The Pitfalls and Possibilities of Machine Learning for Newbies

Machine learning gives computers the possibility of learning – without being explicitly programmed. David Spangenthal, Strategic Growth Manager, Google Cloud Platform at Google, and Alyx Baldwin, Co-Founder and CTO at Kip, are both working to push the boundaries of what A.I. and machine learning can accomplish and help humanity with in the future. At the 2017 Propelify Innovation Festival Alyx and David offered their top tips to companies about potential pitfalls to avoid and possibilities to seize for machine learning in the future.

Think About the Consumer First

As someone who focuses on machine learning from a design perspective, Alyx thinks companies can become so excited about building a new A.I. or ML product or service, new products are made, solely to appease the itch of the company to build something new and cool. The problem with this approach? The consumer’s pain point falls second to the desire to create.

We need to solve the problems with technology, but that technology might already exist. And, after the coolness of building new stuff fades away, you haven’t solved anything, the customer still has their pain point, and nothing has been solved. Sometimes cobbling multiple solutions from tech that’s already out there and works is the key to a solution,” Alyx said.

Takeaway? What ML products or service that are already out there could help your customer?

The Problem with Chatbots

There’s a joke about chatbots: “What do we want?” “Chatbots!” “When do we want them?” “I’m sorry, I didn’t understand that last request.”

Despite many advances in chatbot technology, chatbots are still not able to communicate exactly like humans. And, even as the chatbot technology advances further, chatbots will not be able to understand the subtleties and nuances of a conversation like an actual customer service representative could.

Despite this, many companies have worked hard to produce chatbots that sound like humans. The problem? When a customer experiences communication difficulties with a human-sounding chatbot, the consumer becomes increasingly frustrated with the technology.

Takeaway? Instead of trying to create the most “human-like” chatbot, focus on deploying a chatbot that creates clarity and easy-to-understand communication for your customer.

The Possibilities of the Future

Both Alyx and David believe machine learning has the power to positively transform human life in the future, by automating and optimizing daily processes. They pinpointed a few of the incredible possibilities for ML, like:

  • A.I. programs that can pinpoint a medical symptom by looking at an X-ray
  • Predictive deployment of ambulances to areas – before a 9-1-1 phone call is placed (More on that here)
  • Taking the “reckless” and human factor out of potentially dangerous jobs

Takeaway? With enough time and data, humanity has the possibility to “optimize” the planet with A.I. and Machine Learning.

Watch highlight from Alyx and David’s talk at the 2017 Propelify Innovation Festival:

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