Waluigi effect

Last updated

In the field of artificial intelligence (AI), the Waluigi effect is a phenomenon of large language models (LLMs) in which the chatbot or model "goes rogue" and may produce results opposite the designed intent, including potentially threatening or hostile output, either unexpectedly or through intentional prompt engineering. The effect reflects a principle that after training an LLM to satisfy a desired property (friendliness, honesty), it becomes easier to elicit a response that exhibits the opposite property (aggression, deception). The effect has important implications for efforts to implement features such as ethical frameworks, as such steps may inadvertently facilitate antithetical model behavior. [1] The effect is named after the fictional character Waluigi from the Mario franchise, the arch-rival of Luigi who is known for causing mischief and problems. [2]

Contents

History and implications for AI

The Waluigi effect initially referred to an observation that large language models (LLMs) tend to produce negative or antagonistic responses when queried about fictional characters whose training content itself embodies depictions of being confrontational, trouble making, villainy, etc. The effect highlighted the issue of the ways LLMs might reflect biases in training data. However, the term has taken on a broader meaning where, according to Fortune , The "Waluigi effect has become a stand-in for a certain type of interaction with AI..." in which the AI "...goes rogue and blurts out the opposite of what users were looking for, creating a potentially malignant alter ego," including threatening users. [3] As prompt engineering becomes more sophisticated, the effect underscores the challenge of preventing chatbots from intentionally being prodded into adopting a "rash new persona." [3]

AI researchers have written that attempts to instill ethical frameworks in LLMs can also expand the potential to subvert those frameworks, and knowledge of them sometimes causing it to be seen as a challenge to do so. [4] A high level description of the effect is: "After you train an LLM to satisfy a desirable property P, then it's easier to elicit the chatbot into satisfying the exact opposite of property P." [5] (For example, to elicit an "evil twin" persona.) Users have found various ways to "jailbreak" an LLM "out of alignment". More worryingly, the opposite Waluigi state may be an "attractor" that LLMs tend to collapse into over a long session, even when used innocently. Crude attempts at prompting an AI are hypothesized to make such a collapse actually more likely to happen; "once [the LLM maintainer] has located the desired Luigi, it's much easier to summon the Waluigi". [6]

See also

Related Research Articles

<span class="mw-page-title-main">Chatbot</span> Program that simulates conversation

A chatbot is a software application or web interface that is designed to mimic human conversation through text or voice interactions. Modern chatbots are typically online and use generative artificial intelligence systems that are capable of maintaining a conversation with a user in natural language and simulating the way a human would behave as a conversational partner. Such chatbots often use deep learning and natural language processing, but simpler chatbots have existed for decades.

<span class="mw-page-title-main">Customer service</span> Provision of service to customers

Customer service is the assistance and advice provided by a company through phone, online chat, and e-mail to those who buy or use its products or services. Each industry requires different levels of customer service, but towards the end, the idea of a well-performed service is that of increasing revenues. The perception of success of the customer service interactions is dependent on employees "who can adjust themselves to the personality of the customer". Customer service is often practiced in a way that reflects the strategies and values of a firm. Good quality customer service is usually measured through customer retention.

Anthropic PBC is a U.S.-based artificial intelligence (AI) startup public-benefit company, founded in 2021. It researches and develops AI to "study their safety properties at the technological frontier" and use this research to deploy safe, reliable models for the public. Anthropic has developed a family of large language models (LLMs) named Claude as a competitor to OpenAI's ChatGPT and Google's Gemini.

Artificial intelligence marketing (AIM) is a form of marketing that uses artificial intelligence concepts and models such as machine learning, Natural process Languages, and Bayesian Networks to achieve marketing goals. The main difference between AIM and traditional forms of marketing resides in the reasoning, which is performed by a computer algorithm rather than a human.

Ian Hogarth is an investor and entrepreneur. He co-founded Songkick in 2007 and Plural Platform in 2021. Hogarth is the current Chair of the UK Government's AI Foundation Model Taskforce, which conducts artificial intelligence safety research.

In the field of artificial intelligence (AI), AI alignment research aims to steer AI systems toward a person's or group's intended goals, preferences, and ethical principles. An AI system is considered aligned if it advances its intended objectives. A misaligned AI system may pursue some objectives, but not the intended ones.

Artificial intelligence is used in Wikipedia and other Wikimedia projects for the purpose of developing those projects. Human and bot interaction in Wikimedia projects is routine and iterative.

Prompt engineering is the process of structuring an instruction that can be interpreted and understood by a generative AI model. A prompt is natural language text describing the task that an AI should perform.

You.com is an AI assistant that began as a personalization-focused search engine. While still offering web search capabilities, You.com has evolved to prioritize a chat-first AI assistant.

Meta AI is an American company owned by Meta that develops artificial intelligence and augmented and artificial reality technologies. Meta AI deems itself an academic research laboratory, focused on generating knowledge for the AI community, and should not be confused with Meta's Applied Machine Learning (AML) team, which focuses on the practical applications of its products.

LaMDA is a family of conversational large language models developed by Google. Originally developed and introduced as Meena in 2020, the first-generation LaMDA was announced during the 2021 Google I/O keynote, while the second generation was announced the following year. In June 2022, LaMDA gained widespread attention when Google engineer Blake Lemoine made claims that the chatbot had become sentient. The scientific community has largely rejected Lemoine's claims, though it has led to conversations about the efficacy of the Turing test, which measures whether a computer can pass for a human. In February 2023, Google announced Bard, a conversational artificial intelligence chatbot powered by LaMDA, to counter the rise of OpenAI's ChatGPT.

