Phasing Out the ‘Human’: Can Technology Cure Modern Loneliness

Think about some of the relationships in your life: your mom, your dad, your pet, your partner…Whether its a tinder fling or someone you are deeply in love with and want to share your life, relationships meet a psychological need for everyone.

Of course, humans have certain physiological needs too, like food, water and shelter as well as the existentials in life that keep us fulfilled and engaged. Without the former, our bodies would die, and without the latter, our souls would become stunted, failing to grow, ultimately killing us… inside. At the end of the day, removing relationships, means removing sanity. It means getting rid of love. It means no more sex—which we know is a pretty important factor in the continuance of humanity.

I like you…

We know that relationships are essential to our survival, but what have we done to keep these relationships alive? What have we done to make sure humans have healthier, richer relationships so humanity isn’t at risk of extinction?

We did what humans do best. We moved forward. We advanced. Every 100 years, our technology increases by 1000 percent, leading to improved communication with those we have relationships with and a higher chance of connection with those we’ve never met. Think about the life changing breakthroughs in communication technology.

Let’s start with fire.

Fire may not be the first thing you think of when talking about technology or communication, but imagine yourself as a primitive human in the untouched wilderness for a moment. It’s dark. You’re in survival mode. Your belly is empty and all of a sudden, a fellow Neanderthal conjures up this warm, glowing, beautiful source of light and shares it with the rest of your tribe.

You’re witnessing a social innovation bringing people together for entertainment, comfort and survival. It’s a source for resting, cooking, dancing, laughing and story-telling—all of which help to improve relationships.

In the glow of the fire, Neanderthals go from acquaintance to friend. As such, fire can easily be argued as the first technological innovation that fosters a better relationship.

Since the first fire, we’ve come up with ways to bring people closer at a more rapid pace. From the printing press, the telegram, the telephone, cars, planes, the World Wide Web, and most recently, the influx of social media platforms. Facebook has roughly two billion monthly active users all sitting around their modern camp fires” telling stories, sharing moments, maintaining and growing relationships. We’re all still cave women and men trying to survive and entertain, we now just congregate around a slightly more complex source of warmth.

Do you like me?

In addition to relationship maintenance, we’re also seeing humans use tech to create relationships with non-humans. Sure, people need interaction, but not necessarily human interaction. This isn’t a brand new concept, this is happening. This is the fictitious character you fall in love with or vomit hate for in a television series or movie or even a podcast. This is the video game character you attach yourself to, making intricate relationships that were all designed by other humans. We’re inserting ourselves into these lives made possible because of technology.

Even when you are having an interaction with another human, is tech obfuscating the relationship? When you text someone you’re not really having a human interaction. At least not in the traditional sense because for better or worse, talking to someone without hearing their voice or reading the signals on their face or even seeing the imperfections in their handwriting has become the new norm.

And if these non-human, tech induced interactions have already become the new normal, then maybe technology can be used to create genuine relationships for humans. That is, a relationship that comforts and inspires and grows alongside its partner.

Consider the strides in artificial intelligence. It might be some time before we get to the days of machines being indistinguishable from humans, but that doesn't mean we can’t create a relationship through tech.

I don’t mean one of those life-like” dolls that inevitably emits an eerie emotional response from unfamiliar onlookers. Because when a robot is realistic, but still distinguishable that it’s artificial, our empathy for it drops dramatically into the distinctive dip called the Uncanny Valley.

Of course, science fiction movies like Her and 2001: A Space Odyssey have explored the relationship between humans and technology, and the possible, negative, dystopian outcomes, but Skynet isn’t taking over and John Connor isn’t the last hope of the human race. Technology is still about progress. It’s about improving the world we live in.

The idea of falling in love with something that was created by another person, something that’s not a physiological creation, not human birthed, will certainly seem offensive to most, but if you couldn’t tell the difference, would it matter? If this relationship could provide empathetic companionship for the aging widow who lost her partner, or save the sanity of the astronaut drifting alone in outer space, we’ve ultimately used technology to cure loneliness.

SEE ALSO: What YML is doing to help reshape early education learning in a screen-obsessed world>

AI for Marketers 101: What You Need to Know to Get Ahead

It's true that companies like Spotify, Amazon, and Netflix have set an incredible bar for customer experiences with AI. But unlike the past, when lofty advertising goals, could only be achieved by mammoth companies with deep pockets, today, marketing departments of all sizes can rely on the input and efficiency of machine-driven AI applications.

Thanks to the increasing availability of AI to smaller businesses, marketers everywhere can now engage with each customer in meaningful and personalized ways.

This doesn’t mean humans rely on AI to do all the work. Instead, the performance of AI-based algorithms does best when reviewed, sanitized, and operated by real people.

With AI-based programming, new marketing platforms are appearing almost daily. Most of them can be classified into the following categories: vision, language, insight extraction, and anticipatory predictions.

