Tag Archives: self

#435196 Avatar Love? New ‘Black Mirror’ ...

This week, the widely-anticipated fifth season of the dystopian series Black Mirror was released on Netflix. The storylines this season are less focused on far-out scenarios and increasingly aligned with current issues. With only three episodes, this season raises more questions than it answers, often leaving audiences bewildered.

The episode Smithereens explores our society’s crippling addiction to social media platforms and the monopoly they hold over our data. In Rachel, Jack and Ashley Too, we see the disruptive impact of technologies on the music and entertainment industry, and the price of fame for artists in the digital world. Like most Black Mirror episodes, these explore the sometimes disturbing implications of tech advancements on humanity.

But once again, in the midst of all the doom and gloom, the creators of the series leave us with a glimmer of hope. Aligned with Pride month, the episode Striking Vipers explores the impact of virtual reality on love, relationships, and sexual fluidity.

*The review contains a few spoilers.*

Striking Vipers
The first episode of the season, Striking Vipers may be one of the most thought-provoking episodes in Black Mirror history. Reminiscent of previous episodes San Junipero and Hang the DJ, the writers explore the potential for technology to transform human intimacy.

The episode tells the story of two old friends, Danny and Karl, whose friendship is reignited in an unconventional way. Karl unexpectedly appears at Danny’s 38th birthday and reintroduces him to the VR version of a game they used to play years before. In the game Striking Vipers X, each of the players is represented by an avatar of their choice in an uncanny digital reality. Following old tradition, Karl chooses to become the female fighter, Roxanne, and Danny takes on the role of the male fighter, Lance. The state-of-the-art VR headsets appear to use an advanced form of brain-machine interface to allow each player to be fully immersed in the virtual world, emulating all physical sensations.

To their surprise (and confusion), Danny and Karl find themselves transitioning from fist-fighting to kissing. Over the course of many games, they continue to explore a sexual and romantic relationship in the virtual world, leaving them confused and distant in the real world. The virtual and physical realities begin to blur, and so do the identities of the players with their avatars. Danny, who is married (in a heterosexual relationship) and is a father, begins to carry guilt and confusion in the real world. They both wonder if there would be any spark between them in real life.

The brain-machine interface (BMI) depicted in the episode is still science fiction, but that hasn’t stopped innovators from pushing the technology forward. Experts today are designing more intricate BMI systems while programming better algorithms to interpret the neural signals they capture. Scientists have already succeeded in enabling paralyzed patients to type with their minds, and are even allowing people to communicate with one another purely through brainwaves.

The convergence of BMIs with virtual reality and artificial intelligence could make the experience of such immersive digital realities possible. Virtual reality, too, is decreasing exponentially in cost and increasing in quality.

The narrative provides meaningful commentary on another tech area—gaming. It highlights video games not necessarily as addictive distractions, but rather as a platform for connecting with others in a deeper way. This is already very relevant. Video games like Final Fantasy are often a tool for meaningful digital connections for their players.

The Implications of Virtual Reality on Love and Relationships
The narrative of Striking Vipers raises many novel questions about the implications of immersive technologies on relationships: could the virtual world allow us a safe space to explore suppressed desires? Can virtual avatars make it easier for us to show affection to those we care about? Can a sexual or romantic encounter in the digital world be considered infidelity?

Above all, the episode explores the therapeutic possibilities of such technologies. While many fears about virtual reality had been raised in previous seasons of Black Mirror, this episode was focused on its potential. This includes the potential of immersive technology to be a source of liberation, meaningful connections, and self-exploration, as well as a tool for realizing our true identities and desires.

Once again, this is aligned with emerging trends in VR. We are seeing the rise of social VR applications and platforms that allow you to hang out with your friends and family as avatars in the virtual space. The technology is allowing for animation movies, such as Coco VR, to become an increasingly social and interactive experience. Considering that meaningful social interaction can alleviate depression and anxiety, such applications could contribute to well-being.

Techno-philosopher and National Geographic host Jason Silva points out that immersive media technologies can be “engines of empathy.” VR allows us to enter virtual spaces that mimic someone else’s state of mind, allowing us to empathize with the way they view the world. Silva said, “Imagine the intimacy that becomes possible when people meet and they say, ‘Hey, do you want to come visit my world? Do you want to see what it’s like to be inside my head?’”

