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#432893 These 4 Tech Trends Are Driving Us ...

From a first-principles perspective, the task of feeding eight billion people boils down to converting energy from the sun into chemical energy in our bodies.

Traditionally, solar energy is converted by photosynthesis into carbohydrates in plants (i.e., biomass), which are either eaten by the vegans amongst us, or fed to animals, for those with a carnivorous preference.

Today, the process of feeding humanity is extremely inefficient.

If we could radically reinvent what we eat, and how we create that food, what might you imagine that “future of food” would look like?

In this post we’ll cover:

Vertical farms
CRISPR engineered foods
The alt-protein revolution
Farmer 3.0

Let’s dive in.

Vertical Farming
Where we grow our food…

The average American meal travels over 1,500 miles from farm to table. Wine from France, beef from Texas, potatoes from Idaho.

Imagine instead growing all of your food in a 50-story tall vertical farm in downtown LA or off-shore on the Great Lakes where the travel distance is no longer 1,500 miles but 50 miles.

Delocalized farming will minimize travel costs at the same time that it maximizes freshness.

Perhaps more importantly, vertical farming also allows tomorrow’s farmer the ability to control the exact conditions of her plants year round.

Rather than allowing the vagaries of the weather and soil conditions to dictate crop quality and yield, we can now perfectly control the growing cycle.

LED lighting provides the crops with the maximum amount of light, at the perfect frequency, 24 hours a day, 7 days a week.

At the same time, sensors and robots provide the root system the exact pH and micronutrients required, while fine-tuning the temperature of the farm.

Such precision farming can generate yields that are 200% to 400% above normal.

Next let’s explore how we can precision-engineer the genetic properties of the plant itself.

CRISPR and Genetically Engineered Foods
What food do we grow?

A fundamental shift is occurring in our relationship with agriculture. We are going from evolution by natural selection (Darwinism) to evolution by human direction.

CRISPR (the cutting edge gene editing tool) is providing a pathway for plant breeding that is more predictable, faster and less expensive than traditional breeding methods.

Rather than our crops being subject to nature’s random, environmental whim, CRISPR unlocks our capability to modify our crops to match the available environment.

Further, using CRISPR we will be able to optimize the nutrient density of our crops, enhancing their value and volume.

CRISPR may also hold the key to eliminating common allergens from crops. As we identify the allergen gene in peanuts, for instance, we can use CRISPR to silence that gene, making the crops we raise safer for and more accessible to a rapidly growing population.

Yet another application is our ability to make plants resistant to infection or more resistant to drought or cold.

Helping to accelerate the impact of CRISPR, the USDA recently announced that genetically engineered crops will not be regulated—providing an opening for entrepreneurs to capitalize on the opportunities for optimization CRISPR enables.

CRISPR applications in agriculture are an opportunity to help a billion people and become a billionaire in the process.

Protecting crops against volatile environments, combating crop diseases and increasing nutrient values, CRISPR is a promising tool to help feed the world’s rising population.

The Alt-Protein/Lab-Grown Meat Revolution
Something like a third of the Earth’s arable land is used for raising livestock—a massive amount of land—and global demand for meat is predicted to double in the coming decade.

Today, we must grow an entire cow—all bones, skin, and internals included—to produce a steak.

Imagine if we could instead start with a single muscle stem cell and only grow the steak, without needing the rest of the cow? Think of it as cellular agriculture.

Imagine returning millions, perhaps billions, of acres of grazing land back to the wilderness? This is the promise of lab-grown meats.

Lab-grown meat can also be engineered (using technology like CRISPR) to be packed with nutrients and be the healthiest, most delicious protein possible.

We’re watching this technology develop in real time. Several startups across the globe are already working to bring artificial meats to the food industry.

JUST, Inc. (previously Hampton Creek) run by my friend Josh Tetrick, has been on a mission to build a food system where everyone can get and afford delicious, nutritious food. They started by exploring 300,000+ species of plants all around the world to see how they can make food better and now are investing heavily in stem-cell-grown meats.

Backed by Richard Branson and Bill Gates, Memphis Meats is working on ways to produce real meat from animal cells, rather than whole animals. So far, they have produced beef, chicken, and duck using cultured cells from living animals.

As with vertical farming, transitioning production of our majority protein source to a carefully cultivated environment allows for agriculture to optimize inputs (water, soil, energy, land footprint), nutrients and, importantly, taste.

