Does This Headline Know You’re Reading It? discusses Text 2.0, a very interesting AI research project that focuses around this premise: What if your computer knew, what you are reading, as you are reading it?
This is an intriguing question and this work could lead to a multitude of interesting applications. The following video (it starts a bit slow, but includes interesting examples later on) shows just a few of those.
People are getting more and more used to rely on technology and getting walking or driving directions using their GPS devices in the car or their mobile phones. I know few people who prefer asking for directions to using their phones in an urban setting.
Autonomous City Explorer (ACE) on the other hand is a robot that has to rely on successful collaboration with humans. According to thefollowing video ACE successfully navigated from the origin to its destination (a distance of about 1.5 kilometers) in about 5 hours – and by asking 38 pedestrians and interpreting their hand signals along the way.
This projects seems like a nice venue to explore a big collection of different problem areas, such as collision avoidance, gesture interpretation, detecting of people, route planning, and many more. I wonder what this project will teach us about the nature of collaboration itself, particularly between humans and machines.
Imagine this situation: A company has hundreds (maybe thousands) of employees. All of them have their own skills and areas of expertise. There is probably lots of overlap, however any one person will not know everyone in the larger group who has particular skill sets. It someone is working on a project and needs assistance to overcome some technical hurdle, it could be very helpful, if they could communicate with those people who also have experience in that area. Those people might be located in entirely different parts of the company.
Email addresses are a means to an end. The goal is usually not to send an email to a particular address, but to a particular person. You want to say hello to your friend Steve or send a message to the VP of marketing at Microsoft or to the head caterer for your wedding. Ideally, you could send a message to a person just by entering his or her name, position, or some other descriptive attribute. If a person’s email address changes, the email system should send to the new address automatically. If the person matching a description differs over time, the email system should send to the person currently matching that description.
In the given example, the user would be able to get answers to his or her questions by reaching out to the people with the fitting skill sets without previously having known those people: The email system can decide, who the most appropriate receivers of the messages are.
I cannot help thinking that Aardvark was at least a little inspired by the ideas behind semantic email addressing. Their process is simple: Users send in questions (using email, twitter, IM, etc.), Aarvark routes the question to another user is (hopefully) qualified to answer it and the user will eventually receive a response, often just a few minutes later. In this social search approach, Aardvark accomplishes the job of finding information by finding the right people who can provide it. The service has received very good press and was recently acquired by google.
Twitter seems like it might be a good platform for this problem area. If someone has a public twitter feed, they are essentially broadcasting their updates to the open stream and anyone can see them. It is probably safe to assume, they are at least open to the idea of talking to strangers/responding to messages from people they do not already know.
How could one go about finding the best people to message though? One method is certainly to search the message stream for specific keywords and basically manually look for people who might be active in areas of interest. You can also search in and add yourself to oneofthemanydirectories that are being developed.
But, if I simply need to talk to someone and ask them “May I ask you a question about XYZ?” then clearly, a) broadcasting my question hoping that someone will answer could be very inefficient and b) first researching who the best person might be for my question(s) puts all the burden on me.
What if the user could simply send out the question and the system would ensure that the most appropriate people see it?
The basic idea here is this: The user submits the question (along with a set of keywords) to his or her software. The software has analyzed other users’ message streams, extracted keywords, etc. and generated a knowledge base. If the query can be confidently matched to another user, a message is generated and send to that user. The message will be visible to that user as a regular name mention and they can choose whether to engage in that conversation.
Some of the obvious challenges:
Generating of meaningful keywords/subject areas based on a person’s message stream.
Successful matching of queries with users.
Establishing an effective communication protocol that does not easily lend itself to abuse, i.e. spam.
A lot of web-based social networks are great at helping you connect with people you already know. Twitter makes it easy to connect with new people. The outlined approach (or a variation thereof) might be a good way of further supporting creation of those new connections, based on areas of interest.
In sci-fi films, when anyone gives a computer emotions, it all goes horribly wrong. The computer becomes vain, doubtful and irrational and Armageddon by wayward technology is only narrowly avoided.
This is not surprising – science fiction has been informing us and becoming part of our culture for a while. It is increasingly really all around us: We Are Living in a Sci-Fi World.
Imagine educational software that modifies its teaching style depending on the user’s mood. Cars that communicate with other drivers, if its driver is angry, intoxicated or talking on the phone. Music players could adjust their playlist based on the listener frowning, smiling or similarly expressing themselves. Email clients could disable the send button, if the user is clearly upset and about to send out an email he or she may regret later.
A lot of different uses are conceivable here and this could contribute to much more personalized computing experiences.
Modern laptops and desktop computers are typically already equipped with microphones and cameras. Future operating systems may well feature a mood evaluation component and search engines may take information from that component as part of the search query. Similar scenarios are conceivable for other types of web-enabled applications.
Imagine logging in to Facebook some evening and finding a notification “John has been having a bad day. Check in with him to make sure he’s okay.” Intriguing.
