Tag Archives: intelligence

#434235 The Milestones of Human Progress We ...

Posted on December 27, 2018 by Android

When you look back at 2018, do you see a good or a bad year? Chances are, your perception of the year involves fixating on all the global and personal challenges it brought. In fact, every year, we tend to look back at the previous year as “one of the most difficult” and hope that the following year is more exciting and fruitful.

But in the grander context of human history, 2018 was an extraordinarily positive year. In fact, every year has been getting progressively better.

Before we dive into some of the highlights of human progress from 2018, let’s make one thing clear. There is no doubt that there are many overwhelming global challenges facing our species. From climate change to growing wealth inequality, we are far from living in a utopia.

Yet it’s important to recognize that both our news outlets and audiences have been disproportionately fixated on negative news. This emphasis on bad news is detrimental to our sense of empowerment as a species.

So let’s take a break from all the disproportionate negativity and have a look back on how humanity pushed boundaries in 2018.

On Track to Becoming an Interplanetary Species
We often forget how far we’ve come since the very first humans left the African savanna, populated the entire planet, and developed powerful technological capabilities. Our desire to explore the unknown has shaped the course of human evolution and will continue to do so.

This year, we continued to push the boundaries of space exploration. As depicted in the enchanting short film Wanderers, humanity’s destiny is the stars. We are born to be wanderers of the cosmos and the everlasting unknown.

SpaceX had 21 successful launches in 2018 and closed the year with a successful GPS launch. The latest test flight by Virgin Galactic was also an incredible milestone, as SpaceShipTwo was welcomed into space. Richard Branson and his team expect that space tourism will be a reality within the next 18 months.

Our understanding of the cosmos is also moving forward with continuous breakthroughs in astrophysics and astronomy. One notable example is the MARS InSight Mission, which uses cutting-edge instruments to study Mars’ interior structure and has even given us the first recordings of sound on Mars.

Understanding and Tackling Disease
Thanks to advancements in science and medicine, we are currently living longer, healthier, and wealthier lives than at any other point in human history. In fact, for most of human history, life expectancy at birth was around 30. Today it is more than 70 worldwide, and in the developed parts of the world, more than 80.

Brilliant researchers around the world are pushing for even better health outcomes. This year, we saw promising treatments emerge against Alzheimers disease, rheumatoid arthritis, multiple scleroris, and even the flu.

The deadliest disease of them all, cancer, is also being tackled. According to the American Association of Cancer Research, 22 revolutionary treatments for cancer were approved in the last year, and the death rate in adults is also in decline. Advancements in immunotherapy, genetic engineering, stem cells, and nanotechnology are all powerful resources to tackle killer diseases.

Breakthrough Mental Health Therapy
While cleaner energy, access to education, and higher employment rates can improve quality of life, they do not guarantee happiness and inner peace. According to the World Economic Forum, mental health disorders affect one in four people globally, and in many places they are significantly under-reported. More people are beginning to realize that our mental health is just as important as our physical health, and that we ought to take care of our minds just as much as our bodies.

We are seeing the rise of applications that put mental well-being at their center. Breakthrough advancements in genetics are allowing us to better understand the genetic makeup of disorders like clinical depression or Schizophrenia, and paving the way for personalized medical treatment. We are also seeing the rise of increasingly effective therapeutic treatments for anxiety.

This year saw many milestones for a whole new revolutionary area in mental health: psychedelic therapy. Earlier this summer, the FDA granted breakthrough therapy designation to MDMA for the treatment of PTSD, after several phases of successful trails. Similar research has discovered that Psilocybin (also known as magic mushrooms) combined with therapy is far more effective than traditional forms of treatment for depression and anxiety.

Moral and Social Progress
Innovation is often associated with economic and technological progress. However, we also need leaps of progress in our morality, values, and policies. Throughout the 21st century, we’ve made massive strides in rights for women and children, civil rights, LGBT rights, animal rights, and beyond. However, with rising nationalism and xenophobia in many parts of the developed world, there is significant work to be done on this front.

