A Thoughtful Look at Grammarly’s Expert Review Fiasco: A Reminder About Names, AI, and Our Digital Dignity
The recent class-action filing against Grammarly and its parent company, Superhuman, isn’t just about an AI feature that went off the rails. It’s a larger, noisier signal about who gets to own a name, a voice, or a credential in a digital age where machines imitate human judgment at scale. Personally, I think this case distills a core tension of our era: the lure of smart tools versus the stubborn reality that human beings deserve consent, credit, and control over how their reputations are used.
Why this matters, beyond the courtroom drama, is simple: AI tools increasingly blur the line between collaboration and appropriation. Grammarly’s “Expert Review” promised to channel the wisdom of well-known writers and scholars—think Stephen King, Neil deGrasse Tyson, or Julia Angwin—into user-editing sessions. The problem isn’t that the feature existed; it’s that the representations of those authors weren’t backed by consent, permission, or actual endorsement. What makes this particularly fascinating is how consent, likeness rights, and professional credibility collide when a corporation tries to monetize the aura of authority. In my opinion, the incident reveals a misalignment between product ambition and ethical boundaries in AI-assisted content creation.
A new kind of naming rights in the age of AI
- What this really highlights is the commodification of a person’s name and authority in a frictionless, automated interface. The lawsuit alleges that Grammarly used hundreds of journalists and writers’ identities to give the product a veneer of expertise, effectively trading on reputations without consent. This isn’t a mere marketing stunt; it’s the erosion of a basic respect for intellectual property and personal agency. From my perspective, the core issue isn’t technical fraud as much as ethical misrepresentation: users think they are tapping into real expertise, while in truth they are engaging with a corporate construct built on borrowed gravitas.
- What many people don’t realize is that consent for name and likeness in commercial use isn’t optional—it's a legal and moral baseline, even if the person isn’t a household name. New York and California law, which are central to this case, strongly protect individuals from commercial exploitation of their identities. If you take a step back and think about it, this is less about who’s famous and more about who gets to decide how a personal brand is deployed in the public square.
- A detail I find especially revealing is the timing. Superhuman announced it would discontinue the feature in the wake of public backlash, signaling that the company heard the dissonance, even if the technological rationale for the feature remains compelling to some users. What this suggests is that product teams across Silicon Valley are learning—often the hard way—that user demand for clever AI tools doesn’t automatically translate into a green light for ethically thorny implementations.
The dynamics of endorsement, not endorsement, and the problem of “digital doppelgängers”
- The case zeroes in on what happens when AI-generated prompts are attributed to real people who never gave explicit endorsements. The authorial aura—whether living or deceased—has long carried weight in shaping readers’ trust. When a platform borrows that aura to guide editing decisions, it creates a dissonance between perceived authority and actual provenance. In my view, this isn’t just about misattribution; it’s about misalignment of incentives. The platform benefits from the halo effect of famous names, while the individuals whose reputations are implicated bear the reputational risk and potential confusion among audiences.
- One thing that immediately stands out is how this episode reveals a blind spot in how tech teams imagine “experts” as interchangeable inputs for AI systems. The reality is that expertise is nuanced, contextual, and ethically tethered to consent. The attempt to automate authoritative feedback by simulating living or dead luminaries collapses if the people being simulated would object to the portrayal—or to the commercial use of their words and persona.
- What this really suggests is a deeper trend: the tech industry’s appetite for scalable influence often outruns legal and cultural guardrails. When corporations chase engagement metrics, they risk eroding trust. If experts’ voices are repurposed without clear opt-in, audiences may start to distrust both the product and the people it purports to echo.
Public backlash as a design feedback loop
- The public backlash wasn’t a mere nuisance; it became a design signal. Superhuman’s decision to disable Expert Review and announce a reimagining of the feature indicates recognition that user trust hinges on transparency and control. In my opinion, this pivot is a teachable moment about product governance: ethical guardrails, consent mechanisms, and the ability for experts to opt in or out should be embedded from the start, not bolted on after the fact.
- A broader takeaway is that companies must assume that imitators of authority—whether real people or fictional personas—will invite scrutiny. If a feature risks misrepresenting someone’s voice, it should include explicit disclosures, a robust opt-in process, and perhaps a way to trace the origin of each suggestion back to a verifiable source. From a practical standpoint, this reduces legal exposure and restores user confidence that the tool isn’t merely gameable by clever prompts.
- The lawsuit also reframes the debate about AI’s role in editorial assistance. If the value proposition is to blend human expertise with machine efficiency, the handshake needs to be transparent: who’s contributing to the feedback, in what capacity, and with what consent? Without that clarity, the line between helpful guidance and deceptive representation becomes dangerously blurry.
Broader implications for how we value expertise online
- This case spotlights a broader social question: as AI systems become more capable of mimicking expertise, how do we preserve the integrity of professional voices? Personally, I think society benefits from AI augmenting human judgment, but not at the expense of consent, attribution, or accountability. What makes this episode so provocative is that it forces a reckoning about how we monetize knowledge in public forums where the celebrity endorser model is easier to simulate than to manage ethically.
- If you step back and look at the ecosystem, the risk isn’t only to individuals; it’s to the public’s understanding of expertise. When AI repurposes the words and reputations of well-known figures without permission, it teaches a disquieting lesson: credentialed opinion can be manufactured. That has serious implications for journalism, academia, and informed civic discourse.
- A counterpoint worth considering is that some experts might welcome wider reach and new income streams through AI-assisted amplification. The challenge is implementing this in a way that protects autonomy and ensures accurate representation. The path forward likely involves consent-centric design, verifiable authorial signals, and opt-in publicity rights that align commercial incentives with respect for intellectual property.
Deeper analysis: what this signals for the AI product landscape
- The Grammarly episode foreshadows a broader trend: the legal and ethical scaffolding for AI-assisted tools will become as consequential as the models themselves. The industry needs concrete norms around consent, attribution, and representation. In my view, the most successful AI products will treat expert voices as collaborative participants with agency, not as interchangeable templates.
- Technically, this means developing provenance features: clear labeling of when a suggestion is AI-generated, who selected or authored the input, and what sources informed the advice. It also requires robust opt-out mechanisms and perhaps even a standardized, enforceable consent framework for public figures whose identities appear in product features.
- Culturally, this pushes back against the impulse to monetize authority by sheer novelty. What people want is trustworthy tools that respect the people behind the advice. If the industry can marry innovative capability with transparent ethics, we may see AI assistants that feel more like responsible colleagues than clever impersonators.
Conclusion: a test for future AI-integrated platforms
- The Grammarly case isn’t just a lawsuit; it’s a moral experiment about whether we can maintain human-centric standards in an increasingly algorithmic world. Personally, I believe the outcome will influence how tech companies design, disclose, and deploy AI features that touch professional reputations. What this really questions is whether convenience and cleverness should ever trump consent and attribution.
- If the field learns from this moment, we could move toward AI tools that invite agreement, not guesswork, about who represents expertise. The hard task ahead is building systems that honor real voices while still delivering the efficiency and insight that users crave. What this means in practical terms is clearer disclosures, explicit opt-ins, and a culture that treats names and reputations with the same gravity we expect for the words themselves.
- In sum, this is less a single product misstep and more a bellwether for how we’ll navigate the ethics of AI-powered assistance in the years ahead. The question isn’t only what the technology can do, but what kind of digital society we want to inhabit when machines speak with somebody else’s voice.
Would you like this article adapted for a shorter web headline and three-paragraph summary, or expanded with a dedicated section on precedent cases in likeness rights and AI?