Farmer 3.0
Vertical farming and cellular agriculture are reinventing how we think about our food supply chain and what food we produce.

The next question to answer is who will be producing the food?

Let’s look back at how farming evolved through history.

Farmers 0.0 (Neolithic Revolution, around 9000 BCE): The hunter-gatherer to agriculture transition gains momentum, and humans cultivated the ability to domesticate plants for food production.

Farmers 1.0 (until around the 19th century): Farmers spent all day in the field performing backbreaking labor, and agriculture accounted for most jobs.

Farmers 2.0 (mid-20th century, Green Revolution): From the invention of the first farm tractor in 1812 through today, transformative mechanical biochemical technologies (fertilizer) boosted yields and made the job of farming easier, driving the US farm job rate down to less than two percent today.

Farmers 3.0: In the near future, farmers will leverage exponential technologies (e.g., AI, networks, sensors, robotics, drones), CRISPR and genetic engineering, and new business models to solve the world’s greatest food challenges and efficiently feed the eight-billion-plus people on Earth.

An important driver of the Farmer 3.0 evolution is the delocalization of agriculture driven by vertical and urban farms. Vertical farms and urban agriculture are empowering a new breed of agriculture entrepreneurs.

Let’s take a look at an innovative incubator in Brooklyn, New York called Square Roots.

Ten farm-in-a-shipping-containers in a Brooklyn parking lot represent the first Square Roots campus. Each 8-foot x 8.5-foot x 20-foot shipping container contains an equivalent of 2 acres of produce and can yield more than 50 pounds of produce each week.

For 13 months, one cohort of next-generation food entrepreneurs takes part in a curriculum with foundations in farming, business, community and leadership.

The urban farming incubator raised a $5.4 million seed funding round in August 2017.

Training a new breed of entrepreneurs to apply exponential technology to growing food is essential to the future of farming.

One of our massive transformative purposes at the Abundance Group is to empower entrepreneurs to generate extraordinary wealth while creating a world of abundance. Vertical farms and cellular agriculture are key elements enabling the next generation of food and agriculture entrepreneurs.

Conclusion
Technology is driving food abundance.

We’re already seeing food become demonetized, as the graph below shows.

From 1960 to 2014, the percent of income spent on food in the U.S. fell from 19 percent to under 10 percent of total disposable income—a dramatic decrease over the 40 percent of household income spent on food in 1900.

The dropping percent of per-capita disposable income spent on food. Source: USDA, Economic Research Service, Food Expenditure Series
Ultimately, technology has enabled a massive variety of food at a significantly reduced cost and with fewer resources used for production.

We’re increasingly going to optimize and fortify the food supply chain to achieve more reliable, predictable, and nutritious ways to obtain basic sustenance.

And that means a world with abundant, nutritious, and inexpensive food for every man, woman, and child.

What an extraordinary time to be alive.

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#432512 How Will Merging Minds and Machines ...

One of the most exciting and frightening outcomes of technological advancement is the potential to merge our minds with machines. If achieved, this would profoundly boost our cognitive capabilities. More importantly, however, it could be a revolution in human identity, emotion, spirituality, and self-awareness.

Brain-machine interface technology is already being developed by pioneers and researchers around the globe. It’s still early and today’s tech is fairly rudimentary, but it’s a fast-moving field, and some believe it will advance faster than generally expected. Futurist Ray Kurzweil has predicted that by the 2030s we will be able to connect our brains to the internet via nanobots that will “provide full-immersion virtual reality from within the nervous system, provide direct brain-to-brain communication over the internet, and otherwise greatly expand human intelligence.” Even if the advances are less dramatic, however, they’ll have significant implications.

How might this technology affect human consciousness? What about its implications on our sentience, self-awareness, or subjective experience of our illusion of self?

Consciousness can be hard to define, but a holistic definition often encompasses many of our most fundamental capacities, such as wakefulness, self-awareness, meta-cognition, and sense of agency. Beyond that, consciousness represents a spectrum of awareness, as seen across various species of animals. Even humans experience different levels of existential awareness.

From psychedelics to meditation, there are many tools we already use to alter and heighten our conscious experience, both temporarily and permanently. These tools have been said to contribute to a richer life, with the potential to bring experiences of beauty, love, inner peace, and transcendence. Relatively non-invasive, these tools show us what a seemingly minor imbalance of neurochemistry and conscious internal effort can do to the subjective experience of being human.

