What You’re Buying Is Not Artificial Intelligence: How To Tell Fact From Fiction
In business, the buzzword ‘AI’ is thrown around frequently. Even people with baseline knowledge of technology often mix it up with simple automation, statistical tests and even excel formulae.
It’s getting harder and harder to tell real from the fake when it comes to products of artificial intelligence (AI). So hard, in fact, that dating apps are now boosting their numbers with profiles with fake faces, and advertisers are even using them to increase diversity in their ads. This ambiguity around AI spans wide and is, unbeknownst to many of us, creeping further into our daily lives.
These are examples of AI helping to fake it in the real world. But what about attempts by technology providers to fake AI solutions at the first place?
In business, the buzzword ‘AI’ is thrown around frequently. Even people with baseline knowledge of technology often mix it up with simple automation, statistical tests and even excel formulae.
It was found that 40 per cent of European AI start-ups do not actually use AI, with many of them not correcting the misclassification made by third-party analytics sites due to the hype around the technology. And it’s not uncommon for firms to secretly use humans to do AI bots’ work: It was revealed that AI start-up Engineer.ai was claiming to automate app development using AI while actually relying on human engineers and conventional software to do the job.
In this scenario, how can you evaluate technology solutions when your organization is ready to start the AI journey? There are some standard questions you should ask to make sure you get exactly what you’re paying for. These guidelines apply to evaluating any ‘smart’ machine learning solution, including advanced techniques such as AI.
So, you’ve decided to expand your capabilities and invest in AI. Ask these six questions to get a good understanding of what you’re being offered and how advanced it actually is.
Start by asking a vendor exactly how their solution works and why it’s an example of AI. Get a good grasp of how it does what it claims to do, and question why automation or simpler techniques won’t suffice. A company selling AI technologies should be able to explain the need for AI and the approach they use in a digestible way. Don’t worry about sounding naive here.
With this you can start making the distinction between an AI algorithm and brilliant marketing. For example, a system that recommends products to customers can be built on simple business heuristics or could also be powered by AI. Asking probing questions must be your first step to unravel the truth.
Any AI solution needs lots of data. Data is what makes AI smart, so find out what data has been used to train the AI. For example, Open AI’s GPT 2 model has the ability to write news articles, and was trained on millions of Wikipedia articles to give it the intelligence.
