Demystifying AI for Business

Original
Confusion about artificial intelligence (AI) in business can be cleared up by understanding there are two different types of AI discussed in the press, which have completely different meanings. Once you start to understand the limitations of AI at the moment, compared to what the potential of the technology is, then you can understand how it can be practically implemented in your business.

In every prediction about the future of work, artificial intelligence appears pretty close to the top of technology trends for businesses to prepare for. This makes sense. Google and other technology giants are developing algorithms which can learn from human inputs, meaning that they can accelerate their learning in a particular area at an incredibly rapid rate.

However, before diving into a new artificial intelligence strategy for business, it’s worth taking a look at what the capabilities of AI actually are right now, because the media presents a confusing picture. When the mainstream media refers to AI, they could be referring to (broadly) two things:

1. The AI ‘Personal Assistant’
  • This is a very basic ‘input’ and ‘output’ algorithm. For example, a bot that replies to emails and then puts dates in diaries. It has a very specific purpose and is completely limited in what it can do.

2. The Ex Machina, Skynet or Her AI which Elon Musk believes is an existential threat to humanity
  • This is an intelligence which has the depth and breadth of human understanding. This intelligence could potentially surpass what humans are capable of very quickly, with consequences which would be entirely out of our control.

The first type of AI is highly achievable, and probably shouldn’t be called AI at all – it’s just a good algorithm. More successful types of this AI are the ‘recommendation engines’ – characterised by you-watched-this-movie so you-may-like-this-TV-show. These are extremely helpful for customer engagement, and bringing people personalised recommendations to make them come back to your product.

There are other ways to develop this AI, but you first need to give this AI a very specific purpose. That is, you have to understand what you could possibly automate, what purpose the automation serves, and ensure that the AI has a specific and rich set of human inputs to train it. In order for it to improve the results it produces, it's learning algorithms need human interaction to absorb new potential outcomes and appear to become more intelligent.

Once you can identify where this area could be for your business – you could be onto a real winner and create competitive advantage.

The Limitations of Today’s AI

To give a personal experience, I often get asked about content automation for business – can algorithms accurately find information relevant for their business? In their head, our clients are just asking for a recommendation engine for intelligence.

However, there is a crucial difference here. The AI recommendation engines in Netflix, Tinder and Amazon have the purpose to keep people within that site – there are a finite number of links between films, people and shopping items. When I am asked for recommendation engines for all articles published on the internet we come to a problem of ‘too much information’ or ‘too much irrelevant information’. The people who are going between different articles on the internet have entirely different purposes - so what is relevant for them, may not be relevant for you.

So what can algorithms do? They can currently search for keywords,  phrases and passages within text. They can also predict what you may be interested in based on other peoples’ needs and searches. However, when it comes to understanding a specific purpose or problem that you may have, and then coming up with articles which will definitely be relevant for you, and your work, then AI is far off. Even though AI can determine the meaning behind the words, they are very poor at matching that meaning to the meaning to that derived from your question. Even more importantly, they don’t understand why you are searching for the information, and so can’t point you in the direction of the right articles.

This is why services like Curation Corporation exist and have viable business models. Humans are still the best at finding intelligence and applying it to consulting projects. The AI in this area is still like the jerky robots you find at Japanese conventions – and you wouldn’t trust something like that to look after your children or clean a house full of china. Why would you assume that algorithms are close to this point for business intelligence?

In fact, when AI is employed to have these kinds of complicated tasks – it is detrimental for your business. If you rely on what the masses are reading, and take that as your starting point for research, then the chances are you’ve missed the boat. You wanted to understand a concept and act on it before it started trending. We take a different approach - we understand that algorithms can be put to good use when they are within certain parameters. Which is why our software takes your trusted sources and searches them for key words - that way you are very likely to surface information which is useful.

In conclusion, the capabilities of future artificial intelligence are immense. But when it comes to your business today, it’s worth placing your intelligence strategy in concrete factors; you know that the human brain is still the most intelligent object in the known world, so make sure you rely on that for complicated decision making. The super intelligence Ex-Machina is still a mythical unknown.

Alice Thwaite is the Head of Commercial at Cronycle – a platform which helps you get intelligence from articles you read online every day. She can be contacted via alice[at]cronycle[dot]com. You can sign up for Cronycle for free at cronycle.com.

Would you like to be our next guest author? Find out how here!

This is a guest blog and may not represent the views of RE•WORK. As a result some opinions may even go against the views of RE•WORK but are posted in order to encourage debate and well-rounded knowledge sharing, and to allow alternate views to be presented to the RE•WORK community.

Learn more about the future of artificial intelligence for business at our upcoming events:
  • Deep Learning in Healthcare Summit, London, 7-8 April 2016
  • Connected Home Summit, Boston, 12-13 May 2016
  • Machine Intelligence Summit, Berlin, 29-30 June 2016
  • Deep Learning in Finance Summit, London, 23 Sept 2016
  • Virtual Assistant Summit, San Francisco, 26-27 Jan 2017
  • View all upcoming RE•WORK events here.

    Big Data Data Mining Guest Blogs AI AI Assistants Deep Learning Algorithms


    2 Comments

    • Thanks regarding providing these types of great content. 10 months ago

      Thanks regarding providing these types of great content.

    • Francis 10 months ago

      Thanks for the article

    As Featured In

    Original
    Original
    Original
    Original
    Original
    Original

    Partners & Attendees

    Intel.001
    Nvidia.001
    Graphcoreai.001
    Ibm watson health 3.001
    Facebook.001
    Acc1.001
    Rbc research.001
    Twentybn.001
    Forbes.001
    Maluuba 2017.001
    Mit tech review.001
    Kd nuggets.001