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#432303 What If the AI Revolution Is Neither ...

Why does everyone assume that the AI revolution will either lead to a fiery apocalypse or a glorious utopia, and not something in between? Of course, part of this is down to the fact that you get more attention by saying “The end is nigh!” or “Utopia is coming!”

But part of it is down to how humans think about change, especially unprecedented change. Millenarianism doesn’t have anything to do with being a “millennial,” being born in the 90s and remembering Buffy the Vampire Slayer. It is a way of thinking about the future that involves a deeply ingrained sense of destiny. A definition might be: “Millenarianism is the expectation that the world as it is will be destroyed and replaced with a perfect world, that a redeemer will come to cast down the evil and raise up the righteous.”

Millenarian beliefs, then, intimately link together the ideas of destruction and creation. They involve the idea of a huge, apocalyptic, seismic shift that will destroy the fabric of the old world and create something entirely new. Similar belief systems exist in many of the world’s major religions, and also the unspoken religion of some atheists and agnostics, which is a belief in technology.

Look at some futurist beliefs around the technological Singularity. In Ray Kurzweil’s vision, the Singularity is the establishment of paradise. Everyone is rendered immortal by biotechnology that can cure our ills; our brains can be uploaded to the cloud; inequality and suffering wash away under the wave of these technologies. The “destruction of the world” is replaced by a Silicon Valley buzzword favorite: disruption. And, as with many millenarian beliefs, your mileage varies on whether this destruction paves the way for a new utopia—or simply ends the world.

There are good reasons to be skeptical and interrogative towards this way of thinking. The most compelling reason is probably that millenarian beliefs seem to be a default mode of how humans think about change; just look at how many variants of this belief have cropped up all over the world.

These beliefs are present in aspects of Christian theology, although they only really became mainstream in their modern form in the 19th and 20th centuries. Ideas like the Tribulations—many years of hardship and suffering—before the Rapture, when the righteous will be raised up and the evil punished. After this destruction, the world will be made anew, or humans will ascend to paradise.

Despite being dogmatically atheist, Marxism has many of the same beliefs. It is all about a deterministic view of history that builds to a crescendo. In the same way as Rapture-believers look for signs that prophecies are beginning to be fulfilled, so Marxists look for evidence that we’re in the late stages of capitalism. They believe that, inevitably, society will degrade and degenerate to a breaking point—just as some millenarian Christians do.

In Marxism, this is when the exploitation of the working class by the rich becomes unsustainable, and the working class bands together and overthrows the oppressors. The “tribulation” is replaced by a “revolution.” Sometimes revolutionary figures, like Lenin, or Marx himself, are heralded as messiahs who accelerate the onset of the Millennium; and their rhetoric involves utterly smashing the old system such that a new world can be built. Of course, there is judgment, when the righteous workers take what’s theirs and the evil bourgeoisie are destroyed.

Even Norse mythology has an element of this, as James Hughes points out in his essay in Nick Bostrom’s book Global Catastrophic Risks. Ragnarok involves men and gods being defeated in a final, apocalyptic battle—but because that was a little bleak, they add in the idea that a new earth will arise where the survivors will live in harmony.

Judgement day is a cultural trope, too. Take the ancient Egyptians and their beliefs around the afterlife; the Lord of the underworld, Osiris, weighs the mortal’s heart against a feather. “Should the heart of the deceased prove to be heavy with wrongdoing, it would be eaten by a demon, and the hope of an afterlife vanished.”

Perhaps in the Singularity, something similar goes on. As our technology and hence our power improve, a final reckoning approaches: our hearts, as humans, will be weighed against a feather. If they prove too heavy with wrongdoing—with misguided stupidity, with arrogance and hubris, with evil—then we will fail the test, and we will destroy ourselves. But if we pass, and emerge from the Singularity and all of its threats and promises unscathed, then we will have paradise. And, like the other belief systems, there’s no room for non-believers; all of society is going to be radically altered, whether you want it to be or not, whether it benefits you or leaves you behind. A technological rapture.

It almost seems like every major development provokes this response. Nuclear weapons did, too. Either this would prove the final straw and we’d destroy ourselves, or the nuclear energy could be harnessed to build a better world. People talked at the dawn of the nuclear age about electricity that was “too cheap to meter.” The scientists who worked on the bomb often thought that with such destructive power in human hands, we’d be forced to cooperate and work together as a species.

