Github Keshav83 Biaschecker Biaschecker Is An Intelligent Chatbot

Bonisiwe Shabane

-Dec 6, 2025, 11:56 PM

github keshav83 biaschecker biaschecker is an intelligent chatbot

BiasChecker Chatbot Overview BiasChecker is an intelligent chatbot that detects biased language in real time and provides a neutral, respectful rephrasing of user inputs. Using state-of-the-art transformer models, it first checks if your message is biased and then, if needed, generates a more neutral version. Features Bias Detection: Uses a zero-shot classification model (facebook/bart-large-mnli) to determine if a message is biased. Real-Time Correction: If bias is detected, it automatically rephrases the input into a neutral tone using a text generation model (t5-small). Interactive Chat: Engage in a conversation where your inputs are evaluated and corrected on the fly. Prerequisites Python 3.x Transformers library Install the required package with:

bash Copy Edit pip install transformers How It Works User Input: The chatbot waits for your input. Bias Detection: Your message is analyzed to check whether it is biased. Neutral Rephrasing: If the input is flagged as biased, the chatbot generates a neutral version. Interactive Loop: You can continue chatting, or exit by typing "quit" or "exit". BiasChecker follows a distributed and extendable architecture that allows us to simulate users following and unfollowing accounts, search for different polarised topics in a concurrent manner and measure bias. It may be applied to multiple social media platforms.

open another terminal(the number of terminals is dependent on the experiment) There are two main references for this work: Paper [1] carries out a study on personalisation on Twitter using a previous version of the BiasChecker tool whereas paper [2] introduces the BiasChecker tool and... Typescript/React Library for AI Chat💬🚀 Fully customizable AI chatbot component for your website OSS AI Companion Chatbot - Build your own AI companion in Python using ChatGPT. Rill is a tool for effortlessly transforming data sets into powerful, opinionated dashboards using SQL.

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Have you ever read an article that didn't sit right with you, but you couldn't quite put your finger on why? It lists the facts, seems to include diverse perspectives, yet something feels off. This common experience got us thinking: How often do we encounter this feeling? How much can subtly slanted text skew our perception without us realizing it? That's why we're developing BiasChecker.ai, an AI-powered bias detection tool. Our mission is to make these subtle biases more visible, fostering more informed discussions and decision-making.

Artificial Intelligence is uniquely suited for bias detection because it can: You might be surprised to learn just how many ways bias can manifest in text. We've compiled a collection of over 100 detectable biases. Curious? Check out our bias types page to explore the full list. As we develop BiasChecker.ai, we're eager to hear your thoughts:

An End-to-End project for letting user create a Vanilla-Retrieval based ChatBot. User can create thier own Dataset, and choose among various training hyperparameters to train their model. Deployed the model on web interface via Heroku. (Optional) Take the Demo and ask the bot for help. Step 2: Train your bot with suitable hyperparameters. Training will take approximately 30 seconds with default parameters.

Step 3: Once the bot is trained, you can converse with your ChatBot. You can access the chatbot from : DIY-Chatbot Are all AI chatbots the same? Absolutely not. Each has unique strengths and weaknesses that affect how and whether you should use them. We've been testing AI chatbots since their inception, cutting through the hype and assessing what they can really do.

On a basic level, they can help you find information, but they can also create images and videos, generate comprehensive research reports, and process files. Furthermore, you can also have conversations with them. ChatGPT is our Editors' Choice winner for the category because it provides the most accurate and detailed answers out of all the chatbots we've tested. However, the field is rapidly evolving, and lots of other options stand out for various reasons. Read on for all of our top picks, followed by what you need to know before choosing the best AI chatbot for your needs. Now with GPT-5, ChatGPT's advanced, mature models, helpful sourcing abilities, and superb research tools make it the leader among chatbots.

It works well as a standalone AI chatbot, but Gemini's true value comes from its bundled cloud storage and deep integration with nearly every Google app. Microsoft's conversational Copilot AI offers impressive research capabilities, generative features, and diverse cross-platform experiences. Perplexity stands out for its strong AI-powered web searches and can handle most tasks you'd expect from an AI chatbot, but its limited deep research abilities are somewhat disappointing. BiasChecker.ai was brought to life by Peter Troshin and Svetlana Fomina with the help of their LLM friends. We are a small team with expertise in software engineering, data analysis and statistics. At BiasChecker.ai, we're on a mission to boost media literacy and sharpen critical thinking skills.