What is most fascinating about Striking Vipers is that it explores how we may redefine love with virtual reality; we are introduced to love between virtual avatars. While this kind of love may seem confusing to audiences, it may be one of the complex implications of virtual reality on human relationships.

In many ways, the title Black Mirror couldn’t be more appropriate, as each episode serves as a mirror to the most disturbing aspects of our psyches as they get amplified through technology. However, what we see in uplifting and thought-provoking plots like Striking Vipers, San Junipero, and Hang The DJ is that technology could also amplify the most positive aspects of our humanity. This includes our powerful capacity to love.

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#435186 What’s Behind the International Rush ...

There’s no better way of ensuring you win a race than by setting the rules yourself. That may be behind the recent rush by countries, international organizations, and companies to put forward their visions for how the AI race should be governed.

China became the latest to release a set of “ethical standards” for the development of AI last month, which might raise eyebrows given the country’s well-documented AI-powered state surveillance program and suspect approaches to privacy and human rights.

But given the recent flurry of AI guidelines, it may well have been motivated by a desire not to be left out of the conversation. The previous week the OECD, backed by the US, released its own “guiding principles” for the industry, and in April the EU released “ethical guidelines.”

The language of most of these documents is fairly abstract and noticeably similar, with broad appeals to ideals like accountability, responsibility, and transparency. The OECD’s guidelines are the lightest on detail, while the EU’s offer some more concrete suggestions such as ensuring humans always know if they’re interacting with AI and making algorithms auditable. China’s standards have an interesting focus on promoting openness and collaboration as well as expressly acknowledging AIs potential to disrupt employment.

Overall, though, one might be surprised that there aren’t more disagreements between three blocs with very divergent attitudes to technology, regulation, and economics. Most likely these are just the opening salvos in what will prove to be a long-running debate, and the devil will ultimately be in the details.

The EU seems to have stolen a march on the other two blocs, being first to publish its guidelines and having already implemented the world’s most comprehensive regulation of data—the bedrock of modern AI—with last year’s GDPR. But its lack of industry heavyweights is going to make it hard to hold onto that lead.

One organization that seems to be trying to take on the role of impartial adjudicator is the World Economic Forum, which recently hosted an event designed to find common ground between various stakeholders from across the world. What will come of the effort remains to be seen, but China’s release of guidelines broadly similar to those of its Western counterparts is a promising sign.

Perhaps most telling, though, is the ubiquitous presence of industry leaders in both advisory and leadership positions. China’s guidelines are backed by “an AI industrial league” including Baidu, Alibaba, and Tencent, and the co-chairs of the WEF’s AI Council are Microsoft President Brad Smith and prominent Chinese AI investor Kai-Fu Lee.

Shortly after the EU released its proposals one of the authors, philosopher Thomas Metzinger, said the process had been compromised by the influence of the tech industry, leading to the removal of “red lines” opposing the development of autonomous lethal weapons or social credit score systems like China’s.

For a long time big tech argued for self-regulation, but whether they’ve had an epiphany or have simply sensed the shifting winds, they are now coming out in favor of government intervention.

Both Amazon and Facebook have called for regulation of facial recognition, and in February Google went even further, calling for the government to set down rules governing AI. Facebook chief Mark Zuckerberg has also since called for even broader regulation of the tech industry.

But considering the current concern around the anti-competitive clout of the largest technology companies, it’s worth remembering that tough rules are always easier to deal with for companies with well-developed compliance infrastructure and big legal teams. And these companies are also making sure the regulation is on their terms. Wired details Microsoft’s protracted effort to shape Washington state laws governing facial recognition technology and Google’s enormous lobbying effort.

“Industry has mobilized to shape the science, morality and laws of artificial intelligence,” Harvard law professor Yochai Benkler writes in Nature. He highlights how Amazon’s funding of a National Science Foundation (NSF) program for projects on fairness in artificial intelligence undermines the ability of academia to act as an impartial counterweight to industry.

