GUEST: Neil Sahota – IBM Master Inventor, United Nations (UN) Artificial Intelligence (AI) subject matter expert, and Professor at UC Irvine
AI is a hot topic these days.
Whether it’s in an incoherent tech-startup pitch or ominous warnings from scientists about a techno-dystopian future, everyone seems to be talking about it.
Yet, despite the publicity, many of us are confused about what it actually is — and what it means for the future of our businesses.
To clear up the confusion, I spoke with Neil Sahota – IBM Master Inventor, United Nations (UN) Artificial Intelligence (AI) subject matter expert, and Professor at UC Irvine, to learn more about how AI is being used.
He went over:
- What AI is
- What AI means for your business
- Whether we should be excited or worried about AI
- Why the human element will always be more important
What is AI and what does it mean for your business?
First, it would be helpful to clear up a bit of confusion surrounding the cluster of terms which get lumped together when most people talk about AI.
AI stands for Artificial Intelligence, which is actually somewhat of a moving target to define. Machine learning, on the other hand, is an aspect of AI but is often used interchangeably with AI. More on this in a moment.
AI consists of 3 main components:
- Neural networks (where machine learning comes into play)
- Natural language processing
- The ability to have a conversation with a person like it’s another person
So, in the first case, neural networks are how the machine learns. Rather than being programmed like other computer programs to rigidly follow rules, AI has the ability to wire its own pathways and try its own rules.
This is based on something called “ground truth,” which is a set of rules on how to make decisions. This way, you can feed the machine a bunch of data and it can sift through it and try its own rules or ways to deal with it — much like how we learn through observation.
Natural language processing
The second component is the ability to understand natural language. Where other computational processing relies on the extremely literal language of computer code, AI is more flexible.
“If I tell you, ‘Yo, I’m feeling really down because it’s raining cats and dogs,’ you know what I’m saying. If I tell that to a machine, it would think I’m sinking into the earth and small animals are falling from the sky. It doesn’t compute.”
If you’ve ever learned another language in a classroom and gone to use in the real world, you’ll know context is as important as the literal meaning of words. In fact, it’s probably more important.
Which is why AI prioritizes connotation over notation, unlike the overly-literal language processing of traditional machines.
The ability to converse with a person like it’s a person
Conversational skills are important in AI because, in order to interact naturally with AI, it’s easier if we don’t have to worry about direct commands.
Think of when your spouse or roommate dramatically hug themselves, pretend to shiver and say “It’s freezing in here.” Well, it might be annoyingly passive-aggressive, but you know it’s a command to action — not a simple statement of fact — even if you would like to pretend it doesn’t compute.
Basically, with AI, you can be as passive-aggressive as you want and not only will the machine not get annoyed, it will also actually understand you. Unlike your roommate who seems to think the house should have a “summer in Phoenix” feel year-round.
How can AI be used?
The difference between how we think and machines think actually can be harnessed for positive benefits.
One way Neil saw the power of AI was in an initiative called Project Lucy, which had the aim to develop infrastructure in impoverished areas in Africa. Massive amounts of data on agriculture, education and healthcare were fed into AI.
“The synergy between how people think and how machines think is unlocking whole new opportunities and avenues for us in terms of business, as well as social impact.”
The results ended up being shared with African governments, NGOs and some big tech companies. Neil was able to take these results and help efficiency and output across many industries in Africa.
For instance, analyzing soil content and weather patterns allowed Neil to make recommendations on planting crops, offering 20-30% higher yields for farmers.
And the same process can be used to similarly increase efficiency in your business.
Terminator or tool?
Of course, Neil is cognizant of the fact there is a lot of fear around the change AI will bring to the workforce.
And those of us around a certain age grew up with similar fears after watching Terminator 2 a few too many times. But rather than Skynet coming online and time-traveling robotic Austrian bodybuilders coming to kill John Conner, most of the change people fear now centers around job loss and transformed economies.
For his part, Neil is optimistic about AI as a tool — and not a Terminator. And, though he acknowledges massive change and disruption will come to the workforce through the increasingly rapid march of technology, he is certain the change will bring with it myriad new opportunities for those intrepid enough to capitalize.
“For the new jobs of future work — You don’t have to be the passenger for that. You don’t have to wait until someone figures something out. You can be part of that wave that actually defines what that future work will be.”
The human element
Of course, with all this change, the human element is becoming even more important as technology takes over so many more aspects of our lives.
But think about sales, for instance. With all the technology in the world at your disposal, with all the automation or the digital assistants, there still isn’t a silver bullet to do your job.
And this is a good thing because it means the core of sales is still the human element. It’s still a job about building trust, credibility and rapport with other human beings. And this skillset is one which is becoming increasingly valuable for those with the right mindset.
So figure out which skills and elements aren’t going to get automated out from your job and focus on leveling those up.
Don’t race to catch up; ride the wave!
This blogpost includes highlights of our podcast interview with Neil Sahota – IBM Master Inventor, United Nations (UN) Artificial Intelligence (AI) subject matter expert, and Professor at UC Irvine. For the entire interview, you can listen to The B2B Revenue Executive Experience.
If you don’t use Apple Podcasts, we suggest this link.