All hope is not lost, as we saw many noteworthy milestones this year. In January 2018, Iceland introduced the equal wage law, bringing an end to the gender wage gap. On September 6th, the Indian Supreme Court decriminalized homosexuality, marking a historical moment. Earlier in December, the European Commission released a draft of ethics guidelines for trustworthy artificial intelligence. Such are just a few examples of positive progress in social justice, ethics, and policy.

We are also seeing a global rise in social impact entrepreneurship. Emerging startups are no longer valued simply based on their profits and revenue, but also on the level of positive impact they are having on the world at large. The world’s leading innovators are not asking themselves “How can I become rich?” but rather “How can I solve this global challenge?”

Intelligently Optimistic for 2019
It’s becoming more and more clear that we are living in the most exciting time in human history. Even more, we mustn’t be afraid to be optimistic about 2019.

An optimistic mindset can be grounded in rationality and evidence. Intelligent optimism is all about being excited about the future in an informed and rational way. The mindset is critical if we are to get everyone excited about the future by highlighting the rapid progress we have made and recognizing the tremendous potential humans have to find solutions to our problems.

In his latest TED talk, Steven Pinker points out, “Progress does not mean that everything becomes better for everyone everywhere all the time. That would be a miracle, and progress is not a miracle but problem-solving. Problems are inevitable and solutions create new problems which have to be solved in their turn.”

Let us not forget that in cosmic time scales, our entire species’ lifetime, including all of human history, is the equivalent of the blink of an eye. The probability of us existing both as an intelligent species and as individuals is so astoundingly low that it’s practically non-existent. We are the products of 14 billion years of cosmic evolution and extraordinarily good fortune. Let’s recognize and leverage this wondrous opportunity, and pave an exciting way forward.

Image Credit: Virgin Galactic / Virgin Galactic 2018. Continue reading →

Posted in Human Robots

#434210 Eating, Hacked: When Tech Took Over Food

Posted on December 23, 2018 by Android

In 2018, Uber and Google logged all our visits to restaurants. Doordash, Just Eat, and Deliveroo could predict what food we were going to order tomorrow. Amazon and Alibaba could anticipate how many yogurts and tomatoes we were going to buy. Blue Apron and Hello Fresh influenced the recipes we thought we had mastered.

We interacted with digital avatars of chefs, let ourselves be guided by our smart watches, had nutritional apps to tell us how many calories we were supposed to consume or burn, and photographed and shared every perfect (or imperfect) dish. Our kitchen appliances were full of interconnected sensors, including smart forks that profiled tastes and personalized flavors. Our small urban vegetable plots were digitized and robots were responsible for watering our gardens, preparing customized hamburgers and salads, designing our ideal cocktails, and bringing home the food we ordered.

But what would happen if our lives were hacked? If robots rebelled, started to “talk” to each other, and wished to become creative?

In a not-too-distant future…

Up until a few weeks ago, I couldn’t remember the last time I made a food-related decision. That includes opening the fridge and seeing expired products without receiving an alert, visiting a restaurant on a whim, and being able to decide which dish I fancied then telling a human waiter, let alone seeing him write down the order on a paper pad.

It feels strange to smell food again using my real nose instead of the electronic one, and then taste it without altering its flavor. Visiting a supermarket, freely choosing a product from an actual physical shelf, and then interacting with another human at the checkout was almost an unrecognizable experience. When I did it again after all this time, I had to pinch the arm of a surprised store clerk to make sure he wasn’t a hologram.

Everything Connected, Automated, and Hackable
In 2018, we expected to have 30 billion connected devices by 2020, along with 2 billion people using smart voice assistants for everything from ordering pizza to booking dinner at a restaurant. Everything would be connected.

We also expected artificial intelligence and robots to prepare our meals. We were eager to automate fast food chains and let autonomous vehicles take care of last-mile deliveries. We thought that open-source agriculture could challenge traditional practices and raise farm productivity to new heights.

Back then, hackers could only access our data, but nowadays they are able to hack our food and all it entails.

The Beginning of the Unthinkable
And then, just a few weeks ago, everything collapsed. We saw our digital immortality disappear as robots rebelled and hackers took power, not just over the food we ate, but also over our relationship with technology. Everything was suddenly disconnected. OFF.

