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Treating Your Stress with AI Technology

Robots are our stress relief

Anxiety, stress, overthinking, and trauma are commonly used words to describe people suffering from mental health disorders that appear from work overload, depression, negative feedback, and much more. It’s very likely to see people suffering from anxiety faster than coming in contact with positive and uplifting people. Here is how to treat your stress with AI technology.

Will AI technology become a panacea for mental disorders?

The fact is, the world isn’t becoming a safer or stable place. It’s rather becoming stressful and discouraging with the COVID 19 pandemic taking over the world and putting us on lockdown.

Nevertheless, technology hasn’t given up on humankind yet. Researchers and scientists are doing their best to provide aid and stabilize the situation for the greater good.

 

“We are changing the world with technology.� Bill Gates

Changing the world with AI Technology
It’s one small step for man, one giant step for technology.

Artificial intelligent technology is now blasting through the roof with its extraordinary inventions. You have robots that can clean, play with you, and make you a drink with just a simple voice command. It’s remarkable how today’s modern age high-tech gadgets can complete simple human tasks, and even complex ones, to make everyday life easier. Sometimes robots can even do these tasks better than humans.

We have used technology to facilitate our lives and make the world a better place with motor-related tasks. The real question is, how far can Artificial Intelligence go from there? Can it subserve humans in the mental aspect? Can AI technology treat anxiety and depression?

What is Artificial Intelligence Technology?

Artificial Intelligence is the process of having robots or technology adapt and react to human tasks by learning from experiences. It’s using the technology of machine learning, deep learning, and natural language processing to have robots doing motor-related tasks, competing in chess, and driving cars without passengers. Which are the type of inventions we see now.

This definition of artificial intelligence can vary from one person to another. Though what’s known for sure is that it’s robots thinking and acting like humans. It all depends on programming technology for problem-solving.

You notice today’s modern development in AI technology and the inventions created using this deep machine learning process, with phone features like the voice activation commands you can give to your phone to make it schedule an appointment, make a call, or set a reminder for you.

You might also be aware of the word translation feature on your phone. A simple scan of a written page (handwritten or typed) will have it fully translated for you by using the camera on your phone.

AI technology is found all around us nowadays.

You can see your phone using AI — it’s all over the internet, other technological objects like cars, and much more. It makes you wonder how all of this works and how it’s possible to make robots interpret human thinking.

How AI works is not the essence of this article. I can tell you that it all relies on the processing of data through advanced algorithms and learning from the patterns or features from the data given. It includes machine learning, deep learning, cognitive computing, and other factors that make the process possible.

After that brief explanation of AI, a question comes to mind. If robots can almost think and do what humans can, is it possible for them to develop emotions as well?

Can AI Technology Feel?

As we have mentioned, AI technology processes data and algorithms to distinguish certain patterns and features. This process allows them to solve problems as well as think and do what humans can do. So, is it possible for AI robots to develop emotions just like humans?

AI Technology Robots are our stress relief
Let robots help you with your stress.

While it’s never scientifically proven that AI technology can acquire or develop human emotions from using deep and machine learning, a group of researchers at the Massachusetts Institute of Technology has developed a neural-network model that can detect signs of depression from a person’s voice or written text. It detects depression in a person’s speech depending on the answers to the series of questions given to him/her.

Although this might seem a massive leap for AI and can help numerous people suffering from depression. It still isn’t accurate enough, for the process relies on the person’s specific answers to specific questions. Therefore, it limits how and on whom this model can be used.

On the other hand, researchers have discussed a neural-network model that might be introduced in the future to mobile apps and more. This model is able to indicate depression from speech patterns and text typing. They are hoping that this modified model can help distinguish depression even in natural conversations.

If this model succeeds, it will facilitate many people suffering from depression that can’t get a clinical diagnosis because of the distance, high cost, or other factors.

AI Technology Treating Depression and Anxiety

It’s clear to us now that there’s no proof or successful implementation of AI technology developing human emotions. Even so, are emotions needed to treat human’s mental health? Is it required to have emotions to treat others’ anxiety?

There are numerous techniques and methods that help people reduce anxiety and depression.

