No Room For Privacy
As smart hotel rooms promise to offer utmost convenience, privacy will become elusive.
It is not just smart home products, social media accounts or browsing activities on the web that open up user data to those waiting to harvest it; smart hotel rooms, too, are in the reckoning. All over the world, hotels are trying to keep up with tech innovations that could transform a person's hotel stay. This would also mean creating a ton of rich data on each hotel guest. In a single overnight stay, the sheer amount of data yielded and necessarily retained would be voluminous.
As a guest walks into a hotel room with a special digital key, practically every object will involve sensors and voice controls. A recent report from CBS News describes the research at a Marriott Hotel in Maryland where rooms are personalised via an intelligent engine. Window shades can instantly be commanded to the desired light or darkness level and the temperature in the room can be adjusted too. TV viewing preferences, consumption from a mini bar, bath water temperature, meal preferences (even if outside of the room) and much more can quite conceivably be recorded. This has already begun in some top hotels. There will be smart mirrors that interact with the guest and, in fact, even the glass in the shower areas can be used for finger-tracing hot-shower ideas and be emailed to the guest. Mirrors and glass surfaces can also display a guest's preferred workout routine.
The scope of truly intimate and personal information possible - how warm must a toilet seat be for this guest, what kind of make-up is being used, what he/ she likes to drink, how hot should the coffee be, etc - is limitless. Information such as these will go on to make subsequent hotel stays even more personalised, meeting a guest's every specific need, but raises serious privacy concerns.
Every company that provides services will, of course, ask for consent and pledge never to share any of the data with a third party. But that third party may not always wait to get the data legitimately. If the right combination of data pieces, including a digital signature, is misappropriated somehow, the results could be drastic.
While it may be accurate to ask hotel guests to be careful and use only what is absolutely necessary, that would actually defeat the very purpose of paying for a smart room in a top-end hotel. If users are to make use of all the conveniences, the security has to be made more stringent. Machine Learning
Social networks are hotbeds for explosive conversations. Verbal clashes, abuse, bullying and harassment are commonplace on platforms such as Twitter and Facebook. Researchers at Cornell University may be able to help tackle this. In a study, spotted by The Verge, a group of scientists have figured out how to feed volumes of data on the indicators that a conversation is likely to turn sour. Looking back over a conversation, it isn't difficult for humans to spot early warning signs. The researchers believe that when predictions become good enough, one can salvage a conversation in its initial stages.
For example, an obvious lack of polite words or overly confrontational questions and a tendency to personalise are signs that a conversation is headed down the wrong path. Give enough instances of this to an AI system and it will quickly learn to spot trouble. Potential uses for this could be better moderation on social networks and comment forums, preventing abuse or harassment and even better meetings at the workplace.