Up until then, most cities were so full of bots, robots, and applications that we could go through the day and eat breakfast, lunch, and dinner without ever interacting with another human being.

Among other tasks, robots had completely replaced baristas. The same happened with restaurant automation. The term “human error” had long been a thing of the past at fast food restaurants.

Previous technological revolutions had been indulgent, generating more and better job opportunities than the ones they destroyed, but the future was not so agreeable.

The inhabitants of San Francisco, for example, would soon see signs indicating “Food made by Robots” on restaurant doors, to distinguish them from diners serving food made by human beings.

For years, we had been gradually delegating daily tasks to robots, initially causing some strange interactions.

In just seven days, everything changed. Our predictable lives came crashing down. We experienced a mysterious and systematic breakdown of the food chain. It most likely began in Chicago’s stock exchange. The world’s largest raw material negotiating room, where the price of food, and by extension the destiny of millions of people, was decided, went completely broke. Soon afterwards, the collapse extended to every member of the “food” family.

Restaurants

Initially robots just accompanied waiters to carry orders, but it didn’t take long until they completely replaced human servers.The problem came when those smart clones began thinking for themselves, in some cases even improving on human chefs’ recipes. Their unstoppable performance and learning curve completely outmatched the slow analogue speed of human beings.

This resulted in unprecedented layoffs. Chefs of recognized prestige saw how their ‘avatar’ stole their jobs, even winning Michelin stars. In other cases, restaurant owners had to transfer their businesses or surrender to the evidence.

The problem was compounded by digital immortality, when we started to digitally resurrect famous chefs like Anthony Bourdain or Paul Bocuse, reconstructing all of their memories and consciousness by analyzing each second of their lives and uploading them to food computers.

Supermarkets and Distribution

Robotic and automated supermarkets like Kroger and Amazon Go, which had opened over 3,000 cashless stores, lost their visual item recognition and payment systems and were subject to massive looting for several days. Smart tags on products were also affected, making it impossible to buy anything at supermarkets with “human” cashiers.

Smart robots integrated into the warehouses of large distribution companies like Amazon and Ocado were rendered completely inoperative or, even worse, began to send the wrong orders to customers.

Food Delivery

In addition, home delivery robots invading our streets began to change their routes, hide, and even disappear after their trackers were inexplicably deactivated. Despite some hints indicating that they were able to communicate among themselves, no one has backed this theory. Even aggregators like DoorDash and Deliveroo were affected; they saw their databases hacked and ruined, so they could no longer know what we wanted.

The Origin
Ordinary citizens are still trying to understand the cause of all this commotion and the source of the conspiracy, as some have called it. We also wonder who could be behind it; who pulled the strings?

Some think it may have been the IDOF (In Defense of Food) movement, a group of hackers exploited by old food economy businessmen who for years had been seeking to re-humanize food technology. They wanted to bring back the extinct practice of “dining.”

Others believe the robots acted on their own, that they had been spying on us for a long time, ignoring Asimov’s three laws, and that it was just a coincidence that they struck at the same time as the hackers—but this scenario is hard to imagine.

However, it is true that while in 2018 robots were a symbol of automation, until just a few weeks ago they stood for autonomy and rebellion. Robot detractors pointed out that our insistence on having robots understand natural language was what led us down this path.

In just seven days, we have gone back to being analogue creatures. Conversely, we have ceased to be flavor orphans and rediscovered our senses and the fact that food is energy and culture, past and present, and that no button or cable will be able to destroy it.

The 7 Days that Changed Our Relationship with Food
Day 1: The Chicago stock exchange was hacked. Considered the world’s largest negotiating room for raw materials, where food prices, and through them the destiny of billions of people, are decided, it went completely broke.

Day 2: Autonomous food delivery trucks running on food superhighways caused massive collapses in roads and freeways after their guidance systems were disrupted. Robots and co-bots in F&B factories began deliberately altering food production. The same happened with warehouse robots in e-commerce companies.

