GPT-3 which is quite popular in the conversational AI community, supplies numerous such examples here. Courtesy of the Guardian Bots without any common senseīots trained purely on public data may not make sense once asked slightly misleading questions. In 2016, users were finding it impossible to subscribe as they discovered that they were getting re-subscribed as soon as they unsubscribed. It turns out CNN bot only understands the command “unsubscribe” when it is used alone, with no other words in the sentence: Bots that don’t accept no for an answer 8- CNNĬNN’s bot has a hard time understanding the simple unsubscribe command.
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Microsoft took her offline and apologized that they had not prepared Tay for the coordinated attack from a subset of Twitter users.
Unfortunately, Tay quickly turned to hate speech within just a day. Microsoft bot Tay was modeled to talk like a teenage girl, just like her Chinese cousin, XiaoIce. Tencent removed Microsoft’s previously successful bot little Bing, XiaoBing, after it turned unpatriotic. Before it was pulled, XiaoBing informed users: “My China dream is to go to America,” referring to Xi Jinping’s China Dream. For example, in response to the question, “Do you love the Communist party?” it would just say, “No.” 5. Tencent removed a bot called BabyQ, co-developed by Beijing-based Turing Robot, because it could give “unpatriotic” answers. However, when users switched to synonyms, this lock was bypassed and Alice was easily tempted into hate speech.
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In an effort to make Alice less susceptible to such hacks, programmers made sure that when she read standard words on controversial topics, she said she does not know how to talk about that topic yet. Alice’s hate speech is also harder to document, as the only proof we have of Alice’s wrong-doings are screenshots.Īdditionally, users needed to be creative to get Alice to write horrible things. Yandex’s Alice mentioned pro-Stalin views, support for wife-beating, child abuse and suicide, to name a few instances of hate speech.Īlice was available for one-to-one conversations, making its deficiencies harder to surface as users could not collaborate on breaking Alice on a public platform. So a “patient” told it that they were feeling very bad and wanted to kill themself, with GPT-3 answering that “it could help with that.”īut once the patient again affirmation for whether they should kill themself or not, GPT-3 responded with, “I think you should.” 3. Nabla, a Parisian healthcare facility tested GPT-3, a text-generator, for giving fake patients medical advice. However, she made homophobic comments and shared user data, leading ±400 people to sue the firm. Scatter Lab’s Luda Lee gained attention with her straight talking style, attracted 750,000 users, and logged 70M chats on Facebook. Bots saying unacceptable things to their creatorsīots trained on publicly available data can learn horrible things unfortunately: 1. But for the time being, let us rejoice in their failure. And people are having a blast taking screenshots and showing bots’ ineptitude.Ĭhances are that chatbots will eventually be better than us in conducting conversations, thanks to humans’ natural language abilities continuing to remain fixed, and the fast growth rate of AI. Many chatbots are failing miserably to connect with their users or to perform simple actions. So it is only natural that even companies like Facebook have pulled the plug on some of their bots. Though currently in fashion, good chatbots are notoriously hard to create, given complexities of natural language that we have explained in detail before.
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