Whether it’s picking up a new hobby, playing some sports, or even traveling to a country to clear the mind can aid your stress and reduce depression levels. The one method that I want to shed some light on is owning a pet. Yes! Taking care of your dog, cat, or any other pet is proven to reduce anxiety and help people suffering from depression.

Studies have shown that snuggling up to your furry friend and showing unconditional love to it will make a pet owner less likely to suffer from depression than other people who don’t own a pet. Also, it’s proof that playing with a cat or dog can stimulate high levels of dopamine, which will ease a person’s mind, relax them, and calm them down.

Different studies prove caring for a pet will reduce anxiety, depression, loneliness, and other health disorders. Besides, pets also help us develop healthy lifestyles like increasing exercise, meeting new people, and more, but that’s a whole different story. So, what do animals have to do with AI treating human anxiety and depression?

Since animals don’t have human emotions, and can sometimes sense depression. But at the same time can help their owners with their anxiety by just playing and snuggling. Can’t a robot do the same?

Vector the Robot

Take Vector the robot, for example. This magnificent AI technology gadget is a small robot. It’s about the size of the palm of your hand. It can take pictures, tell you the time and temperature, and do other tasks by using your voice.

This innovative invention amazes me because it has a curious and attentive personality that makes it almost think and act like a pet. It gets sad when you ignore it, gets angry when it loses a game against you, and it gets excited when it sees you. Now call me crazy, but I think you can call this robot a somewhat animal pet (that is a pet-robot). And think — no allergies!

Even though it’s not proven that Vector, the robot will reduce your depression and anxiety levels. It seems to me that it almost acts like a pet but with a more intellectual background. Meaning, what has been proven that pets can treat human health disorders, can also be treated by AI technology robots like Vector. As well as other AI operating robots in the market.

Conclusion:

To make things clear, this was only my opinion on the topic at hand, for no scientific breakthrough has proven my theory and thoughts on AI treating human anxiety. But I believe that there are many ills — both in society and in mental and physical healthcare that AI will be able to help with, if not cure.

To conclude, Artificial Intelligence technology is truly remarkable and has yet to exceed the limits in the near future. Although my opinion is just a theory, it still seems like at some point in time; AI technology will improve and develop to things we have not yet imagined — aside from the motor-related tasks it provides and iterates on today.

Image Credit: lenin estrada; pexels

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Time to Build Robots for Humans, Not to Replace

robots

Thinking about the future of robots and autonomy is exciting; driverless cars, lights-out factories, urban air mobility, robotic surgeons available anywhere in the world. We’ve seen the building blocks come together in warehouses, retail stores, farms, and on the roads. It is now time to build robots for humans, not to replace them.

We still have a long way to go. Why? Because building robots that intend to work fully autonomously in a physical world is hard.

Humans are incredibly good at adapting to dynamic situations to achieve a goal. Robotic and autonomous systems are incredibly powerful at highly precise, responsive, multivariate operations. A new generation of companies is turning their attention to bringing the two together, building robots to work for humans, not replace them, and reinventing several industries in the process.

Innovation through limitation

New methods of ML, such as reinforcement learning and adversarial networks, have transformed both the speed and capability of robot systems.

These methods work extremely well when:

  1. Designed for well-known tasks.
  2. Within constrained environments and limited variable change.
  3. Where most end states are known.

Where the probability of unforeseen situations and ‘rules’ are low, robots can work miraculously better than any human can.

An Amazon robot-powered warehouse is an excellent illustration of well-characterized tasks (goods movement), in constrained environments (warehouse), with limited diversity (structured paths), and all end states are known (limited task variability).

Robots in a complex world

What about in a less structured environment, where there are greater complexity and variability? The probability of errors and unforeseen situations is proportional to the complexity of the process.

In the physical world, what is a robot to do when it encounters a situation it has never seen before? That question conflicts with the robots’ understanding of the expected environment and has unknown end states.

The conflicted robot is precisely the challenge companies are facing when introducing robots into the physical world.

Audi claimed they would hit level 3 autonomy by 2019 (update: they recently gave up). Waymo has driven 20 million miles yet operationally and geographically constrained.

