I recently sat down with Bob Rogers. Bob is Intel’s Chief Data Scientist for Analytics and AI. I sought out answers to the some of the most popular questions related to artificial and augmented intelligence. The entire interview was illuminating, and shed some light on aspects that many people wouldn’t know about.
So what is AI? Artificial intelligence is human-like intelligence that works in a similar way to our brains—though not quite, of course. It supports our capabilities, simplifies our life, and improves our ability to make use of information. AI can do what we can’t do in the sense that it can process a lot more data than we can at any given instance. Current AI technology is powerful enough to identify a kitten in a picture, or identify an object lying on the roadside, and then determine the chances of that object moving onto the road. In fact, autonomous vehicles are a great example of AI technologies in action.
In the future, AI will be able to identify the most important elements in huge data chunks, and then take advantageous actions. So here’s the question that most of us ask: How will AI show up in our lives? For the foreseeable future, AI is there augmenting our capabilities, allowing us to do more, with better accurately, in less time.
Let us see what Bob Rogers has to say about AI, augmented intelligence and their interesting applications.
There is a fine line between AI and augmented intelligence. Bob Rogers describes it as, “the difference is in how we apply the technology.” AI has progressed rapidly in the recent past; the era began with us describing the information and extracting meaning. But today, AI solutions are a lot more advanced, so advanced that they can play around with huge amounts of data in just a matter of seconds.
Analytical systems in the past were just basic questioning-answering systems. So for instance, if you wanted to know how many products had been sold in the past quarter, the technology would prepare a simple report. Later on, machine learning algorithms were used, and somewhat more advanced questions were answered, for instance grouping customers meaningfully based on their characteristics. This is referred to as clustering which led to supervised learning. Today, AI can perform much more complex tasks such as determining which customers are most likely to buy another product and when, based on previous buying habits.
AI can now understand elements of unstructured data, such as images, text and videos. It can now perform simple image recognition tasks faster, more accurately and more consistently than humans can. Going back to the kitten in the photo, AI becomes more interesting when we can start asking contextual questions. Are there other objects in the photo? What else is there in the background? A simple example of this kind of AI in action is automatically organizing similar-themed photos on your phone or via an app.
Most of us worry that AI will replace cognitive tasks. Think about it this way: AI can identify people breaking a specific traffic rule in tens of millions of locations simultaneously, and capture an instantaneous images to document their findings. Humans can’t work on this kind of scale, and frankly wouldn’t want to with only a single cognitive task. AI is not really replacing us, it is just augmenting our capabilities.
Technology promises to harness human-like intelligence to solve complex challenges and global issues. The “Intel Inside, Safer Children Outside” project, aimed at ending child sexual abuse, is one such example. A non-profit organization matches children in escort ads to children who have gone missing. The database of missing children includes 460,000 images which must be searched every time an escort ad containing a child’s image is identified by law enforcement. While humans have been working on this, AI can be used to achieve quicker results through a system.