Taking this into account, what implications might emerging brain-machine interface technologies have on the “self”?

The Tools for Self-Transcendence
At the basic level, we are currently seeing the rise of “consciousness hackers” using techniques like non-invasive brain stimulation through EEG, nutrition, virtual reality, and ecstatic experiences to create environments for heightened consciousness and self-awareness. In Stealing Fire, Steven Kotler and Jamie Wheal explore this trillion-dollar altered-states economy and how innovators and thought leaders are “harnessing rare and controversial states of consciousness to solve critical challenges and outperform the competition.” Beyond enhanced productivity, these altered states expose our inner potential and give us a glimpse of a greater state of being.

Expanding consciousness through brain augmentation and implants could one day be just as accessible. Researchers are working on an array of neurotechnologies as simple and non-invasive as electrode-based EEGs to invasive implants and techniques like optogenetics, where neurons are genetically reprogrammed to respond to pulses of light. We’ve already connected two brains via the internet, allowing the two to communicate, and future-focused startups are researching the possibilities too. With an eye toward advanced brain-machine interfaces, last year Elon Musk unveiled Neuralink, a company whose ultimate goal is to merge the human mind with AI through a “neural lace.”

Many technologists predict we will one day merge with and, more speculatively, upload our minds onto machines. Neuroscientist Kenneth Hayworth writes in Skeptic magazine, “All of today’s neuroscience models are fundamentally computational by nature, supporting the theoretical possibility of mind-uploading.” This might include connecting with other minds using digital networks or even uploading minds onto quantum computers, which can be in multiple states of computation at a given time.

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. With advancements in genetic engineering, we are indeed seeing evolution become an increasingly conscious process with an accelerated pace. This could one day apply to the evolution of our consciousness as well; we would be using our consciousness to expand our consciousness.

What Will It Feel Like?
We may be able to come up with predictions of the impact of these technologies on society, but we can only wonder what they will feel like subjectively.

It’s hard to imagine, for example, what our stream of consciousness will feel like when we can process thoughts and feelings 1,000 times faster, or how artificially intelligent brain implants will impact our capacity to love and hate. What will the illusion of “I” feel like when our consciousness is directly plugged into the internet? Overall, what impact will the process of merging with technology have on the subjective experience of being human?

The Evolution of Consciousness
In The Future Evolution of Consciousness, Thomas Lombardo points out, “We are a journey rather than a destination—a chapter in the evolutionary saga rather than a culmination. Just as probable, there will also be a diversification of species and types of conscious minds. It is also very likely that new psychological capacities, incomprehensible to us, will emerge as well.”

Humans are notorious for fearing the unknown. For any individual who has never experienced an altered state, be it spiritual or psychedelic-induced, it is difficult to comprehend the subjective experience of that state. It is why many refer to their first altered-state experience as “waking up,” wherein they didn’t even realize they were asleep.

Similarly, exponential neurotechnology represents the potential of a higher state of consciousness and a range of experiences that are unimaginable to our current default state.

Our capacity to think and feel is set by the boundaries of our biological brains. To transform and expand these boundaries is to transform and expand the first-hand experience of consciousness. Emerging neurotechnology may end up providing the awakening our species needs.

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#431995 The 10 Grand Challenges Facing Robotics ...

Robotics research has been making great strides in recent years, but there are still many hurdles to the machines becoming a ubiquitous presence in our lives. The journal Science Robotics has now identified 10 grand challenges the field will have to grapple with to make that a reality.

Editors conducted an online survey on unsolved challenges in robotics and assembled an expert panel of roboticists to shortlist the 30 most important topics, which were then grouped into 10 grand challenges that could have major impact in the next 5 to 10 years. Here’s what they came up with.

1. New Materials and Fabrication Schemes
Roboticists are beginning to move beyond motors, gears, and sensors by experimenting with things like artificial muscles, soft robotics, and new fabrication methods that combine multiple functions in one material. But most of these advances have been “one-off” demonstrations, which are not easy to combine.

Multi-functional materials merging things like sensing, movement, energy harvesting, or energy storage could allow more efficient robot designs. But combining these various properties in a single machine will require new approaches that blend micro-scale and large-scale fabrication techniques. Another promising direction is materials that can change over time to adapt or heal, but this requires much more research.

