​Analogue Living

Virtual customer service uses AI to detect human emotion

IPsoft’s Amelia is an AI customer service agent that can accurately detect the mood of the customer to better deal with their request.

Dealing with the customer support department of many companies can be an infuriating task — as a recent viral recording of a Comcast call demonstrated pretty perfectly. But can digital alternatives offer an improvement? IPsoft’s Amelia is an AI customer service agent that can accurately detect the mood of the customer to better deal with their request.

While many businesses have already experimented with artificial intelligence for online web support, it can soon become very obvious when the ‘agent’ doesn’t respond in an appropriately emotional way, especially if the request is an angry one. Amelia is able to process the natural language of both business manuals and the customer in need of support. Not only can it search those business guides and the web for information to help each customer, but it also tracks their mood and other contextual data. This way, if a customer is unhappy, Amelia tailors its support to offer greater reassurance and works to ensure customers end the call in a better mood. If in any case the issue isn’t resolved, Amelia passes the call or chat onto a human. All communication is stored so Amelia can pick up each case with reference to any previous contact.

Detecting customers’ feelings and responding appropriately could make online helpdesks even more like face-to-face support, while helping reduce the burden of customer service teams on businesses. Are there other ways this type of mood-detecting technology could help digitize human responsibilities?


AI restaurant guide makes friendly recommendations

Finding a new place to eat with a friend or that special someone often requires a trawl throughGoogle search results or Yelp reviews, but they're not very good at knowing the types of restaurants you already like. Adding a touch of natural language recognition and artificial intelligence, Russia's IO is an app that learns users' preferences and chats with them to help them find restaurants nearby. Users simply start by typing questions into IO, without having to fill out any preferences up front. IO will then begin to reply with an easy-to-understand answer in a friendly tone. Users can type as if they were speaking to a friend over text and IO will understand what they're saying. When recommending a restaurant, the app brings up all of the relevent details -- location, description, menu, prices, opening times and contact details. Users can also ask what's good on the menu, what the atmosphere's like and if it's good for a date, along with other questions they might have. For each response, users can let IO know if they think it looks good, if they want to know more info or a different suggestion. This way, the app learns their preferences and can make better recommendations in the future. The more they use it, the smarter it becomes. Over time, users can save information about their favorite restaurants to create their own unique collection.

Recently launched in New York City and with plans to expand to major European cities, IO is part of a trend for presenting data in a more friendly way using AI and machine learning, and at times it feels close to the vision of the future presented in Spike Jonze's Her. Are there other ways to make tech user interfaces feel less like working with a computer and more like speaking with a human?

Rooftop Socialite or Moonlight Gypsy ?!

Ever wondered why and how you chose a certain perfume? Was it promoted by a famous A- list celebrity, you just liked the looks or did you actually liked the smell? I guess It's personal and there's a difference between men and women, there's that.

Nevertheless fragrancy startup Pinrose took another approach with it's “scent finder”. Answer a couple of questions and based on an algorithm a top 3 dazzling scents pop out. The scents have names like Camp Rebel, Ballroom Philosopher, Rooftop Socialite, Moonlight Gypsy and sell for around $50.


According to the founders Erika Shumate and Christine Luby it works around 75% of the time.  The fragrances work appealing because they match the wearers mood and fit their personalities given the answers from the questionnaire. Although the proces of finding the right scent becomes so simple it would definitely speak to men - Like.Buy.Done.  It's only available for women, for now.

It's a clear signal that companies are using different business models and techniques to reach customers nowadays. In the future they are planning to combine with Big Data to their advantages as well, for defining preferences based on a person’s Instagram or Pinterest profiles.

It's interesting to see how people will react with technology being used in new way and predicting what will appeal to them. And with the privacy issue intensely burning, will the collected data about you, also be used for example when you shop for groceries? Because my mood and eating tendencies are quite the happy bunch. A lot of our behavior is based on emotion. Basic marketing; Finding out what people want and give it to hem. Making a businessmodel work based on moods is therefore more personalized and that's they way we're heading.  

Wondering if a algorithm beats your girlfriend's advice on cologne, check it out and take the test here!