AI has become such a common term it would be easy to think that the addition of a little AI can improve everything. The reality is that no organization ever became more successful by going out and purchasing a ‘bucket load of AI.’ AI does not have any intrinsic value until it is applied to a specific business problem.
As AI works its way into the enterprise, we have noticed one particular term gaining traction, that of ‘Deep Learning.’ Both in conversations with buyers of AI and technology vendors of AI, Deep Learning appears to have caught the imagination. That is worrisome as Deep Learning is a branch of AI that promises a lot, but you should approach it with extreme caution.
In our upcoming book ‘The AI Playbook’ we discuss in some detail the issue of bias in AI. For those that don’t know, AI bias is the phenomena of an AI system giving prejudiced results due to misassumptions in the process. It’s easy to label biases as mistakes, but frequently they are not, they are answers that we do not agree with.
It seems like every week; a technology vendor tells me how their AI product will free workers from mundane jobs and enable them to do more exciting work. And, every week I respond the same way (though sometimes more diplomatically) ‘that is not true.’ As AI works its way through blue-collar jobs, lower-paid white-collar jobs and now into higher-paid professions, that sales pitch that falls flat. In theory, AI automation could free workers from the mundane and create new and more exciting jobs. But in reality, that will seldom happen, workers are made redundant.