2. Bioinspired and Bio-Hybrid Robots
Nature has already solved many of the problems roboticists are trying to tackle, so many are turning to biology for inspiration or even incorporating living systems into their robots. But there are still major bottlenecks in reproducing the mechanical performance of muscle and the ability of biological systems to power themselves.

There has been great progress in artificial muscles, but their robustness, efficiency, and energy and power density need to be improved. Embedding living cells into robots can overcome challenges of powering small robots, as well as exploit biological features like self-healing and embedded sensing, though how to integrate these components is still a major challenge. And while a growing “robo-zoo” is helping tease out nature’s secrets, more work needs to be done on how animals transition between capabilities like flying and swimming to build multimodal platforms.

3. Power and Energy
Energy storage is a major bottleneck for mobile robotics. Rising demand from drones, electric vehicles, and renewable energy is driving progress in battery technology, but the fundamental challenges have remained largely unchanged for years.

That means that in parallel to battery development, there need to be efforts to minimize robots’ power utilization and give them access to new sources of energy. Enabling them to harvest energy from their environment and transmitting power to them wirelessly are two promising approaches worthy of investigation.

4. Robot Swarms
Swarms of simple robots that assemble into different configurations to tackle various tasks can be a cheaper, more flexible alternative to large, task-specific robots. Smaller, cheaper, more powerful hardware that lets simple robots sense their environment and communicate is combining with AI that can model the kind of behavior seen in nature’s flocks.

But there needs to be more work on the most efficient forms of control at different scales—small swarms can be controlled centrally, but larger ones need to be more decentralized. They also need to be made robust and adaptable to the changing conditions of the real world and resilient to deliberate or accidental damage. There also needs to be more work on swarms of non-homogeneous robots with complementary capabilities.

5. Navigation and Exploration
A key use case for robots is exploring places where humans cannot go, such as the deep sea, space, or disaster zones. That means they need to become adept at exploring and navigating unmapped, often highly disordered and hostile environments.

The major challenges include creating systems that can adapt, learn, and recover from navigation failures and are able to make and recognize new discoveries. This will require high levels of autonomy that allow the robots to monitor and reconfigure themselves while being able to build a picture of the world from multiple data sources of varying reliability and accuracy.

6. AI for Robotics
Deep learning has revolutionized machines’ ability to recognize patterns, but that needs to be combined with model-based reasoning to create adaptable robots that can learn on the fly.

Key to this will be creating AI that’s aware of its own limitations and can learn how to learn new things. It will also be important to create systems that are able to learn quickly from limited data rather than the millions of examples used in deep learning. Further advances in our understanding of human intelligence will be essential to solving these problems.

7. Brain-Computer Interfaces
BCIs will enable seamless control of advanced robotic prosthetics but could also prove a faster, more natural way to communicate instructions to robots or simply help them understand human mental states.

Most current approaches to measuring brain activity are expensive and cumbersome, though, so work on compact, low-power, and wireless devices will be important. They also tend to involve extended training, calibration, and adaptation due to the imprecise nature of reading brain activity. And it remains to be seen if they will outperform simpler techniques like eye tracking or reading muscle signals.

8. Social Interaction
If robots are to enter human environments, they will need to learn to deal with humans. But this will be difficult, as we have very few concrete models of human behavior and we are prone to underestimate the complexity of what comes naturally to us.

Social robots will need to be able to perceive minute social cues like facial expression or intonation, understand the cultural and social context they are operating in, and model the mental states of people they interact with to tailor their dealings with them, both in the short term and as they develop long-standing relationships with them.

9. Medical Robotics
Medicine is one of the areas where robots could have significant impact in the near future. Devices that augment a surgeon’s capabilities are already in regular use, but the challenge will be to increase the autonomy of these systems in such a high-stakes environment.

Autonomous robot assistants will need to be able to recognize human anatomy in a variety of contexts and be able to use situational awareness and spoken commands to understand what’s required of them. In surgery, autonomous robots could perform the routine steps of a procedure, giving way to the surgeon for more complicated patient-specific bits.

Micro-robots that operate inside the human body also hold promise, but there are still many roadblocks to their adoption, including effective delivery systems, tracking and control methods, and crucially, finding therapies where they improve on current approaches.

10. Robot Ethics and Security
As the preceding challenges are overcome and robots are increasingly integrated into our lives, this progress will create new ethical conundrums. Most importantly, we may become over-reliant on robots.