When we see the same response over and over again to different circumstances, cropping up in different areas, whether it’s science, religion, or politics, we need to consider human biases. We like millenarian beliefs; and so when the idea of artificial intelligence outstripping human intelligence emerges, these beliefs spring up around it.

We don’t love facts. We don’t love information. We aren’t as rational as we’d like to think. We are creatures of narrative. Physicists observe the world and we weave our observations into narrative theories, stories about little billiard balls whizzing around and hitting each other, or space and time that bend and curve and expand. Historians try to make sense of an endless stream of events. We rely on stories: stories that make sense of the past, justify the present, and prepare us for the future.

And as stories go, the millenarian narrative is a brilliant and compelling one. It can lead you towards social change, as in the case of the Communists, or the Buddhist uprisings in China. It can justify your present-day suffering, if you’re in the tribulation. It gives you hope that your life is important and has meaning. It gives you a sense that things are evolving in a specific direction, according to rules—not just randomly sprawling outwards in a chaotic way. It promises that the righteous will be saved and the wrongdoers will be punished, even if there is suffering along the way. And, ultimately, a lot of the time, the millenarian narrative promises paradise.

We need to be wary of the millenarian narrative when we’re considering technological developments and the Singularity and existential risks in general. Maybe this time is different, but we’ve cried wolf many times before. There is a more likely, less appealing story. Something along the lines of: there are many possibilities, none of them are inevitable, and lots of the outcomes are less extreme than you might think—or they might take far longer than you think to arrive. On the surface, it’s not satisfying. It’s so much easier to think of things as either signaling the end of the world or the dawn of a utopia—or possibly both at once. It’s a narrative we can get behind, a good story, and maybe, a nice dream.

But dig a little below the surface, and you’ll find that the millenarian beliefs aren’t always the most promising ones, because they remove human agency from the equation. If you think that, say, the malicious use of algorithms, or the control of superintelligent AI, are serious and urgent problems that are worth solving, you can’t be wedded to a belief system that insists utopia or dystopia are inevitable. You have to believe in the shades of grey—and in your own ability to influence where we might end up. As we move into an uncertain technological future, we need to be aware of the power—and the limitations—of dreams.

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#432271 Your Shopping Experience Is on the Verge ...

Exponential technologies (AI, VR, 3D printing, and networks) are radically reshaping traditional retail.

E-commerce giants (Amazon, Walmart, Alibaba) are digitizing the retail industry, riding the exponential growth of computation.

Many brick-and-mortar stores have already gone bankrupt, or migrated their operations online.

Massive change is occurring in this arena.

For those “real-life stores” that survive, an evolution is taking place from a product-centric mentality to an experience-based business model by leveraging AI, VR/AR, and 3D printing.

Let’s dive in.

E-Commerce Trends
Last year, 3.8 billion people were connected online. By 2024, thanks to 5G, stratospheric and space-based satellites, we will grow to 8 billion people online, each with megabit to gigabit connection speeds.

These 4.2 billion new digital consumers will begin buying things online, a potential bonanza for the e-commerce world.

At the same time, entrepreneurs seeking to service these four-billion-plus new consumers can now skip the costly steps of procuring retail space and hiring sales clerks.

Today, thanks to global connectivity, contract production, and turnkey pack-and-ship logistics, an entrepreneur can go from an idea to building and scaling a multimillion-dollar business from anywhere in the world in record time.

And while e-commerce sales have been exploding (growing from $34 billion in Q1 2009 to $115 billion in Q3 2017), e-commerce only accounted for about 10 percent of total retail sales in 2017.

In 2016, global online sales totaled $1.8 trillion. Remarkably, this $1.8 trillion was spent by only 1.5 billion people — a mere 20 percent of Earth’s global population that year.

There’s plenty more room for digital disruption.

AI and the Retail Experience
For the business owner, AI will demonetize e-commerce operations with automated customer service, ultra-accurate supply chain modeling, marketing content generation, and advertising.

In the case of customer service, imagine an AI that is trained by every customer interaction, learns how to answer any consumer question perfectly, and offers feedback to product designers and company owners as a result.