Vision-driven AI applications

AI technology can do a lot for physical stores, especially with analysis and analytics. For instance, machine-learning algorithms can identify behavioral patterns of repeat customers. They can use facial recognition technology based on CCTV footage inside stores and see patterns of efficiency in various product layouts. These can then be leveraged to optimize store design and operations.

But visual-driven AI isn’t confined to in-store experiences. Vision-based AI can also be used to recognize license plates for passing cars. Since every license plate is registered to an individual, retailers can partner with third-party data collectors to get more information on the owner of a vehicle. For brick-and-mortar establishments, this allows them greater insight into potential customers who drive past their place of business on a daily basis. These companies can then target marketing communications specifically to that vehicle owner, with a message designed to draw them in the next time they're driving by. However, retailers must be aware and compliant with customer privacy when applying both in and out of store AI technologies.

Language-driven AI technology

When it comes to the speech-enabled side of AI technology, Alexa, Siri, and Watson from Amazon, Apple, and IBM, respectively, are undoubtedly the leaders. They demonstrate the maturation of language understanding and processing for other elements of consumer interaction  In the past, communicating with customers was restricted to email or other far less personal experiences. Thanks to the new frontier of language technology, customers can now literally speak to their device and end up interacting with a business or brand. AI speech technology is bringing a new level of personalization to customer service and outreach. 

For more direct and natural conversations with customers, chatbots and conversational UIs are providing a great deal of opportunities. Successful adoption of language-driven AI technology can be used to support and even partially replace call-centers for the customer service needs of companies across industry verticals.

Even more, AI can now automatically detect sentiments, meaning certain degrees of frustration apparent in a customer’s voice is recognized by the technology. This is extremely helpful for companies, because the technology understands when it's appropriate to  transfer the customer from automated voice systems to human representatives.

Another application of language-driven AI already being leveraged is the generation of marketing messages using machine learning software. Communication templates based on general vocabularies are integrated with customer preferences. These and observed behaviors enable systems to interact with customers through the right channels, at the right times, in the right tone, and with the most relevant content.

For example, ZenDesk implemented a machine learning strategy to bring down the costs of their PPC campaign. Utilizing an advanced social media engagement software, they were able to compile a list of contacts based on their behavioral patterns. Then, they segmented them into personas in order to best target those ready to purchase their product. ZenDesk claims that this earned them 4 times greater lead generation volume and reduced their cost-per-lead.

Insight Extraction

AI developments have made the analysis and mining of big data possible in order to extract actionable insights. The three common uses for this type of AI are programmatic advertising, lookalike audience modeling, and algorithmic real-time personalization.

Programmatic advertising allows marketers to optimize decision-making strategies. When it comes to the purchase of advertising space in relation to audiences, demographics, and keywords to target, there are various strategic ways AI technology can be used. This is considered a must-have for businesses wishing to optimize their online media spend and campaign performance.

Lookalike modelling is often part of data management platform toolkits. It allows businesses to collate first, second, and third-party data to determine and manage their target segments and consolidate user profile information.

Algorithmic real-time personalization today is usually driven by manually-created rules that look for particular contextual data points. Details like user location, customer status, or estimated household income are all available as areas of focus. The AI program then delivers content based on an assessment of relevance to the campaign’s goals. This can include personalizing websites for a user’s browsing session and dynamic offers of discounts based on established probability models.

Decision-making AI applications

Product recommendations in the e-commerce space have been around for some time. However, AI-powered engines are able to avoid cold-start problems by considering a broader set of data. They analyze customer purchase data along with third party information on relevant associated topics. 

For instance, Infinite Analytics is one such platform that identifies and finds products straight from pictures. With their Infinite Search feature, once a customer snaps an image from their mobile device or shares a picture from a social media feed, the software is able to provide recommendations of similar offerings from your own brand's catalog of products. Additionally, they can personalize online shopping websites, and communicate search results through Amazon Echo.

Predictive analytics and anticipatory design essentially provides predictions about the future. It thereby expands the traditional digital analytics approach from reporting on historical data to predicting and alerting marketers of likely business-critical moments. Predictions are based on mountains of data points spanning from general market trends to personal data.

AI technology is no longer an abstract toolkit for global tech companies. Today, the tools previously only available to enterprise-level companies have become affordable and accessible to medium and small businesses too. If you’re a marketing leader and not already leveraging AI technology for your day-to-day operations, you should start identifying and prioritizing areas within the company that these programs can be implemented.

What YML is Doing to Help Reshape Early Education Learning in a Screen Obsessed Society

At some point in our lives, each one of us has experienced a feeling of complete awe while watching a small child expertly swipe to unlock a smart device or open mobile apps to enter their own digital universe.

Over here in the YML labs, we have long been curious of the role that emerging technologies play in learning and development for young brains.

Our curiosity started a few years back when we teamed up with education startup Montessorium to develop a full app suite aimed at empowering kids to learn at their own pace. That project turned out to be especially rewarding because we provided kids a fun way to learn everything from the alphabet to international geography. We also got some digital recognition from Steve Jobs once the app launched.