That could lead to humans losing certain skills and capabilities, making us unable to take the reins in the case of failures. We may end up delegating tasks that should, for ethical reasons, have some human supervision, and allow people to pass the buck to autonomous systems in the case of failure. It could also reduce self-determination, as human behaviors change to accommodate the routines and restrictions required for robots and AI to work effectively.

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#431958 The Next Generation of Cameras Might See ...

You might be really pleased with the camera technology in your latest smartphone, which can recognize your face and take slow-mo video in ultra-high definition. But these technological feats are just the start of a larger revolution that is underway.

The latest camera research is shifting away from increasing the number of mega-pixels towards fusing camera data with computational processing. By that, we don’t mean the Photoshop style of processing where effects and filters are added to a picture, but rather a radical new approach where the incoming data may not actually look like at an image at all. It only becomes an image after a series of computational steps that often involve complex mathematics and modeling how light travels through the scene or the camera.

This additional layer of computational processing magically frees us from the chains of conventional imaging techniques. One day we may not even need cameras in the conventional sense any more. Instead we will use light detectors that only a few years ago we would never have considered any use for imaging. And they will be able to do incredible things, like see through fog, inside the human body and even behind walls.

Single Pixel Cameras
One extreme example is the single pixel camera, which relies on a beautifully simple principle. Typical cameras use lots of pixels (tiny sensor elements) to capture a scene that is likely illuminated by a single light source. But you can also do things the other way around, capturing information from many light sources with a single pixel.

To do this you need a controlled light source, for example a simple data projector that illuminates the scene one spot at a time or with a series of different patterns. For each illumination spot or pattern, you then measure the amount of light reflected and add everything together to create the final image.

Clearly the disadvantage of taking a photo in this is way is that you have to send out lots of illumination spots or patterns in order to produce one image (which would take just one snapshot with a regular camera). But this form of imaging would allow you to create otherwise impossible cameras, for example that work at wavelengths of light beyond the visible spectrum, where good detectors cannot be made into cameras.

These cameras could be used to take photos through fog or thick falling snow. Or they could mimic the eyes of some animals and automatically increase an image’s resolution (the amount of detail it captures) depending on what’s in the scene.

It is even possible to capture images from light particles that have never even interacted with the object we want to photograph. This would take advantage of the idea of “quantum entanglement,” that two particles can be connected in a way that means whatever happens to one happens to the other, even if they are a long distance apart. This has intriguing possibilities for looking at objects whose properties might change when lit up, such as the eye. For example, does a retina look the same when in darkness as in light?

Multi-Sensor Imaging
Single-pixel imaging is just one of the simplest innovations in upcoming camera technology and relies, on the face of it, on the traditional concept of what forms a picture. But we are currently witnessing a surge of interest for systems that use lots of information but traditional techniques only collect a small part of it.

This is where we could use multi-sensor approaches that involve many different detectors pointed at the same scene. The Hubble telescope was a pioneering example of this, producing pictures made from combinations of many different images taken at different wavelengths. But now you can buy commercial versions of this kind of technology, such as the Lytro camera that collects information about light intensity and direction on the same sensor, to produce images that can be refocused after the image has been taken.

The next generation camera will probably look something like the Light L16 camera, which features ground-breaking technology based on more than ten different sensors. Their data are combined using a computer to provide a 50 MB, re-focusable and re-zoomable, professional-quality image. The camera itself looks like a very exciting Picasso interpretation of a crazy cell-phone camera.

Yet these are just the first steps towards a new generation of cameras that will change the way in which we think of and take images. Researchers are also working hard on the problem of seeing through fog, seeing behind walls, and even imaging deep inside the human body and brain.

All of these techniques rely on combining images with models that explain how light travels through through or around different substances.

Another interesting approach that is gaining ground relies on artificial intelligence to “learn” to recognize objects from the data. These techniques are inspired by learning processes in the human brain and are likely to play a major role in future imaging systems.

Single photon and quantum imaging technologies are also maturing to the point that they can take pictures with incredibly low light levels and videos with incredibly fast speeds reaching a trillion frames per second. This is enough to even capture images of light itself traveling across as scene.

Some of these applications might require a little time to fully develop, but we now know that the underlying physics should allow us to solve these and other problems through a clever combination of new technology and computational ingenuity.

This article was originally published on The Conversation. Read the original article.

