But, what it means is up for interpretation. For example, one of the top digital marketers remains largely unfazed. Below is a video I did with Ryan Deiss, who has a different perspective on AI than I do.
Check it out:
Ryan understands that marketing relies heavily on data-analytics and automation … but he believes that it is also reliant on the personal touch.
I agree that people are still a vital aspect of many businesses, and can't be fully replaced. However, I am dramatically more bullish on AI and its future and impact.
In many instances, today, what passes as AI is just an elegant use of brute force.
Nonetheless, AI is great at solving problems … and is becoming increasingly able to digest and perform complex tasks (including tasks formerly thought of as done exclusively by humans).
Ryan believes that the best AI makes a conversation more human (in regards to selling and retail) and allows humans to be more human. In other words, as technology frees people up – they are free to spend their time on more valuable tasks and processes.
This has happened many times in society. Fewer people work in farming or manufacturing … and yet there are more people doing more jobs.
So, obviously, in the same way that mechanization freed up workforces for better jobs, AI can do the same.
Realize, however, that human perception is linear … while technological growth is exponential. Consequently, we probably do not know what AI will give (or take from) humans.
Only time will tell.
Meanwhile, some of the biggest companies are making big bets on R&D.
According to the World Economic Forum, if the Japanese wanted to pay off their national debt, each individual would owe approximately $90,345. For comparison, US citizens would owe $61,539 a person.
It's also worth noting that lower debt levels don't translate to safety on a global scale. Yugoslavia had very low government debt until its breakup.
If you want to see an updated, interactive version of the U.S. Debt Clock, just click here. It is worth spending a little time to watch the pace the numbers turn.
Years ago, when my kids were still children, Macy Gray came out with a song called "I Try."
When I heard the kids singing, the chorus went:
I try to say goodbye and I choke, I try to walk away and I stumble, though I try to hide it, it's clear, I wear goggles when you are not near.
Of course, it's not "I wear goggles when you are not here", even if my youngest son swore it was … The actual line is "My world crumbles when you are not near" … which makes a lot more sense.
This has happened to me several times as well (recently, too – which prompted this post).
Turns out, we humans are pattern-matching machines. But not all of the patterns we perceive are really there.
Peter Kay plays on our disposition with this funny bit about misheard lyrics.
Alan is a wealth manager to the ultra-wealthy. His American Dreams show is very popular in Silicon Valley.
It's a show about finding your path in life, and making businesses thrive through adversity and challenging economic times.
We talked about my career path and how I went from a young lawyer to spending over 25 years running tech companies … and we talked about the lessons I learned along the way.
It is different than other interviews I've done. Take a look.
There's a lot of "hype" these days. Social media and tools like Kickstarter would have you believe that every new idea is the "next big new thing".
In contrast, Gartner's Hype Cycle Report is a considered analysis of market excitement, maturity, and the benefit of various technologies. It aggregates data and distills more than 2,000 technologies into a succinct, contextually understandable, snapshot of where various emerging technologies sit on the hype cycle.
Understanding this hype cycle framework enables you to ask important questions like "How will these technologies impact my business?" and "Which technologies can I trust to stay relevant in 5 years?"
What's a "Hype Cycle"?
As technology advances, it is human-nature to get excited about the possibilities we imagine … and then to get disappointed when those expectations aren't met.
At its core, the Hype Cycle tells us where in the product's timeline we are, and how long it will take the technology to hit maturity.
This year, according to Gartner, there are three overarching "mega-trends" to watch.
AI Everywhere shows the transition towards a ubiquitous AI experience, from self-driving cars, to machine learning, and to smart robots. Consider the impact on traffic/accidents with the adoption of autonomous vehicles, or the ability of machine learning to process more data faster.
Transparently Immersive Experiences shows our transition towards human-centric contextual and fluid technological experiences. – like Connected Homes or Virtual Reality. Consider the impact of Augmented Reality on advertisements or gamification.
Digital Platforms shows the transition of emergent platforms into adoption. Platforms like Blockchain, IoT, and Quantum Computing. Consider the effects of bitcoin and other blockchain initiatives, as well as the opportunity for new business models centered around these platforms.
Here is the chart. You can click the image to see it larger.
The hype cycle gives us an idea of which of these technologies will likely survive the market hype and have a potential to become a part of our daily life.
Peak of Inflated Expectations (Success stories through early publicity),
Trough of Disillusionment (waning interest),
Slope of Enlightenment (2nd & 3rd generation products appear), and
Plateau of Productivity (Mainstream adoption starts).
Which technologies do you think are over-hyped … and which ones might survive the hype?
I find this stuff fascinating. Consider some of the interesting technologies just starting their hype cycle:
Human Augmentation has the potential to enhance our bodies and minds using electrical currents, chips, or exoskeletons, but also raises ethical and legal questions.
Smart Dust opens up the possibility of monitoring essentially everything by creating a vast network of minuscule sensors that can detect various inputs.
