system of proprioception, built on redundant sensors that change and shift in position as we age.

In Search of a Perfect Arm
Another approach to training robots in using their bodies comes from Robert Kwiatkowski and Hod Lipson of Columbia University in New York. In their paper “Task-agnostic self-modeling machines,” also recently published in Science Robotics, they describe a new type of robotic arm.

Robotic arms and hands are getting increasingly dexterous, but training them to grasp a large array of objects and perform many different tasks can be an arduous process. It’s also an extremely valuable skill to get right: Amazon is highly interested in the perfect robot arm. Google hooked together an array of over a dozen robot arms so that they could share information about grasping new objects, in part to cut down on training time.

Individually training a robot arm to perform every individual task takes time and reduces the adaptability of your robot: either you need an ML algorithm with a huge dataset of experiences, or, even worse, you need to hard-code thousands of different motions. Kwiatkowski and Lipson attempt to overcome this by developing a robotic system that has a “strong sense of self”: a model of its own size, shape, and motions.

They do this using deep machine learning. The robot begins with no prior knowledge of its own shape or the underlying physics of its motion. It then repeats a series of a thousand random trajectories, recording the motion of its arm. Kwiatkowski and Lipson compare this to a baby in the first year of life observing the motions of its own hands and limbs, fascinated by picking up and manipulating objects.

Again, once the robot has trained itself to interpret these signals and build up a robust model of its own body, it’s ready for the next stage. Using that deep-learning algorithm, the researchers then ask the robot to design strategies to accomplish simple pick-up and place and handwriting tasks. Rather than laboriously and narrowly training itself for each individual task, limiting its abilities to a very narrow set of circumstances, the robot can now strategize how to use its arm for a much wider range of situations, with no additional task-specific training.

Damage Control
In a further experiment, the researchers replaced part of the arm with a “deformed” component, intended to simulate what might happen if the robot was damaged. The robot can then detect that something’s up and “reconfigure” itself, reconstructing its self-model by going through the training exercises once again; it was then able to perform the same tasks with only a small reduction in accuracy.

Machine learning techniques are opening up the field of robotics in ways we’ve never seen before. Combining them with our understanding of how humans and other animals are able to sense and interact with the world around us is bringing robotics closer and closer to becoming truly flexible and adaptable, and, eventually, omnipresent.

But before they can get out and shape the world, as these studies show, they will need to understand themselves.

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Posted in Human Robots

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

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

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

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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