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#431920 If We Could Engineer Animals to Be as ...

Advances in neural implants and genetic engineering suggest that in the not–too–distant future we may be able to boost human intelligence. If that’s true, could we—and should we—bring our animal cousins along for the ride?
Human brain augmentation made headlines last year after several tech firms announced ambitious efforts to build neural implant technology. Duke University neuroscientist Mikhail Lebedev told me in July it could be decades before these devices have applications beyond the strictly medical.
But he said the technology, as well as other pharmacological and genetic engineering approaches, will almost certainly allow us to boost our mental capacities at some point in the next few decades.
Whether this kind of cognitive enhancement is a good idea or not, and how we should regulate it, are matters of heated debate among philosophers, futurists, and bioethicists, but for some it has raised the question of whether we could do the same for animals.
There’s already tantalizing evidence of the idea’s feasibility. As detailed in BBC Future, a group from MIT found that mice that were genetically engineered to express the human FOXP2 gene linked to learning and speech processing picked up maze routes faster. Another group at Wake Forest University studying Alzheimer’s found that neural implants could boost rhesus monkeys’ scores on intelligence tests.
The concept of “animal uplift” is most famously depicted in the Planet of the Apes movie series, whose planet–conquering protagonists are likely to put most people off the idea. But proponents are less pessimistic about the outcomes.
Science fiction author David Brin popularized the concept in his “Uplift” series of novels, in which humans share the world with various other intelligent animals that all bring their own unique skills, perspectives, and innovations to the table. “The benefits, after a few hundred years, could be amazing,” he told Scientific American.
Others, like George Dvorsky, the director of the Rights of Non-Human Persons program at the Institute for Ethics and Emerging Technologies, go further and claim there is a moral imperative. He told the Boston Globe that denying augmentation technology to animals would be just as unethical as excluding certain groups of humans.
Others are less convinced. Forbes’ Alex Knapp points out that developing the technology to uplift animals will likely require lots of very invasive animal research that will cause huge suffering to the animals it purports to help. This is problematic enough with normal animals, but could be even more morally dubious when applied to ones whose cognitive capacities have been enhanced.
The whole concept could also be based on a fundamental misunderstanding of the nature of intelligence. Humans are prone to seeing intelligence as a single, self-contained metric that progresses in a linear way with humans at the pinnacle.
In an opinion piece in Wired arguing against the likelihood of superhuman artificial intelligence, Kevin Kelly points out that science has no such single dimension with which to rank the intelligence of different species. Each one combines a bundle of cognitive capabilities, some of which are well below our own capabilities and others which are superhuman. He uses the example of the squirrel, which can remember the precise location of thousands of acorns for years.
Uplift efforts may end up being less about boosting intelligence and more about making animals more human-like. That represents “a kind of benevolent colonialism” that assumes being more human-like is a good thing, Paul Graham Raven, a futures researcher at the University of Sheffield in the United Kingdom, told the Boston Globe. There’s scant evidence that’s the case, and it’s easy to see how a chimpanzee with the mind of a human might struggle to adjust.
There are also fundamental barriers that may make it difficult to achieve human-level cognitive capabilities in animals, no matter how advanced brain augmentation technology gets. In 2013 Swedish researchers selectively bred small fish called guppies for bigger brains. This made them smarter, but growing the energy-intensive organ meant the guppies developed smaller guts and produced fewer offspring to compensate.
This highlights the fact that uplifting animals may require more than just changes to their brains, possibly a complete rewiring of their physiology that could prove far more technically challenging than human brain augmentation.
Our intelligence is intimately tied to our evolutionary history—our brains are bigger than other animals’; opposable thumbs allow us to use tools; our vocal chords make complex communication possible. No matter how much you augment a cow’s brain, it still couldn’t use a screwdriver or talk to you in English because it simply doesn’t have the machinery.
Finally, from a purely selfish point of view, even if it does become possible to create a level playing field between us and other animals, it may not be a smart move for humanity. There’s no reason to assume animals would be any more benevolent than we are, having evolved in the same ‘survival of the fittest’ crucible that we have. And given our already endless capacity to divide ourselves along national, religious, or ethnic lines, conflict between species seems inevitable.
We’re already likely to face considerable competition from smart machines in the coming decades if you believe the hype around AI. So maybe adding a few more intelligent species to the mix isn’t the best idea.
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