Facebook’s handover protocol allows live customer service representatives and language-learning bots to work within the same Facebook Messenger conversation.

Taking it one step further, imagine an AI that is empathic to a consumer’s frustration, that can take any amount of abuse and come back with a smile every time. As one example, meet Ava. “Ava is a virtual customer service agent, to bring a whole new level of personalization and brand experience to that customer experience on a day-to-day basis,” says Greg Cross, CEO of Ava’s creator, an Austrian company called Soul Machines.

Predictive modeling and machine learning are also optimizing product ordering and the supply chain process. For example, Skubana, a platform for online sellers, leverages data analytics to provide entrepreneurs constant product performance feedback and maintain optimal warehouse stock levels.

Blockchain is set to follow suit in the retail space. ShipChain and Ambrosus plan to introduce transparency and trust into shipping and production, further reducing costs for entrepreneurs and consumers.

Meanwhile, for consumers, personal shopping assistants are shifting the psychology of the standard shopping experience.

Amazon’s Alexa marks an important user interface moment in this regard.

Alexa is in her infancy with voice search and vocal controls for smart homes. Already, Amazon’s Alexa users, on average, spent more on Amazon.com when purchasing than standard Amazon Prime customers — $1,700 versus $1,400.

As I’ve discussed in previous posts, the future combination of virtual reality shopping, coupled with a personalized, AI-enabled fashion advisor will make finding, selecting, and ordering products fast and painless for consumers.

But let’s take it one step further.

Imagine a future in which your personal AI shopper knows your desires better than you do. Possible? I think so. After all, our future AIs will follow us, watch us, and observe our interactions — including how long we glance at objects, our facial expressions, and much more.

In this future, shopping might be as easy as saying, “Buy me a new outfit for Saturday night’s dinner party,” followed by a surprise-and-delight moment in which the outfit that arrives is perfect.

In this future world of AI-enabled shopping, one of the most disruptive implications is that advertising is now dead.

In a world where an AI is buying my stuff, and I’m no longer in the decision loop, why would a big brand ever waste money on a Super Bowl advertisement?

The dematerialization, demonetization, and democratization of personalized shopping has only just begun.

The In-Store Experience: Experiential Retailing
In 2017, over 6,700 brick-and-mortar retail stores closed their doors, surpassing the former record year for store closures set in 2008 during the financial crisis. Regardless, business is still booming.

As shoppers seek the convenience of online shopping, brick-and-mortar stores are tapping into the power of the experience economy.

Rather than focusing on the practicality of the products they buy, consumers are instead seeking out the experience of going shopping.

The Internet of Things, artificial intelligence, and computation are exponentially improving the in-person consumer experience.

As AI dominates curated online shopping, AI and data analytics tools are also empowering real-life store owners to optimize staffing, marketing strategies, customer relationship management, and inventory logistics.

In the short term,retail store locations will serve as the next big user interface for production 3D printing (custom 3D printed clothes at the Ministry of Supply), virtual and augmented reality (DIY skills clinics), and the Internet of Things (checkout-less shopping).

In the long term,we’ll see how our desire for enhanced productivity and seamless consumption balances with our preference for enjoyable real-life consumer experiences — all of which will be driven by exponential technologies.

One thing is certain: the nominal shopping experience is on the verge of a major transformation.

Implications
The convergence of exponential technologies has already revamped how and where we shop, how we use our time, and how much we pay.

Twenty years ago, Amazon showed us how the web could offer each of us the long tail of available reading material, and since then, the world of e-commerce has exploded.

And yet we still haven’t experienced the cost savings coming our way from drone delivery, the Internet of Things, tokenized ecosystems, the impact of truly powerful AI, or even the other major applications for 3D printing and AR/VR.

Perhaps nothing will be more transformed than today’s $20 trillion retail sector.

Hold on, stay tuned, and get your AI-enabled cryptocurrency ready.

Join Me
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Abundance Digital is my ‘onramp’ for exponential entrepreneurs — those who want to get involved and play at a higher level. Click here to learn more.

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Posted in Human Robots

#432262 How We Can ‘Robot-Proof’ Education ...

