Can Oral History and Auto-autobiography Have a Candid Conversation?

The practice of conducting interpersonal inquiry for the purpose of creating and sharing family memory across generations is persistent, from ancient oral traditions to printed memoirs to the archiving of audio reminiscences. This deep impulse to trace our story, for a growing number of technology firms, is lucrative. The company that grew to become Ancestry.com tapped into the interest as early as 1983, setting out to democratize access to scattered archives and engage genealogy communities. Ancestry added tools steadily through the decades that followed, expanding from a boutique print publishing house to a privately held, subscription-based global online heritage brand now worth as much as $10 billion (Wang 2025).

Ancestry promises “to empower personal journeys” and “connect everyone with their past so they can discover, preserve, and share their unique family stories” (Ancestry n.d.). Its newest products, propelled in part by the 2025 purchase of analog digitization giant iMemories, promote human-AI interaction through a set of tools—AI Stories, Ask AncestryAI, Listen and Explore, and AncestryPreserve—that, combined, can summarize, add context, and otherwise “enhance” a subscriber’s family records.

This shift is subtle but significant: from products that assisted in the finding, organizing, and transcribing of a family story to products that suggest, interpret, and ultimately reshape the story itself, giving it a more familiar and readable narrative form. Ancestry remains cautious about this interpretive trend when compared to ambitious competitors in the living memoir space like Storyworth, Remento, or Autobiographer, which offer applications that variously use algorithmic question protocols or dynamic conversational AI to extract and record biographical information from users, reformulate that content, and return it as a narrative tailored to readers, in book form.

I think of this development as auto-autobiography, the production of a life narrative grounded in the documented reminiscences of a human author but retold without methodological transparency. It is a marketing evolution for the family history industry, which has long treated research as an act of personal agency—an inherently valuable labor of investigation and discovery—and as work best assisted by limited support tools analogous to a librarian and an amanuensis. Contemporary auto-autobiography is far more outcome-oriented, selling consumers a faster and more efficient path to discovery and a more prestigious final product. I call the methods that produce this outcome Automated Biographical Elicitation and Re-tell (ABER). These methods remain opaque, yet millions of subscribers now rely on them, sharing family stories that a language model has collected and reformulated. I am investigating how ABER compares to human-conducted oral history.

I am a social historian who studies geragogy, the way adults in later life learn and make meaning. On the surface, practitioners in both social history and geragogy should be encouraged by the growing accessibility and affordability of ABER. Social history evolved over the last half-century as an explicit rebuke to institutional archives that failed to record or otherwise omitted the experiences of ordinary people. That historiographical direction, frequently described as “history from below,” helped shape oral history as a distinct methodology—a specific set of inquiry tools, ethics, goals, and practices—that dramatically democratized inquiry, reimagined the archive, and diversified historical production. Other impacts of this practice go beyond the work of history. Purposeful oral inquiry, whether for journalism, or clinical life review, or history, has shown wide-ranging positive effects—especially on the emotional and cognitive health of older adult narrators (the people interviewed).

ABER reduces both the friction and the cost of these practices. They are known to ease depression and loneliness in older adults, produce family stories associated with stronger identity and well-being in younger generations, shift power toward groups on the margins, promote intergenerational connection, and ground a more inclusive, dynamic human historical record (Pinquart and Forstmeier 2012; Yang et al. 2025; Duke et al. 2008; Merrill and Fivush 2016; Thompson and Bornat 2017).

Why then are oral historians skeptical of tools promising to make these practices more common? What does oral history do that ABER cannot?

To address these questions, my project at the Digital Life Initiative at Cornell Tech surveys several previous efforts to define historical methods. It then proposes a rubric to facilitate a more careful comparison of oral history and ABER. I do not rehash decades of historiographical debate or contentious technical arguments over ethics and method. Oral history and adjacent ethnographic practices are fiercely multidisciplinary, prone to definitional disagreement, and drawn to a wide range of approaches. Consensus on what practitioners do and what to call it has not come easily (Gluck 2018). Both the Oral History Association (OHA) in the United States and, to a lesser degree, the Oral History Society in Britain have gravitated away from specific “standards” toward a “suite of statements” elucidating principles, guidelines, ethics, and toolkits (Reeves and Milligan 2018; Oral History Association 2018a). This aversion to standards is rooted in years of activism and in an acknowledgment that co-created practice resists codification. The resulting statements offer insight into decades of nuanced disagreement about how to conduct oral history, but they lack the incisive language of human authorship and accountability that scholarly publishing bodies have adopted to address the rise of generative AI (COPE 2023).

The commercial success of auto-autobiography and the growth of AI more broadly, however, should spur a greater reexamination of just how much oral history practitioners actually share, and should encourage a bolder articulation of that common ground in public settings. That articulation is suddenly critical. Millions of consumers are now reading a family past that was collected and told back to them in a machine’s words. The vendors call this history. The consumers call it history. But what makes it so?

To ask this question more generally: On what grounds does the profession name as “history” a narrative generated artificially?