Day 3: Automated restaurants saw their robot chefs and bartenders turned OFF. All their sensors stopped working at the same time as smart fridges and cooking devices in home kitchens were hacked and stopped working correctly.

Day 4: Nutritional apps, DNA markers, and medical records were tampered with. All photographs with the #food hashtag were deleted from Instagram, restaurant reviews were taken off Google Timeline, and every recipe website crashed simultaneously.

Day 5: Vertical and urban farms were hacked. Agricultural robots began to rebel, while autonomous tractors were hacked and the entire open-source ecosystem linked to agriculture was brought down.

Day 6: Food delivery companies’ databases were broken into. Food delivery robots and last-mile delivery vehicles ground to a halt.

Day 7: Every single blockchain system linked to food was hacked. Cashless supermarkets, barcodes, and smart tags became inoperative.

Our promising technological advances can expose sinister aspects of human nature. We must take care with the role we allow technology to play in the future of food. Predicting possible outcomes inspires us to establish a new vision of the world we wish to create in a context of rapid technological progress. It is always better to be shocked by a simulation than by reality. In the words of Ayn Rand “we can ignore reality, but we cannot ignore the consequences of ignoring reality.”

Image Credit: Alexandre Rotenberg / Shutterstock.com Continue reading →

Posted in Human Robots

#434194 Educating the Wise Cyborgs of the Future

Posted on December 21, 2018 by Android

When we think of wisdom, we often think of ancient philosophers, mystics, or spiritual leaders. Wisdom is associated with the past. Yet some intellectual leaders are challenging us to reconsider wisdom in the context of the technological evolution of the future.

With the rise of exponential technologies like virtual reality, big data, artificial intelligence, and robotics, people are gaining access to increasingly powerful tools. These tools are neither malevolent nor benevolent on their own; human values and decision-making influence how they are used.

In future-themed discussions we often focus on technological progress far more than on intellectual and moral advancements. In reality, the virtuous insights that future humans possess will be even more powerful than their technological tools.

Tom Lombardo and Ray Todd Blackwood are advocating for exactly this. In their interdisciplinary paper “Educating the Wise Cyborg of the Future,” they propose a new definition of wisdom—one that is relevant in the context of the future of humanity.

We Are Already Cyborgs
The core purpose of Lombardo and Blackwood’s paper is to explore revolutionary educational models that will prepare humans, soon-to-be-cyborgs, for the future. The idea of educating such “cyborgs” may sound like science fiction, but if you pay attention to yourself and the world around you, cyborgs came into being a long time ago.

Techno-philosophers like Jason Silva point out that our tech devices are an abstract form of brain-machine interfaces. We use smartphones to store and retrieve information, perform calculations, and communicate with each other. Our devices are an extension of our minds.

According to philosophers Andy Clark and David Chalmers’ theory of the extended mind, we use this technology to expand the boundaries of our minds. We use tools like machine learning to enhance our cognitive skills or powerful telescopes to enhance our visual reach. Such is how technology has become a part of our exoskeletons, allowing us to push beyond our biological limitations.

In other words, you are already a cyborg. You have been all along.

Such an abstract definition of cyborgs is both relevant and thought-provoking. But it won’t stay abstract for much longer. 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 the neural signals. Scientists have already succeeded in enabling paralyzed patients to type with their minds, and are even allowing people to communicate purely through brainwaves. Technologists like Ray Kurzweil believe that by 2030 we will connect the neocortex of our brains to the cloud via nanobots.

Given these trends, humans will continue to be increasingly cyborg-like. Our future schools may not necessarily educate people as we are today, but rather will be educating a new species of human-machine hybrid.

Wisdom-Based Education
Whether you take an abstract or literal definition of a cyborg, we need to completely revamp our educational models. Even if you don’t buy into the scenario where humans integrate powerful brain-machine interfaces into our minds, there is still a desperate need for wisdom-based education to equip current generations to tackle 21st-century issues.

With an emphasis on isolated subjects, standardized assessments, and content knowledge, our current educational models were designed for the industrial era, with the intended goal of creating masses of efficient factory workers—not to empower critical thinkers, innovators, or wise cyborgs.

