The machines are coming – 2049?

It is notoriously difficult to predict the future. I lived my life at IBM, following Alan Kays 1982 aphorism

The best way to predict the future is to invent it

In my career I got many things right, and many things wrong. While Amazon was still a small time bookseller, and Youtube for the most part didn’t exist, it was obvious both business models would thrive. While I couldn’t convince IBM to pursue either of these opportunities with ny success, we demonstrated the technology perfectly. My “Wired for Life
Presentation contains some of my wins, and many of my losses.

It was much easier to build on these, especially the societal impact in my 2003 “Trends and Directions” presentation.  Societal impact is much easier to predict as you can demographic data, current trends and it’s pretty easy to extrapolate. Technology adoption is much harder.

Many of these predictions are not useful, after all who needs  a robot to write high school essays? Many though will continue to fundementally change work and life as we know it.

What they are though is a signal in the way the World Economic Forum predicts the technology will develop, and to some degree it’s a self fulfilling prophecy. Watching this and reading many of the “machines are coming” articles that have been published over the past 5-years, it’s easy to become depressed about the rise of automation, AI, and robots. In a year when the sequel for Blade Runner will finally appear on our screens, there are some key things to remember.

  1. There is no magic, no silver bullet – If they can’t explain it, or worse don’t understand it, they have not invented it. Machine learning is great, but the machines can only learn with the machine learning constraints they have.
  2. Listen to the doubters – Doubt is very different to dismissal. People who dismiss possibility out-of-hand either don’t understand the opportunity and the potential, or are afraid of the change. It’s the doubters who have thought things through and understand the problems and the weaknesses.
  3. Don’t fear automation – If you do, you will be left behind. Learn, adapt, change; if possible work to invent the future By all means be a doubter, don’t be a dismisser.
  4. Find a problem, don’t start with a solution – AI, Robotics, Big Data, Machine Learning, Algorithms, Neural Networks are all speciality fields, grabbing onto them and asking how can we use them isn’t useful. The more specific you can be about a problem that needs solving, the easier it will be to identify the correct technology.
  5. Be Human – the more we automate, the more important human interaction becomes. The more empathy you have for someone who has a problem, the more likely you are to be able to understand how to solve it. Empathy, the arts, sports and human interaction are all fields where robotics and automation are least likely to take over.

More Human than Human – Dr Eldon Tyrell, The Tyrell Corporation

Author: Mark Cathcart

Formerly an Executive Director of Systems Engineering and a Senior Distinguished Engineer at Dell. Prior to that, an IBM Distinguished Engineer working for the Systems Group in NY and Austin. I’m currently “retired until further notice”.

Leave a Reply