Excluding industry from the process of setting the rules to govern AI in a fair and equitable way is clearly not practical, writes Benkler, because they are the ones with the expertise. But there also needs to be more concerted public investment in research and policymaking, and efforts to limit the influence of big companies when setting the rules that will govern AI.

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#435172 DARPA’s New Project Is Investing ...

When Elon Musk and DARPA both hop aboard the cyborg hypetrain, you know brain-machine interfaces (BMIs) are about to achieve the impossible.

BMIs, already the stuff of science fiction, facilitate crosstalk between biological wetware with external computers, turning human users into literal cyborgs. Yet mind-controlled robotic arms, microelectrode “nerve patches”, or “memory Band-Aids” are still purely experimental medical treatments for those with nervous system impairments.

With the Next-Generation Nonsurgical Neurotechnology (N3) program, DARPA is looking to expand BMIs to the military. This month, the project tapped six academic teams to engineer radically different BMIs to hook up machines to the brains of able-bodied soldiers. The goal is to ditch surgery altogether—while minimizing any biological interventions—to link up brain and machine.

Rather than microelectrodes, which are currently surgically inserted into the brain to hijack neural communication, the project is looking to acoustic signals, electromagnetic waves, nanotechnology, genetically-enhanced neurons, and infrared beams for their next-gen BMIs.

It’s a radical departure from current protocol, with potentially thrilling—or devastating—impact. Wireless BMIs could dramatically boost bodily functions of veterans with neural damage or post-traumatic stress disorder (PTSD), or allow a single soldier to control swarms of AI-enabled drones with his or her mind. Or, similar to the Black Mirror episode Men Against Fire, it could cloud the perception of soldiers, distancing them from the emotional guilt of warfare.

When trickled down to civilian use, these new technologies are poised to revolutionize medical treatment. Or they could galvanize the transhumanist movement with an inconceivably powerful tool that fundamentally alters society—for better or worse.

Here’s what you need to know.

Radical Upgrades
The four-year N3 program focuses on two main aspects: noninvasive and “minutely” invasive neural interfaces to both read and write into the brain.

Because noninvasive technologies sit on the scalp, their sensors and stimulators will likely measure entire networks of neurons, such as those controlling movement. These systems could then allow soldiers to remotely pilot robots in the field—drones, rescue bots, or carriers like Boston Dynamics’ BigDog. The system could even boost multitasking prowess—mind-controlling multiple weapons at once—similar to how able-bodied humans can operate a third robotic arm in addition to their own two.

In contrast, minutely invasive technologies allow scientists to deliver nanotransducers without surgery: for example, an injection of a virus carrying light-sensitive sensors, or other chemical, biotech, or self-assembled nanobots that can reach individual neurons and control their activity independently without damaging sensitive tissue. The proposed use for these technologies isn’t yet well-specified, but as animal experiments have shown, controlling the activity of single neurons at multiple points is sufficient to program artificial memories of fear, desire, and experiences directly into the brain.

“A neural interface that enables fast, effective, and intuitive hands-free interaction with military systems by able-bodied warfighters is the ultimate program goal,” DARPA wrote in its funding brief, released early last year.

The only technologies that will be considered must have a viable path toward eventual use in healthy human subjects.

“Final N3 deliverables will include a complete integrated bidirectional brain-machine interface system,” the project description states. This doesn’t just include hardware, but also new algorithms tailored to these system, demonstrated in a “Department of Defense-relevant application.”

The Tools
Right off the bat, the usual tools of the BMI trade, including microelectrodes, MRI, or transcranial magnetic stimulation (TMS) are off the table. These popular technologies rely on surgery, heavy machinery, or personnel to sit very still—conditions unlikely in the real world.

The six teams will tap into three different kinds of natural phenomena for communication: magnetism, light beams, and acoustic waves.

Dr. Jacob Robinson at Rice University, for example, is combining genetic engineering, infrared laser beams, and nanomagnets for a bidirectional system. The $18 million project, MOANA (Magnetic, Optical and Acoustic Neural Access device) uses viruses to deliver two extra genes into the brain. One encodes a protein that sits on top of neurons and emits infrared light when the cell activates. Red and infrared light can penetrate through the skull. This lets a skull cap, embedded with light emitters and detectors, pick up these signals for subsequent decoding. Ultra-fast and utra-sensitvie photodetectors will further allow the cap to ignore scattered light and tease out relevant signals emanating from targeted portions of the brain, the team explained.