Since then, our curiosity in learning and development in early education has only grown, especially as AI development continues to advance in great strides. We decided to further explore how we could bring the power of artificial intelligence tools to education.

What research is saying:

Research shows that during the preschool years, expansive psychological growth takes place and the brain is particularly sensitive. We know that screen times can greatly affect the forming of neural pathways and the way brains develop.

But because technology changes in our society are nascent, the effects of those changes are still relatively unknown and often debated. Decades ago, researchers learned that young brains need tons of stimulation to develop normally.

As a result, parents were encouraged to expose their children to as many sensory stimulations as possible. Later, digital designs and technology became more integrated into our everyday lives. We started seeing studies suggest that children who had too much screen time were more likely to develop ADHD.

For instance, in one particular study, young mice were exposed to six hours of a light and sound show on a daily basis. Results showed that there were "dramatic changes everywhere in the brain,” Jan-Marino Ramirez, director of the Center for Integrative Brain Research at Seattle Children's Hospital, told NPR.

Results like this lead some researchers to believe that our brains being wired up all the time can’t be a good thing. We weren’t built for this kind of over-stimulation. On the other hand, some researchers believe that our brains have to evolve in the way it processes information because our world is increasingly becoming more fast-paced.

In the mice study mentioned, mice that were exposed to stimulation were able to stay calm in environments that typically stressed out those who didn’t experience as much excitement.

Leah Krubitzer, a neurobiologist at the University of California, Davis, thinks studies like this show that benefits of an overstimulated brain may outweigh its negatives. During last year’s Society for Neuroscience meeting in San Diego, Krubitzer explained that we already live in a world where overstimulation is the reality. This means our brains have, whether we like it or not, already changed. Using technology correctly, in a useful, healthy way, is just the kind of stimulation that will prepare children for an always on, fast-moving world.

Because what other option do we have? We can’t turn back the clock. We can’t teach our kids in the archaic ways our grandparents were taught. Those good ol’ days don’t exist anymore.

"Less than 300 years ago we had an industrial revolution and today we're using mobile phones and we interact on a regular basis with machines," Krubitzer said during the meeting. "So the brain must have changed."

The truth of the matter is, data on how screen time affects the brain isn’t large enough to draw sweeping conclusions. Just consider how last October, the American Academy of Pediatrics lifted its longstanding rule against any screen time for kids under two. This is a standard that had been put in place since 1999.

The current recommendation comes from the result of new research. It states that young children should get screen time to help them develop the abilities to transfer knowledge from screens to the real world.

Daniel Simmonds, a resident pediatrician at the University of Maryland in Baltimore who has a PhD in neuroscience, says the key is to stick to the middle ground somewhere between the past and the future. So let your little ones interact with technology, but don’t let AI replace social human interactions.

“So much of our brain is dedicated to sensing things and making movements around [those physical things],” said Simmonds, pointing out that the show “Sesame Street helps kids learn but it’s not going to help them learn if you just sit them in front of a TV without any human interactions.”

Further proving Simmonds’ point, a 2015 study found that when iPads were given to kindergarten students to share, those students outperformed students who had their own iPads.

The study’s researchers suspected that those results have to do with the fact that sharing an iPad boosted social interactions. This type of camaraderie is crucial for development in young children. Perhaps even more telling, students who weren’t provided iPads at all scored much lower on their end-of-year achievement test compared to students who had access to an iPad.

Breaking through archaic ways of learning

Armed with knowledge that back and forth interactions between children and a caregiver is critical to language and brain development, we built an educational app that uses machine learning and image recognition to help create engaging, interactive moments. In this particular project, when our custom built iOS app asks,"Can you show me the flag of Canada?" image recognition is then used to identify whether the child is holding up the correct index-sized flag or not. This recognition happens in real-time and is instantaneous.

Teaching children about the flags of the various countries in the world requires a bit of focus on machine learning. Achieving our goal of image classification and detection to work offline in real-time required several important decisions, like whether we wanted to go with an image classification or object detection approach. In the end, we decided object detection would allow our users the flexibility of showing multiple types of flags at once.

Other important decisions we had to make include selecting the right framework for mobile devices, the network for object detection, and feeding the right data into the network during training. All of these decisions are crucial to performance and accuracy of the end product.

Ultimately, we are excited about the beginning of our exploration and the possibilities ahead!

As humans, our history stretches back hundreds of millions of years and like all biological traits, our brains have changed just like the world around us. We can’t expect to get by on outdated ways of learning. However, the key here is to not use AI tools in a way that is meant to replace humans. The true power and purpose of technology is not to substitute for human interactions but to enhance that experience and bring to life what hasn't been imagined yet. Much like Simmonds said, the key is to take advantage of what AI development can offer, and that’s a lot when it comes to sharpening young minds through learning, interacting, and communicating.

“The integration of technology and physical learning is not new, and there’s a lot of potential for it,” said Simmonds.

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