2018 is here! It’s time to take stock of what’s new and what’s next. Here are 5 book recommendations which will answers those questions and inspire you to learn something new. Enjoy!
While machine and deep learning are advancing the state of artificial intelligence, there’s still a long way to go before machines can replace us; if ever. Still, we have to recognize that today we are surrounded by computing power: devices, virtual assistants and robots; it’s everywhere.
Right now machines are really good at replicating and doing a better job than humans at repetitive tasks that require a lot of processing power and pattern recognition. But AI has trouble replicating those things that humans are really good at: understanding, motivating, and interacting with human beings.
Which is why you shouldn’t be worried machines will take your job: Machines will not replace us until they become emotionally intelligent.
This is important because as artificial intelligence continues its journey into the mainstream in 2018, and emotion AI becomes more present in discussions about AI; it’s worth asking: why does AI need emotional intelligence?
AI needs emotional intelligence to facilitate machine-human interaction
Before we can share our lives with machines, we must teach them to understand and mimic human emotion. Today machines can recognize faces, and they can also read our emotions:
With that said, beyond the “cool” factor, why does AI need emotion?
Here are three reasons why:
- To assist us. For now, bots are mindless minions that do our bidding. Google Home is a sidekick that tells us NFL scores. But when we want to send a bot on an errand to pick up the kids in an autonomous car? When the bot will fill in for us in an interview? When we want a bot that cares for an elderly person? The AI of the not-so-distant future had better be ready to tackle more complex challenges than simply looking up the weather.
- To understand us. If we are going to empower machines, algorithms, and software to do more of the work that humans used to perform, we have to imbue them with some of the empathy and limitations that people have; aka emotional intelligence.
- To make us better human beings. Just because technology can do something doesn’t mean it should. But we believe emotionally intelligent technology can makes us better human beings.
The future is already here. For a look into how this looks like, checkout our last post where we outlined 10 useful things emotion AI can do.
Originally posted in Vibetek blog.
This was the year most every large company took notice of the rise of artificial intelligence. But while it encapsulates many categories – machine learning, deep learning, computer vision, natural language processing, speech recognition and others – there is still one category that hasn’t been recognized, beyond academia, and that’s emotion recognition; or affective computing.
If you have not been keeping up, emerging technologies will drive the Next Economy. Which means that in the future, you’re either a digital business or a dead business.
With that said, business leaders need to keep up with the pace of technology because exponential technologies require exponential leadership.
How? Beyond blogs and podcasts to cover your heart’s desire on all tech related news and topics; there are also newsletters.
In the future you’re either a digital business or a dead business; and it’s up to you to decide whether that happens or not. This was Lewis Farran’s message from a recent presentation he gave at a conference in Tijuana focused on Gartner’s top 10 strategic technology trends list, which include: AI foundations, intelligent apps, intelligent things, digital twins, cloud to the edge, conversational platform, immersive experience, blockchain, event-driven and continuous adaptive risk and trust.
Computers are increasingly able to figure out what we’re feeling. A recent report predicts that the global affective computing market will grow from $12.2 billion in 2016 to $53.98 billion by 2021. The report by research and consultancy firm MarketsandMarkets observed that enabling technologies have already been adopted in a wide range of industries and noted a rising demand for facial feature extraction software.
Affective computing is also referred to as emotion AI or artificial emotional intelligence.
On this episode of the Big Bang Podcast I’m joined by Sergio Langarica, President of Netek – a neuro applications technology company, to talk about the future of emotionally intelligent technology.
Sergio has 20 years of experience in Information Technology ranging from Start-Ups to Global Players. He is an avid promoter of these industries in Mexico and abroad in various Board of Directors roles at the Mexican Chamber for the Electronics, IT and Telecommunications Sectors.
Netek, based in Tijuana Mexico, has recently finished developing it’s technology after two years of R&D. Their first product, still in beta, is a an affective computing platform called Vibetek.
Below are some questions and our chat:
- Talk to me about Netek
- What is affective computing?
- Why does emotion recognition matter? How do businesses benefit?
- In what types of applications does emotion recognition have a big impact?
- What applications have caught your attention recently that use emotion recognition?
- Which industries have adopted affective computing faster and why?
- How do we combat people’s fear that emotion AI will replace them? And on the flip side, how do we combat consumers fear that this technology is to invasive to their privacy?
- How far are we from mass adoption from companies? What has to be true for the adoption to happen?
- What is your advice to B2C companies that want to embed emotion AI into their business? How do they get started? What strategies will lead to success?
- How can communities connect with NETEK?
We invite you to experiment using our API or download our app.
The Big Bang is a weekly podcast. Tune in every Tuesday for more discussions on what’s possible.
Intro audio is by Arturo Arriaga, outro audio is Candyland by Guy J.
No matter how many articles are published on a day to day basis, we’re nowhere close to full out automation of jobs because there are many things that have to happen; it’s going to take a while. It’s not because the technology isn’t progressing fast enough; it’s because the number one obstacle is resistance from humans.