The Difference between AI, Machine Learning & Deep Learning – does it really matter? 

  • Published: 28 November 2022,
  • Say Technology Team

There’s a great deal of time, energy, creativity and money spent by companies on convincing us that they’re using Artificial Intelligence (AI) or Machine Learning (ML) to make their products and services seem more cutting edge or alluring.  Algorithms are spotlighted and neural networks promoted, but do we really care and should we? 

Businesses and consumers relate to technological advances in similar ways – how can this tech make my life better? What problem can I solve and how will I use it tomorrow?  Those companies that are putting their AI and ML capabilities at the heart of their marketing and communication efforts are in danger of repeating the communication errors of previous technology waves – no one cared that Betamax was technologically superior to VHS. They liked the content available on VHS, it made their life better and Betamax was forgotten. 

Benefits not Features

Your personalised viewing suggestions on Netflix, the Daily Mixes on Spotify and the autofill on Google queries are all examples of different kinds of AI and ML.  Consumers view these as really helpful and demonstrate ways in which the technology, (and they don’t care or want to know which technology is involved) is improving their lives. 

By putting the benefits of technology, rather than the technology itself, at the centre of the marketing and communications effort you are far more likely to engage and retain consumer and business interest. 

So, who is doing this well and who is missing the mark?  Organisations like Netflix and Spotify have been excellent at putting the consumer benefits derived from AI and Machine Learning front and centre rather than mentioning the technology at all.  It’s always positioned as helping you, the consumer, get the best out of the content they have available. It is this sense of personalisation that is being presented to the consumer, with no mention of AI. 

Smart is Better and Best

Alexa, when it was first introduced, was positioned as an AI-enabled assistant.  This led to a number of concerns being raised by consumers – “is Alexa always listening to me?” was a common question, and there were a flurry of examples of Alexa buying things on misheard statements in the early days.  To counter this concern, Amazon started to position Alexa as a “smart speaker” rather than an “intelligent assistant” moving further away from the technology and closer to the benefits. 

This is the sensible approach for companies to take.  People don’t want to think that they have artificially intelligent machines in their home monitoring and reporting on them, but a smart speaker helping them is much more acceptable as they can see the value it brings to them. 

Leave the computer scientists, software developers and data scientists to get excited about the possibilities of neural networks and deep learning, being inspired by the potential of massive data and pattern recognition. Most consumers are much more pragmatic in their outlook. For example, seeking out a mapping app that is better at suggesting routes or a shopping service that can predict when they are likely to run out of peanut butter.   

While it is interesting to know how the technology works and what is behind the various developments it is more interesting for consumers to understand the ways it is going to make their lives better or how it is going to position them for success in the future. 

How to Rectify the Problem?

The challenge for many tech companies when communicating to potential customers and the wider market is that they stay talking about the technology, as that is what they understand, are comfortable with and in many cases have spent so much time developing.  Finding the right narrative to highlight the benefits of the technology can often seem to be a harder challenge than understanding the tech itself. 

The best organisations work with partners who understand how to capture the difference that the technology can bring. At SAY we work with a simple mantra to help understand technology “What can I do today that I couldn’t do yesterday and what will I be able to do tomorrow that I can’t do today?”   

For help communicating what you can do today and tomorrow, get in touch…. 

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