Tesla reverted from a fully robotic factory approach back to a human-machine mix, the company stating, “Automation simply can’t deal with the complexity, inconsistencies, variation and ‘things gone wrong’ that humans can.�

Yes — this complex issue will be figured out — but the situation is not solved yet.

To solve these problems in the physical world, we’ve implemented humans as technology guardrails.

Applications such as driverless cars, last-mile delivery robots, warehouse robots, robots making pizza, cleaning floors, and more, can operate in the real world thanks to ‘humans in the loop’ monitoring their operations.

Humans are acting as either remote operators, AI data trainers, and exception managers.

Human-in-the-Loop robotics

The ‘human in the loop’ has accelerated the pace of technology and opened up capabilities we didn’t think we would see in our lifetime, as the examples mentioned earlier.

At the same time, it has bounded the use cases to which we build. When we design robotic systems around commodity skill sets, the range of tasks is limited to those just those skills.

Training and operating a driverless car, delivery robot, or warehouse robot all require the same generally held skill sets.

As a result, what robots are capable of today primarily cluster around the ability to navigate and identify people/objects.

As these companies bring their solutions to market, they quickly realize two realities:

(1) Commodity tasks make it easier for others to also attempt a similar solution (as seen with the number of AV and warehouse robot companies emerging over the past few years).

(2) High labor liquidity depresses wages, thus requiring these solutions to fully replace the human, not augment, in high volumes to generate any meaningful economics. E.g., Waymo/Uber/Zoox needs to remove the driver and operate at high volumes to turn a profit eventually.

The result of the commodity approach to robotics has forced these technology developers to completely replace the human from the loop to become viable businesses.

Changing the intersection of robotics and humans

The open question is: is this the right intersection between machine and human? Is this the best we can do to leverage the precision of a robot with the creativity of a human?

Expert-in-the-Loop robotics

To accelerate what robots are capable of doing, we need to shift focus from trying to replace humans, to building solutions that put the robot and human hand-in-hand. For robots to find their way into critical workflows of our industries, we needed them to augment experts and trained technicians.

Industries such as general aviation, construction, manufacturing, retail, farming, and healthcare could be made safer, more efficient, and more profitable. Changing the human’s role of operator and technician to manager and strategist.

Helicopter pilots could free themselves from the fatiguing balance of flight and control management. Construction machine operators could focus on strategies and exceptions rather than repetitive motions.

Manufacturing facilities could free up workers to focus on throughput, workflow, and quality, rather than tiring manual labor. Retail operators could focus on customer experiences rather than trying to keep up with stocking inventory.

These industries all suffer from limited labor pools, highly variable environments, with little technology, and high cost of errors. Pairing robotic or autonomous systems that work hand in hand with the experts could invert from the set of dynamics compared to commodity use cases.

Companies could build solutions that need only to augment the operator, not replace him or her, to meaningfully change the economics of the operation.

Building for an expert-robot generation

The current generation of technology innovation is starting, with a new generation of companies using robotics and autonomy to change the operating experience across industries.

  • Innovative companies such as Skyryse* with complex aircraft flight controls.
  • Built Robotics in the construction.
  • Path Robotics in manufacturing.
  • Caterpillar in mining.
  • Blue River in agriculture.
  • Saildrone in ocean exploration.
  • Simbe Robotics* in retail.
  • Intuitive Surgical in healthcare.

Robot solutions that share many key dimensions:

  • Introduce advanced levels of automation or autonomy that can pair with its human operator.
  • Deliver at least two of the three value dimensions: safer operation, improved cost of operation, high total utilization of assets.
  • Shift the operators’ time to higher-value tasks; eventually to manage across multiple functions in parallel.
  • Primarily software-defined across both control and perception systems.
  • Easily retrofit into customers’ assets base at price points less than 20% of the cost of the underlying asset.
  • Can go to market ‘as a service’ with recurring revenue and healthy margins.

Technology has empowered humankind to be capable of the impossible.

The impossible means we can make more complex decisions at orders of magnitude more precision and speed. Yet so many industries still rely on human labor and operations over human ingenuity and authority.

As the world adapts to social distancing and remote work, it’s more important than ever to leverage technology as our proverbial exoskeletons to maximize what humans are great at, and let technology do the rest.

*Venrock is an investor in Skyryse and Simbe Robotics

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