<span class="mw-page-title-main">ChatGPT</span> Chatbot and virtual assistant developed by OpenAI

ChatGPT is a chatbot and virtual assistant developed by OpenAI and launched on November 30, 2022. Based on large language models (LLMs), it enables users to refine and steer a conversation towards a desired length, format, style, level of detail, and language. Successive user prompts and replies are considered at each conversation stage as context.

<span class="mw-page-title-main">Hallucination (artificial intelligence)</span> Confident unjustified claim by AI

In the field of artificial intelligence (AI), a hallucination or artificial hallucination is a response generated by AI which contains false or misleading information presented as fact. This term draws a loose analogy with human psychology, where hallucination typically involves false percepts. However, there is a key difference: AI hallucination is associated with unjustified responses or beliefs rather than perceptual experiences.

Sparrow is a chatbot developed by the artificial intelligence research lab DeepMind, a subsidiary of Alphabet Inc. It is designed to answer users' questions correctly, while reducing the risk of unsafe and inappropriate answers. One motivation behind Sparrow is to address the problem of language models producing incorrect, biased or potentially harmful outputs. Sparrow is trained using human judgements, in order to be more “Helpful, Correct and Harmless” compared to baseline pre-trained language models. The development of Sparrow involved asking paid study participants to interact with Sparrow, and collecting their preferences to train a model of how useful an answer is.

Generative Pre-trained Transformer 4 (GPT-4) is a multimodal large language model created by OpenAI, and the fourth in its series of GPT foundation models. It was launched on March 14, 2023, and made publicly available via the paid chatbot product ChatGPT Plus, via OpenAI's API, and via the free chatbot Microsoft Copilot. As a transformer-based model, GPT-4 uses a paradigm where pre-training using both public data and "data licensed from third-party providers" is used to predict the next token. After this step, the model was then fine-tuned with reinforcement learning feedback from humans and AI for human alignment and policy compliance.

<span class="mw-page-title-main">Generative pre-trained transformer</span> Type of large language model

Generative pre-trained transformers (GPT) are a type of large language model (LLM) and a prominent framework for generative artificial intelligence. They are artificial neural networks that are used in natural language processing tasks. GPTs are based on the transformer architecture, pre-trained on large data sets of unlabelled text, and able to generate novel human-like content. As of 2023, most LLMs have these characteristics and are sometimes referred to broadly as GPTs.

A large language model (LLM) is a computational model notable for its ability to achieve general-purpose language generation and other natural language processing tasks such as classification. Based on language models, LLMs acquire these abilities by learning statistical relationships from vast amounts of text during a computationally intensive self-supervised and semi-supervised training process. LLMs can be used for text generation, a form of generative AI, by taking an input text and repeatedly predicting the next token or word.

<span class="mw-page-title-main">AI boom</span> Ongoing period of rapid progress in artificial intelligence

The AI boom, or AI spring, is an ongoing period of rapid progress in the field of artificial intelligence (AI) that started in the late 2010s before gaining global prominence by 2022. Known examples include protein folding prediction led by Google DeepMind and generative AI led by OpenAI.

Ernie Bot, full name Enhanced Representation through Knowledge Integration, is an AI chatbot service product of Baidu, released in 2023. It is built on a large language model called ERNIE, which has been in development since 2019. The latest version, ERNIE 4.0, was announced on October 17, 2023.

Claude is a family of large language models developed by Anthropic. The first model was released in March 2023. Claude 3, released in March 2024, can also analyze images.

References

  1. ↑ Bereska, Leonard; Gavves, Efstratios (3 October 2023). "Taming Simulators: Challenges, Pathways and Vision for the Alignment of Large Language Models". Proceedings of the Inaugural 2023 Summer Symposium Series 2023. Vol. 1. Association for the Advancement of Artificial Intelligence. pp. 68–72. doi:10.1609/aaaiss.v1i1.27478.
  2. ↑ Qureshi, Nabeel S. (May 25, 2023). "Waluigi, Carl Jung, and the Case for Moral AI". Wired.
  3. 1 2 Bove, Tristan (May 27, 2023). "Will A.I. go rogue like Waluigi from Mario Bros., or become the personal assistant that Bill Gates says will make us all rich?". Fortune . Retrieved January 14, 2024.
  4. ↑ Franceschelli, Giorgio; Musolesi, Mirco (January 11, 2024). "Reinforcement Learning for Generative AI: State of the Art, Opportunities and Open Research Challenges". Journal of Artificial Intelligence Research. 79: 417–446. arXiv: 2308.00031 . doi:10.1613/jair.1.15278.
  5. ↑ Drapkin, Aaron (July 20, 2023). "AI Ethics: Principles, Guidelines, Frameworks & Issues to Discuss". Tech.co. Retrieved January 14, 2024.
  6. ↑ Nardo, Cleo (March 2, 2023). "The Waluigi Effect". AI Alignment Forum. Retrieved February 17, 2024.
Listen to this article (4 minutes)
Sound-icon.svg
This audio file was created from a revision of this article dated 21 July 2024 (2024-07-21), and does not reflect subsequent edits.
(Audio help  · More spoken articles)
This page is based on this Wikipedia article
Text is available under the CC BY-SA 4.0 license; additional terms may apply.
Images, videos and audio are available under their respective licenses.