What would you say if I told you that ‘Imperfect’ artificial intelligence (AI) can do more for your business than facial recognition ever will?
Your response might be to suggest that facial recognition is needed for 100% accuracy in data insights, and you probably think that this is important for keeping up with the competition. You may also tell me that it’s necessary to meet growing customer expectations, or even go into the things that you ‘just can’t do’ without it.
But one thing you won’t be able to argue is that facial recognition technology is good for compliance. The use of facial recognition is on the rise and causing a stir across Europe, with 11 EU nations reportedly already using it, and the European Data Watchdog warning that nations are not ready for AI-powered surveillance.
Tech is supposed to solve problems, not cause bigger ones, and decision makers are wrong to see compliance as a secondary consideration when it comes to insights and analytics (which are ultimately about creating more revenue). In fact, accepting a marginal reduction in accuracy is the only way to ensure compliance, protect privacy rights, and put you and your business out of harm’s way when it comes to reputational damages caused by data leaks and the storage of personal data that doesn’t belong to you.
A radical cultural shift in thinking on artificial intelligence needs to take place, where we alter standard practice and move towards a more transparent, honest, and ethical model, where businesses are open about the data they are collecting and accept a small reduction in accuracy in order to protect their customers.
AI that is partnered with a visual element, for example in CCTV cameras for smart video monitoring (or in facial recognition technology), has become increasingly popular in industries like urban planning and real estate.
The tech can allow users to garner analytics on the number and type of vehicles in a space, where people go and how long they spend there, and even allows you to collect demographic data such as age, gender and race. Much of the AI currently being used is developed through supervised learning, and the ethical pulse of these particular algorithms comes from the data scientists behind it. This means that the data scientists manually teach the AI which defining characteristics correspond with which type of person. AI’s ‘judgment’ is therefore no better than any ordinary person’s.