Like millions of other individuals in the workforce, you’re probably wondering if you will one day be replaced by a machine. If you’re a student, you’re probably wondering if your chosen profession will even exist by the time you’ve graduated. From driving to legal research, there isn’t much that technology hasn’t already automated (or begun to automate). Many of us will need to adapt to this disruption in the workforce.

But it’s not enough for students and workers to adapt, become lifelong learners, and re-skill themselves. We also need to see innovation and initiative at an institutional and governmental level. According to research by The Economist, almost half of all jobs could be automated by computers within the next two decades, and no government in the world is prepared for it.

While many see the current trend in automation as a terrifying threat, others see it as an opportunity. In Robot-Proof: Higher Education in the Age of Artificial Intelligence, Northeastern University president Joseph Aoun proposes educating students in a way that will allow them to do the things that machines can’t. He calls for a new paradigm that teaches young minds “to invent, to create, and to discover”—filling the relevant needs of our world that robots simply can’t fill. Aoun proposes a much-needed novel framework that will allow us to “robot-proof” education.

Literacies and Core Cognitive Capacities of the Future
Aoun lays a framework for a new discipline, humanics, which discusses the important capacities and literacies for emerging education systems. At its core, the framework emphasizes our uniquely human abilities and strengths.

The three key literacies include data literacy (being able to manage and analyze big data), technological literacy (being able to understand exponential technologies and conduct computational thinking), and human literacy (being able to communicate and evaluate social, ethical, and existential impact).

Beyond the literacies, at the heart of Aoun’s framework are four cognitive capacities that are crucial to develop in our students if they are to be resistant to automation: critical thinking, systems thinking, entrepreneurship, and cultural agility.

“These capacities are mindsets rather than bodies of knowledge—mental architecture rather than mental furniture,” he writes. “Going forward, people will still need to know specific bodies of knowledge to be effective in the workplace, but that alone will not be enough when intelligent machines are doing much of the heavy lifting of information. To succeed, tomorrow’s employees will have to demonstrate a higher order of thought.”

Like many other experts in education, Joseph Aoun emphasizes the importance of critical thinking. This is important not just when it comes to taking a skeptical approach to information, but also being able to logically break down a claim or problem into multiple layers of analysis. We spend so much time teaching students how to answer questions that we often neglect to teach them how to ask questions. Asking questions—and asking good ones—is a foundation of critical thinking. Before you can solve a problem, you must be able to critically analyze and question what is causing it. This is why critical thinking and problem solving are coupled together.

The second capacity, systems thinking, involves being able to think holistically about a problem. The most creative problem-solvers and thinkers are able to take a multidisciplinary perspective and connect the dots between many different fields. According to Aoun, it “involves seeing across areas that machines might be able to comprehend individually but that they cannot analyze in an integrated way, as a whole.” It represents the absolute opposite of how most traditional curricula is structured with emphasis on isolated subjects and content knowledge.

Among the most difficult-to-automate tasks or professions is entrepreneurship.

In fact, some have gone so far as to claim that in the future, everyone will be an entrepreneur. Yet traditionally, initiative has been something students show in spite of or in addition to their schoolwork. For most students, developing a sense of initiative and entrepreneurial skills has often been part of their extracurricular activities. It needs to be at the core of our curricula, not a supplement to it. At its core, teaching entrepreneurship is about teaching our youth to solve complex problems with resilience, to become global leaders, and to solve grand challenges facing our species.

Finally, with an increasingly globalized world, there is a need for more workers with cultural agility, the ability to build amongst different cultural contexts and norms.

One of the major trends today is the rise of the contingent workforce. We are seeing an increasing percentage of full-time employees working on the cloud. Multinational corporations have teams of employees collaborating at different offices across the planet. Collaboration across online networks requires a skillset of its own. As education expert Tony Wagner points out, within these digital contexts, leadership is no longer about commanding with top-down authority, but rather about leading by influence.

An Emphasis on Creativity
The framework also puts an emphasis on experiential or project-based learning, wherein the heart of the student experience is not lectures or exams but solving real-life problems and learning by doing, creating, and executing. Unsurprisingly, humans continue to outdo machines when it comes to innovating and pushing intellectual, imaginative, and creative boundaries, making jobs involving these skills the hardest to automate.