The other new gene helps write commands into the brain. This protein tethers iron nanoparticles to the neurons’ activation mechanism. Using magnetic coils on the headset, the team can then remotely stimulate magnetic super-neurons to fire while leaving others alone. Although the team plans to start in cell cultures and animals, their goal is to eventually transmit a visual image from one person to another. “In four years we hope to demonstrate direct, brain-to-brain communication at the speed of thought and without brain surgery,” said Robinson.

Other projects in N3 are just are ambitious.

The Carnegie Mellon team, for example, plans to use ultrasound waves to pinpoint light interaction in targeted brain regions, which can then be measured through a wearable “hat.” To write into the brain, they propose a flexible, wearable electrical mini-generator that counterbalances the noisy effect of the skull and scalp to target specific neural groups.

Similarly, a group at Johns Hopkins is also measuring light path changes in the brain to correlate them with regional brain activity to “read” wetware commands.

The Teledyne Scientific & Imaging group, in contrast, is turning to tiny light-powered “magnetometers” to detect small, localized magnetic fields that neurons generate when they fire, and match these signals to brain output.

The nonprofit Battelle team gets even fancier with their ”BrainSTORMS” nanotransducers: magnetic nanoparticles wrapped in a piezoelectric shell. The shell can convert electrical signals from neurons into magnetic ones and vice-versa. This allows external transceivers to wirelessly pick up the transformed signals and stimulate the brain through a bidirectional highway.

The magnetometers can be delivered into the brain through a nasal spray or other non-invasive methods, and magnetically guided towards targeted brain regions. When no longer needed, they can once again be steered out of the brain and into the bloodstream, where the body can excrete them without harm.

Four-Year Miracle
Mind-blown? Yeah, same. However, the challenges facing the teams are enormous.

DARPA’s stated goal is to hook up at least 16 sites in the brain with the BMI, with a lag of less than 50 milliseconds—on the scale of average human visual perception. That’s crazy high resolution for devices sitting outside the brain, both in space and time. Brain tissue, blood vessels, and the scalp and skull are all barriers that scatter and dissipate neural signals. All six teams will need to figure out the least computationally-intensive ways to fish out relevant brain signals from background noise, and triangulate them to the appropriate brain region to decipher intent.

In the long run, four years and an average $20 million per project isn’t much to potentially transform our relationship with machines—for better or worse. DARPA, to its credit, is keenly aware of potential misuse of remote brain control. The program is under the guidance of a panel of external advisors with expertise in bioethical issues. And although DARPA’s focus is on enabling able-bodied soldiers to better tackle combat challenges, it’s hard to argue that wireless, non-invasive BMIs will also benefit those most in need: veterans and other people with debilitating nerve damage. To this end, the program is heavily engaging the FDA to ensure it meets safety and efficacy regulations for human use.

Will we be there in just four years? I’m skeptical. But these electrical, optical, acoustic, magnetic, and genetic BMIs, as crazy as they sound, seem inevitable.

“DARPA is preparing for a future in which a combination of unmanned systems, AI, and cyber operations may cause conflicts to play out on timelines that are too short for humans to effectively manage with current technology alone,” said Al Emondi, the N3 program manager.

The question is, now that we know what’s in store, how should the rest of us prepare?

Image Credit: With permission from DARPA N3 project. Continue reading

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#435161 Less Like Us: An Alternate Theory of ...

The question of whether an artificial general intelligence will be developed in the future—and, if so, when it might arrive—is controversial. One (very uncertain) estimate suggests 2070 might be the earliest we could expect to see such technology.

Some futurists point to Moore’s Law and the increasing capacity of machine learning algorithms to suggest that a more general breakthrough is just around the corner. Others suggest that extrapolating exponential improvements in hardware is unwise, and that creating narrow algorithms that can beat humans at specialized tasks brings us no closer to a “general intelligence.”

But evolution has produced minds like the human mind at least once. Surely we could create artificial intelligence simply by copying nature, either by guided evolution of simple algorithms or wholesale emulation of the human brain.

