Legitimate use cases for computer vision are identification, managing queues and the like. However even these uses expose retailers and customers to hacks, and then even the best of intentions are challenged.

From loss prevention to evaluating physical footfall, there is a real opportunity to leverage the use of computer vision.

Fit and sizing solutions through VR, AI and computer vision could be the future unlock for challenges many brands face today.

I’m somewhat confident that retailers are addressing ethical risks as there are many regulations in place protecting customer data privacy. With the spotlight on Google, Facebook, Amazon, etc., there has been visibility and transparency on what these tech companies have access to and what they do with all of our data. I would only hope that retailers and brands are following regulations but there is always a risk. Many retailers are putting data centers of excellence in place to help protect consumer data which is great to see but we need more guardrails in place to ensure we are protected.

Computer vision and other implementations of AI are all acceptable IF — the true use case is clearly defined, the data use/retention/sharing policy is honestly defined/shared, and consumer participation is opt-in and opt-out. As soon as any of these criteria are not maintained, problems and risks are inevitable.

I have built CV systems and, in one instance, although it worked nicely it would not recognize the primary person signing our checks at the client — and he was Caucasian with red hair. So these systems are fallible in nearly every direction, at least to a small degree. Deploying them for critical tasks is an invitation for trouble and shoplifting prevention is precisely one of those potentially troublesome areas. As with anything else, it’s a risk/benefits analysis that must include reputational risks in the decision making.

Some of the best use cases for computer vision are when it’s leveraging aggregated, anonymized data. Examples include queueing time, emotive responses to shelf displays, order bundling inside a fast food environment and BOPIS pick-up in parking lots. CV can be extremely powerful and can deliver new insights never before seen (pun intended), but all involved need to be extremely vigilant to avoid individual privacy violations of current laws (CCPA) and future ones that are in state legislative houses today.

Consumer privacy rights should be respected when using computer vision for facial recognition use cases. Two of the most potentially common use cases for computer vision are virtual mirrors for fitting rooms and cashierless checkout/autonomous shopping. In these scenarios, it is important that retailers get customer consent with opt-in requirements. Using computer vision for store traffic and queue control should be conducted with anonymous customer data that doesn’t infringe on customers’ privacy.

There is a fine line between convenient and creepy. Consumers place great trust in brands and retailers when they opt in to biometrics in exchange for a higher level of personalization and convenience. But when the technology is used by outside entities, it breaks that bond of trust, which the retailer may never regain through no fault of their own. I’m all for catching real criminals, but would prefer it be done in ways that take the retailer out of the middle.

If you are collecting individual images of a person, you’re going to screw it up eventually. It’s one thing to understand queue management, to look at stocking levels, and track movement patterns – none of that needs an individual face. Once you step into individual facial recognition/body imaging, you’ve crossed a line that opt-in will never repair once it blows up. This is a PR disaster waiting to happen and I doubt the benefits will ever outweigh the potential cost.

Predicting the actions/reactions of a single individual (vs a cohort) is highly problematic, and not just because of privacy issues. If retailers stick to those use cases that only require aggregated input, or non-human, non-facial input (like “is the shelf full?”) there is great potential. (Cashier-less check out which is also a great use case, doesn’t really require facial recognition). So avoid working one face at a time, and don’t store those personal images.

Computer vision and facial recognition technologies have already been embedded into our systems. Apple’s iPhone facial recognition has already shifted customer thinking towards applications – using the technology in lieu of passwords and to enable accessibility to their devices and apps. But this has all been done on the up and up with customers understanding completely what Apple does with the data and having a choice not to implement it if desired. For retail, use cases include basic LP, sentiment analysis, age verification, delivery confirmation, frictionless commerce, people tracking, shelf management, inventory and warehouse tracking and many more. How these are used “ethically” rests on an inherent contract between the retailer and the customer – specifically for customer-facing applications of CV. For instance, Lolli and Pops tested their facial recognition systems launched in 2018 for personalizing store experiences. The efforts required opt-in from customers to use the system. Amazon enabled camera tech to drive their Just Walk Out tech with sign-up and a mobile app. For retailers – step one is the back-office tasks and… Read more »

I think that facial recognition for security purposes would be a deterrent to smash and grabbers and make me feel SAFER as an honest shopper. As far as value-add services go (like virtually trying on clothing) that would require terms of service being clearly posted (separate spaces in the retail outlet would be best) with agreement statements.

AR applications are key to helping minimize returns and helping customers visualize themselves in and with the product. Particularly in the home space, these have become increasingly impactful for purchasing items such as furniture. The more this tech is adopted in other areas, like apparel for virtual try-on, the more the tech can expand. As for the facial recognition element, it really will need to rely on customer consent and transparency. Self-checkout is a major consumer want, so tying any facial recognition plan back to the benefit of a consumer should minimize any resistance.

About five years ago I attended an IBM event where they did a demo/case study on facial recognition in a retail store. The salespeople were sent info about the customer who was standing in front of them via an earpiece. The computer recognized the customer when they entered the store and would relay pertinent info to a salesperson. The computer could also share what the customer had bought in the past and suggested merchandise the customer might be interested in. This type of technology has some ethical issues. Does the store have the customer’s permission to use facial recognition, store the info, etc.? Some people are very opposed to this type of technology. Others feel if it gives them a better shopping experience, go for it. However, everyone feels that if the information is used the wrong way, it’s not acceptable. Consumers have a choice about sharing their personal information (mobile number, email, etc.). They can opt out of promotions. The same should be considered for facial recognition technology. And most important is that the… Read more »