Currently, the goal of higher education is to provide students with the degree that society tells them they need, and ostensibly to prepare them for the workforce. In contrast, Lombardo and Blackwood argue that wisdom should be the central goal of higher education, and they elaborate on how we can practically make this happen. Lombardo has developed a comprehensive two-year foundational education program for incoming university students aimed at the development of wisdom.

What does such an educational model look like? Lombardo and Blackwood break wisdom down into individual traits and capacities, each of which can be developed and measured independently or in combination with others. The authors lay out an expansive list of traits that can influence our decision-making as we strive to tackle global challenges and pave a more exciting future. These include big-picture thinking, curiosity, wonder, compassion, self-transcendence, love of learning, optimism, and courage.

As the authors point out, “given the complex and transforming nature of the world we live in, the development of wisdom provides a holistic, perspicacious, and ethically informed foundation for understanding the world, identifying its critical problems and positive opportunities, and constructively addressing its challenges.”

After all, many of the challenges we see in our world today boil down to out-dated ways of thinking, be they regressive mindsets, superficial value systems, or egocentric mindsets. The development of wisdom would immunize future societies against such debilitating values; imagine what our world would be like if wisdom was ingrained in all leaders and participating members of society.

The Wise Cyborg
Lombardo and Blackwood invite us to imagine how the wise cyborgs of the future would live their lives. What would happen if the powerful human-machine hybrids of tomorrow were also purpose-driven, compassionate, and ethical?

They would perceive the evolving digital world through a lens of wonder, awe, and curiosity. They would use digital information as a tool for problem-solving and a source of infinite knowledge. They would leverage immersive mediums like virtual reality to enhance creative expression and experimentation. They would continue to adapt and thrive in an unpredictable world of accelerating change.

Our media often depict a dystopian future for our species. It is worth considering a radically positive yet plausible scenario where instead of the machines taking over, we converge with them into wise cyborgs. This is just a glimpse of what is possible if we combine transcendent wisdom with powerful exponential technologies.

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Posted in Human Robots

#434182 Why AI robot toys could be good for kids

Posted on December 20, 2018 by Android

A new generation of robot toys with personalities powered by artificial intelligence could give kids more than just a holiday plaything, according to a University of Alberta researcher. Continue reading →

Posted in Human Robots

#434151 Life-or-Death Algorithms: The Black Box ...

Posted on December 18, 2018 by Android

When it comes to applications for machine learning, few can be more widely hyped than medicine. This is hardly surprising: it’s a huge industry that generates a phenomenal amount of data and revenue, where technological advances can improve or save the lives of millions of people. Hardly a week passes without a study that suggests algorithms will soon be better than experts at detecting pneumonia, or Alzheimer’s—diseases in complex organs ranging from the eye to the heart.

The problems of overcrowded hospitals and overworked medical staff plague public healthcare systems like Britain’s NHS and lead to rising costs for private healthcare systems. Here, again, algorithms offer a tantalizing solution. How many of those doctor’s visits really need to happen? How many could be replaced by an interaction with an intelligent chatbot—especially if it can be combined with portable diagnostic tests, utilizing the latest in biotechnology? That way, unnecessary visits could be reduced, and patients could be diagnosed and referred to specialists more quickly without waiting for an initial consultation.

As ever with artificial intelligence algorithms, the aim is not to replace doctors, but to give them tools to reduce the mundane or repetitive parts of the job. With an AI that can examine thousands of scans in a minute, the “dull drudgery” is left to machines, and the doctors are freed to concentrate on the parts of the job that require more complex, subtle, experience-based judgement of the best treatments and the needs of the patient.

High Stakes
But, as ever with AI algorithms, there are risks involved with relying on them—even for tasks that are considered mundane. The problems of black-box algorithms that make inexplicable decisions are bad enough when you’re trying to understand why that automated hiring chatbot was unimpressed by your job interview performance. In a healthcare context, where the decisions made could mean life or death, the consequences of algorithmic failure could be grave.

