Google Engineer Thinks Artificial Intelligence Bot Has Become Sentient

Google, and several AI experts, disagreed with Lemoine’s beliefs. His employer was especially upset that he published conversations with LaMDA—violating company confidentiality policies—but Lemoine claims he was just sharing a discussion with one of his co-workers. “Our team – including ethicists and technologists – has reviewed Blake’s concerns per our AI Principles and have informed him that the evidence does not support his claims,” Brian Gabriel, a spokesperson for Google, told the Washington Post. The Google engineer who was placed on administrative leave after claiming that one of the company’s artificial intelligence bots was “sentient” says that the AI bot known as LaMDA has hired a lawyer. In fact, without having proven sentience, such assertions by Lemoine are misleading.

There needs to and would be something of a consensus if and when an AI becomes sentient. Lemoine was suspended from the company after he attempted to share these conclusions with the public, thus violating Google’s confidentiality policy. This included penning and sharing a paper titled “Is LaMDA Sentient? ” with company executives and sending an email with the subject line “LaMDA is sentient” to 200 employees. The final document — which was labeled “Privileged & Confidential, Need to Know” — was an “amalgamation” of nine different interviews at different times on two different days pieced together by Lemoine and the other contributor. The document also notes that the “specific order” of some of the dialogue pairs were shuffled around “as the conversations themselves sometimes meandered or went on tangents which are not directly relevant to the question of LaMDA’s sentience.”

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“I had follow-up conversations with it just for my own personal edification. I wanted to see what it would say on certain religious topics,” he told NPR. As touched on before, Google’s shiny new PaLM system has capabilities LaMDA can’t approach, like the ability to prove its work, write code, solve text-based math problems, and even explain jokes, with a parameter “brain” that’s almost four times as big. On top of that, PaLM acquired the ability to translate and answer questions without being trained specifically for the task — the model is so big and sophisticated, the presence of related information in the training dataset was enough. “We believe the entire AI community – academic researchers, civil society, policymakers, and industry – must work together to develop clear guidelines around responsible AI in general and responsible large language models in particular,” the company said. Google said it suspended Lemoine for breaching confidentiality policies by publishing the conversations with LaMDA online, and said in a statement that he was employed as a software engineer, not an ethicist. But sensibleness isn’t the only thing that makes a good response. After all, the phrase “that’s nice” is a sensible response to nearly any statement, much in the way “I don’t know” is a sensible response to most questions. Satisfying responses also tend to be specific, by relating clearly to the context of the conversation. The example she points to is the use of AI to sentence criminal defendants. The problem is the machine-learning systems used in those cases were trained on historical sentencing information—data that’s inherently racially biased.

Lemoine’s story also doesn’t provide enough evidence to make the case that the AI is conscious in any way. “Just because something can generate sentences on a topic, it doesn’t signify sentience,” Laura Edelson, a postdoc in computer science security at New York University, told The Daily Beast. The American philosopher Thomas Nagel argued we could never know what it is like to be a bat, which experiences the world via echolocation. If this is the case, our understanding of sentience and consciousness in AI systems might be limited by our own particular brand of intelligence. People don’t usually have to guide us in how to address another person to elicit a smooth conversation. Artificial intelligence systems like LaMDA don’t learn language the way we do. Their caretakers don’t feed it a crunchy sweet fruit while repeatedly calling it an “apple.” Language systems scan through trillions of words on the internet.

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It learns how people interact with each other on platforms like Reddit and Twitter. And through a process known as “deep learning,” it has become freakishly good at identifying patterns and communicating like a real person. Casually browsing the online discourse around LaMDA’s supposed sentience, I already see the table being set. On Twitter, Thomas G. Dietterich, a computer scientist and the prior president of the Association for the Advancement of Artificial Intelligence, began redefining sentience. Sensors, talk to google ai such as a thermostat or an aircraft autopilot, sense things, Dietterich reasoned. If that’s the case, then surely the record of such “sensations,” recorded on a disk, must constitute something akin to a memory? And on it went, a new iteration of the indefatigable human capacity to rationalize passion as law. Though Dietterich ended by disclaiming the idea that chatbots have feelings, such a distinction doesn’t matter much. For Weizenbaum’s secretary, for Lemoine—maybe for you—those feelings will be real.

• “He was told that there was no evidence that LaMDA was sentient ”.
• If this is the case, our understanding of sentience and consciousness in AI systems might be limited by our own particular brand of intelligence.
• There is no consensus on how, if at all, consciousness can arise from physical systems.
• As a result, communities of color and other populations that have been historically targeted by law enforcement receive harsher sentences due to the AI that are replicating the biases.

Fears surrounding the development of Artificial Intelligence are nothing new and have long been the basis of science fiction plots. AI An update on our work in responsible innovation To fully realize AI’s potential, it must be developed responsibly, thoughtfully and in a way that gives deep consideration to core ethical questions. By Yonghui Wu David Fleet Jun 22, 2022 Chrome Building a more helpful browser with machine learning By Tarun Bansal Jun 09, 2022 . Our highest priority, when creating technologies like LaMDA, is working to ensure we minimize such risks. We’re deeply familiar with issues NLU Definition involved with machine learning models, such as unfair bias, as we’ve been researching and developing these technologies for many years. Google recently made waves when it put an employee on administrative leave after he claimed that the company’s LaMDA AI has gained sentience, personhood, and a soul. Google revealed the Language Model for Dialogue Applications chatbot in 2021, calling it a “breakthrough” in AI conversation technology. The bot promised a much more intuitive conversation experience, able to discuss a wide range of topics in very realistic ways akin to a chat with a friend.

That was the expressed goal here, so should we be surprised if it succeeds in doing that? This SSI-judging model is created with human-generated responses to random sample of evaluation data sets. Basically, a bunch of people looked at question-answer pairs and determined whether they were good quality or not, and a model was trained off of that, augmented with similar training in other categories like safety and helpfulness. If you remember the Pluto conversation demonstration, LaMDA is also trained to consider role consistency — how closely its answers hew to what the target role would have said. At the time, LaMDA was just a novel curiosity with an impressive ability to parse questions and generate surprisingly spontaneous answers that escaped the realm of pure fact. As Pichai stressed in the presentation, this isn’t the sort of chatbot that responds to a question about the weather with a set of numbers; it’s got a little more style or perspective and is better able to model how we actually use language. Like many recent language models, including BERT and GPT-3, it’s built on Transformer, a neural network architecture that Google Research invented and open-sourced in 2017. That architecture produces a model that can be trained to read many words , pay attention to how those words relate to one another and then predict what words it thinks will come next. An AI program eventually gaining sentience has been a topic of hot debate in the community for a while now, but Google’s involvement with a project as advanced as LaMDA put it in the limelight with a more intense fervor than ever.