In an effort to provide readers with quick and accurate information, news outlets are experimenting with AI chatbots. Foundry, the media company operating Macworld, PCWorld, Tech Advisor, and TechHive, recently introduced an AI chatbot called Smart Answers. The chatbot is trained on the content from the four sites and is designed to deliver trustworthy responses based on past articles and reviews. While the chatbot aims to provide valuable information to users, it still struggles with some queries and relies on user feedback for improvements. Additionally, Smart Answers serves as a revenue stream through affiliate marketing, offering buying options related to users’ search queries. The introduction of AI chatbots in the media landscape raises questions about the future of journalistic content and reader engagement.
In recent years, news outlets have been exploring the use of artificial intelligence (AI) to enhance their capabilities and deliver a better user experience. One area where AI has been particularly intriguing is in the development of chatbots that can interact with readers and provide them with information. However, the challenge lies in building a chatbot that is not only efficient but also trustworthy. In this article, we will explore the concept of building a “trustworthy” AI chatbot for news outlets and examine the introduction of a specific chatbot called Smart Answers.
The use of AI in news outlets
News outlets have been increasingly utilizing AI technology to streamline their operations and improve their content production. AI tools have been used to generate travel guides, film blogs, and explainers, with the primary goal of creating more pages for ads without the need for additional writers. However, the introduction of AI in the news industry has raised questions about the reliability and accuracy of the generated content.
The introduction of Smart Answers
An AI chatbot called Smart Answers was recently introduced by a media company operating Macworld, PCWorld, Tech Advisor, and TechHive. The chatbot is trained using the sites’ archives and aims to provide readers with answers to their tech-related questions based on the expertise of the outlets’ experts. Unlike other AI tools, Smart Answers doesn’t have a byline and is designed to assist readers in finding specific information within the vast amount of content available.
How Smart Answers works
Smart Answers operates by allowing readers to input their questions, to which the chatbot generates a response based on the corpus of English language articles from the four sites. The chatbot excludes sponsored content and deals posts and provides links to the articles from which the information was extracted. Additionally, readers can select queries from an FAQ list that is AI-generated but based on popular questions and user interactions.
Testing and quality assurance
Prior to its launch, Smart Answers underwent rigorous testing and quality assurance procedures. The editorial staff tested early versions of the chatbot and assessed the accuracy and trustworthiness of its responses. The goal was to ensure that the answers provided by the chatbot were equivalent to what an editor would provide. This testing phase lasted for several months to ensure that the chatbot met the necessary standards.
Addressing errors and limitations
Despite the thorough testing process, Smart Answers is not immune to errors and limitations. Some queries may receive incorrect or incomplete responses, highlighting the challenges in training an AI chatbot to provide accurate information consistently. In cases where errors are identified, user feedback plays a crucial role in flagging issues and helping improve the chatbot’s functionality. The company relies on the AI company building the chatbot to address and rectify any errors or limitations.
The role of Smart Answers in generating revenue
Smart Answers serves a dual purpose for the media company: providing valuable information to readers and generating revenue through affiliate marketing. In addition to the generated answers and relevant story links, the chatbot includes buying options for items related to the user’s search. This approach allows the media company to monetize content by earning commissions from purchases made through the provided links. Smart Answers thus becomes a revenue-generating tool that enhances the user experience.
Challenges in the face of AI content generation
The introduction of AI content generation in news outlets brings with it a set of challenges. As AI-driven search experiences, such as Google’s Search Generative Experience, gain popularity, news publishers risk losing traffic and ad revenue. AI-generated snippets and excerpts from articles can undermine the need for users to click through to the original content. To counteract this, news outlets like the one operating Smart Answers must find ways to engage and retain readers on their sites.
The potential benefits for journalists
While the roll-out of AI initiatives in news outlets has faced criticism, the Smart Answers chatbot can actually be beneficial for journalists. User queries and unsatisfactory responses can provide valuable insights to reporters and editors, signaling areas where more coverage or clarification is needed. This feedback loop allows journalists to refine their reporting and ensure that they are addressing relevant topics and questions from their audience. Smart Answers, therefore, becomes a complementary tool in the journalistic process.
Building a “trustworthy” AI chatbot for news outlets is a complex endeavor that requires thorough testing, quality assurance, and ongoing improvements. The introduction of Smart Answers by a media company operating several tech-focused outlets demonstrates the potential of AI chatbots in delivering specific information to readers. However, challenges in accuracy and limitations remain, necessitating constant feedback and improvements. Additionally, Smart Answers offers the opportunity for revenue generation through affiliate marketing and can serve as a complementary tool for journalists in their reporting processes. As AI continues to shape the news industry, news outlets will need to navigate the complexities of AI content generation to ensure the delivery of reliable and valuable information to their readers.