While it’s a known fact that Animals can see danger better than humans. Elephants and fishes particularly, can sense a tsunami hours before it hits. Can this insight be used to better predict tsunamis and setup alert systems that save lives? According to an observation yes it is One hundred percent possible.
But there's a big catch here. Apart from tsunami while animals can move to higher grounds or safety caves based on local weather triggers or as a part of their annual migration, the elimination of the wrong cause is a bit difficult in human scenarios. This is where the power of AI truly shines over other elements.
It has the ability of looking at massively large data sets and provides humans with futuristic insights that we would probably know but not necessarily see immediately, says Bob Lord who was at the recently concluded IBM Dev Day.
He's the Chief Digital Officer and Senior Vice President Of Cognitive Applications at IBM. A man with a very long job title he is tasked with discretely embedding AI into the biggest companies in the world and is making a fabulous job of it.
Bob Lord is also involved with the development of Watson, IBM's supercomputer which combines sophisticated machine learning and natural language processing as a question and answering machine. In fact it was IBM Watson which gave the world its first true glimpse into voice-based computing long before even Amazon's Alexa was born.
Is it Artificial Intelligence or Augmented Intelligence then?
While Stephen Hawking and Elon Musk have warned us about the dangers of AI to humanity. IBM doesn't believe in that worst case scenario. "Whether it's neural machine learning tool or Watson, it's what the tools are doing the work that matters," adds Bob Lord.
They help evaluate a lot of data and bring better insights to a human being to make better decisions. Therefore, the word augmented intelligence, which literally means to augment a human being's intelligence contextually.
So how does IBM Watson help humans make more intelligent decisions? Bob Lord explains this with an example/anecdote.
In the medical field IBM Watson is looking at millions of patient records, and presenting those complex records in an easily understandable form to a doctor. This helps the doctor make a better decision under pressure," says Bob Lord.
It's all about getting better insights or a clear signal in all that data noise. And the machine learning algorithms that are underneath over time learn what is most effective and they learn what is the most impactful. And that's a revolutionary change to how human beings will make better decisions in the future.
In the medical field, Watson is looking at millions of patient records, and presenting those records in a digestible form to a doctor. This helps the doctor make a better decision under pressure says Bob Lord. It's all about getting insight or a clear signal in all that data noise and machine learning algorithms that are underneath over time learn what is most effective, and they learn what is the most impactful.
In Small instances the transformation is already underway in call centers right now. Bob Lord explains how when you call for customer support, Watson is listening to what your request is, deciphering what the request is, and then deciding whether to answer the call and provide insight or route the call to the appropriate representative, so you get better customer service. This is only the beginning of what IBM Watson can do.
Unleashing the power of Watson
IBM Watson's is looking at videos, imagery, PDFs, which are really not indexed by text and digesting all that information heuristically continues Bob Lord. Voice recognition has come up a very long way. And with Project Debater, IBM Watson knows the nuance of debating one side of an argument, not against it. That's how advanced IBM Watson has become, because you can actually give it a lane to operate in.
The speed of processing and getting insights is greater than ever before. But an AI system today takes a lot of training, Bob Lord says Even if it's trained on a particular application, we can't actually take that training and apply it to another application. We can assist companies on this aspect at large though.
When people think about Artificial Intelligence there's a lot of fear mongering going on around artificial intelligence. While the human brain is fascinating and the neural networks that exist in the human brain cannot be duplicated, there can be reskilling initiatives designed.
AI and the future of tech jobs?
One of the biggest hurdles in AI-related jobs is finding people with the right skills.
Just like Intel in 2017, IBM has launched a niche STEM program for girls in India, which will impact more than 200,000 girls here in India. This also extends to re-skilling existing workforce where we are working in hands with IBM, so they can get into jobs of the future also called as New Collar Jobs.
What we have seen as long as these programs are fun and interactive, people want to learn and move their career and we have seen cafe baristas become apprentices at IBM and have started working on quantum computing even with no formal degrees.
While we think that there is a place for degrees, Bob Lord says, which in essence, helps you to think about a problem the more experience you get through a degree program and the better off that you are in the world.
But if you want to get a job, that doesn't necessarily mean that you have to have a degree and that you can learn a particular craft through a set of training programs and get a job.
It may not make you the best thinker in the world, and you may not be the best problem solver in the world. But if you need a job, you can get trained and you can get a job without having a degree. And I think it's both, not either or where can assist candidates at large.
What's a genuine nightmare scenario about AI right now?
I think the biggest challenge we have is to ensure that the data that we're training the models on doesn't become biased Bob Lord says. "Because a lot of the training data that we have particularly may be biased already before we're actually training the model itself."
Sure, companies will take care to work around AI bias and account for it, but awareness about this initiative needs to be higher. If you don't go in knowing that there could be biases in your data that you start with that the model actually could be, you know, wrong and we can provide turnaround assistance to corporates on this extensively.
Know more about our New Collared Job Reskilling programmes today!