In fact, technological trends are giving rise to what many thought leaders refer to as the imagination economy. This is defined as “an economy where intuitive and creative thinking create economic value, after logical and rational thinking have been outsourced to other economies.” Consequently, we need to develop our students’ creative abilities to ensure their success against machines.

In its simplest form, creativity represents the ability to imagine radical ideas and then go about executing them in reality.

In many ways, we are already living in our creative imaginations. Consider this: every invention or human construct—whether it be the spaceship, an architectural wonder, or a device like an iPhone—once existed as a mere idea, imagined in someone’s mind. The world we have designed and built around us is an extension of our imaginations and is only possible because of our creativity. Creativity has played a powerful role in human progress—now imagine what the outcomes would be if we tapped into every young mind’s creative potential.

The Need for a Radical Overhaul
What is clear from the recommendations of Aoun and many other leading thinkers in this space is that an effective 21st-century education system is radically different from the traditional systems we currently have in place. There is a dramatic contrast between these future-oriented frameworks and the way we’ve structured our traditional, industrial-era and cookie-cutter-style education systems.

It’s time for a change, and incremental changes or subtle improvements are no longer enough. What we need to see are more moonshots and disruption in the education sector. In a world of exponential growth and accelerating change, it is never too soon for a much-needed dramatic overhaul.

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#432051 What Roboticists Are Learning From Early ...

You might not have heard of Hanson Robotics, but if you’re reading this, you’ve probably seen their work. They were the company behind Sophia, the lifelike humanoid avatar that’s made dozens of high-profile media appearances. Before that, they were the company behind that strange-looking robot that seemed a bit like Asimo with Albert Einstein’s head—or maybe you saw BINA48, who was interviewed for the New York Times in 2010 and featured in Jon Ronson’s books. For the sci-fi aficionados amongst you, they even made a replica of legendary author Philip K. Dick, best remembered for having books with titles like Do Androids Dream of Electric Sheep? turned into films with titles like Blade Runner.

Hanson Robotics, in other words, with their proprietary brand of life-like humanoid robots, have been playing the same game for a while. Sometimes it can be a frustrating game to watch. Anyone who gives the robot the slightest bit of thought will realize that this is essentially a chat-bot, with all the limitations this implies. Indeed, even in that New York Times interview with BINA48, author Amy Harmon describes it as a frustrating experience—with “rare (but invariably thrilling) moments of coherence.” This sensation will be familiar to anyone who’s conversed with a chatbot that has a few clever responses.

The glossy surface belies the lack of real intelligence underneath; it seems, at first glance, like a much more advanced machine than it is. Peeling back that surface layer—at least for a Hanson robot—means you’re peeling back Frubber. This proprietary substance—short for “Flesh Rubber,” which is slightly nightmarish—is surprisingly complicated. Up to thirty motors are required just to control the face; they manipulate liquid cells in order to make the skin soft, malleable, and capable of a range of different emotional expressions.

A quick combinatorial glance at the 30+ motors suggests that there are millions of possible combinations; researchers identify 62 that they consider “human-like” in Sophia, although not everyone agrees with this assessment. Arguably, the technical expertise that went into reconstructing the range of human facial expressions far exceeds the more simplistic chat engine the robots use, although it’s the second one that allows it to inflate the punters’ expectations with a few pre-programmed questions in an interview.

Hanson Robotics’ belief is that, ultimately, a lot of how humans will eventually relate to robots is going to depend on their faces and voices, as well as on what they’re saying. “The perception of identity is so intimately bound up with the perception of the human form,” says David Hanson, company founder.

Yet anyone attempting to design a robot that won’t terrify people has to contend with the uncanny valley—that strange blend of concern and revulsion people react with when things appear to be creepily human. Between cartoonish humanoids and genuine humans lies what has often been a no-go zone in robotic aesthetics.

The uncanny valley concept originated with roboticist Masahiro Mori, who argued that roboticists should avoid trying to replicate humans exactly. Since anything that wasn’t perfect, but merely very good, would elicit an eerie feeling in humans, shirking the challenge entirely was the only way to avoid the uncanny valley. It’s probably a task made more difficult by endless streams of articles about AI taking over the world that inexplicably conflate AI with killer humanoid Terminators—which aren’t particularly likely to exist (although maybe it’s best not to push robots around too much).

The idea behind this realm of psychological horror is fairly simple, cognitively speaking.