Both of these ideas are far easier to conceive of than they are to achieve. The 302 neurons of the nematode worm’s brain are still an extremely difficult engineering challenge, let alone the 86 billion in a human brain.

Leaving aside these caveats, though, many people are worried about artificial general intelligence. Nick Bostrom’s influential book on superintelligence imagines it will be an agent—an intelligence with a specific goal. Once such an agent reaches a human level of intelligence, it will improve itself—increasingly rapidly as it gets smarter—in pursuit of whatever goal it has, and this “recursive self-improvement” will lead it to become superintelligent.

This “intelligence explosion” could catch humans off guard. If the initial goal is poorly specified or malicious, or if improper safety features are in place, or if the AI decides it would prefer to do something else instead, humans may be unable to control our own creation. Bostrom gives examples of how a seemingly innocuous goal, such as “Make everyone happy,” could be misinterpreted; perhaps the AI decides to drug humanity into a happy stupor, or convert most of the world into computing infrastructure to pursue its goal.

Drexler and Comprehensive AI Services
These are increasingly familiar concerns for an AI that behaves like an agent, seeking to achieve its goal. There are dissenters to this picture of how artificial general intelligence might arise. One notable alternative point of view comes from Eric Drexler, famous for his work on molecular nanotechnology and Engines of Creation, the book that popularized it.

With respect to AI, Drexler believes our view of an artificial intelligence as a single “agent” that acts to maximize a specific goal is too narrow, almost anthropomorphizing AI, or modeling it as a more realistic route towards general intelligence. Instead, he proposes “Comprehensive AI Services” (CAIS) as an alternative route to artificial general intelligence.

What does this mean? Drexler’s argument is that we should look more closely at how machine learning and AI algorithms are actually being developed in the real world. The optimization effort is going into producing algorithms that can provide services and perform tasks like translation, music recommendations, classification, medical diagnoses, and so forth.

AI-driven improvements in technology, argues Drexler, will lead to a proliferation of different algorithms: technology and software improvement, which can automate increasingly more complicated tasks. Recursive improvement in this regime is already occurring—take the newer versions of AlphaGo, which can learn to improve themselves by playing against previous versions.

Many Smart Arms, No Smart Brain
Instead of relying on some unforeseen breakthrough, the CAIS model of AI just assumes that specialized, narrow AI will continue to improve at performing each of its tasks, and the range of tasks that machine learning algorithms will be able to perform will become wider. Ultimately, once a sufficient number of tasks have been automated, the services that an AI will provide will be so comprehensive that they will resemble a general intelligence.

One could then imagine a “general” intelligence as simply an algorithm that is extremely good at matching the task you ask it to perform to the specialized service algorithm that can perform that task. Rather than acting like a single brain that strives to achieve a particular goal, the central AI would be more like a search engine, looking through the tasks it can perform to find the closest match and calling upon a series of subroutines to achieve the goal.

For Drexler, this is inherently a safety feature. Rather than Bostrom’s single, impenetrable, conscious and superintelligent brain (which we must try to psychoanalyze in advance without really knowing what it will look like), we have a network of capabilities. If you don’t want your system to perform certain tasks, you can simply cut it off from access to those services. There is no superintelligent consciousness to outwit or “trap”: more like an extremely high-level programming language that can respond to complicated commands by calling upon one of the myriad specialized algorithms that have been developed by different groups.

This skirts the complex problem of consciousness and all of the sticky moral quandaries that arise in making minds that might be like ours. After all, if you could simulate a human mind, you could simulate it experiencing unimaginable pain. Black Mirror-esque dystopias where emulated minds have no rights and are regularly “erased” or forced to labor in dull and repetitive tasks, hove into view.

Drexler argues that, in this world, there is no need to ever build a conscious algorithm. Yet it seems likely that, at some point, humans will attempt to simulate our own brains, if only in the vain attempt to pursue immortality. This model cannot hold forever. Yet its proponents argue that any world in which we could develop general AI would probably also have developed superintelligent capabilities in a huge range of different tasks, such as computer programming, natural language understanding, and so on. In other words, CAIS arrives first.