We help people spot and understand biases in the news and information they consume every day. In today's digital world, where information comes at us fast and furious, knowing how to spot bias is key to making smart, informed choices. BiasChecker.ai leverages advanced artificial intelligence, powered by the most powerful LLM systems like ChatGPT and OpenAI's Claude, to analyze media content for potential biases. Our system is designed to identify and evaluate various types of bias, including: Large Language Models (LLMs) like ChatGPT or Claude are exceptionally well-suited for detecting biases in media content for several reasons: By leveraging these capabilities, BiasChecker.ai provides a nuanced and comprehensive analysis of potential biases in media content, helping users develop a more critical and informed perspective on the information they consume.

After analysis, BiasChecker.ai provides a detailed report highlighting: Chatbots have been studied for more than half a century. With the rapid development of natural language processing (NLP) technologies in recent years, chatbots using large language models (LLMs) have received much attention nowadays. Compared with traditional ones, modern chatbots are more powerful and have been used in real-world applications. There are however, bias and fairness concerns in modern chatbot design. Due to the huge amounts of training data, extremely large model sizes, and lack of interpretability, bias mitigation and fairness preservation of modern chatbots are challenging.

Thus, a comprehensive overview on bias and fairness in chatbot systems is given in this paper. The history of chatbots and their categories are first reviewed. Then, bias sources and potential harms in applications are analyzed. Considerations in designing fair and unbiased chatbot systems are examined. Finally, future research directions are discussed. A chatbot is an intelligent software system designed to simulate natural human language conversations between humans and machines [35].

As a human-computer interaction (HCI) system [41], it takes human voice or text as input and uses the natural language processing (NLP) technology to understand and respond accordingly [6]. With the rapid development of the Internet and artificial intelligence (AI), chatbots have become a hot research topic and a real-world application system that attracts much attention [136]. One of the most common occasions is to use chatbots as a dialogue agent in the service industry [175, 4, 110]. Chatbots have changed the way customers and companies interact. While chatbots may not be as good as human services in answering complex questions, they are accessible, responsive, and always available. They can answer most simple questions, which proves to be valuable in applications like product ordering and travel booking [92, 117, 186].

For companies, chatbots can respond to customer requests at any time, improve user experience, and contribute to saving in the service cost [220]. As to users, a study [30] showed that people would be interested in chatbot services for effective and efficient information access. Other motivations include entertainment, socializing, and curiosity about new things. To realize these benefits, chatbots need to understand user input and analyze users’ sentiments and intentions accurately, find appropriate answers, and generate fast and fluent responses. Sometimes, it may need to take the user identity (or attributes) into account in providing a proper answer. Recent advances and breakthroughs in NLP and machine learning (ML) have changed the landscape of language understanding and processing [139, 97, 198].

These developments are driven by the availability of increased computing power, massive amounts of training data, and the advent of sophisticated ML algorithms. The introduction of transformer networks [190] leads to large pre-trained models, such as GPT-3 [31], BERT [56], PaLM [44], etc. They have become popular [146, 93, 196, 214] in the past decade. Based on these developments, ChatGPT, a chatbot from OpenAI, has taken the world by storm by providing real-time, plausible-looking responses to input questions. ChatGPT has a good performance in text generation, language understanding, and translation. As a chatbot, it can be applied in various fields [71], such as education [67, 14], healthcare [23, 158], marketing [89, 151], environmental research [218, 22], etc.

The prevalence of ChatGPT has made chatbots a focus of attention. Leading technology companies have also released their own chatbots, such as Google’s Bard and Meta’s BlenderBot 3. With the help of AI, chatbots have become more intelligent and can answer people’s questions smoothly. On the other hand, chatbots are not as neutral as expected, raising ethical concerns among the general public [144]. Fig. 1 shows the number of papers on chatbot since 2014.

Github Keshav83 Biaschecker Biaschecker Is An Intelligent Chatbot

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