We were perfectly happy without it. Then, somewhere this decennium, Artificial Intelligence (AI) turned into the new fashion for companies. If we believe the trend, your business is lost without. But if you ask what AI it is all about, a clear definition is hard to get. Also on how it can drive your business value, an answer might not come easy. Still, at the same time, you know from past experiences, as does research show, that your business benefits from a high-level understanding of emerging technologies. Time to make AI work for you!
What is Artificial Intelligence?
AI as a driver for business value is growing rapidly and so is the number of universities where AI is being educated. AI is considered the magic of the future. However, till today, there is no consensus on the definition. One of the ways to describe the phenomenon is as a set of algorithms and techniques that enables computers to mimic human intelligence and human behaviour. This description goes hand in hand with what some call the seminal moment of AI: the Dartmouth Summer Research Project on Artificial Intelligence of 1956. A workshop organized by John Mc Carthy, at that time Assistant Professor Mathematics, to clarify and develop ideas about thinking machines.
The project group was set out to create an artificially intelligent being and programming computers to behave like humans. In order to achieve that goal, these computers needed to have some kind of representation of the world as we know it. They needed to be able to do some kind of reasoning and problem solving, to navigate our world and plan accordingly, to process natural language and last but not least to perceive the outside world and react to it, preferably in real-time. Basically, that’s what AI research has been about for half a century.
The hocus pocus of Machine Learning
For the last decade or so, the focus within AI has been on a subset called Machine Learning. The word says it all: the machine learns by itself. It is both adaptive, able to improve by experience, and autonomous, in that it doesn’t need continuous guidance by an external person. So what is Machine Learning all about? It is all about one thing: PATTERNS. It can perform statistical analysis of data to find patterns (‘algorithms’) that computers could not see before. Patterns that humans don’t understand either. How does this happen? In two phases:
- Training data are being fed into the system and a model is created automatically.
- Next the model is used to make predictions about the actual ‘production data’.
Needless to say that the more data are being used to train the system, the more accurate the algorithm will be.
And so, if years of research and experimentation have gone into this and algorithms of various types have been created, what can we actually use them for? How can we make use of AI in a controlled way? In a way that helps us to navigate business successful into the future instead of hocus pocus, keeping our fingers crossed and eyes closed when hoping for the best. There is little hocus pocus to AI. It all comes to POCUS; to five application areas. Five areas that provide great opportunities for companies to make a big leap forwards.
POCUS: five application areas of AI
Prediction
This truly is AI’s most powerful feature and represents great opportunities for companies. Using Machine Learning, you can make very diverse predictions: how your customers will behave, what their future needs will be, how machines will behave and whether or not they will need maintenance, how your state of health is evolving, how particular cells within your body might lead to cancer, and so on and so forth. And the truly remarkable thing here is that AI is very strong at weak features: combinations of certain elements that we as humans do not regard as relevant for a particular outcome may indeed prove to be so. For example the Chinese micro-finance company Smart Finance uses phone data of the borrower to predict whether a small loan will be paid back; apparently, non-obvious data points such as the speed with which the date of birth was typed in, the battery power left on the phone, the day of the week or even the speed of swiping the screen, together with thousands of other parameters, proved apparently correlated to the creditworthiness of the applicant!
Object Recognition
Algorithms have become so advanced that they can now recognize still or moving objects with greater accuracy than humans. This typically proves useful for example in visual search (such as performed by Pinterest), in categorizing pictures (like most of our smartphones do), but also in precision agriculture where fertilizing crops is no longer a mass action, but is performed for the individual crop based on the recognition of its development state.
Content Creation
Algorithms will be used to create content automatically. This is already being done in sports, where AI can write “basic coverage” articles. During the last summer Olympics, two bots by the Washington Post and Toutiaou wrote tweets or even short articles based on the result and video footage of games. With regards to business, Gartner already predicts that by 2020, 20% of all content will be generated by algorithms.
But it’s not just words that algorithms can create. You can now have AI create photo-realistic pictures from text, compose music, make paintings (The Next Rembrandt) or even create extremely natural-looking pictures of non-existent people (thispersondoesnotexist.com).
Understanding People
This is of course the area of chat bots and voice assistants where automatic speech recognition and speech synthesis play a major role and the algorithms have greatly improved over the past decade. The quality metric for automatic speech recognition is “word error rate”, so how many words do you get wrong. The human word error rate is around 5-6%, algorithms are now at 4% and falling.
Next to having voice assistants and home devices like Amazon Echo and Google Home, algorithms in this application area are also being developed to help you with writing texts, automatic replies to emails and real-time translation.
Self-moving vehicles
And of course, this last area is the one that probably appeals to the human imagination the most. Self-driving cars, self-flying drones, self-walking robots, no one knows exactly when they will become widespread but that they will is definitely a certainty.
How to POCUS your business into the future?
Although there are already numerous algorithms available with the big tech companies and in open-source frameworks, the challenge for anyone leading a business is how to make optimal use of AI. Actually, and that might be disappointing after finally having an understanding of something which you might have considered hocus pocus before, making AI work for you does not come easy. Sorry about that!
From experience I expect that to make AI work, you probably need to get new capabilities on board – or hire experts – and you need to get everybody trained at least on the most basic principles of AI. Get the right tools in place, decide on ‘Buy over Build’ yourself and make sure you ask your software provider in what way their applications make optimal use of Machine Learning techniques. And besides all that, you need to find some projects to start experimenting. How? Look at the challenges you already have now. Pick some projects where you think the corresponding business outcomes would benefit most from AI. Collect all the data that are needed – they will most definitely need some cleansing as well – and just start. And of course, since they’re experiments, the outcomes will most probably not be successful every time, so perseverance is required!
Once you are on the go and you see your business grow, your hard work will be rewarded. AI will make it work for you!
Interested to learn more? You might find a more extensive talk on this subject very useful, just drop me an email for more information on my full keynote speech!