Perplexity - chatbot

Transparency, accountability 🙈

In some ways, Perplexity appears transparent: after delivering an answer, the system presents the sources of information it has used, allowing users to verify and explore further, setting it apart from traditional search engines that simply provide links. 

On the other hand, the system is opaque in a number of important ways: 

• Data and information sources. Perplexity AI does not reveal all the sources of the information it provides, making it difficult for users to verify the credibility and reliability of responses.

• Training data. The details of the training data and potential biases within Perplexity's AI answer engine are not transparent, raising concerns about the objectivity and fairness of the system's responses.

• Algorithmic decision-making. Perplexity AI provides limited information on how its algorithms work, notably how they select, filter, and prioritise information.

• Content moderation. The mechanisms and criteria used for content moderation and the prevention of misinformation and disinformation are not clearly outlined.

• User feedback. The processes by which user feedback is collected, assessed, and integrated into improving the AI's performance are not clearly explained.

Risks, harms 🛑

Perplexity's AI answer engine has been accused of causing serious harms to publishers and others, including: 

• IP/copyright abuse. Perplexity has been accused of collecting, summarising and/or paraphrasing publishers' content without acknowledgement or permission, thereby reducing their revenue and profit margins.

• Trademark dilution. Publishers argue that by placing their famous logos and names next to incorrect AI-generated text, Perplexity "tarnishes" their reputation for accuracy and reliability.

• Traffic theft. Unlike Google, which traditionally directs users to a website, Perplexity synthesises content into a complete answer on its own page. Publishers report that this removes the incentive for users to click through, siphoning off the traffic necessary to support original journalism. Reports indicate publishers in certain sectors have seen a 50 percent decrease in views due to AI-generated summaries. 

• Competition. It has been argued that Perplexity has effectively become a competitor to the publishers whose content it has plagiarised/stolen and re-published, thereby shifting market dynamics. Smaller publishers are seen as particularly at risk.

• Societal destabilisation. Perplexity's proven susceptibility to generating and amplifying false, misleading and polarising content may have resulted in the increased believability of debunked conspiracy theories and far-right thinking.

• Reputational damage. Perplexity has attributed entirely fabricated quotes or facts to reputable news outlets, potentially damaging their name and image. For example, News Corp alleged that Perplexity falsely attributed "hallucinated" quotes about F-16 jets to its publications.

Lawsuits ⚖️

• December 2025. Chicago Tribune Company, LLC v. Perplexity AI, Inc.

• December 2025. The New York Times Company v. Perplexity AI, Inc.

• November 2025. Amazon.com Services LLC v. Perplexity AI, Inc.

• October 2025. Reddit, Inc. v. SerpApi LLC, Oxylabs UAB, AWMProxy, and Perplexity AI, Inc.

• September 2025. Encyclopædia Britannica, Inc. and Merriam-Webster, Inc. v. Perplexity AI, Inc.

• August 2025. The Yomiuri Shimbun Holdings et al. v. Perplexity AI, Inc.

• August 2025. Nikkei Inc. and The Asahi Shimbun Co. v. Perplexity AI, Inc.

• October 2024. Dow Jones & Company, Inc. and NYP Holdings, Inc. v. Perplexity AI, Inc.

Research, advocacy 🧮

• Search Google Scholar

Investigations, assessments, audits 👁️