The Future In Our Hands?
Drexler argues that his model already incorporates many of the ideas from general AI development. In the marketplace, algorithms compete all the time to perform these services: they undergo the same evolutionary pressures that lead to “higher intelligence,” but the behavior that’s considered superior is chosen by humans, and the nature of the “general intelligence” is far more shaped by human decision-making and human programmers. Development in AI services could still be rapid and disruptive.

But in Drexler’s case, the research and development capacity comes from humans and organizations driven by the desire to improve algorithms that are performing individualized and useful tasks, rather than from a conscious AI recursively reprogramming and improving itself.

In other words, this vision does not absolve us of the responsibility of making our AI safe; if anything, it gives us a greater degree of responsibility. As more and more complex “services” are automated, performing what used to be human jobs at superhuman speed, the economic disruption will be severe.

Equally, as machine learning is trusted to carry out more complex decisions, avoiding algorithmic bias becomes crucial. Shaping each of these individual decision-makers—and trying to predict the complex ways they might interact with each other—is no less daunting a task than specifying the goal for a hypothetical, superintelligent, God-like AI. Arguably, the consequences of the “misalignment” of these services algorithms are already multiplying around us.

The CAIS model bridges the gap between real-world AI, machine learning developments, and real-world safety considerations, as well as the speculative world of superintelligent agents and the safety considerations involved with controlling their behavior. We should keep our minds open as to what form AI and machine learning will take, and how it will influence our societies—and we must take care to ensure that the systems we create don’t end up forcing us all to live in a world of unintended consequences.

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#435159 This Week’s Awesome Stories From ...

ARTIFICIAL INTELLIGENCE
DeepMind Can Now Beat Us at Multiplayer Games Too
Cade Metz | The New York Times
“DeepMind’s project is part of a broad effort to build artificial intelligence that can play enormously complex, three-dimensional video games, including Quake III, Dota 2 and StarCraft II. Many researchers believe that success in the virtual arena will eventually lead to automated systems with improved abilities in the real world.”

ROBOTICS
Tiny Robots Carry Stem Cells Through a Mouse
Emily Waltz | IEEE Spectrum
“Engineers have built microrobots to perform all sorts of tasks in the body, and can now add to that list another key skill: delivering stem cells. In a paper, published [May 29] in Science Robotics, researchers describe propelling a magnetically-controlled, stem-cell-carrying bot through a live mouse.” [Video shows microbots navigating a microfluidic chip. MRI could not be used to image the mouse as the bots navigate magnetically.]

COMPUTING
How a Quantum Computer Could Break 2048-Bit RSA Encryption in 8 Hours
Emerging Technology From the arXiv | MIT Technology Review
“[Two researchers] have found a more efficient way for quantum computers to perform the code-breaking calculations, reducing the resources they require by orders of magnitude. Consequently, these machines are significantly closer to reality than anyone suspected.” [The arXiv is a pre-print server for research that has not yet been peer reviewed.]

AUTOMATION
Lyft Has Completed 55,000 Self Driving Rides in Las Vegas
Christine Fisher | Engadget
“One year ago, Lyft launched its self-driving ride service in Las Vegas. Today, the company announced its 30-vehicle fleet has made 55,000 trips. That makes it the largest commercial program of its kind in the US.”

TRANSPORTATION
Flying Car Startup Alaka’i Bets Hydrogen Can Outdo Batteries
Eric Adams | Wired
“Alaka’i says the final product will be able to fly for up to four hours and cover 400 miles on a single load of fuel, which can be replenished in 10 minutes at a hydrogen fueling station. It has built a functional, full-scale prototype that will make its first flight ‘imminently,’ a spokesperson says.”

ETHICS
The World Economic Forum Wants to Develop Global Rules for AI
Will Knight | MIT Technology Review
“This week, AI experts, politicians, and CEOs will gather to ask an important question: Can the United States, China, or anyone else agree on how artificial intelligence should be used and controlled?”

SPACE
Building a Rocket in a Garage to Take on SpaceX and Blue Origin
Jackson Ryan | CNET
“While billionaire entrepreneurs like SpaceX’s Elon Musk and Blue Origin’s Jeff Bezos push the boundaries of human spaceflight and exploration, a legion of smaller private startups around the world have been developing their own rocket technology to launch lighter payloads into orbit.”

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