Facebook chatbot agents have spontaneously created their own non-human language. Researchers were developing negotiating chatbots when they found out the bots had developed a unique way to communicate with each other. Facebook chatbots have accidentally given us a glimpse into the future of language.
[Image Souce: FAIR]
Researchers from the Facebook Artificial Intelligence Research lab (FAIR) have released a report that describes training their chatbots to negotiate using machine learning. The chatbots were actually very successful negotiators but researchers soon realized they needed to change their modes because when the bots were allowed to communicate among themselves they started to develop their own unique negotiating language.
[Image Souce: FAIR]
This unique and spontaneous development of non-human language was an incredible surprise for the researchers who had to redevelop their modes of teaching to allow for less unstructured and unsupervised bot-to-bot time.
Bots develop sophisticated negotiation tactics
The chatbots surprised its developers in other ways too proving to excel at the art of negotiation. Going as far as to use advanced negotiation techniques such as feigning interest in something valueless in order to ‘concede’ it later in the negotiations ensuring the best outcome. Co-author of the report, Dhruv Batra, said, “No human [programmed] that strategy, this is just something they discovered by themselves that leads to high rewards.”
But don’t panic, the accidental discovery of some basic communication between chatbots isn’t about to trigger singularity. Singularity, if you are not up on the doomsday techno jargon, is the term used for ”the hypothesis that the invention of artificial superintelligence will abruptly trigger runaway technological growth, resulting in unfathomable changes to human civilization.”
But these chatty bots definitely provide some solid opportunities for thinking about the way we understand language. Particularly the general view that language is ‘our’ domain and exclusive to humans.
Mysteries of machine learning
The research also highlights the fact that we have a long way to go in understanding machine learning. Right now there is a lot of guessing games that often involve examining how the machine thinks by evaluating the output after feeding a neural net a massive meal of data.
The idea that the machine can create its own language highlights just how many holes there are in our knowledge around machine learning, even for the experts designing the systems.
The findings got the team at Facebook fired up, they write, “There remains much potential for future work, particularly in exploring other reasoning strategies, and in improving the diversity of utterances without diverging from human language.”
Chatbots are widespread across the customer service industry using common keywords to answer ‘FAQ’ type inquiries. Often these bots have a short run time before the requests get too complicated. Facebook has been investing heavily in chatbot technology and other large corporations are to follow. While there isn’t a strong indication of how these negotiating bots will be used by Facebook, other projects are getting big results.
The bot called, DoNotPay has helped over 250,000 people overturn more than 160,000 parking tickets for users in New York and London by working out if an appeal to a ticket is possible through a series of simple questions, and then guiding the user through the appeal process.
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