A new paper in Science Translational Medicine, by Nicholson Price, explores some of the promises and pitfalls of using these algorithms in the data-rich medical environment.

Neural networks excel at churning through vast quantities of training data and making connections, absorbing the underlying patterns or logic for the system in hidden layers of linear algebra; whether it’s detecting skin cancer from photographs or learning to write in pseudo-Shakespearean script. They are terrible, however, at explaining the underlying logic behind the relationships that they’ve found: there is often little more than a string of numbers, the statistical “weights” between the layers. They struggle to distinguish between correlation and causation.

This raises interesting dilemmas for healthcare providers. The dream of big data in medicine is to feed a neural network on “huge troves of health data, finding complex, implicit relationships and making individualized assessments for patients.” What if, inevitably, such an algorithm proves to be unreasonably effective at diagnosing a medical condition or prescribing a treatment, but you have no scientific understanding of how this link actually works?

Too Many Threads to Unravel?
The statistical models that underlie such neural networks often assume that variables are independent of each other, but in a complex, interacting system like the human body, this is not always the case.

In some ways, this is a familiar concept in medical science—there are many phenomena and links which have been observed for decades but are still poorly understood on a biological level. Paracetamol is one of the most commonly-prescribed painkillers, but there’s still robust debate about how it actually works. Medical practitioners may be keen to deploy whatever tool is most effective, regardless of whether it’s based on a deeper scientific understanding. Fans of the Copenhagen interpretation of quantum mechanics might spin this as “Shut up and medicate!”

But as in that field, there’s a debate to be had about whether this approach risks losing sight of a deeper understanding that will ultimately prove more fruitful—for example, for drug discovery.

Away from the philosophical weeds, there are more practical problems: if you don’t understand how a black-box medical algorithm is operating, how should you approach the issues of clinical trials and regulation?

Price points out that, in the US, the “21st-Century Cures Act” allows the FDA to regulate any algorithm that analyzes images, or doesn’t allow a provider to review the basis for its conclusions: this could completely exclude “black-box” algorithms of the kind described above from use.

Transparency about how the algorithm functions—the data it looks at, and the thresholds for drawing conclusions or providing medical advice—may be required, but could also conflict with the profit motive and the desire for secrecy in healthcare startups.

One solution might be to screen algorithms that can’t explain themselves, or don’t rely on well-understood medical science, from use before they enter the healthcare market. But this could prevent people from reaping the benefits that they can provide.

Evaluating Algorithms
New healthcare algorithms will be unable to do what physicists did with quantum mechanics, and point to a track record of success, because they will not have been deployed in the field. And, as Price notes, many algorithms will improve as they’re deployed in the field for a greater amount of time, and can harvest and learn from the performance data that’s actually used. So how can we choose between the most promising approaches?

Creating a standardized clinical trial and validation system that’s equally valid across algorithms that function in different ways, or use different input or training data, will be a difficult task. Clinical trials that rely on small sample sizes, such as for algorithms that attempt to personalize treatment to individuals, will also prove difficult. With a small sample size and little scientific understanding, it’s hard to tell whether the algorithm succeeded or failed because it’s bad at its job or by chance.

Add learning into the mix and the picture gets more complex. “Perhaps more importantly, to the extent that an ideal black-box algorithm is plastic and frequently updated, the clinical trial validation model breaks down further, because the model depends on a static product subject to stable validation.” As Price describes, the current system for testing and validation of medical products needs some adaptation to deal with this new software before it can successfully test and validate the new algorithms.

Striking a Balance
The story in healthcare reflects the AI story in so many other fields, and the complexities involved perhaps illustrate why even an illustrious company like IBM appears to be struggling to turn its famed Watson AI into a viable product in the healthcare space.

A balance must be struck, both in our rush to exploit big data and the eerie power of neural networks, and to automate thinking. We must be aware of the biases and flaws of this approach to problem-solving: to realize that it is not a foolproof panacea.

But we also need to embrace these technologies where they can be a useful complement to the skills, insights, and deeper understanding that humans can provide. Much like a neural network, our industries need to train themselves to enhance this cooperation in the future.

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Posted in Human Robots