We know how to categorize things that are unambiguously human or non-human. This is true even if they’re designed to interact with us. Consider the popularity of Aibo, Jibo, or even some robots that don’t try to resemble humans. Something that resembles a human, but isn’t quite right, is bound to evoke a fear response in the same way slightly distorted music or slightly rearranged furniture in your home will. The creature simply doesn’t fit.

You may well reject the idea of the uncanny valley entirely. David Hanson, naturally, is not a fan. In the paper Upending the Uncanny Valley, he argues that great art forms have often resembled humans, but the ultimate goal for humanoid roboticists is probably to create robots we can relate to as something closer to humans than works of art.

Meanwhile, Hanson and other scientists produce competing experiments to either demonstrate that the uncanny valley is overhyped, or to confirm it exists and probe its edges.

The classic experiment involves gradually morphing a cartoon face into a human face, via some robotic-seeming intermediaries—yet it’s in movement that the real horror of the almost-human often lies. Hanson has argued that incorporating cartoonish features may help—and, sometimes, that the uncanny valley is a generational thing which will melt away when new generations grow used to the quirks of robots. Although Hanson might dispute the severity of this effect, it’s clearly what he’s trying to avoid with each new iteration.

Hiroshi Ishiguro is the latest of the roboticists to have dived headlong into the valley.

Building on the work of pioneers like Hanson, those who study human-robot interaction are pushing at the boundaries of robotics—but also of social science. It’s usually difficult to simulate what you don’t understand, and there’s still an awful lot we don’t understand about how we interpret the constant streams of non-verbal information that flow when you interact with people in the flesh.

Ishiguro took this imitation of human forms to extreme levels. Not only did he monitor and log the physical movements people made on videotapes, but some of his robots are based on replicas of people; the Repliee series began with a ‘replicant’ of his daughter. This involved making a rubber replica—a silicone cast—of her entire body. Future experiments were focused on creating Geminoid, a replica of Ishiguro himself.

As Ishiguro aged, he realized that it would be more effective to resemble his replica through cosmetic surgery rather than by continually creating new casts of his face, each with more lines than the last. “I decided not to get old anymore,” Ishiguro said.

We love to throw around abstract concepts and ideas: humans being replaced by machines, cared for by machines, getting intimate with machines, or even merging themselves with machines. You can take an idea like that, hold it in your hand, and examine it—dispassionately, if not without interest. But there’s a gulf between thinking about it and living in a world where human-robot interaction is not a field of academic research, but a day-to-day reality.

As the scientists studying human-robot interaction develop their robots, their replicas, and their experiments, they are making some of the first forays into that world. We might all be living there someday. Understanding ourselves—decrypting the origins of empathy and love—may be the greatest challenge to face. That is, if you want to avoid the valley.

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#432036 The Power to Upgrade Our Own Biology Is ...

Upgrading our biology may sound like science fiction, but attempts to improve humanity actually date back thousands of years. Every day, we enhance ourselves through seemingly mundane activities such as exercising, meditating, or consuming performance-enhancing drugs, such as caffeine or adderall. However, the tools with which we upgrade our biology are improving at an accelerating rate and becoming increasingly invasive.

In recent decades, we have developed a wide array of powerful methods, such as genetic engineering and brain-machine interfaces, that are redefining our humanity. In the short run, such enhancement technologies have medical applications and may be used to treat many diseases and disabilities. Additionally, in the coming decades, they could allow us to boost our physical abilities or even digitize human consciousness.

What’s New?
Many futurists argue that our devices, such as our smartphones, are already an extension of our cortex and in many ways an abstract form of enhancement. According to philosophers Andy Clark and David Chalmers’ theory of extended mind, we use technology to expand the boundaries of the human mind beyond our skulls.

One can argue that having access to a smartphone enhances one’s cognitive capacities and abilities and is an indirect form of enhancement of its own. It can be considered an abstract form of brain-machine interface. Beyond that, wearable devices and computers are already accessible in the market, and people like athletes use them to boost their progress.

However, these interfaces are becoming less abstract.

