Fair to all publishers? A Revenue Share Model of Perplexity AI

San Francisco, CA – [Date] – Artificially intelligent, next-generation search engine Perplexity AI has just announced a revenue-sharing program that is sure to put the publishing sectors at their debating best. The initiative is intended to pay publishers for content used in its search results but has raised questions over possible inequities in sharing the benefits.

The company just announced the creation of the Perplexity Publishers Program, outlining its plan to share ad revenue with publishers whose content is referenced in its search results. Kicking the program off, Perplexity has extended juicy offers to the following six high-profile publishers: Der Spiegel, Entrepreneur, Fortune, The Texas Tribune, TIME, and WordPress.com. The latter will pocket a substantial sum upfront for a double-digit percentage of expected revenue.

While the prospect of handsome monetary returns for these larger media houses is no doubt an alluring one, details of how the program would be structured for smaller publishers were sketchy enough to raise eyebrows. The move could inadvertently encourage a two-tier system where only the biggest and most influential publishers would gain any real benefits.

Perplexity itself said it needed to be more transparent with the wider publishing world. In an update, it said, “In the next few months, we’ll be rolling out ads in our related questions feature. Brands can pay to pose specific related follow-up questions within our answer engine interface and on Pages. Any time Perplexity generates revenue from an interaction where a publisher’s content is sourced, that publisher will earn money too.”

It has also partnered with ScalePost.ai, a platform designed to assist publishers in licensing content more easily, as well as to track analytics for AI use. This would make it easier for publishers to see exactly how their content is being used by Perplexity.

This, of course, was before the entry of ScalePost.ai into the scene. Introduce one more player in it, and the equation has become all the more complicated. Given that this is a relatively unknown entity with hardly any online presence, serious questions have been raised over its capability to manage the revenue-sharing programme and ensure that there is a fair flow of money.

The opacity surrounding the inner mechanics of the program to smaller publishers has supplied a great deal of fuel to speculation and apprehension. Most content creators are afraid that without transparent guidelines and mechanisms for distribution on equanimity bases, the initiative of revenue sharing might sharpen existing imbalances in power between large and small publishers.

Independent publishers say that Perplexity should be compelled to design an open field where all content creators, regardless of their size and influence, have equal opportunities to participate in its revenue-sharing programs. They underline the necessity of eligibility criteria, transparency in the revenue-sharing calculations, and strong dispute resolution mechanisms.

There are also fears that the program may not ensure quality content. According to experts, this shift in focus to revenue generation may make publishers inclined towards prioritizing quantity over quality, therefore leading to less original reporting and in-depth analysis.

To address these concerns and build trust with the publishing community, Perplexity must provide detailed information about the revenue-sharing program, including eligibility criteria, revenue calculation methodologies, and payment terms. The company should also commit to regular communication with publishers to provide updates on the program’s progress and address any issues or concerns.

Thus, being open and including everybody in its sharing model would allow Perplexity to decrease the possible risks it inflicts to a degree, therefore acting as a responsible and just partner to the publishing industry.

The sharing model for Perplexity AI is a finely complex dance between technological advancement and ethics. Much as the case of opening a revenue flow to publishers cannot be denied, this might just be increasing existing disparities within the industry, which casts a long shadow thereafter. How then will Perplexity strike a balance and come up with a model that works for everyone?

What, then, is “fairness”? It would seem that, all other things being equal, the more content a site produces, the more it would be referenced; hence, more value it would generate, and so more revenue should be returned to the originating site. But clearly, that can’t be the only defining factor. Quality of content, content originality, and audience engagement all matter. How does Perplexity plan to ensure that small publishers, who may not have as much data to contribute, don’t get shortchanged in this revenue-sharing formula?

In view of these concerns, Perplexity could have a tiered revenue-sharing model. For instance, a basic share to all of those whose content is referenced while further incentivizing the top publishers for certain quality or engagement thresholds. This would drive excellence in content but ensure that even the smallest of publishers get to join in the program.

Another vital constituent of a fair revenue-sharing model is transparency. Perplexity has to clearly define the definition, methodology, and processes of revenue calculation, distribution, and auditing. Periodic reporting with regard to the performance of the program—detailed information on revenues generated and distributed—can instill confidence in the minds of publishers. This aspect of transparency and accountability can be further enhanced through the constitution of an independent oversight body for monitoring the implementation process.

A partnership with ScalePost.ai will certainly raise a few questions regarding the role of intermediaries in this revenue-sharing ecosystem. While the value bought in through such partnerships certainly cannot go in vain, finally, care needs to be taken that such relationships and arrangements do not add unnecessary complexities and introduce additional costs for publishers. Perplexity needs to clearly understand the pros and cons of such partnerships and study ways in which they turn out to be mala fide as far as the interest of the publishers is concerned.

Beyond the monetary points, the Perplexity model spells a larger question of the relationship between AI and content creation. How will the role of the human creator evolve? That is how revenue-sharing models can incentivize quality content and authenticity while recognizing the value brought in by AI-driven curation and analysis.

With the association to professional bodies and institutions of higher learning, there would be a place for Perplexity regarding the research on AI’s effects on content creation and distribution. This way, in funding research and development, Perplexity will have contributed to driving best practices and standards in AI-driven content platforms.

In the final analysis, this will be the Perplexity AI revenue-sharing model redefining how search engines and content developers relate to each other. By appealing to fairness, transparency, and collaboration, Perplexity can come up with a model that works for publishers of all sizes while really driving innovation within the AI and Content Creation Space. However, ahead lies a challenging road, and it is a company that has to be ready to change its approach with industry evolution.

Sources:

• https://www.searchenginejournal.com/is-perplexity-ais-revenue-share-plan-fair/523513/
• https://tvnewscheck.com/ai/article/perplexity-offers-news-publishers-a-rev-share-deal-but-is-it-fair-compensation/
• https://www.techtarget.com/searchenterpriseai/news/366599602/Perplexity-AI-revenue-share-model-appeases-publishers
• https://www.thehindu.com/sci-tech/technology/perplexity-ai-starts-ad-revenue-sharing-partnership-after-weeks-of-plagiarism-allegations/article68468064.ece

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