Yet the profession’s efforts to grapple with the AI revolution, though encouraging, are addressing other questions. The American Historical Association (AHA) issued guiding principles for AI in history education (American Historical Association 2025), and a separate AHA committee is finalizing guidelines for research and publication (American Historical Association n.d.). In a 2026 special section of the Oral History Review, Mary Larson weighs analytical and generative AI against the OHA’s principles and best practices, with particular attention to context and consent (Larson 2026). The AHA also hosted a major conference on AI in 2026. These signs of critical reflection come at a pivotal moment, but further work is needed to translate what historians do for audiences beyond the pages of academic journals and conference proceedings.

The effort need not start from scratch. A close reading of OHA statements demonstrates shared commitments to ethics, values, and goals. Most practitioners, including those apprehensive about establishing “standards,” would likely agree on the characteristics of their practice once they compared their work to auto-autobiography. Most would agree that disciplined oral history must be preplanned and co-created by a trained interviewer and an informed narrator, and that it must incorporate ethics and practices such as co-constructed rolling consent, procedural disclosure, recognition of interviewer bias and power dynamics, trauma awareness, community involvement, measures to reduce risk and harm, and avoidance of stereotypes and misrepresentation. The OHA definition of their field adds even greater specificity, establishing that the practice helps “to place people’s experiences within a larger social and historical context,” and, from another angle, “to contextualize social and historical events through how people lived them” (Oral History Association n.d.). Together, the OHA statements suggest that practitioners must be schooled in questioning protocols that contextualize, corroborate, and periodize, applying these and other historical thinking methods to a structured, improvisational, and transparent inquiry.

One particular passage in the OHA’s “Oral History Best Practices,” describing how follow-up questioning should be framed, illustrates many of these disciplinary expectations and points to a value worth upholding.

Along with asking open-ended questions and actively listening to the answers, interviewers should ask follow-up questions, seeking additional clarification, elaboration, and reflection. When asking questions, the interviewer should keep the following in mind:

. . .

b. Interviewers should work to achieve a balance between the objectives of the project and the perspectives of their narrators. Interviewers should provide challenging and perceptive inquiry, fully and respectfully exploring appropriate subjects, and not being satisfied with superficial responses. At the same time, they should encourage narrators to respond to questions in their own style and language and to address issues that reflect their concerns.

c. Interviewers should be prepared to extend the inquiry beyond the specific focus of the project to allow the narrator to freely define what is most relevant.

d. In recognition of not only the importance of oral history to an understanding of the past but also of the cost and effort involved, interviewers and narrators should mutually strive to record candid information of lasting value to future audiences. (Oral History Association 2018b)

This key passage offers a potential standard against which both ABER and human-conducted inquiry can be measured. It reminds practitioners that historical inquiry is a form of labor, one that invites extensive judgment about content and context and requires a determination about what is or is not worth keeping. But perhaps most tellingly, it identifies the problem of superficiality and positions candor as a unique characteristic of oral history inquiry.

The current trend toward auto-autobiography again provides a useful contrast. Ancestry’s chief technology officer, Sriram Thiagarajan, has openly acknowledged the company’s early struggles with hallucination, and he has promoted human review as a central strategy “to ensure historical accuracy” (Thiagarajan 2026). But for oral historians, accuracy is only one modest element of candor. The disciplinary obligation to seek candor goes beyond authenticating or corroborating a fact. Instead, it focuses the practitioner on the broader disposition of the narrator: identifying evidence of openness and resistance and promoting, as far as possible, an interpersonal exchange characterized by sincerity, forthrightness, and a willingness to tell it the way it is. In this sense, a practitioner’s commitment to emotional safety, care, and co-ownership is not merely an ethical stance; it is a method designed to produce better history.

The popular use of auto-autobiography for historical understanding requires more study. Researchers in adjacent fields have found that nonhuman interviewers offer a safety and anonymity that increase disclosure (Lucas et al. 2014; Lucas et al. 2017), and that a conversational AI can deliver therapeutic benefits (Heinz et al. 2025). Other research complicates the disclosure finding by showing that users disclose no more intimately to a chatbot than to a person (Croes et al. 2024). In a study of eleven leading models, AI gave more positive affirmation than human interlocutors did to users who described personal conflicts—a potentially sycophantic response, in contrast to the “challenging” inquiry urged in the OHA’s best practices—and study subjects preferred it (Cheng et al. 2026). Memory research is also instructive. One study, for example, found that generative chatbot interviewing induced more than three times as many immediate false memories as a control condition (Chan et al. 2024). None of these examples directly explore oral history or life review or consider what AI-conducted elicitation and AI-generated narrative accounts do to history production. But these issues are existential for historians. Does ABER elicit history or something else? Does it re-tell history or something else? These are big questions, ready-made for a discipline that knows how to ask them candidly.

References

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To cite: Mucher, Stephen. 2026. "Can Oral History and Auto-autobiography Have a Candid Conversation?" Digital Life Initiative, Cornell Tech. https://auto-autobiography.stephenmucher.org/essay.html