Not long ago, Elon Musk announced a new company, Neuralink, with the goal of merging the human mind with AI. The past few years have seen remarkable developments in both the hardware and software of brain-machine interfaces. Experts are designing more intricate electrodes while programming better algorithms to interpret neural signals. Scientists have already succeeded in enabling paralyzed patients to type with their minds, and are even allowing brains to communicate with one another purely through brainwaves.

Ethical Challenges of Enhancement
There are many social and ethical implications of such advancements.

One of the most fundamental issues with cognitive and physical enhancement techniques is that they contradict the very definition of merit and success that society has relied on for millennia. Many forms of performance-enhancing drugs have been considered “cheating” for the longest time.

But perhaps we ought to revisit some of our fundamental assumptions as a society.

For example, we like to credit hard work and talent in a fair manner, where “fair” generally implies that an individual has acted in a way that has served him to merit his rewards. If you are talented and successful, it is considered to be because you chose to work hard and take advantage of the opportunities available to you. But by these standards, how much of our accomplishments can we truly be credited for?

For instance, the genetic lottery can have an enormous impact on an individual’s predisposition and personality, which can in turn affect factors such as motivation, reasoning skills, and other mental abilities. Many people are born with a natural ability or a physique that gives them an advantage in a particular area or predisposes them to learn faster. But is it justified to reward someone for excellence if their genes had a pivotal role in their path to success?

Beyond that, there are already many ways in which we take “shortcuts” to better mental performance. Seemingly mundane activities like drinking coffee, meditating, exercising, or sleeping well can boost one’s performance in any given area and are tolerated by society. Even the use of language can have positive physical and psychological effects on the human brain, which can be liberating to the individual and immensely beneficial to society at large. And let’s not forget the fact that some of us are born into more access to developing literacy than others.

Given all these reasons, one could argue that cognitive abilities and talents are currently derived more from uncontrollable factors and luck than we like to admit. If anything, technologies like brain-machine interfaces can enhance individual autonomy and allow one a choice of how capable they become.

As Karim Jebari points out (pdf), if a certain characteristic or trait is required to perform a particular role and an individual lacks this trait, would it be wrong to implement the trait through brain-machine interfaces or genetic engineering? How is this different from any conventional form of learning or acquiring a skill? If anything, this would be removing limitations on individuals that result from factors outside their control, such as biological predisposition (or even traits induced from traumatic experiences) to act or perform in a certain way.

Another major ethical concern is equality. As with any other emerging technology, there are valid concerns that cognitive enhancement tech will benefit only the wealthy, thus exacerbating current inequalities. This is where public policy and regulations can play a pivotal role in the impact of technology on society.

Enhancement technologies can either contribute to inequality or allow us to solve it. Educating and empowering the under-privileged can happen at a much more rapid rate, helping the overall rate of human progress accelerate. The “normal range” for human capacity and intelligence, however it is defined, could shift dramatically towards more positive trends.

Many have also raised concerns over the negative applications of government-led biological enhancement, including eugenics-like movements and super-soldiers. Naturally, there are also issues of safety, security, and well-being, especially within the early stages of experimentation with enhancement techniques.

Brain-machine interfaces, for instance, could have implications on autonomy. The interface involves using information extracted from the brain to stimulate or modify systems in order to accomplish a goal. This part of the process can be enhanced by implementing an artificial intelligence system onto the interface—one that exposes the possibility of a third party potentially manipulating individual’s personalities, emotions, and desires by manipulating the interface.

A Tool For Transcendence
It’s important to discuss these risks, not so that we begin to fear and avoid such technologies, but so that we continue to advance in a way that minimizes harm and allows us to optimize the benefits.

Stephen Hawking notes that “with genetic engineering, we will be able to increase the complexity of our DNA, and improve the human race.” Indeed, the potential advantages of modifying biology are revolutionary. Doctors would gain access to a powerful tool to tackle disease, allowing us to live longer and healthier lives. We might be able to extend our lifespan and tackle aging, perhaps a critical step to becoming a space-faring species. We may begin to modify the brain’s building blocks to become more intelligent and capable of solving grand challenges.

In their book Evolving Ourselves, Juan Enriquez and Steve Gullans describe a world where evolution is no longer driven by natural processes. Instead, it is driven by human choices, through what they call unnatural selection and non-random mutation. Human enhancement is bringing us closer to such a world—it could allow us to take control of our evolution and truly shape the future of our species.

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