Much has been made of the warnings of really smart people that have said artificial intelligence (AI) advances lead to the end of us all. No kidding. Steven Hawking said, “The development of full artificial intelligence could spell the doom of the human race”. Elon Musk said, “I have exposure to the very cutting-edge AI, and I think people should be really concerned about it. I keep sounding the alarm bell, but until people see robots going down the street killing people, they don’t know how to react, because it seems so ethereal.”
Hmm. Sounds like something to be worried about. I’ll certainly be worried when I see robots going down the street killing people. I’ll probably be worried when someone decides that robots don’t need a programmer background check and code review on the software for robot open carry.
AI vs. Machine Learning: What’s the Difference?
So where are we going with all this? And what are the differences between artificial intelligence and machine learning (ML)?
In short, machine learning is a subset of AI. AI might describe the way a computer is programmed to play a game. Machine learning is when the machine not only applies rules to how to play the game that someone has programmed in, but also learns from its experiences and mistakes, in essence teaching itself how to play better. Taken further, a machine might be programmed to learn to learn, to apply a general intelligence.
AI and Machine Learning in Business
We are enjoying the benefits of AI and machine learning even now. My smart phone has gotten pretty good at knowing what I’m going to text before I type it. But how about an AI application that will predict what hackers will do before they break into your network, and even learn how to prevent them from doing so? Forester Research has predicted AI Will Revolutionize Cybersecurity. That would keep me from lying awake at night trying to anticipate the next attack vector.
Does your Marketing team have enough resources? Maybe AI can help out by analyzing successful and unsuccessful account-based marketing campaigns, delivering insights that otherwise would be missed and predictions that could improve account targeting.
For most project-based companies, their human resource allocation and project progress (or lack thereof) are of great concern, and the complexity of contemporary business is growing well beyond the ability to track a folder full of spreadsheets and a few project files. Real-time predictive analysis is crucial; but to fuel that analysis you need data. Accurate data on what employees are doing on a daily basis is crucial. An AI-enabled timesheet would know what projects and tasks I need to track time on before I spend any time on those tasks.
What About the Killer Robots?
Yes, there are robots with AI and machine learning capabilities to drive automated, process-based work. The possibilities for business and society are…well, I won’t say unimaginable; but for now, we don’t have to worry about killer robots.